We acknowledge the contributions of Sarah S. Chang, BS, for the initial cell culture and preparation of MH-S cells for experimentation. This work was supported by NIAAA R01-AA026086 to SMY (ORCID: 0000-0001-9309-0233), NIAAA F31-F31AA029938 to KMC, and NIGMS T32-GM008602 to Randy Hall, Department of Pharmacology and Chemical Biology, Emory University. The contents of this report do not represent the views of the Department of Veterans Affairs or the US Government.

1. Chronic EtOH exposure in vitro
<ol>
	<li>Culture MH-S cells, a mouse alveolar macrophage cell line, in complete media containing RPMI-1640 with 10% fetal bovine serum, 1% penicillin/streptomycin, 11.9 mM sodium bicarbonate, 40 mg/mL gentamicin, and 50 &#181;M 2-mercaptoethanol at 37&#176;C with 5% CO2 in a humidified incubator.</li>
	<li>Treat cultured MH-S cells with or without EtOH (0.8 mg/mL or 0.08%) for 72 h, where EtOH should be changed every 24 h. Incubate EtOH-treated MH-S cells at 37 &#176;C with 5% CO2 in a separate humidified incubator containing 0.08% EtOH in the incubator water.</li>
</ol>
2. Plating MH-S cells for assessing glutamine as a fuel source using an extracellular flux bioanalyzer
<ol>
	<li>Ensure that untreated control (Con)- and chronic EtOH-treated MH-S cells are grown to at least 50% confluency (70%-90% confluency is ideal) in T-75 flasks to passage into a 96-well extracellular flux microculture plate. Prepare a plate map for 5-6 technical replicates per biological replicate of Con and EtOH experimental conditions and media controls for each to compare against BPTES injections (four groups total for biological n= 1). </li>
	<li>Rinse cells with media or phosphate-buffered saline.</li>
	<li>Add 6 mL of serum-containing media to the flask.</li>
	<li>Scrape cells until they are detached and the bottom of the plate is clear. Trypsin is not needed for MH-S cell detachment but may be helpful in other cell types.</li>
	<li>Separate the cells using a serological pipet or 1 mL pipette.</li>
	<li>Transfer the suspended cells to a 15 mL conical tube and centrifuge them at 200 x g for 6 min.</li>
	<li>Aspirate the supernatant.</li>
	<li>Add 1 mL of media and resuspend the cells thoroughly.</li>
	<li>Transfer 10 &#181;L to a microcentrifuge tube and add 10 &#181;L of trypan blue. Mix well.</li>
	<li>Transfer 10 &#181;L of the cell/trypan blue mixture to one side of a hemocytometer or cell counter.</li>
	<li>Count the number of cells using a light microscope or cell counter.</li>
	<li>Calculate the cell density as an average live cell count per milliliter.</li>
	<li>Make calculations for the dilutions that are needed: 
	Number of wells needed x 10000-15000 cells = total number of cells needed. 
	Number of wells needed x 80 &#181;L = total volume of resuspended cells needed.</li>
	<li>Apply 80 &#181;L of cells to the necessary wells of the 96-well extracellular flux microculture plate.</li>
	<li>Leave the corner wells completely devoid of any cells or media. These wells will be used for background measurements.</li>
	<li>Incubate cells in a 37 &#176;C humidified incubator with 5% CO2 overnight to allow cells to adhere and equilibrate in the extracellular flux microculture plate.</li>
	<li>Treat MH-S cells in the 96-well extracellular flux microculture plate for 72 h using step 1.</li>
	<li>At least 4 h and up to 24 h before running the extracellular flux bioanalyzer experiment, hydrate a 96-well extracellular flux pak cartridge.
	<ol>
		<li>Remove the top portion of the extracellular flux pak and place the probed portion of the flux pak face up on the bench. Apply 200 &#181;L of extracellular flux calibrant solution to each well in the bottom part of the extracellular flux pak cartridge.</li>
		<li>Put the sections together and wrap the extracellular flux pak cartridge in parafilm. Place it in a 37 &#176;C non-CO2 humidified incubator or 37 &#176;C bead bath.</li>
	</ol>
	</li>
	<li>Turn on the computer containing the assay design and open the running/analysis software attached to the extracellular flux bioanalyzer instrument to allow it to warm up at least 4 h prior to performing the experiment.</li>
</ol>
3. Using an extracellular flux bioanalyzer to assess glutamine as a fuel source for mitochondrial respiration in MH-S cells
NOTE: The general overview of this procedure is shown in Figure 1.
<ol>
	<li>Check Con- and EtOH-treated cultured MH-S cells under a light microscope and ensure that cells are healthy and adhered to the wells in a monolayer. Ensure that the cells are at least 70% confluent (90% confluency is ideal) to perform the assay reliably.</li>
	<li>Prepare the extracellular flux base medium with the following supplements:
	<ol>
		<li>Aliquot 35 mL of extracellular flux base medium into a 50 mL tube.</li>
		<li>Add 350 &#181;L of 100 mM sodium pyruvate (1 mM final concentration), 350 &#181;L D-glucose (10 mM final concentration), and 350 &#181;L of GlutaMAX, which is more shelf-stable compared to L-glutamine (2 mM final concentration). 
		NOTE: Fresh L-glutamine may also be used at the same concentration.</li>
		<li>Warm the solution to 37 &#176;C and ensure the pH is 7.4 &#177; 0.05 at 37 &#176;C.</li>
	</ol>
	</li>
	<li>Gently aspirate out the growth media from the extracellular microculture plate. Leave as little media as possible without aspirating cells from the bottom. Wash once with a maximum of 50 &#181;L of the extracellular flux-supplemented base medium.</li>
	<li>Add 180 &#181;L of extracellular flux supplemented base medium to each well and incubate the extracellular microculture plate in a 37 &#176;C non-CO2 humidified incubator for 30 min to 1 h to allow for equilibration.</li>
	<li>Dissolve glutamine oxidation test reagents:
	<ol>
		<li>Into the BPTES tube, add 700 &#181;L of extracellular flux-supplemented base medium to make a 120 mM stock solution. Pipette up and down 10 times to properly solubilize the compound. 
		CAUTION: BPTES causes skin and eye irritation and may cause respiratory irritation. Wear protective gloves, eye protection, and face protection when handling. Dispose of contents and containers to an approved waste disposal facility.</li>
		<li>Into the oligomycin tube, add 630 &#181;L of extracellular flux supplemented base medium to make a 100 mM stock solution. Pipette up and down 10 times to properly solubilize the compound.</li>
		<li>Into the FCCP tube, add 720 &#181;L of extracellular flux-supplemented base medium to make a 100 mM stock solution. Pipette up and down 10 times to properly solubilize the compound. 
		CAUTION: FCCP is harmful if swallowed, causes severe skin burns and eye damage, may cause an allergic skin reaction, and may cause long-lasting harmful effects to aquatic life. Wear protective gloves, protective clothing, eye protection, and face protection when handling. Dispose of contents and containers to an approved waste disposal facility.</li>
		<li>Into the R/A tube, add 540 &#181;L of extracellular flux-supplemented base medium to make a 50 mM stock solution. Pipette up and down 10 times to properly solubilize the compound. 
		CAUTION: Rotenone is fatal if swallowed or if inhaled, causes skin irritation, causes serious eye irritation, may cause respiratory irritation, and is very toxic to aquatic life with long-lasting effects. Wear protective gloves, eye protection, face protection, and respiratory protection. Dispose of contents and containers to an approved waste disposal facility. Antimycin A is fatal if swallowed and is very toxic to aquatic life, with long-lasting effects. Dispose of contents and containers to an approved waste disposal facility.</li>
	</ol>
	</li>
	<li>Prepare working concentrations of substrate oxidation and mitochondrial stress test reagents:
	<ol>
		<li>For BPTES, mix 1,500 &#181;L of extracellular flux supplemented base medium with 500 &#181;L of 120 mM BPTES stock solution to make a 30 &#181;M BPTES working solution.</li>
		<li>For oligomycin, mix 2,520 &#181;L of extracellular flux supplemented base medium with 480 &#181;L of 100 mM oligomycin to make a 16 mM oligomycin working solution.</li>
		<li>For FCCP, mix 2,865 &#181;L of extracellular flux supplemented base medium with 135 &#181;L of 100 mM FCCP to make a 4.5 mM FCCP working solution.</li>
		<li>For R/A, mix 2,700 &#181;L of extracellular flux supplemented base medium with 300 &#181;L of 50 mM R/A to make a 5 mM R/A working solution.</li>
	</ol>
	</li>
	<li>Load the ports of the upper of the extracellular flux pak cartridge with the following:
	<ol>
		<li>Load the background and media control wells with 20 &#181;L of extracellular flux supplemented base medium into port A, 22 &#181;L of oligomycin into port B, 25 &#181;L of FCCP into port C, and 27 &#181;L of R/A into port D.</li>
		<li>Load the cell-containing wells with 20 &#181;L of media control or BPTES into port A (final concentration of 3 &#181;M for BPTES), 22 &#181;L of oligomycin into port B (final concentration of 2 &#181;M for oligomycin), 25 &#181;L of FCCP into port C (final concentration of 0.5 &#181;M for FCCP), and 27 &#181;L of R/A (final concentration of 0.5 &#181;M for R/A) into port D.</li>
	</ol>
	</li>
	<li>Perform the extracellular flux bioanalyzer experiment using the computer software program for assay design and analysis that is attached to the instrument using the following timing and injection strategy:
	<ol>
		<li>For the injection with port A for BPTES, set the number of measurements to 6. Set the mix time to 3 min, with a 0-min wait time and a 3-min measurement time.</li>
		<li>For the injection with port B for oligomycin, set the number of measurements to 3. Set the mix time to 3 min, with a 0-min wait time and a 3-min measurement time.</li>
		<li>For the injection with port C for FCCP, set the number of measurements to 3. Set the mix time to 3 min, with a 6-min wait time and a 3-min measurement time.</li>
		<li>For the injection with port D for R/A, set the number of measurements to 3. Set the mix time to 3 min, with a 0-min wait time and a 3-min measurement time.</li>
		<li>Review all set background, media control, and experimental group wells. Save and run the assay. First, load the extracellular flux pak with A-D injections. Calibration will occur until the cell plate is ready to load.</li>
		<li>Remove the cell plate immediately at the end of the assay. Save results to analyze later on another device.</li>
		<li>Check if the cells are still adhered to using a light microscope. Wash 1x with phosphate-buffered saline and lyse cells with a preferred cell lysis buffer. Store at -80 &#176;C or assay immediately for protein concentration.</li>
	</ol>
	</li>
</ol>
4. Analysis of results to assess glutamine as a fuel source for mitochondrial respiration in MH-S cells
<ol>
	<li>Extract protein from cells in each well to normalize oxygen consumption rate (OCR) data to protein:
	<ol>
		<li>Calculate the concentration (nanograms/microliter [ng/&#181;L]) of protein per well.</li>
		<li>Calculate the average protein concentration (ng/&#181;L) for the entire extracellular flux microculture plate.</li>
		<li>Divide each well&#39;s protein concentration by the average plate&#39;s protein concentration to get a normalization factor.</li>
		<li>Apply the normalization factor to the data file of interest using the computer software program for assay design and analysis.</li>
	</ol>
	</li>
	<li>Ensure that the OCR values of all background wells are close to 0.</li>
	<li>Deselect any cell wells where OCR is &#60; 10 at baseline. Data will not be deleted, but highlighted wells will show up in the exported data file.</li>
	<li>Export the data from the computer software program for assay design and analysis into a computer spreadsheet program.</li>
	<li>Open the file in the computer spreadsheet program and sort all data by decreasing the values of OCR. Delete background wells, wells that were previously deselected (and had not been deleted), any wells with low cell viability, wells with low cell confluency, wells without full injection strategy completion, wells with inaccurate protein concentration readings, wells with baseline OCR &#60; 10, and any other predetermined criteria.</li>
	<li>Sort all remaining data by measurement, then by group, and then by OCR.</li>
	<li>Average each biological N&#39;s technical replicates independently by measurement. Ensure there is a minimum of 18 different values (3 baseline, 3 after media/BPTES, 3 after oligomycin, 3 after FCCP, and 6 after rotenone/antimycin A) per experimental group per biological N after averaging the technical replicates. Do this for each biological N separately so that the standard deviation or standard error of the mean can be calculated later for analyzed data.</li>
	<li>Copy all averaged values into a new spreadsheet, separated by experimental group.</li>
	<li>Average the OCR values by injection strategy in each experimental group.</li>
	<li>Calculate parameters of mitochondrial bioenergetics based on oxygen consumption:
	<ol>
		<li>Calculate basal respiration:
		<ol>
			<li>Calculate basal mitochondrial respiration as follows: 
			Basal mitochondrial respiration (pmol O2 consumed) = ([AVG OCR measurements #1, 2, 3 - AVG OCR measurements #16, 17, 18] x [Time #3 - Time #1]) 
			&#8203;NOTE: Basal respiration should be similar between media control and BPTES groups because this is before the inhibitor is injected.</li>
			<li>Calculate basal mitochondrial respiration not dependent on glutamine as follows: 
			Basal mitochondrial respiration not dependent on glutamine (pmol O2 consumed) = ([AVG OCR measurements #4, 5, 6, 7, 8, 9 - AVG OCR measurements #16, 17, 18] x [Time #9 - Time #4]) 
			NOTE: Basal mitochondrial respiration not dependent on glutamine should be less than basal mitochondrial respiration unless cells are not heavily dependent on glutamine.</li>
			<li>Calculate basal mitochondrial respiration dependent on glutamine as follows: 
			Basal mitochondrial respiration dependent on glutamine (pmol O2 consumed) = ([AVG OCR measurements #1, 2, 3 - AVG OCR measurements #4, 5, 6, 7, 8, 9] x [Time #9 - Time #4]) 
			&#8203;NOTE: Total basal mitochondrial respiration should not be subtracted from basal mitochondrial respiration, and it should not be dependent on glutamine since these are calculated at different time points.</li>
		</ol>
		</li>
		<li>Calculate ATP-linked respiration as follows:
		<ol>
			<li>Calculate total mitochondrial ATP-linked respiration from all fuels as follows: 
			Total mitochondrial ATP-linked respiration from all fuels (pmol O2 consumed) = ([AVG OCR measurements #1, 2, 3 - AVG OCR measurements #10, 11, 12] x [Time #12 - Time #10]) 
			&#8203;NOTE: The average OCR for measurements #10, 11, and 12 should be similar between media control and BPTES groups since oligomycin should strongly inhibit ATP synthase, and inhibiting one fuel pathway should not change the total ATP-linked respiration.</li>
			<li>Calculate ATP-linked mitochondrial respiration not dependent on glutamine as follows: 
			ATP-linked mitochondrial respiration not dependent on glutamine (pmol O2 consumed) = ([AVG OCR measurements #4, 5, 6, 7, 8, 9 - AVG OCR measurements #10, 11, 12] x [Time #12 - Time #10]) 
			NOTE: ATP-linked mitochondrial respiration not dependent on glutamine should be less than ATP-linked mitochondrial respiration unless cells are not heavily dependent on glutamine.</li>
			<li>Calculate ATP-linked mitochondrial respiration dependent on glutamine as follows: 
			&#8203;ATP-linked mitochondrial respiration dependent on glutamine (pmol O2 consumed) = Total ATP-linked mitochondrial respiration from all fuels - ATP-linked mitochondrial respiration not dependent on glutamine</li>
		</ol>
		</li>
		<li>Calculate maximal respiration as follows:
		<ol>
			<li>Calculate total maximal mitochondrial respiration as follows: 
			&#8203;Total maximal mitochondrial respiration (pmol O2 consumed) = ([AVG OCR measurements #13, 14, 15 - AVG OCR measurements #16, 17, 18] x [Time #15 - Time #13])</li>
			<li>Calculate maximal mitochondrial respiration not dependent on glutamine as follows: 
			&#8203;Maximal mitochondrial respiration not dependent on glutamine (pmol O2 consumed) = ([AVG OCR measurements #13, 14, 15 of BPTES groups - AVG OCR measurements #16, 17, 18 of BPTES groups] x [Time #15 - #Time 13])</li>
			<li>Calculate maximal mitochondrial respiration dependent on glutamine as follows: 
			&#8203;Maximal mitochondrial respiration dependent on glutamine (pmol O2 consumed) = Total maximal mitochondrial respiration from all fuels - Maximal mitochondrial respiration not dependent on glutamine 
			&#8203;NOTE: This calculation may be used to determine cell dependency for the spare capacity of glutamine compared to other fuels. The greater the maximal mitochondrial respiration, the greater the dependency on glutamine, which can be expressed as BPTES groups - control groups to show a loss in maximal mitochondrial respiration or as a percentage of total respiration.</li>
		</ol>
		</li>
		<li>Calculate spare respiratory capacity as follows:
		<ol>
			<li>Calculate total spare respiratory capacity as follows: 
			Total spare respiratory capacity (pmol O2 consumed) = ([AVG OCR measurements #13, 14, 15 - AVG OCR measurements #1, 2, 3] x [Time #15 - Time #13])</li>
			<li>Calculate spare respiratory capacity not dependent on glutamine as follows: 
			&#8203;Spare respiratory capacity not dependent on glutamine (pmol O2 consumed) = ([AVG OCR measurements #13, 14, 15 of BPTES groups - AVG OCR measurements #1, 2, 3 of BPTES groups] x [Time #15 - Time #13])</li>
			<li>Calculate spare respiratory capacity dependent on glutamine as follows: 
			Spare respiratory capacity dependent on glutamine (pmol O2 consumed) = Total spare respiratory capacity from all fuels - Spare respiratory capacity not dependent on glutamine 
			NOTE: This calculation represents the flexibility of cells dependent on glutamine and if they can achieve greater respiration without glutamine when needed.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Subtract media controls by inhibitor groups and normalize pmol O2 consumed relative to the control group if desired.</li>
	<li>Create graphs of OCR bioenergetic profiles (pmol O2/min), basal respiration (pmol O2), ATP-linked respiration (pmol O2), maximal respiration (pmol O2), and spare respiratory capacity (pmol O2) dependent on glutamine.</li>
	<li>Depict mitochondrial bioenergetic endpoint values in bar graphs or express as means of the inhibitor groups relative to the media control groups. If each biological N is calculated separately, then calculate the standard deviation or standard error of the mean for analyzed data across all biological Ns.</li>
</ol>
5. Statistical analysis
<ol>
	<li>Perform all statistical analyses using appropriate data analysis software.</li>
	<li>For linear points of OCR bioenergetic profiles, perform two-way ANOVA followed by Tukey&#39;s post hoc analyses to compare data from these four experimental groups with two factors (treatment and injection strategy): Con + media, Con + BPTES, EtOH + media, and EtOH + BPTES.</li>
	<li>For bar graphs of basal respiration, ATP-linked respiration, maximal respiration, and spare respiratory capacity dependent on glutamine, conduct Student&#39;s t-test analyses to compare data from two experimental groups, Con + BPTES, and EtOH + BPTES.</li>
	<li>Present data as means &#177; standard error of the mean (SEM). Consider p &#60; 0.05 statistically significant.</li>
</ol>

Ethanol Impairs AM Bioenergetics by Shifting to Glutamine-Dependent Respiration

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K., 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=The+Bioenergetic+Health+Index:+a+new+concept+in+mitochondrial+translational+research.">The Bioenergetic Health Index: a new concept in mitochondrial translational research.</a> Clin Sci (Lond). 127 (6), 367-373 (2014).</li><li>Fan, Y., 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=Analyzing+mitochondrial+respiration+of+human+induced+pluripotent+stem+cell-derived+myeloid+progenitors+using+Seahorse+technology.">Analyzing mitochondrial respiration of human induced pluripotent stem cell-derived myeloid progenitors using Seahorse technology.</a> STAR Protoc. 4 (1), 102073 (2023).</li><li>Gu, X., Ma, Y., Liu, Y., Wan, Q. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measurement+of+mitochondrial+respiration+in+adherent+cells+by+Seahorse+XF96+Cell+Mito+Stress+Test.">Measurement of mitochondrial respiration in adherent cells by Seahorse XF96 Cell Mito Stress Test.</a> STAR Protoc. 2 (1), 100245 (2021).</li><li>Plitzko, B., Loesgen, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measurement+of+oxygen+consumption+rate+(OCR)+and+extracellular+acidification+rate+(ECAR)+in+culture+cells+for+assessment+of+the+energy+metabolism.">Measurement of oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) in culture cells for assessment of the energy metabolism.</a> Bio Protoc. 8 (10), e2850 (2018).</li><li>Winnica, D., 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=Bioenergetic+differences+in+the+airway+epithelium+of+lean+versus+obese+asthmatics+are+driven+by+nitric+oxide+and+reflected+in+circulating+platelets.">Bioenergetic differences in the airway epithelium of lean versus obese asthmatics are driven by nitric oxide and reflected in circulating platelets.</a> Antioxid Redox Signal. 31 (10), 673-686 (2019).</li><li>Nickens, K. P., Wikstrom, J. D., Shirihai, O. S., Patierno, S. R., Ceryak, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+bioenergetic+profile+of+non-transformed+fibroblasts+uncovers+a+link+between+death-resistance+and+enhanced+spare+respiratory+capacity.">A bioenergetic profile of non-transformed fibroblasts uncovers a link between death-resistance and enhanced spare respiratory capacity.</a> Mitochondrion. 13 (6), 662-667 (2013).</li><li>Mdaki, K. S., Larsen, T. D., Weaver, L. J., Baack, M. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Age+related+bioenergetics+profiles+in+isolated+rat+cardiomyocytes+using+extracellular+flux+analyses.">Age related bioenergetics profiles in isolated rat cardiomyocytes using extracellular flux analyses.</a> PLoS One. 11 (2), e0149002 (2016).</li><li>Dranka, B. P., 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=Assessing+bioenergetic+function+in+response+to+oxidative+stress+by+metabolic+profiling.">Assessing bioenergetic function in response to oxidative stress by metabolic profiling.</a> Free Radic Biol Med. 51 (9), 1621-1635 (2011).</li><li>Chacko, B. K., 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=Methods+for+defining+distinct+bioenergetic+profiles+in+platelets,+lymphocytes,+monocytes,+and+neutrophils,+and+the+oxidative+burst+from+human+blood.">Methods for defining distinct bioenergetic profiles in platelets, lymphocytes, monocytes, and neutrophils, and the oxidative burst from human blood.</a> Lab Invest. 93 (6), 690-700 (2013).</li><li>Tyrrell, D. J., Bharadwaj, M. S., Jorgensen, M. J., Register, T. C., Molina, A. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Blood+cell+respirometry+is+associated+with+skeletal+and+cardiac+muscle+bioenergetics:+Implications+for+a+minimally+invasive+biomarker+of+mitochondrial+health.">Blood cell respirometry is associated with skeletal and cardiac muscle bioenergetics: Implications for a minimally invasive biomarker of mitochondrial health.</a> Redox Biol. 10, 65-77 (2016).</li><li>Shah-Simpson, S., Pereira, C. F., Dumoulin, P. C., Caradonna, K. L., Burleigh, B. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bioenergetic+profiling+of+Trypanosoma+cruzi+life+stages+using+Seahorse+extracellular+flux+technology.">Bioenergetic profiling of Trypanosoma cruzi life stages using Seahorse extracellular flux technology.</a> Mol Biochem Parasitol. 208 (2), 91-95 (2016).</li><li>Nicholls, D. 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=Bioenergetic+profile+experiment+using+C2C12+myoblast+cells.">Bioenergetic profile experiment using C2C12 myoblast cells.</a> J Vis Exp. 46, e2511 (2010).</li><li>Chance, B., Williams, G. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Respiratory+enzymes+in+oxidative+phosphorylation.+I.+Kinetics+of+oxygen+utilization.">Respiratory enzymes in oxidative phosphorylation. I. Kinetics of oxygen utilization.</a> J Biol Chem. 217 (1), 383-393 (1955).</li><li>Gerencser, A. A., 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=Quantitative+microplate-based+respirometry+with+correction+for+oxygen+diffusion.">Quantitative microplate-based respirometry with correction for oxygen diffusion.</a> Anal Chem. 81 (16), 6868-6878 (2009).</li><li>Yeligar, S. M., 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=PPARgamma+regulates+mitochondrial+structure+and+function+and+human+pulmonary+artery+smooth+muscle+cell+proliferation.">PPARgamma regulates mitochondrial structure and function and human pulmonary artery smooth muscle cell proliferation.</a> Am J Respir Cell Mol Biol. 58 (5), 648-657 (2018).</li><li>Yeligar, S., Tsukamoto, H., Kalra, V. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ethanol-induced+expression+of+ET-1+and+ET-BR+in+liver+sinusoidal+endothelial+cells+and+human+endothelial+cells+involves+hypoxia-inducible+factor-1alpha+and+microrNA-199.">Ethanol-induced expression of ET-1 and ET-BR in liver sinusoidal endothelial cells and human endothelial cells involves hypoxia-inducible factor-1alpha and microrNA-199.</a> J Immunol. 183 (8), 5232-5243 (2009).</li><li>Yeligar, S. M., Harris, F. L., Brown, L. A. S., Hart, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pharmacological+reversal+of+post-transcriptional+alterations+implicated+in+alcohol-induced+alveolar+macrophage+dysfunction.">Pharmacological reversal of post-transcriptional alterations implicated in alcohol-induced alveolar macrophage dysfunction.</a> Alcohol. 106, 30-43 (2023).</li></ol>

All authors do not have any relevant financial conflicts of interest to report.

The data presented herein are additional biological replicates for untreated and chronic EtOH-exposed MH-S cells treated with media control or BPTES, which are published in Crotty et al.11. The protocol described is used to assess the dependency of EtOH-exposed MH-S cells on glutamine as a fuel source for mitochondrial respiration and bioenergetics using an extracellular flux bioanalyzer. There are several critical steps in the protocol. Firstly, MH-S cell formation and confluency are important. M...

Alcohol use disorder (AUD) affects over 28 million people in the United States1. People with AUD are 2-4 times more likely to develop respiratory infections2,3, increasing risk for premature morbidity and mortality3,4,5. Alcohol misuse increases susceptibility to respiratory infections, in part through suppressing lung immune function. Alveolar macrophages (AMs) are the first line of cellular defense against pathogens in the lower lung, where they phagocytize and clear inhaled microbes. However, chronic alcohol consumption impairs the capacity of AMs to engulf and kill pathogens6,7.
The immune functions of AMs, such as phagocytosis, are energy-demanding processes that require metabolically active pathways necessary for high adenosine triphosphate (ATP) generation. Mitochondrial oxidative phosphorylation is the most efficient cellular process for producing ATP, but chronic ethanol (EtOH) exposure increases mitochondrial-derived oxidative stress, which can result in mitochondrial dysfunction in AMs8,9,10. Mitochondrial respiration measured using cellular oxygen consumption rate (OCR) can be quantified using an extracellular flux bioanalyzer in real-time. Mitochondrial respiration profiles assessed in response to oligomycin (ATP synthase inhibitor), carbonyl cyanide- p-trifluoromethoxyphenylhydrazone (FCCP, proton uncoupler), and rotenone/antimycin A (R/A, mitochondrial complex I and III inhibitors, respectively) are used to determine mitochondrial bioenergetics. Chronic EtOH decreases mitochondrial bioenergetics in AMs, as evidenced by diminished mitochondrial basal respiration, ATP-linked respiration, maximal respiration, and spare respiratory capacity10.
Cells have various levels of dependency on sources of fuels, such as pyruvate, glutamine, or fatty acids, for ATP production. They also have a level of flexibility whereby they can switch fuel usage to regulate cellular bioenergetics. Glutaminolysis is a key pathway for mitochondrial respiration, particularly when pyruvate is shunted towards lactic acid production or when fatty acids are insufficient. Our recent study showed that chronic EtOH exposure increases AM dependency on glutamine and decreases AM flexibility to use glutamine and other fuel sources for mitochondrial respiration11. These results, along with data demonstrating that treatment of EtOH-exposed MH-S cells with the pyruvate oxidation inhibitor UK5099 did not alter mitochondrial bioenergetics compared to media control-exposed MH-S cells treated with UK5099, suggested a shift away from pyruvate-dependent respiration and towards glutamine-dependent respiration in EtOH MH-S cells. However, this shift is insufficient to meet AM bioenergetic demands11. Herein, we describe the methods to assess glutamine as a fuel source for mitochondrial respiration in chronic EtOH-exposed AMs using an extracellular flux bioanalyzer. This protocol was created and optimized for a 96-well (11.04 mm2 area) format and should be adjusted for larger cell culture well sizes. Glutamine dependency for mitochondrial bioenergetics is determined using bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl) ethyl sulfide (BPTES, inhibitor of glutaminase 1) to selectively inhibit the enzymatic conversion of glutamine to glutamate. The data presented in this study are additional biological replicates for the media control- and BPTES-treated experimental groups of untreated control- and chronic EtOH-exposed mouse AM cell line, MH-S cells, that are published in Crotty et al.11.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>15 mL conical tube&#160;</td>
			<td>VWR International, Inc.</td>
			<td>21008-670</td>
			<td>Used for preparing stock concentrations of mitochondria-related reagents.</td>
		</tr>
		<tr>
			<td>2-mercaptoethanol&#160;</td>
			<td>Sigma Aldrich Co.</td>
			<td>M6250</td>
			<td>Used for culturing MH-S cells.</td>
		</tr>
		<tr>
			<td>Cell scraper</td>
			<td>Dot Scientific, Inc.</td>
			<td>70-1180</td>
			<td>Used for scraping MH-S cells from T-75 flasks.</td>
		</tr>
		<tr>
			<td>Countess 3 FL Instrument: cell counter</td>
			<td>Fisher Scientific Company</td>
			<td>AMQAF2000</td>
			<td>Used for counting the number of MH-S cells to plate for experiments.</td>
		</tr>
		<tr>
			<td>D-glucose&#160;</td>
			<td>Sigma Aldrich Co.</td>
			<td>G8270</td>
			<td>Used for the extracellular flux base medium.</td>
		</tr>
		<tr>
			<td>Ethanol</td>
			<td>Fisher Scientific Company</td>
			<td>4355720</td>
			<td>Experimental treatment for MH-S cells.</td>
		</tr>
		<tr>
			<td>Fetal bovine serum</td>
			<td>Sciencell Research Laboratories</td>
			<td>500</td>
			<td>Used for culturing MH-S cells.</td>
		</tr>
		<tr>
			<td>Gentamicin</td>
			<td>Sigma Aldrich Co.</td>
			<td>G1397</td>
			<td>Used for culturing MH-S cells.</td>
		</tr>
		<tr>
			<td>GlutaMAX</td>
			<td>Thermo Fisher Scientific</td>
			<td>35050061</td>
			<td>Used for the extracellular flux base medium.</td>
		</tr>
		<tr>
			<td>GraphPad Prism 10.2.3</td>
			<td>GraphPad Software</td>
			<td>N/A</td>
			<td>Software for statistical analysis. Downloadable after purchase at https://www.graphpad.com/features.</td>
		</tr>
		<tr>
			<td>MH-S cells</td>
			<td>American Type Culture Collection</td>
			<td>CRL-2019</td>
			<td>Mouse alveolar macrophage cell line.</td>
		</tr>
		<tr>
			<td>Microcentrifuge tube&#160;</td>
			<td>USA Scientific, Inc.</td>
			<td>4036-3212</td>
			<td>Used for preparing working concentrations of mitochondria-related reagents.</td>
		</tr>
		<tr>
			<td>Microsoft 365 Excel: computer spreadsheet program</td>
			<td>Microsoft</td>
			<td>N/A</td>
			<td>Software for data organization and mitochondrial bioenergetics calculations. Downloadable after purchase at https://www.microsoft.com/en-us/microsoft-365/excel.</td>
		</tr>
		<tr>
			<td>Penicillin/streptomycin</td>
			<td>Fisher Scientific Company</td>
			<td>15140122</td>
			<td>Used for culturing MH-S cells.</td>
		</tr>
		<tr>
			<td>Phosphate buffered saline</td>
			<td>VWR International, Inc.</td>
			<td>45000-446</td>
			<td>Used for washing MH-S cells.</td>
		</tr>
		<tr>
			<td>RPMI-1640</td>
			<td>VWR International, Inc.</td>
			<td>45000-396</td>
			<td>Used for culturing MH-S cells.</td>
		</tr>
		<tr>
			<td>Seahorse Wave Pro Software: computer software program for assay design and analysis</td>
			<td>Agilent Technologies, Inc.</td>
			<td>N/A</td>
			<td>The computer is attached to the Seahorse XF Pro Analyzer instrument. Downloadable from&#160; https://www.agilent.com/en/product/cell-analysis/real-time-cell-metabolic-analysis/xf-software/software-download-for-seahorse-wave-pro-software?productURL=https%3A%2F%2Fwww.agilent.com%2Fen%2Fproduct%2Fcell-analysis%2Freal-time-cell-metabolic-analysis%2Fxf-software%2Fseahorse-wave-pro-software-2007523.</td>
		</tr>
		<tr>
			<td>Seahorse XF Base Medium: extracellular flux base medium, pH 7.4</td>
			<td>Agilent Technologies, Inc.</td>
			<td>103334-100</td>
			<td>Used for preparing stock and working concentrations of mitochondria-related reagents and culturing MH-S cells prior to experimental runs.</td>
		</tr>
		<tr>
			<td>Seahorse XF Glutamine Oxidation Stress Test Kit</td>
			<td>Agilent Technologies, Inc.</td>
			<td>103674-100</td>
			<td>Contains stock BPTES, oligomycin, FCCP, and rotenone/antimycin A.</td>
		</tr>
		<tr>
			<td>Seahorse XF Pro Analyzer: extracellular flux bioanalyzer</td>
			<td>Agilent Technologies, Inc.</td>
			<td>N/A</td>
			<td>Extracellular flux bioanalyzer.</td>
		</tr>
		<tr>
			<td>Seahorse XFe96 FluxPak: 96-well extracellular flux pak cartridges, 96-well extracellular flux microculture plates, and calibrant solution</td>
			<td>Agilent Technologies, Inc.</td>
			<td>102416-100</td>
			<td>Used to prepare MH-S cells for assays using an extracellular flux bioanalyzer.</td>
		</tr>
		<tr>
			<td>Serological pipet&#160;</td>
			<td>Santa Cruz Biotechnology, Inc.</td>
			<td>sc-550678</td>
			<td>Used for removing media from MH-S cells.</td>
		</tr>
		<tr>
			<td>Sodium bicarbonate</td>
			<td>Sigma Aldrich Co.</td>
			<td>S6014</td>
			<td>Used for culturing MH-S cells.</td>
		</tr>
		<tr>
			<td>Sodium pyruvate&#160;</td>
			<td>Sigma Aldrich Co.</td>
			<td>P4562</td>
			<td>Used for the extracellular flux base medium.</td>
		</tr>
		<tr>
			<td>T-75 flasks</td>
			<td>Santa Cruz Biotechnology, Inc.</td>
			<td>sc-200263</td>
			<td>Used for culturing MH-S cells.</td>
		</tr>
	</tbody>
</table>

assessment of glutamine as a fuel source for alveolar macrophages exposed to chronic ethanol using an extracellular flux bioanalyzer

Alveolar macrophages (AMs) are the first line of cellular defense in the lower airway against pathogens. However, chronic and excessive alcohol use impairs the ability of AMs to phagocytize and clear pathogens from the alveolar space, in part through dysregulated fuel metabolism and bioenergetics. Our prior work has shown that chronic ethanol (EtOH) consumption impairs mitochondrial bioenergetics and increases lactate levels in AMs. Further, we recently demonstrated that EtOH increases glutamine dependency and glutamine-dependent maximal respiration while decreasing flexibility, shifting away from pyruvate-dependent respiration and towards glutamine-dependent respiration. Glutaminolysis is an important compensatory pathway for mitochondrial respiration when pyruvate is used for lactic acid production or when other fuel sources are insufficient. Using a mouse AM cell line, MH-S cells, exposed to either no EtOH or EtOH (0.08%) for 72 h, we determined the dependency of mitochondrial respiration and bioenergetics on glutamine as a fuel source using an extracellular flux bioanalyzer. Real-time measures were done in response to bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl) ethyl sulfide (BPTES), an inhibitor of glutaminase 1, which prevents the enzymatic conversion of glutamine to glutamate, in media vehicle or in response to vehicle alone, followed by testing mitochondrial stress. The step-by-step protocol provided herein describes our methods and calculations for analyzing average levels of glutamine-dependent basal mitochondrial respiration, mitochondrial ATP-linked respiration, maximal mitochondrial respiration, and mitochondrial spare respiratory capacity across multiple biological and experimental replicates.

Chronic EtOH exposure decreases glutamine dependency in MH-S cells. 
Glutaminolysis is a critical pathway for mitochondrial respiration, supporting glutamine as an important fuel source for cellular bioenergetics. To determine whether chronic exposure to EtOH alters the dependency of MH-S cells on glutamine as a fuel source for mitochondrial respiration, MH-S cells were treated with no EtOH control (Con) or EtOH, and OCR was measured over time in response to serial injections of reagents associated ...

Assessment of Glutamine as a Fuel Source for Alveolar Macrophages Exposed to Chronic Ethanol Using an Extracellular Flux Bioanalyzer

Alcohol misuse impairs alveolar macrophage (AM) immunity due to suppressed mitochondrial respiration and bioenergetics. We recently demonstrated that ethanol (EtOH) exposure increases glutamine dependency for mitochondrial respiration in AMs. Herein, methods are provided to determine the usage of glutamine for mitochondrial respiration in EtOH-treated AMs using an extracellular flux bioanalyzer.

Alveolar macrophages (AMs) are the first line of cellular defense in the lower airway against pathogens. However, chronic and excessive alcohol use ...

assessment-glutamine-as-fuel-source-for-alveolar-macrophages-exposed

Research

JoVE Journal

Immunology and Infection

196 Views.  Emory University. Alcohol misuse impairs alveolar macrophage (AM) immunity due to suppressed mitochondrial respiration and bioenergetics. We recently demonstrated that ethanol (EtOH) exposure increases glutamine dependency for mitochondrial respiration in AMs. Herein, methods are provided to determine the usage of glutamine for mitochondrial respiration in EtOH-treated AMs using an extracellular flux bioanalyzer. 

Video: Assessment of Glutamine as a Fuel Source for Alveolar Macrophages Exposed to Chronic Ethanol Using an Extracellular Flux Bioanalyzer

Introducing Shear Stress in the Study of Bacterial Adhesion

During bacterial infections a sequence of interactions occur between the pathogen and its host. Bacterial adhesion to the host cell surface is often the initial and determining step of the pathogenesis. Although experimentally adhesion is mostly studied in static conditions adhesion actually takes place in the presence of flowing liquid. First encounters between bacteria and their host often occur at the mucosal level, mouth, lung, gut, eye, etc. where mucus flows along the surface of epithelial cells. Later in infection, pathogens occasionally access the blood circulation causing life-threatening illnesses such as septicemia, sepsis and meningitis. A defining feature of these infections is the ability of these pathogens to interact with endothelial cells in presence of circulating blood. The presence of flowing liquid, mucus or blood for instance, determines adhesion because it generates a mechanical force on the pathogen. To characterize the effect of flowing liquid one usually refers to the notion of shear stress, which is the tangential force exerted per unit area by a fluid moving near a stationary wall, expressed in dynes/cm2. Intensities of shear stress vary widely according to the different vessels type, size, organ, location etc. (0-100 dynes/cm2). Circulation in capillaries can reach very low shear stress values and even temporarily stop during periods ranging between a few seconds to several minutes 1. On the other end of the spectrum shear stress in arterioles can reach 100 dynes/cm2 2. The impact of shear stress on different biological processes has been clearly demonstrated as for instance during the interaction of leukocytes with the endothelium 3. To take into account this mechanical parameter in the process of bacterial adhesion we took advantage of an experimental procedure based on the use of a disposable flow chamber 4. Host cells are grown in the flow chamber and fluorescent bacteria are introduced in the flow controlled by a syringe pump. We initially focused our investigations on the bacterial pathogen Neisseria meningitidis, a Gram-negative bacterium responsible for septicemia and meningitis. The procedure described here allowed us to study the impact of shear stress on the ability of the bacteria to: adhere to cells 1, to proliferate on the cell surface 5and to detach to colonize new sites 6 (Figure 1). Complementary technical information can be found in reference 7. Shear stress values presented here were chosen based on our previous experience1 and to represent values found in the literature. The protocol should be applicable to a wide range of pathogens with specific adjustments depending on the objectives of the study.

During the infection process, a key step is the adhesion of pathogens with host cells. In most instances this adhesion step occurs in the presence of mechanical stress generated by flowing liquid. We describe a technique that introduces shear stress as an important parameter in the study of bacterial adhesion.

During bacterial infections a sequence of interactions occur between the pathogen and its host. Bacterial adhesion to the host cell surface is often the ...

Staphylococcus aureus Growth using Human Hemoglobin as an Iron Source

S. aureus is a pathogenic bacterium that requires iron to carry out vital metabolic functions and cause disease. The most abundant reservoir of iron inside the human host is heme, which is the cofactor of hemoglobin. To acquire iron from hemoglobin, S. aureus utilizes an elaborate system known as the iron-regulated surface determinant (Isd) system1. Components of the Isd system first bind host hemoglobin, then extract and import heme, and finally liberate iron from heme in the bacterial cytoplasm2,3. This pathway has been dissected through numerous in vitro studies4-9. Further, the contribution of the Isd system to infection has been repeatedly demonstrated in mouse models8,10-14. Establishing the contribution of the Isd system to hemoglobin-derived iron acquisition and growth has proven to be more challenging. Growth assays using hemoglobin as a sole iron source are complicated by the instability of commercially available hemoglobin, contaminating free iron in the growth medium, and toxicity associated with iron chelators. Here we present a method that overcomes these limitations. High quality hemoglobin is prepared from fresh blood and is stored in liquid nitrogen. Purified hemoglobin is supplemented into iron-deplete medium mimicking the iron-poor environment encountered by pathogens inside the vertebrate host. By starving S. aureus of free iron and supplementing with a minimally manipulated form of hemoglobin we induce growth in a manner that is entirely dependent on the ability to bind hemoglobin, extract heme, pass heme through the bacterial cell envelope and degrade heme in the cytoplasm. This assay will be useful for researchers seeking to elucidate the mechanisms of hemoglobin-/heme-derived iron acquisition in S. aureus and possibly other bacterial pathogens.

Staphylococcus aureus Growth using Human Hemoglobin as an Iron Source

Here we describe a growth assay for Staphylococcus aureus using hemoglobin as the sole source of available nutrient iron. This assay establishes the role of bacterial factors involved in hemoglobin-derived iron acquisition.

S. aureus is a pathogenic bacterium that requires iron to  carry out vital metabolic functions and cause disease. The most abundant  reservoir of iron ...

Investigation of Macrophage Polarization Using Bone Marrow Derived Macrophages

The article describes a readily easy adaptive in vitro model to investigate macrophage polarization. In the presence of GM-CSF/M-CSF, hematopoietic stem/progenitor cells from the bone marrow are directed into monocytic differentiation, followed by M1 or M2 stimulation. The activation status can be tracked by changes in cell surface antigens, gene expression and cell signaling pathways.

The article describes a readily easy adaptive in vitro model to investigate macrophage polarization. In the presence of GM-CSF/M-CSF, hematopoietic stem/progenitor cells from the bone marrow are directed into monocytic differentiation, followed by M1 or M2 stimulation. The activation status can be tracked by changes in cell surface antigens, gene expression and cell signaling pathways.

The article describes a readily easy adaptive in vitro model to investigate macrophage polarization. In the presence of GM-CSF/M-CSF, hematopoietic ...

Establishment of an In vitro System to Study Intracellular Behavior of Candida glabrata in Human THP-1 Macrophages

A cell culture model system, if a close mimic of host environmental conditions, can serve as an inexpensive, reproducible and easily manipulatable alternative to animal model systems for the study of a specific step of microbial pathogen infection. A human monocytic cell line THP-1 which, upon phorbol ester treatment, is differentiated into macrophages, has previously been used to study virulence strategies of many intracellular pathogens including Mycobacterium tuberculosis. Here, we discuss a protocol to enact an in vitro cell culture model system using THP-1 macrophages to delineate the interaction of an opportunistic human yeast pathogen Candida glabrata with host phagocytic cells. This model system is simple, fast, amenable to high-throughput mutant screens, and requires no sophisticated equipment. A typical THP-1 macrophage infection experiment takes approximately 24 hr with an additional 24-48 hr to allow recovered intracellular yeast to grow on rich medium for colony forming unit-based viability analysis. Like other in vitro model systems, a possible limitation of this approach is difficulty in extrapolating the results obtained to a highly complex immune cell circuitry existing in the human host. However, despite this, the current protocol is very useful to elucidate the strategies that a fungal pathogen may employ to evade/counteract antimicrobial response and survive, adapt, and proliferate in the nutrient-poor environment of host immune cells.

Establishment of an In vitro System to Study Intracellular Behavior of Candida glabrata in Human THP-1 Macrophages

The current article outlines a protocol to establish an in vitro cell culture model system to study the interaction of a facultative intracellular human fungal pathogen Candida glabrata with human macrophages which will be a useful tool to advance our knowledge of fungal virulence mechanisms.

A cell culture model system, if a close mimic of host environmental conditions, can serve as an inexpensive, reproducible and easily manipulatable ...

Using RNA-interference to Investigate the Innate Immune Response in Mouse Macrophages

Macrophages are key phagocytic innate immune cells. When macrophages encounter a pathogen, they produce antimicrobial proteins and compounds to kill the pathogen, produce various cytokines and chemokines to recruit and stimulate other immune cells, and present antigens to stimulate the adaptive immune response. Thus, being able to efficiently manipulate macrophages with techniques such as RNA-interference (RNAi) is critical to our ability to investigate this important innate immune cell. However, macrophages can be technically challenging to transfect and can exhibit inefficient RNAi-induced gene knockdown. In this protocol, we describe methods to efficiently transfect two mouse macrophage cell lines (RAW264.7 and J774A.1) with siRNA using the Amaxa Nucleofector 96-well Shuttle System and describe procedures to maximize the effect of siRNA on gene knockdown. Moreover, the described methods are adapted to work in 96-well format, allowing for medium and high-throughput studies. To demonstrate the utility of this approach, we describe experiments that utilize RNAi to inhibit genes that regulate lipopolysaccharide (LPS)-induced cytokine production.

In this protocol, we describe methods to efficiently transfect murine macrophage cell lines with siRNAs using the Amaxa Nucleofector 96-well Shuttle System, stimulate the macrophages with lipopolysaccharide, and monitor the effects on inflammatory cytokine production.

Macrophages are key phagocytic innate immune cells.  When macrophages encounter a pathogen, they produce antimicrobial proteins and compounds to kill the ...

Use of Shigella flexneri to Study Autophagy-Cytoskeleton Interactions

Shigella flexneri is an intracellular pathogen that can escape from phagosomes to reach the cytosol, and polymerize the host actin cytoskeleton to promote its motility and dissemination. New work has shown that proteins involved in actin-based motility are also linked to autophagy, an intracellular degradation process crucial for cell autonomous immunity. Strikingly, host cells may prevent actin-based motility of S. flexneri by compartmentalizing bacteria inside &#8216;septin cages&#8217; and targeting them to autophagy. These observations indicate that a more complete understanding of septins, a family of filamentous GTP-binding proteins, will provide new insights into the process of autophagy. This report describes protocols to monitor autophagy-cytoskeleton interactions caused by S. flexneri in vitro using tissue culture cells and in vivo using zebrafish larvae. These protocols enable investigation of intracellular mechanisms that control bacterial dissemination at the molecular, cellular, and whole organism level.

Use of Shigella flexneri to Study Autophagy-Cytoskeleton Interactions

To counteract pathogen dissemination, host cells reorganize their cytoskeleton to compartmentalize bacteria and induce autophagy. Using Shigella infection of tissue culture cells, host and pathogen determinants underlying this process are identified and characterized. Using zebrafish models of Shigella infection, the role of discovered molecules and mechanisms are investigated in vivo.

Shigella flexneri is an intracellular pathogen that can escape from phagosomes to reach the cytosol, and polymerize the host actin cytoskeleton to promote ...

Assessing Anti-fungal Activity of Isolated Alveolar Macrophages by Confocal Microscopy

The lung is an interface where host cells are routinely exposed to microbes and microbial products. Alveolar macrophages are the first-line phagocytic cells that encounter inhaled fungi and other microbes. Macrophages and other immune cells recognize Aspergillus motifs by pathogen recognition receptors and initiate downstream inflammatory responses. The phagocyte NADPH oxidase generates reactive oxygen intermediates (ROIs) and is critical for host defense. Although NADPH oxidase is critical for neutrophil-mediated host defense1-3, the importance of NADPH oxidase in macrophages is not well defined. The goal of this study was to delineate the specific role of NADPH oxidase in macrophages in mediating host defense against A. fumigatus. We found that NADPH oxidase in alveolar macrophages controls the growth of phagocytosed A. fumigatus spores4. Here, we describe a method for assessing the ability of mouse alveolar macrophages (AMs) to control the growth of phagocytosed Aspergillus spores (conidia). Alveolar macrophages are stained in vivo and ten days later isolated from mice by bronchoalveolar lavage (BAL). Macrophages are plated onto glass coverslips, then seeded with green fluorescent protein (GFP)-expressing A. fumigatus spores. At specified times, cells are fixed and the number of intact macrophages with phagocytosed spores is assessed by confocal microscopy.

A method to evaluate the ability of isolated mouse alveolar macrophages to control the growth of phagocytosed Aspergillus spores by confocal microscopy.

The lung is an interface where host cells are routinely exposed to microbes and microbial products. Alveolar macrophages are the first-line phagocytic ...

Metabolic Characterization of Polarized M1 and M2 Bone Marrow-derived Macrophages Using Real-time Extracellular Flux Analysis

Specific metabolic pathways are increasingly being recognized as critical hallmarks of macrophage subsets. While LPS-induced classically activated M1 or M(LPS) macrophages are pro-inflammatory, IL-4 induces alternative macrophage activation and these so-called M2 or M(IL-4) support resolution of inflammation and wound healing. Recent evidence shows the crucial role of metabolic reprogramming in the regulation of M1 and M2 macrophage polarization. 
In this manuscript, an extracellular flux analyzer is applied to assess the metabolic characteristics of naive, M1 and M2 polarized mouse bone marrow-derived macrophages. This instrument uses pH and oxygen sensors to measure the extracellular acidification rate (ECAR) and oxygen consumption rate (OCR), which can be related to glycolytic and mitochondrial oxidative metabolism. As such, both glycolysis and mitochondrial oxidative metabolism can be measured in real-time in one single assay.
Using this technique, we demonstrate here that inflammatory M1 macrophages display enhanced glycolytic metabolism and reduced mitochondrial activity. Conversely, anti-inflammatory M2 macrophages show high mitochondrial oxidative phosphorylation (OXPHOS) and are characterized by an enhanced spare respiratory capacity (SRC). 
The presented functional assay serves as a framework to investigate how particular cytokines, pharmacological compounds, gene knock outs or other interventions affect the macrophage&#8217;s metabolic phenotype and inflammatory status.

Metabolic reprogramming is a characteristic and prerequisite for M1 and M2 macrophage polarization. This manuscript describes an assay for the measurement of fundamental parameters of glycolysis and mitochondrial function in mouse bone marrow-derived macrophages. This tool can be applied to investigate how particular factors affect the macrophage&#8217;s metabolism and phenotype.

Specific metabolic pathways are increasingly being recognized as critical hallmarks of macrophage subsets. While LPS-induced classically activated M1 or ...

Establishment of a High-throughput Setup for Screening Small Molecules That Modulate c-di-GMP Signaling in Pseudomonas aeruginosa

Bacterial resistance to traditional antibiotics has driven research attempts to identify new drug targets in recently discovered regulatory pathways. Regulatory systems that utilize intracellular cyclic di-GMP (c-di-GMP) as a second messenger are one such class of target. c-di-GMP is a signaling molecule found in almost all bacteria that acts to regulate an extensive range of processes including antibiotic resistance, biofilm formation and virulence. The understanding of how c-di-GMP signaling controls aspects of antibiotic resistant biofilm development has suggested approaches whereby alteration of the cellular concentrations of the nucleotide or disruption of these signaling pathways may lead to reduced biofilm formation or increased susceptibility of the biofilms to antibiotics. We describe a simple high-throughput bioreporter protocol, based on green fluorescent protein (GFP), whose expression is under the control of the c-di-GMP responsive promoter cdrA, to rapidly screen for small molecules with the potential to modulate c-di-GMP cellular levels in Pseudomonas aeruginosa (P. aeruginosa). This simple protocol can screen upwards of 3,500 compounds within 48 hours and has the ability to be adapted to multiple microorganisms.

Establishment of a High-throughput Setup for Screening Small Molecules That Modulate c-di-GMP Signaling in Pseudomonas aeruginosa

This article describes the high-throughput assay that has been successfully established to screen large libraries of small molecules for their potential ability to manipulate cellular levels of cyclic di-GMP in Pseudomonas aeruginosa, providing a new powerful tool for antibacterial drug discovery and compound testing.

Bacterial resistance to traditional antibiotics has driven research attempts to identify new drug targets in recently discovered regulatory pathways. ...

Generation and Identification of GM-CSF Derived Alveolar-like Macrophages and Dendritic Cells From Mouse Bone Marrow

Macrophages and dendritic cells (DCs) are innate immune cells found in tissues and lymphoid organs that play a key role in the defense against pathogens. However, they are difficult to isolate in sufficient numbers to study them in detail, therefore, in vitro models have been developed. In vitro cultures of bone marrow-derived macrophages and dendritic cells are well-established and valuable methods for immunological studies. Here, a method for culturing and identifying both DCs and macrophages from a single culture of primary mouse bone marrow cells using the cytokine granulocyte macrophage colony-stimulating factor (GM-CSF) is described. This protocol is based on the established procedure first developed by Lutz et al. in 1999 for bone marrow-derived DCs. The culture is heterogeneous, and MHCII and fluoresceinated hyaluronan (FL-HA) are used to distinguish macrophages from immature and mature DCs. These GM-CSF derived macrophages provide a convenient source of in vitro derived macrophages that closely resemble alveolar macrophages in both phenotype and function.

Bone marrow cells cultured with granulocyte macrophage colony stimulating factor (GM-CSF) generate a heterogeneous culture containing macrophages and dendritic cells (DCs). This method highlights using MHCII and hyaluronan (HA) binding to differentiate macrophages from the DCs in the GM-CSF culture. Macrophages in this culture have many similarities to alveolar macrophages.

Macrophages and dendritic cells (DCs) are innate immune cells found in tissues and lymphoid organs that play a key role in the defense against pathogens. ...