The authors would like to thank the team of Symcel for fruitful discussions and we would like to acknowledge the great support from Ganna Oliynyk and Wilhelm Paulander. We would also like to thank Daniel Kohnh&#228;user for providing the natural product and Stefanie Schmidt for skillful technical support.

NOTE: The instrument temperature must be set according to the bacterium used at least a day in advance to ensure stability of the system. Here, Acinetobacter baumannii DSM30008 samples are run at 30 &#176;C.
1. Culture preparation
<ol>
	<li>Streak out the strain under investigation (here: A. baumannii) on a CASO agar plate and incubate overnight in a static incubator at 30 &#176;C.</li>
	<li>Prepare an overnight culture by inoculating a single colony in MHB (Mueller-Hinton broth) and incubate on a shaking incubator at 180 rpm at 30 &#176;C.</li>
</ol>
2. Sample preparation
<ol>
	<li>Use 1.5 mL tubes to prepare the concentration range of selected drug or compound (e.g., by adding 1.5 &#181;L of 100x stock solutions in DMSO; see step 2.3).</li>
	<li>Dilute the overnight culture in MHB medium.
	<ol>
		<li>Measure the optical density of the overnight culture using a spectrophotometer at a wavelength of 600 nm.</li>
		<li>Dilute the culture to obtain 5 x 105 colony-forming units (CFU)/mL in fresh MHB medium. An OD600 of one equals approximately 5 x 108 CFU/mL (e.g., Escherichia coli, Staphylococcus aureus, A. baumannii). 
		NOTE: It is important to calibrate the conversion factor OD600 to CFU/mL for each individual bacterial strain under the applied culturing conditions.</li>
	</ol>
	</li>
	<li>Add 150 &#181;L of the cells to the test tubes prepared in step 2.1, ensuring correct final concentration of tested drug or compound and correct final cell concentration.</li>
	<li>Mix the compound with the cells by vortexing. 
	NOTE: The sample plate (see Table of Materials) has six rows, each containing eight wells, a total of 48-wells; Row A and Row F are the thermodynamic reference. Therefore, no samples can be loaded into those wells, corresponding media is loaded into those wells. 32 test samples can be measured per run, using wells in rows B-E. Individual test sample should be run at minimum in duplicate (here: all samples were run as triplicates). Growth controls should be included.</li>
</ol>
3. Insert preparation
<ol>
	<li>Transfer 120 &#181;L from the mixture prepared in step 2.4 to the plastic inserts. 
	NOTE: Use reverse pipetting in step 3.1 to prevent liquid from spraying on the sides of the plastic inserts, which can lead to interference with correct signal readouts.</li>
	<li>Place all titanium vials into the holders (see Table of Materials) with tweezers.</li>
	<li>Gently transfer inserts into the titanium vials in the holder plate.</li>
	<li>Loosely place titanium lids on all titanium vials.</li>
</ol>
4. Insert loading
<ol>
	<li>Transfer the holder with titanium cups onto the sample station and place on designated area.</li>
	<li>Use the torque wrench, set to 40 cNm force, to tighten all the lids.</li>
</ol>
5. Running of samples
<ol>
	<li>In calView software, start a new experiment (Supplemental Figure 1).</li>
	<li>Retract the sample insertion arm from the instrument.</li>
	<li>Place the cup holder on the &#8220;bridge&#8221;, column 8 facing the sample insertion opening and gently push the cup holder into the instrument at the designated &#8220;Position 1&#8221;. Wait 10 minutes for the system to stabilize. Label the experimental wells.</li>
	<li>Push the sample insertion arm until the cup holder is at the designated &#8220;Position 2&#8221;. Wait 20 minutes for the system to stabilize.</li>
	<li>Push the sample insertion arm into &#8220;Position 3&#8221; and retract the sample insertion arm until it is at the &#8220;Running position&#8221;. Highlight all the wells in the software and select Reaction Start (Supplemental Figure 4).</li>
	<li>Run the experiment until the heat emission reads are stably back at zero. 
	NOTE: Be sure that all wells behave similar within these steps. Supplemental Figure 5 illustrates what should be observed if the wells are loaded correctly. If loaded incorrectly, repeat steps 5.2-5.4.</li>
</ol>
6. Remove the cup holder
<ol>
	<li>In the software, select Stop (Supplemental Figure 6). The software will then ask if &#8220;you are sure&#8221;, select Yes (Supplemental Figure 7) and save the experiment on a drive or desktop for data analysis (Supplemental Figure 8).</li>
	<li>Insert the sample insertion arm completely into the instrument and engage the magnets to retrieve the cup holder.</li>
	<li>Loosen the lids, remove the inserts and place vials and lids into glass holders and place for 4 hours at 180 &#176;C followed by placing the vials and lids into a desiccator to ensure lids and vials are dry.</li>
</ol>
7. Analyzing data
<ol>
	<li>Open the software (Supplemental Figure 9), select Open experiment in the left upper corner (Supplemental Figure 10). In the popup window select the experiment of interest and press Open (Supplemental Figure 11). The application will open the experiment in default wells view (Supplemental Figure 12).</li>
	<li>Press Select all or Ctrl+A (Supplemental Figure 13).</li>
	<li>Press Define Baseline, this parameter normalizes the data in each position (Supplemental Figure 14). In the popup window select a time period of &#62;30 min located in the lag phase (the heat flow has to be low, between zero and ten &#181;W; Supplemental Figure 15). After selection of base line time period the chosen baseline will appear in green in the thermogram. Close the Define Baseline Section window.</li>
	<li>Press Save or Ctrl+S and close the software (Supplemental Figure 16).</li>
	<li>Open web-based Symcel Calorimetry analysis application (https://symcel.shinyapps.io/symcel_calorimetricgrowth/).</li>
	<li>To upload the file to the Calorimetry analysis application, press Browse (Supplemental Figure 17), select the experiment and press Open (Supplemental Figure 18). The metabolic parameters will be calculated automatically for the 32 samples in the web application (Supplemental Figure 19).</li>
	<li>In order to fit the heat Flow data to Gompertz and/or Richard&#180;s growth models click Growth Function. Growth models fit will be displayed in the section &#8220;Cumulative&#8221;, also compared to the raw data in the section &#8220;Flow&#8221; (Supplemental Figure 20).</li>
	<li>To download all calculated parameters, press Download Measures. Select the file location and press Save (Supplemental Figure 21). The file will be exported to a spreadsheet for further calculations.</li>
</ol>

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G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Drug+Target+Screening+and+its+Validation+by+Zebrafish+as+a+Novel+Tool.">Drug Target Screening and its Validation by Zebrafish as a Novel Tool.</a> Pharmaceutica Analytica Acta. 6 (10), 426 (2015).</li><li>Kraus, J., Tobin, G., Development, M., Kulka, <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Discovery,+Deveopment,+and+Regulation+of+Natural+Products.">Discovery, Deveopment, and Regulation of Natural Products.</a> Using Old Solutions to New Problems - Natural Drug Discovery in the 21st Century. , 4-36 (2013).</li><li>Tabassum, N., Tai, H., Jung, D., Williams, D. 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U. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Use+of+isothermal+microcalorimetry+to+monitor+microbial+activities.">Use of isothermal microcalorimetry to monitor microbial activities.</a> FEMS Microbiology Letter. 303 (1), 1-8 (2010).</li><li>Braissant, O., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Isothermal+microcalorimetry+accurately+detects+bacteria,+tumorous+microtissues,+and+parasitic+worms+in+a+label-free+well-plate+assay.">Isothermal microcalorimetry accurately detects bacteria, tumorous microtissues, and parasitic worms in a label-free well-plate assay.</a> Biotechnology Journal. 10 (3), 460-468 (2015).</li><li>Butini, M. 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U. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Isothermal+micro+calorimetry+-+a+new+method+for+MIC+determinations:+results+for+12+antibiotics+and+reference+strains+of+E.+coli+and+S.+aureus.">Isothermal micro calorimetry - a new method for MIC determinations: results for 12 antibiotics and reference strains of E. coli and S. aureus.</a> BMC Microbiology. 9 (106), (2009).</li><li>Howell, M., Wirz, D., Daniels, A. U., Braissant, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Application+of+a+Microcalorimetric+Method+for+Determining+Drug+Susceptibility+in+Mycobacterium+Species.">Application of a Microcalorimetric Method for Determining Drug Susceptibility in Mycobacterium Species.</a> Journal of Clinical Microbiology. 50 (1), (2012).</li><li>Wads&#246;, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Isothermal+Microcalorimetry:+Current+problems+and+prospects.">Isothermal Microcalorimetry: Current problems and prospects.</a> Journal of Thermal Analysis and Calorimetry. 64 (2001), 75-84 (2001).</li><li>LeBel, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ciprofloxacin:+chemistry,+mechanism+of+action,+resistance,+antimicrobial+spectrum,+pharmacokinetics,+clinical+trials,+and+adverse+reactions.">Ciprofloxacin: chemistry, mechanism of action, resistance, antimicrobial spectrum, pharmacokinetics, clinical trials, and adverse reactions.</a> Pharmacotherapy. 8 (1), 3-33 (1988).</li><li>Chopra, I., Roberts, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tetracycline+antibiotics:+mode+of+action,+applications,+molecular+biology,+and+epidemiology+of+bacterial+resistance.">Tetracycline antibiotics: mode of action, applications, molecular biology, and epidemiology of bacterial resistance.</a> Microbiology and Molecular Biology Reviews. 65 (2), 232-260 (2001).</li><li>Allison, J. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mode+of+action+of+chloramphenicol.+VII.+Growth+and+multiplication+of+Escherichia+coli+in+the+presence+of+chloramphenicol.">Mode of action of chloramphenicol. VII. Growth and multiplication of Escherichia coli in the presence of chloramphenicol.</a> Journal of Bacteriology. 83 (3), 609-615 (1962).</li><li>Wehrli, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rifampin:+mechanisms+of+action+and+resistance.">Rifampin: mechanisms of action and resistance.</a> Reviews of Infectious Diseases. 5, 407-411 (1983).</li><li>Hancock, R. E. 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The project was performed in collaboration with Symcel, developer of the calScreener technology. The authors have nothing to disclose.

Isothermal microcalorimetry measures energy emitted from a specimen over time and this energy release is a result of all biological, physical and (bio-)chemical processes. The measured heat flow can be exploited to evaluate or determine antibacterial effects of substances as it enables continuous real-time monitoring of metabolic activity.
In order to obtain reliable data for analysis, correct starting colony-forming units (CFU) need to be determined individually for each species or strain used. In case the CFU count is too low, this leads to a prolonged lag phase as it takes longer for the system to reach a critical amount of biomass producing enough heat to be detected. In case the CFU count is too high the lag phase will be very short, and the amount of heat produced can cause heat transfer to neighboring sensor cells (reference and experimental wells) and cause distortions of the thermograms. High numbers of CFU will also lead to a faster oxygen depletion and switch to anaerobic conditions. It also has to be taken into account that during the first 30 minutes of the experiment, when the system is equilibrating, data collection is not possible and the actual recording of effects is delayed. In addition, incorrect CFU determination leads to false MIC determination, ultimately affecting the experiment and the changes observed25. Another critical point is the correct determination of the baseline. Usually, the baseline signal is selected during the lag phase when the heat flow signal is zero and ideally, the time range for baseline definition is &#62;30 min. However, this is not always possible as the time that the bacteria requires to reach the heat signal detection limit differs between strains and species. Some species or strains require more than 30 minutes to reach the heat signal detection limit while other strains or species reach it within the first 30 minutes. In that case, it is possible to select the baseline signal at the end of the experiment when all the heat signals have dropped back to zero and remain stable. Alternatively, baselines from other experiments with the same bacterial strain can be used, which is however not recommended.
The system allows for some flexibility in terms of design and optimization of experiments and troubleshooting. Volumes used are in the range of 100-300 &#181;L when using plastic inserts and 100-600 &#181;L when using titanium cups without the plastic inserts. The recommended working volume by the manufacturer is 120 &#181;L. The use of different volumes in setting up a new experimental series, and while finding optimal conditions for measurements, has an impact mainly on two parameters. By using lower volumes, the amount of required test compound can be decreased, which is particularly important for compounds, which are available only in small amounts. In addition, the used volume directly impacts oxygen availability during the measurement with lower volumes increasing the amount of available oxygen required for bacterial growth. Oxygen depletion is one of the main factors contributing to the maximum possible duration of the experiment. Importantly, it is possible to use solid media, not only liquid media. This is especially important for slow-growing microorganisms as growth on the interface between solid and gas phase enables better oxygen access9.
IMC is a useful analytic tool to discover unknown processes with applications in physics, chemistry and biology. The method measures the heat exchange within a closed system and analysis of the recorded heat exchange provides additional information that cannot always be obtained with standard methods. In microbiology and antibiotics research, one of the biggest advantages of IMC is its ability to distinguish between live, dead and persister or dormant cells, which is not possible using standard turbidity methods11. In addition, IMC is highly sensitive and it can detect heat emission from as few as 104-105 cells9. Another advantage is that the experimental setup is fast and easy, and it allows for continuous, real-time tracking with minimal to no user interference. Further, IMC is non-destructive, which enables further analysis of samples. Data analysis allows for decoupling of biomass formation until late exponential or early stationary phase and metabolic activity in stationary phase.
Besides the novel and exciting application features mentioned above, there are also drawbacks to this method. The major limitation is that IMC instruments measure the total heat produced and released within a specific system, which also include non-specific signals. This highlights the importance of experimental planning with appropriate controls to be able to assess the heat signal changes that are measured by recording heat flow9,20.
In our hands, IMC is an important tool to study antibacterial effects of new natural products and to determine effective concentration ranges. Apart from differentiating bacteriostatic and bactericidal effects, it could be used in future as part of target identification studies and MoA determination. This can be done by comparing thermograms of different antibiotic classes to thermograms of new active compounds as displayed here. However, it still has to be investigated whether certain quantifiable parameters that can be extracted from the measured data are sufficient for such comparisons or if it will be necessary to work on algorithms giving fingerprints based on full thermograms. Another possible application in the field of antibiotic research is the comparison of wildtype to resistant clones, coupled with whole genome sequencing, which can help elucidating the mode-of-resistance (MoR) of new antibacterials. Because of the static nature of the method, investigation of efficacy of new agents on either biofilm formation or on already established biofilms could lead to better understanding of the biological process and the effect of selected agents on microbes in different stages of dormancy. IMC records total energy released in the form of heat making it a suitable method to investigate also sub-inhibitory effects of active substances that might be coupled to transcriptomics. This method can also be used in clinical settings to detect contamination of samples or for the determination of antibiograms helping to rapidly decide on definite treatment of the patients11.

The aim of this method is to apply isothermal microcalorimetry (IMC) as a medium throughput assay in mode-of-action (MoA) profiling of new antibacterial compounds. This method reveals data regarding the activity of compounds on bacterial species and provides information on the bactericidal or bacteriostatic nature of the compound itself.
The rise of emerging antimicrobial resistance (AMR) is a global problem and it leads to less effective treatments of common infections with known antibiotics1. However, the search for new compounds and drugs that can replace or work in combination with known antibiotics are ongoing and this is built on diverse approaches. Natural products are a key player in current drug discovery campaigns and particularly in anti-infective drug discovery2. However, identifying new lead structures for antibiotic development is a lengthy and financially demanding process3. Thus, the early steps of discovery are extremely important in order to filter on most promising scaffolds already at an early stage. Initial steps in natural product drug discovery include obtaining a compound&#8217;s structure, determining the activity in vitro along with MoA and target identification. Most successful compounds being eligible for further development should display a favorable spectrum of activity (i.e., broad-spectrum activity in the case of antibacterials) and a novel MoA by which pre-existing AMR can be overcome. Promising scaffolds are then typically screened in secondary assays, which include in vivo bioavailability, toxicity, and metabolism4. Besides the financial concerns, natural product drug discovery faces further challenges concerning the costs and technical difficulties related to compound isolation and purification, which, in turn, can make it difficult to obtain multi-milligram or even gram amounts in the early stages of the discovery process5,6. Therefore, it is of utmost importance in natural product research to be able to perform state-of-the-art primary screening with minimal compound amounts in order to take a well-informed decision about further investments to make a novel natural product accessible for pre-clinical development. With the use of IMC for antibacterial profiling, the amount of compound needed is significantly reduced in comparison to standard methods. The technique also provides more in-depth information regarding the interaction of new drugs with the microbial community7.
IMC is a well-established method for measuring total energy as a result of all biological, physical and biochemical processes and reactions in a biological system. Bacterial energy release is proportional to the total metabolic reactions8. Within a closed system, such as the used microcalorimeter, the heat levels can be measured in the microwatt range to study the metabolic kinetics of bacteria9,10,11,12. The heat (energy) that is released by bacteria is linked to cellular functions that underlie their metabolism and that are not necessarily proportional to the cellular biomass.
Initially, the applicability of isothermal calorimetry for microbiological assays has been limited due to its low throughput and high testing volumes. However, the used microcalorimeter is unique as it combines the advantages of isothermal calorimetry with increased throughput and lower compound requirements, which makes it a valuable tool for drug discovery applications10. Furthermore, the instrument provides further advantages over alternative methods for measuring bacterial growth kinetics, such as the standard turbidity method, which is based on the measurement of optical density at 600 nm (OD&#60;600). Measuring OD600 is based on the assumption that increased optical density is equal to microbial growth, thereby neglecting the presence of non-viable cells. This method has also been criticized as it excludes small colony variants and persister cells11. In contrast, IMC allows the real-time observation of any type of viable cells. If cells are dormant, they still exhibit metabolic activity and they can thus be detected by IMC, whereas such phenomena are not detectable by the standard turbidity method11. Other advantages of IMC include a shorter antimicrobial susceptibility testing time, measuring drug interactions in a complex community and standard analysis methods without destroying the sample7.
The IMC technology has been implemented in a wide range of studies, ranging from microbiology to thermogenesis and cancer biology13,14,15,16,17. The microbial applications include the determination of minimum inhibitory concentrations (MIC) of compounds against various bacterial strains. Several studies have been done and it has been concluded that MIC data from isothermal calorimetry for the majority of bacterial species can be obtained faster and results are similar compared to other (standard) methods for MIC determination12,18,19. Further applications of IMC include observing the interaction of drugs and combination of drug treatments with complex bacterial communities such as biofilms11. A study focusing on MoA profiling showed that the microcalorimeter can detect a difference in first- and second-generation cephalosporins, while different antibiotics with the same MoA exhibit a similar heat flow curve compared to each other18.
Here, we describe the use of IMC for MoA profiling of new natural products using the new isothermal microcalorimetry instrument. The method is used to determine effective antibiotic concentrations and to describe characteristics of antibiotics in terms of bactericidal or bacteriostatic mechanisms. The method can be broadly implemented in MoA profiling of compounds and it might replace or at least complement standard microbiological methods. Future studies will include in-depth fingerprint analyses that will enable the differentiation of antibiotic classes based on target mechanisms.

<table>
	<tbody>
		<tr>
			<td>Acinetobacter baumannii </td>
			<td>DSMZ</td>
			<td>DSM-30008</td>
			<td>reference strain used in this study</td>
		</tr>
		<tr>
			<td>calPlate</td>
			<td>Symcel</td>
			<td>1220093</td>
			<td>48-well plate for titanium cups to be inserted</td>
		</tr>
		<tr>
			<td>calScreener</td>
			<td>Symcel</td>
			<td>1200001</td>
			<td>isothermal microcalorimetry instrument</td>
		</tr>
		<tr>
			<td>calView software</td>
			<td>Symcel</td>
			<td></td>
			<td>collection and analysis software</td>
		</tr>
		<tr>
			<td>calWell</td>
			<td>Symcel</td>
			<td>1901004</td>
			<td>micro-bio grade (non-active) 48-well plate with plastic inserts which are inserted into the titanium cups</td>
		</tr>
		<tr>
			<td>CASO agar</td>
			<td>Carl Roth</td>
			<td>X937.1</td>
			<td>isolation and cultivation of microorganisms</td>
		</tr>
		<tr>
			<td>Chloroamphenicol</td>
			<td>Sigma-Aldrich</td>
			<td>C0378</td>
			<td>antibiotic</td>
		</tr>
		<tr>
			<td>Ciprofloxacin</td>
			<td>Sigma-Aldrich</td>
			<td>17850</td>
			<td>antibiotic</td>
		</tr>
		<tr>
			<td>Cuvettes</td>
			<td>Brand</td>
			<td>759015</td>
			<td>1.5 mL cuvettes</td>
		</tr>
		<tr>
			<td>Disposable inoculation loops</td>
			<td>Sarsted</td>
			<td>86.1562.050</td>
			<td>10 &#181;L inoculation loops</td>
		</tr>
		<tr>
			<td>Dimethylsulfoxid (DMSO)</td>
			<td>Thermo Fisher Scientific</td>
			<td>85190</td>
			<td></td>
		</tr>
		<tr>
			<td>Eppendorf tubes</td>
			<td>Eppendorf</td>
			<td>30120086</td>
			<td>1.5 mL eppendorf safe-lock tubes</td>
		</tr>
		<tr>
			<td>Ethanol</td>
			<td>Thermo Fisher Scientific</td>
			<td>10428671</td>
			<td></td>
		</tr>
		<tr>
			<td>Falcon Tubes</td>
			<td>Sarsted</td>
			<td>62.554.502</td>
			<td>15 mL falcon tubes</td>
		</tr>
		<tr>
			<td>Hydrochloride (HCL)</td>
			<td>Thermo Fisher Scientific</td>
			<td>10316380</td>
			<td></td>
		</tr>
		<tr>
			<td>Methanol</td>
			<td>Thermo Fisher Scientific</td>
			<td>A412-500</td>
			<td></td>
		</tr>
		<tr>
			<td>Mueller Hinton Broth</td>
			<td>Sigma-Aldrich</td>
			<td>70192</td>
			<td>liquid medium for antibiotic susceptibility studies</td>
		</tr>
		<tr>
			<td>Mueller Hinton Broth II cation adjusted media</td>
			<td>Sigma-Aldrich</td>
			<td>90922</td>
			<td>Mueller Hinton Broth cation-adjusted to 1.25 mM CaCl2, 0.8 mM MgCl2</td>
		</tr>
		<tr>
			<td>Petri dishes</td>
			<td>LABSOLUTE</td>
			<td>7696404</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipette 100 - 1000 &#181;L</td>
			<td>Brand</td>
			<td>705880</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipette 2 - 20 &#181;L</td>
			<td>Brand</td>
			<td>705872</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipette 20 - 200 &#181;L</td>
			<td>Brand</td>
			<td>705878</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipette tips 100 - 1000 L</td>
			<td>Brand</td>
			<td>732032</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipette tips 2 - 200 &#181;L</td>
			<td>Brand</td>
			<td>732028</td>
			<td></td>
		</tr>
		<tr>
			<td>Polymyxin B sulfate</td>
			<td>Sigma-Aldrich</td>
			<td>P0972</td>
			<td>antibiotic</td>
		</tr>
		<tr>
			<td>Rifampicin</td>
			<td>Sigma-Aldrich</td>
			<td>R3501</td>
			<td>antibiotic</td>
		</tr>
		<tr>
			<td>Serological pipette</td>
			<td>Thermo Fisher Scientific</td>
			<td>170356N</td>
			<td>10 mL Nunc serological pipette</td>
		</tr>
		<tr>
			<td>Spectrophotometer</td>
			<td>Eppendorf AG</td>
			<td>6135 000.017</td>
			<td></td>
		</tr>
		<tr>
			<td>Sterile filters</td>
			<td>Minisart</td>
			<td>16534----------K</td>
			<td>0.2 &#181;m pore size sterile filters</td>
		</tr>
		<tr>
			<td>Syringe 50 mL</td>
			<td>NORM-JECT</td>
			<td>22778</td>
			<td></td>
		</tr>
		<tr>
			<td>Tetracycline</td>
			<td>Sigma-Aldrich</td>
			<td>87128</td>
			<td>antibiotic</td>
		</tr>
		<tr>
			<td>Titanium cups</td>
			<td>Symcel</td>
			<td>1220089</td>
			<td>inserted in 48-well titanium calPlate</td>
		</tr>
		<tr>
			<td>Titanium lids</td>
			<td>Symcel</td>
			<td>1220091</td>
			<td>screwed and tightend to the titanium cups</td>
		</tr>
		<tr>
			<td>Trimethroprim</td>
			<td>Sigma-Aldrich</td>
			<td>T7883</td>
			<td>antibiotic</td>
		</tr>
		<tr>
			<td>Tweezers</td>
			<td>Symcel</td>
			<td>1900602</td>
			<td></td>
		</tr>
	</tbody>
</table>

metabolic profiling to determine bactericidal or bacteriostatic effects of new natural products using isothermal microcalorimetry

Due to the global threat of rising antimicrobial resistance, novel antibiotics are urgently needed. We investigate natural products from Myxobacteria as an&#160;innovative source of such new compounds. One bottleneck in the process is typically the elucidation of their mode-of-action. We recently established isothermal microcalorimetry as part of a routine profiling pipeline. This technology allows for investigating the effect of antibiotic exposure on the total bacterial metabolic response, including processes that are decoupled from biomass formation. Importantly, bacteriostatic and bactericidal effects are easily distinguishable without any user intervention during the measurements. However, isothermal microcalorimetry is a rather new approach and applying this method to different bacterial species usually requires pre-evaluation of suitable measurement conditions. There are some reference thermograms available of certain bacteria, greatly facilitating interpretation of results. As the pool of reference data is steadily growing, we expect the methodology to have increasing impact in the future and expect it to allow for in-depth fingerprint analyses enabling the differentiation of antibiotic classes.

Watch this Scientific Journal Video about Metabolic Profiling to Determine Bactericidal or Bacteriostatic Effects of New Natural Products using Isothermal Microcalorimetry at JoVE.com

Metabolic Profiling to Determine Bactericidal or Bacteriostatic Effects of New Natural Products using Isothermal Microcalorimetry

The elucidation of the mode-of-action of a novel antibiotic is a challenging task in the drug discovery process. The goal of the method described here is the application of isothermal microcalorimetry using calScreener in antibacterial profiling to provide additional insight into drug-microbe interactions.

Due to the global threat of rising antimicrobial resistance, novel antibiotics are urgently needed. We investigate natural products from Myxobacteria as ...

metabolic-profiling-to-determine-bactericidal-or-bacteriostatic

Research

JoVE Journal

Bioengineering

8.5K Views.  Saarland University. The elucidation of the mode-of-action of a novel antibiotic is a challenging task in the drug discovery process. The goal of the method described here is the application of isothermal microcalorimetry using calScreener in antibacterial profiling to provide additional insight into drug-microbe interactions.

Video: Metabolic Profiling to Determine Bactericidal or Bacteriostatic Effects of New Natural Products using Isothermal Microcalorimetry

Improved Visualization and Quantitative Analysis of Drug Effects Using Micropatterned Cells

To date, most HCA (High Content Analysis) studies are carried out with adherent cell lines grown on a homogenous substrate in tissue-culture treated micro-plates. Under these conditions, cells spread and divide in all directions resulting in an inherent variability in cell shape, morphology and behavior. The high cell-to-cell variance of the overall population impedes the success of HCA, especially for drug development. The ability of micropatterns to normalize the shape and internal polarity of every individual cell provides a tremendous opportunity for solving this critical bottleneck 1-2.
To facilitate access and use of the micropatterning technology, CYTOO has developed a range of ready to use micropatterns, available in coverslip and microwell formats. In this video article, we provide detailed protocols of all the procedures from cell seeding on CYTOOchip micropatterns, drug treatment, fixation and staining to automated acquisition, automated image processing and final data analysis. With this example, we illustrate how micropatterns can facilitate cell-based assays. Alterations of the cell cytoskeleton are difficult to quantify in cells cultured on homogenous substrates, but culturing cells on micropatterns results in a reproducible organization of the actin meshwork due to systematic positioning of the cell adhesion contacts in every cell. Such normalization of the intracellular architecture allows quantification of even small effects on the actin cytoskeleton as demonstrated in these set of protocols using blebbistatin, an inhibitor of the actin-myosin interaction.

Adhesive micropatterns that normalize cellular architecture can be used to increase sensitivity in the detection of drug effects, improve reproducibility and simplify automated image acquisition and analysis. Such technology will benefit drug/siRNA screening assays, performed on conventional cell culture supports and consequently suffering from excessive cell-to-cell variability.

To date, most HCA (High Content Analysis) studies are carried out with adherent cell lines grown on a homogenous substrate in tissue-culture treated ...

FIBS-enabled Noninvasive Metabolic Profiling

In the era of computational biology, new high throughput experimental systems are necessary in order to populate and refine models so that they can be validated for predictive purposes. Ideally such systems would be low volume, which precludes sampling and destructive analyses when time course data are to be obtained. What is needed is an in situ monitoring tool which can report the necessary information in real-time and noninvasively. An interesting option is the use of fluorescent, protein-based in vivo biological sensors as reporters of intracellular concentrations. One particular class of in vivo biosensors that has found applications in metabolite quantification is based on F&#246;rster Resonance Energy Transfer (FRET) between two fluorescent proteins connected by a ligand binding domain. FRET integrated biological sensors (FIBS) are constitutively produced within the cell line, they have fast response times and their spectral characteristics change based on the concentration of metabolite within the cell. In this paper, the method for constructing Chinese hamster ovary (CHO) cell lines that constitutively express a FIBS for glucose and glutamine and calibrating the FIBS in vivo in batch cell culture in order to enable future quantification of intracellular metabolite concentration is described. Data from fed-batch CHO cell cultures demonstrates that the FIBS was able in each case to detect the resulting change in the intracellular concentration. Using the fluorescent signal from the FIBS and the previously constructed calibration curve, the intracellular concentration was accurately determined as confirmed by an independent enzymatic assay.

A description of how to calibrate F&#246;rster Resonance Energy Transfer integrated biological sensors (FIBS) for in situ metabolic profiling is presented.&#160;The FIBS can be used to measure intracellular levels of metabolites noninvasively aiding in the development of metabolic models and high throughput screening of bioprocess conditions.

In the era of computational biology, new high throughput experimental systems are necessary in order to populate and refine models so that they can be ...

Using Cell-substrate Impedance and Live Cell Imaging to Measure Real-time Changes in Cellular Adhesion and De-adhesion Induced by Matrix Modification

Cell-matrix adhesion plays a key role in controlling cell morphology and signaling. Stimuli that disrupt cell-matrix adhesion (e.g., myeloperoxidase and other matrix-modifying oxidants/enzymes released during inflammation) are implicated in triggering pathological changes in cellular function, phenotype and viability in a number of diseases. Here, we describe how cell-substrate impedance and live cell imaging approaches can be readily employed to accurately quantify real-time changes in cell adhesion and de-adhesion induced by matrix modification (using endothelial cells and myeloperoxidase as a pathophysiological matrix-modifying stimulus) with high temporal resolution and in a non-invasive manner. The xCELLigence cell-substrate impedance system continuously quantifies the area of cell-matrix adhesion by measuring the electrical impedance at the cell-substrate interface in cells grown on gold microelectrode arrays. Image analysis of time-lapse differential interference contrast movies quantifies changes in the projected area of individual cells over time, representing changes in the area of cell-matrix contact. Both techniques accurately quantify rapid changes to cellular adhesion and de-adhesion processes. Cell-substrate impedance on microelectrode biosensor arrays provides a platform for robust, high-throughput measurements. Live cell imaging analyses provide additional detail regarding the nature and dynamics of the morphological changes quantified by cell-substrate impedance measurements. These complementary approaches provide valuable new insights into how myeloperoxidase-catalyzed oxidative modification of subcellular extracellular matrix components triggers rapid changes in cell adhesion, morphology and signaling in endothelial cells. These approaches are also applicable for studying cellular adhesion dynamics in response to other matrix-modifying stimuli and in related adherent cells (e.g., epithelial cells).

Here, we present a protocol to continuously quantify cell adhesion and de-adhesion processes with high temporal resolution in a non-invasive manner by cell-substrate impedance and live cell imaging analyses. These approaches reveal the dynamics of cell adhesion/de-adhesion processes triggered by matrix modification and their temporal relationship to adhesion-dependent signaling events.

Cell-matrix adhesion plays a key role in controlling cell morphology and signaling. Stimuli that disrupt cell-matrix adhesion (e.g., myeloperoxidase and ...

Metabolic Glycoengineering of Sialic Acid Using N-acyl-modified Mannosamines

Sialic acid (Sia) is a highly important constituent of glycoconjugates, such as N- and O-glycans or glycolipids. Due to its position at the non-reducing termini of oligo- and polysaccharides, as well as its unique chemical characteristics, sialic acid is involved in a multitude of different receptor-ligand interactions. By modifying the expression of sialic acid on the cell surface, sialic acid-dependent interactions will consequently be influenced. This can be helpful to investigate sialic acid-dependent interactions and has the potential to influence certain diseases in a beneficial way. Via metabolic glycoengineering (MGE), the expression of sialic acid on the cell surface can be modulated. Herein, cells, tissues, or even entire animals are treated with C2-modified derivatives of N-acetylmannosamine (ManNAc). These amino sugars act as sialic acid precursor molecules and therefore are metabolized to the corresponding sialic acid species and expressed on glycoconjugates. Applying this method produces intriguing effects on various biological processes. For example, it can drastically reduce&#160;the expression of polysialic acid (polySia) in treated neuronal cells and thus affects neuronal growth and differentiation. Here, we show the chemical synthesis of two of the most common C2-modified N-acylmannosamine derivatives, N-propionylmannosamine (ManNProp) as well as N-butanoylmannosamine (ManNBut), and further show how these non-natural amino sugars can be applied in cell culture experiments. The expression of modified sialic acid species is quantified by high performance liquid chromatography (HPLC) and further analyzed via mass spectrometry. The effects on polysialic acid expression are elucidated via Western blot using a commercially available polysialic acid antibody.

Metabolic Glycoengineering of Sialic Acid Using N-acyl-modified Mannosamines

Sialic acid is a typical monosaccharide-unit found in glycoconjugates. It is involved in a plethora of molecular and cellular interactions. Here we present a method to modify cell surface sialic acid expression using metabolic glycoengineering with N-acetylmannosamine derivatives.

Sialic acid (Sia) is a highly important constituent of glycoconjugates, such as N- and O-glycans or glycolipids. Due to its position at the non-reducing ...

Patterning Bioactive Proteins or Peptides on Hydrogel Using Photochemistry for Biological Applications

There are many biological stimuli that can influence cell behavior and stem cell differentiation. General cell culture approaches rely on soluble factors within the medium to control cell behavior. However, soluble additions cannot mimic certain signaling motifs, such as matrix-bound growth factors, cell-cell signaling, and spatial biochemical cues, which are common influences on cells. Furthermore, biophysical properties of the matrix, such as substrate stiffness, play important roles in cell fate, which is not easily manipulated using conventional cell culturing practices. In this method, we describe a straightforward protocol to provide patterned bioactive proteins on synthetic polyethylene glycol (PEG) hydrogels using photochemistry. This platform allows for the independent control of substrate stiffness and spatial biochemical cues. These hydrogels can achieve a large range of physiologically relevant stiffness values. Additionally, the surfaces of these hydrogels can be photopatterned with bioactive peptides or proteins via thiol-ene click chemistry reactions. These methods have been optimized to retain protein function after surface immobilization. This is a versatile protocol that can be applied to any protein or peptide of interest to create a variety of patterns. Finally, cells seeded onto the surfaces of these bioactive hydrogels can be monitored over time as they respond to spatially specific signals.

In this method, we use photopolymerization and click chemistry techniques to create protein or peptide patterns on the surface of polyethylene glycol (PEG) hydrogels, providing immobilized bioactive signals for the study of cellular responses in vitro.

There are many biological stimuli that can influence cell behavior and stem cell differentiation. General cell culture approaches rely on soluble factors ...

Manufacturing of a Nafion-coated, Reduced Graphene Oxide/Polyaniline Chemiresistive Sensor to Monitor pH in Real-time During Microbial Fermentation

Here, we report the engineering of a solid-state micro pH sensor based on polyaniline-functionalized, electrochemically reduced graphene oxide (ERGO-PA). Electrochemically reduced graphene oxide acts as the conducting layer and polyaniline acts as a pH-sensitive layer. The pH-dependent conductivity of polyaniline occurs by doping of holes during protonation and by the dedoping of holes during deprotonation. We found that an ERGO-PA solid-state electrode was not functional as such in fermentation processes. The electrochemically active species that the bacteria produce during the fermentation process interfere with the electrode response. We successfully applied Nafion as a proton-conducting layer over ERGO-PA. The Nafion-coated electrodes (ERGO-PA-NA) show a good sensitivity of 1.71 &#937;/pH (pH 4 - 9) for chemiresistive sensor measurements. We tested the ERGO-PA-NA electrode in real-time in the fermentation of Lactococcus lactis. During the growth of L. lactis, the pH of the medium changed from pH 7.2 to pH 4.8 and the resistance of the ERGO-PA-NA solid-state electrode changed from 294.5 &#937; to 288.6 &#937; (5.9 &#937; per 2.4 pH unit). The pH response of the ERGO-PA-NA electrode compared with the response of a conventional glass-based pH electrode shows that reference-less solid-state microsensor arrays operate successfully in a microbiological fermentation.

Here, we report the protocol for the fabrication of a Nafion-coated, polyaniline-functionalized, electrochemically reduced graphene oxide chemiresistive micro pH sensor. This chemiresistor-based, solid-state micro pH sensor can detect pH changes in real-time during a Lactococcus lactis fermentation process.

Here, we report the engineering of a solid-state micro pH sensor based on polyaniline-functionalized, electrochemically reduced graphene oxide (ERGO-PA). ...

Primary Clarification of CHO Harvested Cell Culture Fluid using an Acoustic Separator

Primary clarification is an essential step in a biomanufacturing process for the initial removal of cells from therapeutic products within the harvested cell culture fluid. While traditional methods like centrifugation or filtration are widely implemented for cell removal, the equipment for these processes have large footprints and operation can involve contamination risks and filter fouling. Additionally, traditional methods may not be ideal for continuous bioprocessing schemes for primary clarification. Thus, an alternate application using acoustic (sound) waves was investigated to continuously separate cells from the cell culture fluid. Presented in this study is a detailed protocol for using a bench-scale acoustic wave separator (AWS) for the primary separation of culture fluid containing a monoclonal IgG1 antibody from a CHO cell bioreactor harvest. Representative data are presented from the AWS and demonstrate how to achieve effective cell clarification and product recovery. Finally, potential applications for AWS in continuous bioprocessing are discussed. Overall, this study provides a practical and general protocol for the implementation of AWS in primary clarification for CHO cell cultures and further describes its application potential in continuous bioprocessing.

Presented here is a protocol for the primary clarification of CHO cell culture using an acoustic separator. This protocol can be used for the primary clarification of shake flask cultures or bioreactor harvests and has the potential application for continuous clarification of the cell bleed material during perfusion bioreactor operations.

Primary clarification is an essential step in a biomanufacturing process for the initial removal of cells from therapeutic products within the harvested ...

Standard Test Method ASTM D 7998-19 for the Cohesive Strength Development of Wood Adhesives

The properties of cured wood adhesives are difficult to study because of the loss of water and other components to the wood, the influence of wood on the adhesive cure, and the effect of adhesive penetration on the wood interphase; thus, normal testing of a neat adhesive film is generally not useful. Most tests of wood adhesive bond strength are slow, laborious, can be strongly influenced by the wood and do not provide information on the kinetics of cure. Test method ASTM D 7998-19, however, can be used for fast evaluation of the strength of wood bonds. The use of a smooth, uniform, and strong wood surface, like maple face-veneer, and sufficient bonding pressure reduces the adhesion and wood strength effects on bond strength. This method has three main applications. The first is to provide consistent data on bond strength development. The second is to measure the dry and wet strengths of bonded lap shear samples. The third is to better understand the adhesive heat resistance by quickly evaluating thermal sensitivity and distinguishing between thermal softening and thermal degradation.

We present a procedure, ASTM D7998-19, for a rapid and more consistent evaluation of both dry and wet strength of adhesive bonds on wood. The method can also be used to provide information on strength development as a function of temperature and time or strength retention up to 250 &#176;C.

The properties of cured wood adhesives are difficult to study because of the loss of water and other components to the wood, the influence of wood on the ...

Rapid Assembly of Multi-Gene Constructs using Modular Golden Gate Cloning

The Golden Gate cloning method enables the rapid assembly of multiple genes in any user-defined arrangement. It utilizes type IIS restriction enzymes that cut outside of their recognition sites and create a short overhang. This modular cloning (MoClo) system uses a hierarchical workflow in which different DNA parts, such as promoters, coding sequences (CDS), and terminators, are first cloned into an entry vector. Multiple entry vectors then assemble into transcription units. Several transcription units then connect into a multi-gene plasmid. The Golden Gate cloning strategy is of tremendous advantage because it allows scar-less, directional, and modular assembly in a one-pot reaction. The hierarchical workflow typically enables the facile cloning of a large variety of multi-gene constructs with no need for sequencing beyond entry vectors. The use of fluorescent protein dropouts enables easy visual screening. This work provides a detailed, step-by-step protocol for assembling multi-gene plasmids using the yeast modular cloning (MoClo) kit. We show optimal and suboptimal results of multi-gene plasmid assembly and provide a guide for screening for colonies. This cloning strategy is highly applicable for yeast metabolic engineering and other situations in which multi-gene plasmid cloning is required.

The goal of this protocol is to provide a detailed, step-by-step guide for assembling multi-gene constructs using the modular cloning system based on Golden Gate cloning. It also gives recommendations on critical steps to ensure optimal assembly based on our experiences.

The Golden Gate cloning method enables the rapid assembly of multiple genes in any user-defined arrangement. It utilizes type IIS restriction enzymes that ...

Liquid Chromatography Coupled to Refractive Index or Mass Spectrometric Detection for Metabolite Profiling in Lysate-based Cell-free Systems

Engineering cellular metabolism for targeted biosynthesis can require extensive design-build-test-learn (DBTL) cycles as the engineer works around the cell&#39;s survival requirements. Alternatively, carrying out DBTL cycles in cell-free environments can accelerate this process and alleviate concerns with host compatibility. A promising approach to cell-free metabolic engineering (CFME) leverages metabolically active crude cell extracts as platforms for biomanufacturing and for rapidly discovering and prototyping modified proteins and pathways. Realizing these capabilities and optimizing CFME performance requires methods to characterize the metabolome of lysate-based cell-free platforms. That is, analytical tools are necessary for monitoring improvements in targeted metabolite conversions and in elucidating alterations to metabolite flux when manipulating lysate metabolism. Here, metabolite analyses using high-performance liquid chromatography (HPLC) coupled with either optical or mass spectrometric detection were applied to characterize metabolite production and flux in E. coli S30 lysates. Specifically, this report describes the preparation of samples from CFME lysates for HPLC analyses using refractive index detection (RID) to quantify the generation of central metabolic intermediates and by-products in the conversion of low-cost substrates (i.e., glucose) to various high-value products. The analysis of metabolite conversion in CFME reactions fed with 13C-labeled glucose through reversed-phase liquid chromatography coupled to tandem mass spectrometry (MS/MS), a powerful tool for characterizing specific metabolite yields and lysate metabolic flux from starting materials, is also presented. Altogether, applying these analytical methods to CFME lysate metabolism enables the advancement of these systems as alternative platforms for executing faster or novel metabolic engineering tasks.

The protocols describe high-performance liquid chromatography methods coupled to refractive index or mass spectrometric detection for studying metabolic reactions in complex lysate-based cell-free systems.

Engineering cellular metabolism for targeted biosynthesis can require extensive design-build-test-learn (DBTL) cycles as the engineer works around the ...