Thea Brennan-Krohn was supported by a Eunice Kennedy Shriver National Institute of Child Health and Human Development pediatric infectious diseases research training grant (T32HD055148), a National Institute of Allergy and Infectious Diseases training grant (T32AI007061), a Boston Children&#39;s Hospital Office of Faculty Development Faculty Career Development fellowship, and a National Institute of Allergy and Infectious Diseases career development award (1K08AI132716). J.E.K. was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under award number R33 AI119114. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

<ol>
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M., Foleno, B., Gownley, C., Wira, E., Bush, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+Inoculum+and+Activity+in+AmpC-+and+Extended-Spectrum+(ESBL)-Producing+Escherichia+coli+and+Klebsiella+pneumoniae+Clinical+Isolates+Tested+by+Using+NCCLS+ESBL+Methodology.">Effects of Inoculum and Activity in AmpC- and Extended-Spectrum (ESBL)-Producing Escherichia coli and Klebsiella pneumoniae Clinical Isolates Tested by Using NCCLS ESBL Methodology.</a> Journal of Clinical Microbiology. 42 (1), 269-275 (2004).</li><li>Smith, K. P., Kirby, J. 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The D300 Digital Dispenser and associated consumables were provided by Tecan (Morrisville, NC). Tecan had no role in study design, data collection/interpretation, manuscript preparation, or decision to publish.

The two methods described here both provide information about the activity of antimicrobials used in combination compared to their individual activity. The automated, inkjet printer-assisted digital dispensing method is an adaption of the method described in the Clinical Microbiology Procedures Handbook33, while the time-kill method more closely follows the corresponding protocol from the same reference34.
In the checkerboard array method, calculations to determine the necessary volume of antimicrobial stock to add to each well as well as the dispensing of these volumes is automated, thus eliminating some of the major potential sources of error encountered in a manual checkerboard array. It is still essential, however, that the investigator determines that original stocks are made at the intended concentration and that goal final concentrations are entered into the D300 software correctly. Adding the antimicrobial suspension to wells in a 384-well plate can be challenging at first and requires care to ensure that pipette tips enter the appropriate wells and that liquid does not splash up the edges of the wells. An automated liquid handler can be used in place of a hand-held multichannel pipette to increase the speed and accuracy with which the bacterial suspension is added to wells. As described in the protocol, the D300 requires the addition of the surfactant, polysorbate 20 (P-20), for proper liquid handling. A different surfactant, polysorbate 80, at a concentration of 0.002%, has been noted to lower colistin MICs for organisms with colistin MICs of &#60;2 &#181;g/mL in standard broth microdilution assays.35,36 Our laboratory previously demonstrated that P-20 at concentrations up to 0.0015% had no effect on D300-assisted MIC results in comparison with reference BMD14. In the assay example presented here, the maximum P-20 is concentration is 0.0014%.
One problem we encountered with some checkerboard array assays was a large number of skipped wells. This occurred at a disproportionate rate with certain antibiotics. Specifically, in a screen of combinations against a collection of carbapenem-resistant Enterobacteriaceae, we found that while 49 of 521 trials (9.4%) were unusable due to multiple skipped wells, 2 of the 12 antibiotics tested (fosfomycin and cefepime) accounted for 46 of these trials (94%). Such increased rates may be more likely in drugs that are particularly susceptible to the inoculum effect31,32,37. Of note, CLSI does not recommend testing fosfomycin in broth dilution25 due to concerns about the reliability of results with this method, which may explain the unreliable results seen with this drug. Some modifications can be made to automated checkerboard method according to investigator preference. Antimicrobials can be dispensed into plates already containing bacterial suspension, rather than into empty wells, if this is preferable for reasons of workflow within the laboratory. While 384-well plates were used here, the method can also be carried out in 96-well plate assays with appropriate modification of well volume. The use of a 96-well plate format may help in reducing skipped wells for antibiotics that are particularly sensitive to small changes in inoculum. When calculating FICI, there may be situations where the MIC is off-scale (i.e., higher than tested), including situations where the drug being tested has no activity individually against the type of organism being tested. In these cases, the FIC can be calculated based on assuming the MIC is one dilution higher than the highest concentration tested. This is the most conservative strategy, as it assumes the maximal possible FIC value for any dilution where inhibition is observed during synergy testing. For example, if the actual MIC were instead two doubling dilutions above the highest concentration tested, then the corresponding FICs would be two-fold lower than the conservative assignments, and so on.
In order to accurately assess the bactericidal activity of drugs in a time-kill assay, it is essential that cultures be in logarithmic-phase growth, particularly when cell-wall active antibiotics are being tested28. For the rapidly-growing bacteria used in this example (K. pneumoniae), 3 hours of incubation with shaking was appropriate to reach this growth phase, but different amounts of time may be necessary for different organisms. In general, the culture should appear visibly but not heavily turbid. The appropriate amount of time can be determined by constructing a growth curve with colony counts taken at serial time points (e.g., every 30 min for 4-6 h)38. The intended starting inoculum in the time-kill study is also important. The target concentration of the starting inoculum is approximately 5 x 105 to 1 x 106 CFU/mL. The dilution described here (100 &#956;L of a 1.0 McFarland suspension in 10 mL of media) generates this inoculum for Klebsiella pneumoniae and other Enterobacteriaceae species on which we have tested it. If the density of the starting inocula in an experiment using different organisms is significantly higher or lower than this, then a different dilution may be needed. (The appropriate dilution required for a given species can be determined by performing a plate count of a 0.5 or 1.0 McFarland suspension to determine how many organisms this turbidity represents, then calculating the amount by which the initial suspension must be diluted to reach the appropriate final concentration.) If, on review of plate counts from the synergy study, the starting inoculum of any of the antibiotic-containing tubes is found to have been significantly lower than the starting inoculum of the growth control, this may indicate either antibiotic carryover or very rapid killing of bacteria in the brief time between addition of bacteria to the antibiotic-containing tube and removal of the aliquot for plating. If the actual number of colonies in the undiluted drop in a series is lower than the number of colonies in subsequent dilutions, this suggests antibiotic carryover effect. Different options have been described for preventing this effect, including spreading a single aliquot over an entire plate38 or spinning down the sample, removing the supernatant, and re-suspending in sterile saline prior to plating39. At each time point in the time-kill method, it is also critical for the investigator to efficiently but accurately remove an aliquot from each culture tube and perform serial dilutions. Delays during this process, particularly during early time points that occur in close succession, can lead to prolonged periods during which cultures are not been incubated and shaken, whereas careless dispensing and serial dilutions can lead to inaccurate plate counts. Compared to the spread plate method of plate counting, in which 100 &#956;L of each dilution is spread over an entire agar plate, the drop plate method described is far more rapid, requires a much smaller number of agar plates, and allows for faster counting, as the maximum countable number of colonies for each drop is 30, whereas up to 300 colonies can typically be counted from a spread plate. However, the spread plate method is also an option if investigators are more comfortable with this technique. If drops spread into each other after dispensing with a multichannel pipette, individual application of more widely spaced drops with a single-channel pipette can be performed instead. In our experience, cooling plates at 4 &#176;C prior to dispensing drops seemed to reduce excessive spreading.
One limitation of the techniques described here is that the results of the two types of synergy assay (checkerboard array and time-kill) are not always concordant, and since most published synergy articles use one method or the other rather than both together, it can be difficult to know how to integrate data from the two types of assays. Because the automated checkerboard array method we developed is simple and high-throughput, we have used it in effect as a kind of screen to test combinations against a larger number of isolates and to determine which concentration combinations were synergistic. We then performed a smaller number of time-kill studies, selecting combinations and concentrations that had been effective in the checkerboard array. Of note, because the checkerboard assay is typically performed on a microbroth dilution scale, while the time-kill assay uses larger volumes (similar to a macrobroth dilution), we found that FICs were sometimes different between the two methods, with higher concentrations generally required in the time-kill assay to demonstrate activity. This phenomenon has been noted previously when macrobroth and microbroth dilution MIC assay results are compared for Gram-negative bacilli26 and when larger inocula (as used in time-kill studies) are compared with the standard inoculum used in microbroth dilution and checkerboard array assays32. A specific limitation of the checkerboard array is the inherent variability in microbroth dilution MIC testing22. While FICI cutoffs for synergy account for this variability mathematically6 such variability inevitably raises concern about the reliability and consistency of checkerboard array results.
Because of the limitations inherent to all in vitro synergy testing methods (including cultivation of bacteria in an artificial growth medium, static antibiotic concentrations, and a limited time course), results obtained by these methods must be confirmed and further evaluated using supplemental techniques. Such methods include in vitro pharmacokinetic/pharmacodynamic (PK/PD) studies (e.g., the hollow fiber infection model40), animal models, and, ultimately, human PK/PD and efficacy studies. The automated checkerboard array method described here, by providing a rapid method with which to screen combinations for potential synergistic activity, allows for more targeted utilization of these techniques. Further automation of all of these methods, as well as more systematic investigation of the relationship between in vitro parameters and clinical outcomes, will be important in scaling up the use of synergy testing and increasing its clinical applicability.

The spread of multidrug-resistant (MDR) bacterial pathogens, particularly MDR Gram-negative bacteria such as carbapenem-resistant Enterobacteriaceae (CRE), has left clinicians with increasingly limited options for successful anti-infective therapy1, a problem exacerbated by the sluggish pace of novel antibacterial drug discovery2,3. Antimicrobial synergy, in which two drugs used in combination exert a greater-than-additive effect, offers the possibility of salvaging existing antibiotics for use in treatment of MDR bacteria, even when these bacteria are resistant to one or both of the antibiotics individually. The techniques described in this paper provide two complementary methods of in vitro synergy testing that, when used together, allow investigators to efficiently screen antimicrobial combinations of interest for evidence of synergistic activity (the automated checkerboard array method) and then to further evaluate the kinetics of inhibition and killing demonstrated by promising combinations identified in the screening stage (the manual time-kill method).
One of the most commonly used methods of in vitro synergy testing is the checkerboard array assay, a modification of minimum inhibitory concentration (MIC) testing in which the inhibitory activity of two different antibiotics against a bacterial isolate are tested over a range of concentration combinations4,5. If the two drugs exert greater than additive activity when used together, the combination is considered synergistic6. However, setting up a checkerboard array manually involves a series of calculations and diluting and pipetting steps that are laborious and vulnerable to human error. These constraints have had the effect of limiting the use of synergy testing primarily to the retrospective evaluation of small numbers of antibiotic combinations and bacterial isolates, and results have not always been consistent among studies7,8,9,10,11. Furthermore, the complexity of synergy testing has contributed to its unavailability in the clinical microbiology laboratory and to the virtual absence of in vitro synergy testing data from clinical studies of combination therapy12,13.
In order to increase the efficiency and throughput of the checkerboard array method, we made use of an automated MIC testing technique previously developed in our laboratory that uses inkjet printing technology to precisely and consistently dispense small volumes of antibiotic stock solution into wells in a microtiter plate14. The platform obviates the need for complex calculations and multiple pipetting steps. The associated software calculates and dispenses appropriate volumes of antibiotics to create a two-dimensional checkerboard array if the user simply inputs the desired concentration range and stock solution concentration of the antibiotics. We initially tested this method against a collection of CRE isolates15 and subsequently have focused on testing colistin-containing combinations for activity against colistin-resistant isolates16. Colistin is a drug of last resort generally reserved for use in the treatment of MDR Gram-negative pathogens17,18, and colistin resistance renders already MDR bacteria nearly pan-resistant19, making them ideal candidates for the development of novel therapeutic strategies using drugs to which they are insensitive individually. We found that the combination of colistin and the protein synthesis inhibitor antibiotic minocycline had a very high rate of synergy, even against strains that were resistant to each of these drugs individually, presumably because colistin exerts a subinhibitory permeabilizing effect on even colistin-resistant bacteria. We have chosen this combination to use as an example in this paper. Of note, synergy testing can also be used to evaluate for enhanced efficacy of two drugs which are both effective individually.
The automated checkerboard array method facilitates rapid, high-throughput synergy testing. However, the checkerboard array method does have limitations. As a modified MIC assay, it provides data only on inhibition of bacterial growth and not on killing, and it does not provide data on antibiotic effects over time. By contrast, manual performance of time-kill synergy assays is more labor intensive but provides information on both inhibition and killing over a 24 h time course20,21. We used time-kill analysis on a smaller number of isolates to confirm our checkerboard array results and to determine whether the synergistic combinations we identified were also bactericidal.
Both checkerboard array and time-kill synergy methods provide valuable information on the activity of drug combinations, and are particularly useful in evaluating potential novel therapeutic options for highly resistant bacterial pathogens. The methods also have inherent limitations. The standard microbroth dilution MIC method has a known expected error range of 1 two-fold dilution22, which is increased when two drugs are tested together in a checkerboard array. The standard definition of synergy, which considers a combination synergistic only if the drugs are active together at one-fourth their respective MICs6, takes into account this expected variability, but such variability (which is thought to result from a combination of biological and technical fluctuations23) inevitably generates uncertainly about the reliability of synergy results. The lack of established quality-control standards for synergy testing is also a current limitation. Perhaps the most significant limitation of all synergy testing methods is the lack of established correlations between in vitro results and clinical outcomes when combinations are used to treat patients24. Simpler and more rapid synergy testing methods, such as the automated checkerboard array method described here, may facilitate the integration of in vitro synergy testing within clinical trials or other evaluations of patient outcomes in order to better characterize the relationship between in vitro and in vivo effects in the future.
The automated checkerboard array method that we present here offers an option for high-throughput screening of a variety of combinations and allows for quick evaluation of unusual, &#34;high risk-high reward&#34; combinations without a major investment of time and resources. The time-kill method, which we subsequently demonstrate, can provide additional supportive information on the synergistic activity of the combination and can help to characterize its bactericidal activity and antibacterial kinetics.

<table>
	<tbody>
		<tr>
			<td>Escherichia coli strain ATCC 25922</td>
			<td>ATCC</td>
			<td>25922</td>
			<td>QC strain</td>
		</tr>
		<tr>
			<td>0.5 mL microcentrifuge tubes</td>
			<td>USA Scientific</td>
			<td>1605-0000</td>
			<td></td>
		</tr>
		<tr>
			<td>1 L 0.22 &#181;m bottle-top filter</td>
			<td>Thermo Scientific Nalgene</td>
			<td>597-4520</td>
			<td></td>
		</tr>
		<tr>
			<td>12 mm x 75 mm borosilicate glass round bottom culture tubes</td>
			<td>Fisherbrand</td>
			<td>14-961-26</td>
			<td></td>
		</tr>
		<tr>
			<td>15 mL conical tubes</td>
			<td>Phenix</td>
			<td>SS-PH15</td>
			<td></td>
		</tr>
		<tr>
			<td>15 x 100 mm or 15 x 150 mm Mueller Hinton agar plates</td>
			<td>Thermo Scientific</td>
			<td>R01620 or R04050</td>
			<td></td>
		</tr>
		<tr>
			<td>25 mm stainless steel closures for 25 x 150 mm glass culture tubes</td>
			<td>Bellco</td>
			<td>2005-02512</td>
			<td></td>
		</tr>
		<tr>
			<td>25 x 150 mm borosilicate glass round bottom culture tubes</td>
			<td>Bellco</td>
			<td>2011-25150</td>
			<td></td>
		</tr>
		<tr>
			<td>348-well sterile clear, flat-bottom, untreated microplates with lids</td>
			<td>Greiner Bio-One</td>
			<td>781186</td>
			<td></td>
		</tr>
		<tr>
			<td>50 mL conical tubes</td>
			<td>Phenix</td>
			<td>SS-PH50</td>
			<td></td>
		</tr>
		<tr>
			<td>50 mL sterile reagent reservoirs</td>
			<td>Corning</td>
			<td>4870</td>
			<td></td>
		</tr>
		<tr>
			<td>96 deep well polypropylene microplate with 2 mL wells</td>
			<td>Fisherbrand</td>
			<td>12-566-612</td>
			<td></td>
		</tr>
		<tr>
			<td>96-well sterile clear, round-bottom, untreated microplates with lids</td>
			<td>Evergreen</td>
			<td>222-8032-01R</td>
			<td></td>
		</tr>
		<tr>
			<td>Cation adjusted Mueller Hinton broth</td>
			<td>BD Diagnostics</td>
			<td>212322</td>
			<td></td>
		</tr>
		<tr>
			<td>Colistin sulfate</td>
			<td>Alfa Aesar</td>
			<td>J60915</td>
			<td></td>
		</tr>
		<tr>
			<td>D300e Control Software</td>
			<td>HP/Tecan</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>DensiCHEK Plus McFarland reader</td>
			<td>bioM&#233;rieux</td>
			<td>21250</td>
			<td></td>
		</tr>
		<tr>
			<td>Excel spreadsheet software</td>
			<td>Microsoft</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Extra long SHARP 10 &#181;L Precision Barrier Tips</td>
			<td>Denville Scientific</td>
			<td>P1096-FR</td>
			<td></td>
		</tr>
		<tr>
			<td>HP D300 digital dispenser</td>
			<td>HP/Tecan</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>HP D300 T8+ cassettes</td>
			<td>HP/Tecan</td>
			<td>30097370</td>
			<td></td>
		</tr>
		<tr>
			<td>Minocycline hydrochloride</td>
			<td>Chem-Impex</td>
			<td>14302</td>
			<td></td>
		</tr>
		<tr>
			<td>Picus 12-channel 10-300 &#181;L pipette</td>
			<td>Sartorius</td>
			<td>735461</td>
			<td></td>
		</tr>
		<tr>
			<td>Polysorbate 20</td>
			<td>Fisher Bioreagents</td>
			<td>BP-337</td>
			<td>Brand name: Tween 20</td>
		</tr>
		<tr>
			<td>Sodium chloride</td>
			<td>Fisher Chemical</td>
			<td>S271</td>
			<td></td>
		</tr>
		<tr>
			<td>Spectrophotometer</td>
			<td>Tecan</td>
			<td>Infinite M1000 PRO</td>
			<td></td>
		</tr>
		<tr>
			<td>Xplorer 12-channel 50-1200 &#181;L pipette</td>
			<td>Eppendorf</td>
			<td>2231000328</td>
			<td></td>
		</tr>
	</tbody>
</table>

antimicrobial synergy testing by the inkjet printer-assisted automated checkerboard array and the manual time-kill method

As rates of multidrug-resistant (MDR) pathogens continue to rise, outpacing the development of new antimicrobials, novel approaches to treatment of MDR bacteria are increasingly becoming a necessity. One such approach is combination therapy, in which two or more antibiotics are used together to treat an infection against which one or both of the drugs may be ineffective alone. When two drugs, in combination, exert a greater than additive effect, they are considered synergistic. In vitro investigation of synergistic activity is an important first step in evaluating the possible efficacy of drug combinations. Two main in vitro synergy testing methods have been developed: the checkerboard array and the time-kill study. In this paper, we present an automated checkerboard array method that makes use of inkjet printing technology to increase the efficiency and accuracy of this technique, as well as a standard manual time-kill synergy method. The automated checkerboard array can serve as a high-throughput screening assay, while the manual time-kill study provides additional, complementary data on synergistic activity and killing.
The checkerboard array is a modification of standard minimum inhibitory concentration (MIC) testing, in which bacteria are incubated with antibiotics at different concentration combinations and evaluated for growth inhibition after overnight incubation. Manual performance of the checkerboard array requires a laborious and error-prone series of calculations and dilutions. In the automated method presented here, the calculation and dispensing of required antibiotic stock solution volumes are automated through the use of inkjet printer technology. In the time-kill synergy assay, bacteria are incubated with the antibiotics of interest, both together and individually, and sampled at intervals over the course of 24 h for quantitative culture. The results can determine whether a combination is synergistic and whether it is bactericidal, and provide data on inhibition and killing of bacteria over time.

Figure 1A presents a grid from a checkerboard array synergy experiment in which minocycline in concentrations of 0-32 &#956;g/mL was combined with colistin at concentrations of 0-16 &#956;g/mL and tested against E. coli strain FDA-CDC 0494. The values represent spectrophotometric readings at optical density 600 nm (OD600). Wells with OD600 values below 0.07 (which corresponds to no growth by visual inspection) are shaded red, while wells with OD600 values 0.07 (which corresponds to growth by visual inspection) are shaded green. For each drug, the minimum inhibitory concentration (MIC; bolded) is the lowest concentration of drug that inhibits bacterial growth. For minocycline, this is 32 &#956;g/mL, and for colistin, it is 8 &#956;g/mL. The shading is retained in Figure 1B, but values within the wells in which growth is inhibited are replaced by fractional inhibitory concentration index (FICI) values. These are determined as follows: in each well, the fractional inhibitory concentration index (FIC) of each drug is calculated by dividing the concentration of antibiotic in that well by the drug&#39;s MIC, and the FICI is calculated by summing the two FICs. Wells with an FICI value of 0.5, which is considered the cutoff for synergy, are indicated with a broken-line border, and the well with the lowest FICI value (0.094) is bolded. Because the minimum FICI value is in the synergistic range, the combination is considered synergistic.
Figure 2A and Figure 2B show grids analogous to those in Figure 1A and Figure 1B, but in this case the combination does not demonstrate synergy against the isolate tested (K. pneumoniae isolate BIDMC 4), because the minimum FICI at which growth is inhibited is 1, which is &#62;0.5.
Figure 3 illustrates the optical density readings from a checkerboard synergy grid in which several skipped wells occurred (Enterobacter cloacae complex isolate BIDMC 27). Skipped wells are wells in which bacterial growth is inhibited despite the presence of bacterial growth in adjacent wells with higher concentrations of antibiotic. This phenomenon, which is known to occur in standard MIC testing as well, is likely due to biological variability in bacterial growth characteristics from well to well and to the sensitivity of some antibiotics to small differences in bacterial inoculum23,31,32. If more than one skipped well occurred in a checkerboard array, we discarded the results and repeated the assay.
Figure 4 presents examples of time-kill synergy results of three combinations tested against K. pneumoniae isolate BIDMC 32. Colony counts are indicated in a logarithmic scale on the y-axis and time, in hours, on the x-axis. The difference between the starting inoculum in the tube containing the drug combination and the concentration of bacteria in that tube at 24 h is illustrated by the red bar and number, while the difference between the concentration of bacteria at 24 h between the tube containing the combination and the tube containing the most active single agent alone is illustrated by the blue bar and number. Figure 4A shows results from the combination of colistin and minocycline; this combination was synergistic (difference between concentrations of bacteria exposed to combination and to most active agent alone &#8805;2 log10 CFU/mL at 24 h) and bactericidal (decline from starting inoculum to concentration at 24 h &#8805;3 log10 CFU/mL). Figure 4B shows results from the combination of colistin and clindamycin, a combination that was synergistic but was not bactericidal. This combination inhibited growth of the bacteria, which neither drug did alone, but did not kill them. Figure 4C shows results from the combination of colistin and erythromycin, which was neither bactericidal nor synergistic.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/58636/58636fig1.jpg" /> 
Figure 1: Checkerboard array results demonstrating synergy (minocycline + colistin tested against E. coli strain FDA-CDC 0494). (A) Spectrophotometric readout and growth interpretation of a checkerboard array. Values in cells are optical density readings at 600 nm (OD600). Cells with OD600 values below 0.07 (corresponding to no growth by visual inspection) are shaded red, while cells with OD600 values 0.07 (corresponding to growth by visual inspection) are shaded green. (B) Fractional inhibitory concentration index (FICI) calculation. Shading indicating growth or no growth has been retained. Values for colistin and minocycline along x- and y-axes, respectively, now represent the fractional inhibitory concentration (FIC), or the ratio of the concentration of the drug in that column or row to the minimum inhibitory concentration (MIC) of that drug alone. The value in each cell is the FICI, or the sum of the FICs of the two drugs in that well. The large broken line-bordered box encloses wells with an FICI of 0.5. The thick-bordered cell indicates the well with the lowest FICI in which growth is inhibited, or the minimum FICI. Because the minimum FICI is 0.5, the combination is considered synergistic. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58636/58636fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/58636/58636fig2.jpg" /> 
Figure 2: Checkerboard array results of a combination that does not demonstrate synergy (minocycline + colistin tested against K. pneumoniae isolate BIDMC 4). (A) Optical density values at 600 nm and growth interpretation of checkerboard array results as described for Figure 1A. (B) Fractional inhibitory concentration index (FICI) calculation as described for Figure 1A. Because the minimum FICI is &#62;0.5, the combination is not considered synergistic. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58636/58636fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/58636/58636fig3.jpg" /> 
Figure 3: Checkerboard array results that are uninterpretable due to skipped wells (minocycline + colistin tested against Enterobacter cloacae complex isolate BIDMC 27). Optical density values at 600 nm and growth interpretation of checkerboard array results as described for Figure 1A. Several skipped wells, in which bacterial growth is inhibited despite the presence of growth in adjacent wells with higher concentrations of antibiotic, are demonstrated. Results are not interpretable, and experiment needs to be repeated. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58636/58636fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/58636/58636fig4.jpg" /> 
Figure 4: Time-kill synergy results of three combinations tested against K. pneumoniae isolate BIDMC 32. Colony counts are indicated in a logarithmic scale on the y-axis and time, in hours, on the x-axis. The difference between the concentration of bacteria in the combination at 24 h and the starting inoculum in the tube is illustrated by the red bar and number. If the decline from starting inoculum to concentration at 24 h is &#8805;3 log10 CFU/mL, the combination is considered bactericidal. The difference between the concentration of bacteria at 24 h between the tube containing the combination and the tube containing the most active single agent alone is illustrated by the blue bar and number; if there is &#8805;2 log10 CFU/mL reduction, the combination is considered synergistic. (A) Colistin (CST) + minocycline (MIN), a combination that is both synergistic and bactericidal. (B) Colistin + clindamycin (CLI), a combination that is synergistic but not bactericidal. (C) Colistin + erythromycin (ERY), a combination that is neither synergistic nor bactericidal. These results were initially published as part of a study of the synergistic activity of colistin-containing combinations against colistin-resistant Enterobacteriaceae, in which we demonstrated that colistin was synergistic with a number of antibiotics that are active individually only (e.g. clindamycin) or primarily (e.g. erythromycin) against Gram-positive bacteria16. (Note that erythromycin was synergistic by checkerboard array against the strain shown, but not by time-kill, so it has been selected here as an example of a non-synergistic combination.) We hypothesized that colistin, which is known to act by permeabilization of the Gram-negative outer membrane, exerts a sub-inhibitory permeabilizing effect on colistin-resistant Gram-negative bacteria, allowing entry of drugs such as clindamycin that normally cannot enter the Gram-negative cell. Panel (A) of this figure has been modified from Brennan-Krohn, Pironti, and Kirby 201816,&#160;copyright &#169; American Society for Microbiology, Antimicrobial Agents and Chemotherapy, 62(10), 2018, pii: e00873-18, doi: 10.1128/AAC.00873-18. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58636/58636fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Antimicrobial Synergy Testing by the Inkjet Printer-assisted Automated Checkerboard Array and the Manual Time-kill Method at JoVE.com

Antimicrobial Synergy Testing by the Inkjet Printer-assisted Automated Checkerboard Array and the Manual Time-kill Method

Antimicrobial synergy testing is used to evaluate the effect of two or more antibiotics used in combination and is typically performed by one of two methods: the checkerboard array or the time-kill assay. Here, we present an automated, inkjet printer-assisted checkerboard array synergy technique and a classic time-kill synergy study.

As rates of multidrug-resistant (MDR) pathogens continue to rise, outpacing the development of new antimicrobials, novel approaches to treatment of MDR ...

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25.8K Views.  Beth Israel Deaconess Medical Center. Antimicrobial synergy testing is used to evaluate the effect of two or more antibiotics used in combination and is typically performed by one of two methods: the checkerboard array or the time-kill assay. Here, we present an automated, inkjet printer-assisted checkerboard array synergy technique and a classic time-kill synergy study.

Video: Antimicrobial Synergy Testing by the Inkjet Printer-assisted Automated Checkerboard Array and the Manual Time-kill Method

Antimicrobial Susceptibility Testing of Mycobacterium Tuberculosis Complex for First and Second Line Drugs by Broth Dilution in a Microtiter Plate Format

The rapid detection of antimicrobial resistance is important in the effort to control the increase in resistant Mycobacterium 
tuberculosis (Mtb). Antimicrobial susceptibility testing (AST) of Mtb has traditionally been performed by the agar method of proportion or by 
macrobroth testing on an instrument such as the BACTEC (Becton Dickinson, Sparks, MD), VersaTREK (TREK Diagnostics, Cleveland, OH) or BacT/ALERT (bioM&eacute;rieux, Hazelwood, MO). The agar proportion method, while considered the &#x201C;gold&#x201D; standard of AST, is labor intensive and requires calculation of resistance by performing colony counts on drug-containing agar as compared to drug-free agar. If there is &ge;1% growth on the drug-containing medium as compared to drug-free medium, the organism is considered resistant to that drug. The macrobroth methods require instrumentation and test break point ("critical") drug concentrations for the first line drugs (isoniazid, ethambutol, rifampin, and pyrazinamide). The method described here is commercially available in a 96 well microtiter plate format [MYCOTB (TREK Diagnostics)] and contains increasing concentrations of 12 antimicrobials used for treatment of tuberculosis including both first (isoniazid, rifampin, ethambutol) and second line drugs (amikacin, cycloserine, ethionamide, kanamycin, moxifloxacin, ofloxacin, para-aminosalicylic acid, rifabutin, and streptomycin). Pyrazinamide, a first line drug, is not included in the microtiter plate due to its need for acidic test conditions. Advantages of the microtiter system include both ease of set up and faster turn around time (14 days) compared with traditional agar proportion (21 days). In addition, the plate can be set up from inoculum prepared using either broth or solid medium. Since the microtiter plate format is new and since Mtb presents unique safety challenges in the laboratory, this protocol will describe how to safely setup, incubate and read the microtiter plate.

Antimicrobial susceptibility testing of Mycobacterium tuberculosis is challenging but critical for patient care. This microtiter plate format offers testing of 12 antimycobacterial drugs and provides minimum inhibitory concentration (MIC) values, which will aid in appropriate treatment.

The rapid detection of antimicrobial resistance is important in the effort to control the increase in resistant Mycobacterium 
tuberculosis (Mtb). ...

One-day Workflow Scheme for Bacterial Pathogen Detection and Antimicrobial Resistance Testing from Blood Cultures

Bloodstream infections are associated with high mortality rates because of the probable manifestation of sepsis, severe sepsis and septic shock1. Therefore, rapid administration of adequate antibiotic therapy is of foremost importance in the treatment of bloodstream infections. The critical element in this process is timing, heavily dependent on the results of bacterial identification and antibiotic susceptibility testing. Both of these parameters are routinely obtained by culture-based testing, which is time-consuming and takes on average 24-48 hours2, 4. The aim of the study was to develop DNA-based assays for rapid identification of bloodstream infections, as well as rapid antimicrobial susceptibility testing. The first assay is a eubacterial 16S rDNA-based real-time PCR assay complemented with species- or genus-specific probes5. Using these probes, Gram-negative bacteria including Pseudomonas spp., Pseudomonas aeruginosa and Escherichia coli as well as Gram-positive bacteria including Staphylococcus spp., Staphylococcus aureus, Enterococcus spp., Streptococcus spp., and Streptococcus pneumoniae could be distinguished. Using this multiprobe assay, a first identification of the causative micro-organism was given after 2 h.
Secondly, we developed a semi-molecular assay for antibiotic susceptibility testing of S. aureus, Enterococcus spp. and (facultative) aerobe Gram-negative rods6. This assay was based on a study in which PCR was used to measure the growth of bacteria7. Bacteria harvested directly from blood cultures are incubated for 6 h with a selection of antibiotics, and following a Sybr Green-based real-time PCR assay determines inhibition of growth. The combination of these two methods could direct the choice of a suitable antibiotic therapy on the same day (Figure 1). In conclusion, molecular analysis of both identification and antibiotic susceptibility offers a faster alternative for pathogen detection and could improve the diagnosis of bloodstream infections.

The design of a straightforward one-day workflow scheme for bacterial pathogen diagnostics enables the rapid recognition of bloodstream infections. The inclusion of eight clinically relevant bacterial targets and their antibiotic resistance profiles offers the clinician an initial insight on the same day, which can lead to more adequate therapy.

Bloodstream infections are associated with high mortality rates because of the probable manifestation of sepsis, severe sepsis and septic shock1. ...

Assessing Hepatic Metabolic Changes During Progressive Colonization of Germ-free Mouse by 1H NMR Spectroscopy

It is well known that gut bacteria contribute significantly to the host homeostasis, providing a range of benefits such as immune protection and vitamin synthesis. They also supply the host with a considerable amount of nutrients, making this ecosystem an essential metabolic organ. In the context of increasing evidence of the link between the gut flora and the metabolic syndrome, understanding the metabolic interaction between the host and its gut microbiota is becoming an important challenge of modern biology.1-4
 Colonization (also referred to as normalization process) designates the establishment of micro-organisms in a former germ-free animal. While it is a natural process occurring at birth, it is also used in adult germ-free animals to control the gut floral ecosystem and further determine its impact on the host metabolism. A common procedure to control the colonization process is to use the gavage method with a single or a mixture of micro-organisms. This method results in a very quick colonization and presents the disadvantage of being extremely stressful5. It is therefore useful to minimize the stress and to obtain a slower colonization process to observe gradually the impact of bacterial establishment on the host metabolism.
 In this manuscript, we describe a procedure to assess the modification of hepatic metabolism during a gradual colonization process using a non-destructive metabolic profiling technique. We propose to monitor gut microbial colonization by assessing the gut microbial metabolic activity reflected by the urinary excretion of microbial co-metabolites by 1H NMR-based metabolic profiling. This allows an appreciation of the stability of gut microbial activity beyond the stable establishment of the gut microbial ecosystem usually assessed by monitoring fecal bacteria by DGGE (denaturing gradient gel electrophoresis).6 The colonization takes place in a conventional open environment and is initiated by a dirty litter soiled by conventional animals, which will serve as controls. Rodents being coprophagous animals, this ensures a homogenous colonization as previously described.7
 Hepatic metabolic profiling is measured directly from an intact liver biopsy using 1H High Resolution Magic Angle Spinning NMR spectroscopy. This semi-quantitative technique offers a quick way to assess, without damaging the cell structure, the major metabolites such as triglycerides, glucose and glycogen in order to further estimate the complex interaction between the colonization process and the hepatic metabolism7-10. This method can also be applied to any tissue biopsy11,12.

Assessing Hepatic Metabolic Changes During Progressive Colonization of Germ-free Mouse by 1H NMR Spectroscopy

A progressive colonization procedure is described to further assess its impact on the host hepatic metabolism. Colonization is monitored non invasively by evaluating the urinary excretion of microbial co-metabolites by NMR-based metabolic profiling while hepatic metabolism is assessed by High Resolution Magic Angle Spinning (HR MAS) NMR profiling of intact biopsy.

It is well known that gut bacteria contribute significantly to the host homeostasis, providing a range of benefits such as immune protection and vitamin ...

Multiplex PCR Assay for Typing of Staphylococcal Cassette Chromosome Mec Types I to V in Methicillin-resistant Staphylococcus aureus

Staphylococcal Cassette Chromosome mec (SCCmec) typing is a very important molecular tool for understanding the epidemiology and clonal strain relatedness of methicillin-resistant Staphylococcus aureus (MRSA), particularly with the emerging outbreaks of community-associated MRSA (CA-MRSA) occurring on a worldwide basis. Traditional PCR typing schemes classify SCCmec by targeting and identifying the individual mec and ccr gene complex types, but require the use of many primer sets and multiple individual PCR experiments. We designed and published a simple multiplex PCR assay for quick-screening of major SCCmec types and subtypes I to V, and later updated it as new sequence information became available. This simple assay targets individual SCCmec types in a single reaction, is easy to interpret and has been extensively used worldwide. However, due to the sophisticated nature of the assay and the large number of primers present in the reaction, there is the potential for difficulties while adapting this assay to individual laboratories. To facilitate the process of establishing a MRSA SCCmec assay, here we demonstrate how to set up our multiplex PCR assay, and discuss some of the vital steps and procedural nuances that make it successful.

Multiplex PCR Assay for Typing of Staphylococcal Cassette Chromosome Mec Types I to V in Methicillin-resistant Staphylococcus aureus

We demonstrate a simple multiplex PCR assay for quick-screening and typing of Staphylococcal Cassette Chromosome mec (SCCmec) types I-V for methicillin-resistant Staphylococcus aureus, and provide some of the vital steps and procedural nuances that make it successful for adapting this assay to individual laboratories.

Staphylococcal Cassette Chromosome mec (SCCmec) typing  is a very important molecular tool for understanding the epidemiology and  clonal strain ...

Analysis of the Epithelial Damage Produced by Entamoeba histolytica Infection

Entamoeba histolytica is the causative agent of human amoebiasis, a major cause of diarrhea and hepatic abscess in tropical countries. Infection is initiated by interaction of the pathogen with intestinal epithelial cells. This interaction leads to disruption of intercellular structures such as tight junctions (TJ). TJ ensure sealing of the epithelial layer to separate host tissue from gut lumen. Recent studies provide evidence that disruption of TJ by the parasitic protein EhCPADH112 is a prerequisite for E. histolytica invasion that is accompanied by epithelial barrier dysfunction. Thus, the analysis of molecular mechanisms involved in TJ disassembly during E. histolytica invasion is of paramount importance to improve our understanding of amoebiasis pathogenesis. This article presents an easy model that allows the assessment of initial host-pathogen interactions and the parasite invasion potential. Parameters to be analyzed include transepithelial electrical resistance, interaction of EhCPADH112 with epithelial surface receptors, changes in expression and localization of epithelial junctional markers and localization of parasite molecules within epithelial cells.

Analysis of the Epithelial Damage Produced by Entamoeba histolytica Infection

Human infection by Entamoeba histolytica leads to amoebiasis, a major cause of diarrhea in tropical countries. Infection is initiated by pathogen interactions with intestinal epithelial cells, provoking the opening of cell-cell contacts and consequently diarrhea, sometimes followed by liver infection. This article provides a model to assess the early host-pathogen interactions to improve our understanding of amoebiasis pathogenesis.

Entamoeba histolytica is the causative agent of human amoebiasis, a major cause of diarrhea and hepatic abscess in tropical countries. Infection is ...

High Throughput, Real-time, Dual-readout Testing of Intracellular Antimicrobial Activity and Eukaryotic Cell Cytotoxicity

Traditional measures of intracellular antimicrobial activity and eukaryotic cell cytotoxicity rely on endpoint assays. Such endpoint assays require several additional experimental steps prior to readout, such as cell lysis, colony forming unit determination, or reagent addition. When performing thousands of assays, for example, during high-throughput screening, the downstream effort required for these types of assays is considerable. Therefore, to facilitate high-throughput antimicrobial discovery, we developed a real-time assay to simultaneously identify inhibitors of intracellular bacterial growth and assess eukaryotic cell cytotoxicity. Specifically, real-time intracellular bacterial growth detection was enabled by marking bacterial screening strains with either a bacterial lux operon (1st generation assay) or fluorescent protein reporters (2nd generation, orthogonal assay). A non-toxic, cell membrane-impermeant, nucleic acid-binding dye was also added during initial infection of macrophages. These dyes are excluded from viable cells. However, non-viable host cells lose membrane integrity permitting entry and fluorescent labeling of nuclear DNA (deoxyribonucleic acid). Notably, DNA binding is associated with a large increase in fluorescent quantum yield that provides a solution-based readout of host cell death. We have used this combined assay to perform a high-throughput screen in microplate format, and to assess intracellular growth and cytotoxicity by microscopy. Notably, antimicrobials may demonstrate synergy in which the combined effect of two or more antimicrobials when applied together is greater than when applied separately. Testing for in vitro synergy against intracellular pathogens is normally a prodigious task as combinatorial permutations of antibiotics at different concentrations must be assessed. However, we found that our real-time assay combined with automated, digital dispensing technology permitted facile synergy testing. Using these approaches, we were able to systematically survey action of a large number of antimicrobials alone and in combination against the intracellular pathogen, Legionella pneumophila.

A high throughput, real-time assay was developed to simultaneously identify (1) eukaryotic cell-penetrant antimicrobials targeting an intracellular bacterial pathogen, and (2) assess eukaryotic cell cytotoxicity. A variation on the same technology was thereafter combined with digital dispensing technology to enable facile, high-resolution, dose-response, and two- and three-dimensional synergy studies.

Traditional measures of intracellular antimicrobial activity and eukaryotic cell cytotoxicity rely on endpoint assays. Such endpoint assays require ...

The Ex Vivo Colon Organ Culture and Its Use in Antimicrobial Host Defense Studies

The intestine displays an architecture of repetitive crypt structures consisting of different types of epithelial cells, lamina propia containing immune cells, and stroma. All of these heterogeneous cells contribute to intestinal homeostasis and participate in antimicrobial host defense. Therefore, identifying a surrogate model for studying immune response and antimicrobial activity of the intestine in an in vitro setting is extremely challenging. In vitro studies using immortalized intestinal epithelial cell lines or even primary crypt organoid culture do not represent the exact physiology of normal intestine and its microenvironment. Here, we discuss a method of culturing mouse colon tissue in a culture dish and how this ex vivo organ culture system can be implemented in studies related to antimicrobial host defense responses. In representative experiments, we showed that colons in organ culture express antimicrobial peptides in response to exogenous IL-1&#946; and IL-18. Further, the antimicrobial effector molecules produced by the colon tissues in the organ culture efficiently kill Escherichia coli in vitro. This approach, therefore, can be utilized to dissect the role of pathogen- and danger-associated molecular patterns and their cellular receptors in regulating intestinal innate immune responses and antimicrobial host defense responses.

The Ex Vivo Colon Organ Culture and Its Use in Antimicrobial Host Defense Studies

The ex vivo organ culture allows investigation of biological processes in the context of the intact tissue architecture. Here, we introduce a method of ex vivo culture of the mouse colon, which can be used to study innate immunity and antimicrobial host defense in the intestine.

The intestine displays an architecture of repetitive crypt structures consisting of different types of epithelial cells, lamina propia containing immune ...

Isolation, Characterization, and Purification of Macrophages from Tissues Affected by Obesity-related Inflammation

Obesity promotes a chronic inflammatory state that is largely mediated by tissue-resident macrophages as well as monocyte-derived macrophages. Diet-induced obesity (DIO) is a valuable model in studying the role of macrophage heterogeneity; however, adequate macrophage isolations are difficult to acquire from inflamed tissues. In this protocol, we outline the isolation steps and necessary troubleshooting guidelines derived from our studies for obtaining a suitable population of tissue-resident macrophages from mice following 18 weeks of high-fat (HFD) or high-fat/high-cholesterol (HFHCD) diet intervention. This protocol focuses on three hallmark tissues studied in obesity and atherosclerosis including the liver, white adipose tissues (WAT), and the aorta. We highlight how dualistic usage of flow cytometry can achieve a new dimension of isolation and characterization of tissue-resident macrophages. A fundamental section of this protocol addresses the intricacies underlying tissue-specific enzymatic digestions and macrophage isolation, and subsequent cell-surface antibody staining for flow cytometric analysis. This protocol addresses existing complexities underlying fluorescent-activated cell sorting (FACS) and presents clarifications to these complexities so as to obtain broad range characterization from adequately sorted cell populations. Alternate enrichment methods are included for sorting cells, such as the dense liver, allowing for flexibility and time management when working with FACS. In brief, this protocol aids the researcher to evaluate macrophage heterogeneity from a multitude of inflamed tissues in a given study and provides insightful troubleshooting tips that have been successful for favorable cellular isolation and characterization of immune cells in DIO-mediated inflammation.

This protocol allows a researcher to isolate and characterize tissue-resident macrophages in various hallmark inflamed tissues extracted from diet-induced models of metabolic disorders.

Obesity promotes a chronic inflammatory state that is largely mediated by tissue-resident macrophages as well as monocyte-derived macrophages. ...

Automated Behavioral Analysis of Large C. elegans Populations Using a Wide Field-of-view Tracking Platform

Caenorhabditis elegans is a well-established animal model in biomedical research, widely employed in functional genomics and ageing studies. To assess the health and fitness of the animals under study, one typically relies on motility readouts, such as the measurement of the number of body bends or the speed of movement. These measurements usually involve manual counting, making it challenging to obtain good statistical significance, as time and labor constraints often limit the number of animals in each experiment to 25 or less. Since high statistical power is necessary to obtain reproducible results and limit false positive and negative results when weak phenotypic effects are investigated, efforts have recently been made to develop automated protocols focused on increasing the sensitivity of motility detection and multi-parametric behavioral profiling. In order to extend the limit of detection to the level needed to capture the small phenotypic changes that are often crucial in genetic studies and drug discovery, we describe here a technological development that enables the study of up to 5,000 individual animals simultaneously, increasing the statistical power of the measurements by about 1,000-fold compared to manual assays and about 100-fold compared to other available automated methods.

Automated Behavioral Analysis of Large C. elegans Populations Using a Wide Field-of-view Tracking Platform

We describe protocols for using the wide field-of-view nematode tracking platform (WF-NTP), which enables high-throughput phenotypic characterization of large populations of Caenorhabditis elegans. These protocols can be used to characterize subtle behavioral changes in mutant strains or in response to pharmacological treatment in a highly scalable fashion.

Caenorhabditis elegans is a well-established animal model in biomedical research, widely employed in functional genomics and ageing studies. To assess the ...

Antibiotic Efficacy Testing in an Ex vivo Model of Pseudomonas aeruginosa and Staphylococcus aureus Biofilms in the Cystic Fibrosis Lung

The effective prescription of antibiotics for the bacterial biofilms present within the lungs of individuals with cystic fibrosis (CF) is limited by a poor correlation between antibiotic susceptibility testing (AST) results using standard diagnostic methods (e.g., broth microdilution, disk diffusion, or Etest) and clinical outcomes after antibiotic treatment. Attempts to improve AST by the use of off-the-shelf biofilm growth platforms show little improvement in results. The limited ability of in vitro biofilm systems to mimic the physicochemical environment of the CF lung and, therefore bacterial physiology and biofilm architecture, also acts as a brake on the discovery of novel therapies for CF infection. Here, we present a protocol to perform AST of CF pathogens grown as mature, in vivo-like biofilms in an ex vivo CF lung model comprised of pig bronchiolar tissue and synthetic CF sputum (ex vivo&#160;pig lung, EVPL).
Several in vitro&#160;assays exist for biofilm susceptibility testing, using either standard laboratory medium or various formulations of synthetic CF sputum in microtiter plates. Both growth medium and biofilm substrate (polystyrene plate vs. bronchiolar tissue) are likely to affect biofilm antibiotic tolerance. We show enhanced tolerance of clinical Pseudomonas aeruginosa and Staphylococcus aureus isolates in the ex vivo model; the effects of antibiotic treatment of biofilms is not correlated with the minimum inhibitory concentration (MIC) in standard microdilution assays or a sensitive/resistant classification in disk diffusion assays.
The ex vivo platform could be used for bespoke biofilm AST of patient samples and as an enhanced testing platform for potential antibiofilm agents during pharmaceutical research and development. Improving the prescription or acceleration of antibiofilm drug discovery through the use of more in vivo-like testing platforms could drastically improve health outcomes for individuals with CF, as well as reduce the costs of clinical treatment and discovery research.

Antibiotic Efficacy Testing in an Ex vivo Model of Pseudomonas aeruginosa and Staphylococcus aureus Biofilms in the Cystic Fibrosis Lung

This workflow can be used to perform antibiotic susceptibility testing using an established&#160;ex vivo model of bacterial biofilm in the lungs of individuals with cystic fibrosis. Use of this model could enhance the clinical validity of MBEC (minimal biofilm eradication concentration) assays.

The effective prescription of antibiotics for the bacterial biofilms present within the lungs of individuals with cystic fibrosis (CF) is limited by a ...