We want to acknowledge FONCYCYT of CONACYT (Mexico), the ministry of Foreign affairs of France and the Universit&#233; Paris 13, though the financial support of the international collaborative ECOS-NORD project named Nano-palpation for diagnosis, No. 263337 (Mexico) and MI5P02 (France). AMR would like to thank the financial support of SIP-IPN through the project No. 20195489. SPC is supported by a PhD fellowship from CONACYT (No. 288029) and IPN through the cotutelle agreement to obtain double PhD certificate (IPN-UPS). ED and CFD are researchers at Centre National de la Recherche Scientifique (CNRS).

1. Microbial cell culture
<ol>
	<li>Revivify cells from a glycerol stock. 
	NOTE: C. albicans are stored at -80 &#176;C in glycerol stocks, on marbles.
	<ol>
		<li>Pick a marble in the -80 &#176;C stock and rub it on yeast peptone dextrose (YPD) agar. Grow the cells for 2 days at 30 &#176;C, before liquid cultivation.</li>
	</ol>
	</li>
	<li>Prepare liquid cultures.
	<ol>
		<li>Fill a culture tube with 5 mL of sterile YPD broth and add a single colony of C. albicans cells, grown on the YPD agar plate.</li>
		<li>Grow the culture in static conditions at 30 &#176;C for 20 h before harvesting by centrifugation (4000 x g, 5 min). Discard the supernatant and eliminate as biohazard waste.</li>
		<li>Wash the pellets 2x with 10 mL of acetate buffer (8 mM sodium acetate, 1 mM CaCl2, 1 mM MnCl2, pH 5.2). Centrifuge (4000 x g, 5 min) in between washings.</li>
		<li>Resuspend the pellet in 2 mL of acetate buffer and use this solution for cell immobilization on the PDMS stamp. 
		NOTE: This suspension cannot be stored and should be prepared fresh for section 3.</li>
	</ol>
	</li>
</ol>
2. PDMS stamp preparation
<ol>
	<li>Silicon master mold preparation
	<ol>
		<li>Draw the desired microstructures using computer assisted design (CAD) software. 
		NOTE: The wells designed should be of similar size to the microbe to trap. The design should provide a large matrix of wells 100 x 100 at list. It is best to make several arrays with slightly different sizes around the average size of the microbe.</li>
		<li>If a clean room is available, follow steps 2 to 12 of the previously published protocol12. Otherwise, silicon master mold can be acquired from commercial clean room facilities.</li>
	</ol>
	</li>
	<li>PDMS stamp molding
	<ol>
		<li>Prepare 55 g of PDMS prepolymer solution containing a mixture of 10 to 1, mass ratio, of PDMS oligomers and curing agent (Table of Materials).</li>
		<li>Mix and degas this solution under vacuum (in the range of 10-1-10-2 bars) until all trapped bubbles are removed from the PDMS solution (5&#8722;10 min).</li>
		<li>Pour 20 g of the degassed solution on the silicon master mold and degas again (in the range of 10-1-10-2 bars). 
		NOTE: The stamp thickness should be around 2&#8722;3 mm.</li>
		<li>When all bubbles are removed, reticulate the PDMS at 80 &#176;C during 1 h.</li>
		<li>Cut the PDMS microstructured stamp with a scalpel (0.5 x 1.5 cm2) in a direction parallel to the visible microstructure arrays.</li>
		<li>Peel the stamp from the silicon master mold.</li>
		<li>Return the stamp to exhibit the microstructures on its upper side and deposit it on a glass slide. Make sure to have the microstructures facing up away from the glass slide. Align the microstructures that can be seen on the stamp with the side of the glass slide, which will later serve as a reference for the AFM automation procedure. 
		NOTE: At this stage, the PDMS stamp is ready for cell immobilization. The PDMS stamps can be stored on the silicon master mold for several months. When all the PDMS is removed from the master mold, a new PDMS stamp can be casted again on the master mold (to keep the master mold safe, it is possible to replicate it in polyurethane)14.</li>
	</ol>
	</li>
</ol>
3. Sample preparation
<ol>
	<li>Cell immobilization
	<ol>
		<li>Centrifuge (500 x g, 5 min) 600 &#181;L of the resuspended cell solution to separate the buffer from the cells.</li>
		<li>Pipet 200 &#181;L of the supernatant from step 3.1.1 onto the PDMS stamp, and degas under vacuum (in the range of 10-1-10-2 bars) for about 40 min. 
		NOTE: This step is important to improve the cell immobilization inside the wells. Molecules from the yeast cell wall, present in the supernatant, are probably deposited on the PDMS surface during this pre-wetting step. These molecules, most probably, enhance the adhesion of the cells and contribute to the increase in the stamp filling rate.</li>
		<li>After 40 min, with a pipette, remove the buffer from the PDMS surface and deposit, with a pipette, 200 &#181;L of the cell solution from step 1.2.4 for 15 min at room temperature.</li>
		<li>Place the cells into the microstructures of the stamp by convective/capillary assembly. For that, manually spread 200 &#181;L of cells suspension across the stamp using a glass slide in both directions with an angle between 30 and 50&#176;. It may be necessary to pass the glass slide several times on the stamp to achieve a high filling rate. 
		NOTE: A full description of this method is available13.</li>
		<li>Remove the cell suspension with a pipette. Wash the stamp 3x with 1 mL of acetate buffer, pH 5.2 to remove the cells that were not trapped.</li>
		<li>Dry the back of the stamp using nitrogen flow, in order to ensure that the stamp will adhere to the dry Petri dish.</li>
		<li>Finally deposit the PDMS stamp filled with cells in a Petri dish (Table of Materials) and fill it with 2 mL of acetate buffer to maintain the cells in liquid medium.</li>
	</ol>
	</li>
	<li>Setting the stamp on the AFM stage
	<ol>
		<li>Center the stage at 0:0 when starting AFM operations.</li>
		<li>Calibrate sensitivity and spring constant of the cantilever on glass and in water as described in Unsay et al.15</li>
		<li>Take the Petri dish with the stamp and place it in the AFM Petri dish holder.</li>
		<li>Align the stamp edge perpendicular to the Petri dish holder Y axis. 
		NOTE: An acceptable tilt angle is under 5&#176; as illustrated in Figure 1.</li>
		<li>Place the AFM head onto the stage and be careful that the stepper motors are sufficiently extended to avoid the tip to crash on the stamp.</li>
	</ol>
	</li>
</ol>
4. Running the AFM program
NOTE: The AFM program is provided as a Supplementary Material (AutomatipSoftware2019.pdf). It requires a JPK-Bruker AFM Nanowizard II or III equipped with a motorized stage and JPK desktop software version 4.3. The program has been developed under Jython (version based on python 2.7)
<ol>
	<li>Data acquisition
	<ol>
		<li>Center the AFM tip on top of the left corner of the 4.5 x 4.5 &#181;m2 wells (corresponding to the cell size) using the AFM optical microscope. If another well size is needed, center on top left corner of the desired wells.</li>
		<li>Perform a 64 x 64 force map (Z range = 4 &#181;m, tip velocity = 90 &#181;m&#183;s-1, applied force 3 to 5 nN) over a 100 x 100 &#181;m&#178; area. Select Force Mapping mode from the Measurement mode drop-down box. In the force control mapping panel input the following parameters: Rel. Setpoint = 3 to 5 nN; z length 4 &#181;m; Z movement: constant duration; extend time: 0.01s; ext. delay:0; Retr delay: 0, Delay mode: Constant Force, Sample rate 2048 Hz; Z closed loop uncheck; Grid: check Square image, Fast 100 &#181;m, slow: 100&#181;m, X offset: 0 &#181;m; Y offset: 0 &#181;m; grid angle: 0 degree; Pixels: 64x64; pixel ratio: 1:1 
		NOTE: A typical result is shown in Figure 2. This image will help measure and verify the pitch between two wells.</li>
		<li>Note the coordinates of the center of the top left well (W1) and of the bottom left well (referred as W2 on Figure 2). To do so, make a square box around the well. The coordinate of the center of the box appears on the left panel of the AFM software in x,y coordinates boxes.</li>
		<li>To open the automation software (Automatip_scan.py): in the JPK desktop software click on advance in the top bar menu and select open the script. In the window that opens select the path toward the script file provided in Supplementary Data (Automatip_scan.py).</li>
		<li>Implement W1 and W2 coordinate values in the Inputs box section of the Jython script (Figure&#160;3). Input the W1 coordinates in the P1 variable line 239 of the script and the W2 coordinates in the P2 variable line 241. 
		NOTE: The wells selected as initial coordinates (W1 and W2) should not be too close from the scanning area edge. Otherwise the centering algorithm would not execute correctly because it needs to measure the height on the PDMS surface on each side of the well. For an example, see Figure 4.</li>
		<li>Attribute the pitch value to the pitch variable line 245 of the script.</li>
		<li>Input the well dimension in the Ws variable line 248. This is known from the design of the well patterns and can be checked on the same image as the one used to verify the pitch (Figure 2).</li>
		<li>Write the path to the saving directory in line 251 to save the data at the desired place.</li>
		<li>Set the totalArea variable line 254 to the desire multiple &#34;n&#34; of 100 &#181;m (that is the maximum scan area of the AFM used). The total number of wells that will be probed can be calculated using this value and the pitch: maximum scan area/pitch*n2. 
		NOTE: In the example of Figure 3, 9 areas of 100 x 100 &#181;m2 will be analyzed.</li>
		<li>Set the force curves matrix, row and column (3, 3 or 4, 4), recorded per well in the numScans variable line 257. 
		NOTE: In the example of Figure&#160;3, a matrix of 3 x 3 = 9 FCs will be recorded for each well.</li>
		<li>Run the program. Click on the Start button. 
		NOTE: The program first automatically executes a centering algorithm to better determine the center of W1 and W2 wells (step 1). It then automatically acquires the Force Curves (FCs) matrix on each well of the first scanning area (step 2). When all the wells of that area are probed, the script automatically moves the AFM tip to the first well of the next scanning area. The tip is retracted, the microscope stage moves to the next area, the tip is again approached on the stamp and the centering algorithm is executed again to re-center automatically on the first well (1&#39;) of that area (step 3). The first area is defined by the user, the second one, is on the right etc. until n is reached. n+1 area is underneath n, n+2 on the left of n+1, etc. until 2n is reached. 2n+1 is underneath 2n, and 2n+2 is on the right on 2n, etc. Globally, the tip serpentines through the total area. Step 2 and 3 are repeated automatically until the total number &#34;n2&#34; of scanning areas have been probed. Figure 5 presents the flowchart of the program. It takes ~4 h to complete the program.</li>
	</ol>
	</li>
	<li>Data analysis
	<ol>
		<li>Execute the &#34;Copy files&#34; python script (Copy_files_L.py, provided in Supplementary Data) to organize the FCs files into one folder. This script was developed with Python 2.7 and the SciPy module. Use Visual&#160;Studio Code software to open the python script. Input path to the general folder (line 67&#160;of the script provided in supplementary data) and where it will be stored (line 73).</li>
		<li>Open the AFM manufacturer data processing software to analyze the force curves. In the top menu File, select open &#8216;batch of spectroscopy curves.</li>
		<li>In the batch processing window, select the process provided in Supplementary Data (StiffnessProcess.jpk-proc-force). Select the last step of the process and click on Keep and Apply to All. All force curves will receive the same treatment. 
		NOTE: The process uses the calibration from the FCs files to convert the deflection curves into force curves calibrated in Newton; a data smoothing algorithm is applied (average of 3 consecutives points); the baseline is translated to rest on the zero axis; the contact point is extrapolated and the FC is offset to place the contact point at coordinate (0,0); the bending of the cantilever is subtracted to the FCs, the retract slope is fitted. At the end of the data treatment, the software generates a file that contains a table giving for each FCs: its name, Young Modulus, contact point, adhesion force, slopes, etc.</li>
		<li>Repeat steps 4.2.1 to 4.2.3 for all experiments. Be careful to save the data in different folders (i.e.: &#8220;&#8230;\TREATED\&#8221; and &#8220;&#8230;\UNTREATED\&#8221;)</li>
		<li>Use the R script provided in Supplementary Data to plot histograms and box plots and perform ANOVA statistical treatments.
		<ol>
			<li>To open the R script (DataAnalisys.R), use R studio software and load the files containing the information extracted with the data processing software (.tsv).</li>
			<li>On the environment window use the Import Dataset button, from the list displayed select from text (readr) and in the new window select the Browser button and find the .tsv file.</li>
			<li>Once the file has loaded, select the columns (stiffness and adhesion) to be included for the analysis. To run all the code, press Ctrl+Alt+R. 
			NOTE: The script works with 4 datasets, consider two experiments both having untreated and treated cells. It is possible to execute blocks of the script and see how the variables change according to the functions executed.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Cross, S. E., Jin, Y. S., Rao, J., Gimzewski, J. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nanomechanical+analysis+of+cells+from+cancer+patients.">Nanomechanical analysis of cells from cancer patients.</a> Nature Nanotechnology. 2 (12), 780-783 (2007).</li><li>Dague, E., 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=Atomic+force+and+electron+microscopic-based+study+of+sarcolemmal+surface+of+living+cardiomyocytes+unveils+unexpected+mitochondrial+shift+in+heart+failure.">Atomic force and electron microscopic-based study of sarcolemmal surface of living cardiomyocytes unveils unexpected mitochondrial shift in heart failure.</a> Journal of Molecular and Cellular Cardiology. 74, 162-172 (2014).</li><li>Muller, D. J., Helenius, J., Alsteens, D., Dufrene, Y. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Force+probing+surfaces+of+living+cells+to+molecular+resolution.">Force probing surfaces of living cells to molecular resolution.</a> Nature Chemical Biology. 5 (6), 383-390 (2009).</li><li>Dague, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Atomic+Force+Microscopy+to+Explore+Electroporation+Effects+on+Cells.">Atomic Force Microscopy to Explore Electroporation Effects on Cells.</a> Handbook of Electroporation. , 1-13 (2016).</li><li>Puntheeranurak, T., Neundlinger, I., Kinne, R. K. H., Hinterdorfer, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-molecule+recognition+force+spectroscopy+of+transmembrane+transporters+on+living+cells.">Single-molecule recognition force spectroscopy of transmembrane transporters on living cells.</a> Nature Protocols. 6 (9), 1443-1452 (2011).</li><li>Formosa, C., 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=Nanoscale+analysis+of+the+effects+of+antibiotics+and+CX1+on+a+Pseudomonas+aeruginosa+multidrug-resistant+strain.">Nanoscale analysis of the effects of antibiotics and CX1 on a Pseudomonas aeruginosa multidrug-resistant strain.</a> Scientific Reports. 2, (2012).</li><li>Pillet, F., Chopinet, L., Formosa, C., Dague, &. #. 2. 0. 1. ;. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Atomic+Force+Microscopy+and+pharmacology:+From+microbiology+to+cancerology.">Atomic Force Microscopy and pharmacology: From microbiology to cancerology.</a> Biochimica et Biophysica Acta (BBA) - General Subjects. 1840 (3), 1028-1050 (2014).</li><li>Wu, P. H., 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=A+comparison+of+methods+to+assess+cell+mechanical+properties.">A comparison of methods to assess cell mechanical properties.</a> Nature Methods. 15 (7), 491-498 (2018).</li><li>Rigato, A., Rico, F., Eghiaian, F., Piel, M., Scheuring, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Atomic+Force+Microscopy+Mechanical+Mapping+of+Micropatterned+Cells+Shows+Adhesion+Geometry-Dependent+Mechanical+Response+on+Local+and+Global+Scales.">Atomic Force Microscopy Mechanical Mapping of Micropatterned Cells Shows Adhesion Geometry-Dependent Mechanical Response on Local and Global Scales.</a> ACS Nano. 9 (6), 5846-5856 (2015).</li><li>Favre, 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=Parallel+AFM+imaging+and+force+spectroscopy+using+two-dimensional+probe+arrays+for+applications+in+cell+biology.">Parallel AFM imaging and force spectroscopy using two-dimensional probe arrays for applications in cell biology.</a> Journal of Molecular Recognition. 24 (3), 446-452 (2011).</li><li>Dujardin, A., Wolf, P. D., Lafont, F., Dupres, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+multi-sample+acquisition+and+analysis+using+atomic+force+microscopy+for+biomedical+applications.">Automated multi-sample acquisition and analysis using atomic force microscopy for biomedical applications.</a> PLOS ONE. 14 (3), 0213853 (2019).</li><li>Formosa, C., 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=Generation+of+living+cell+arrays+for+atomic+force+microscopy+studies.">Generation of living cell arrays for atomic force microscopy studies.</a> Nature Protocols. 10 (1), 199-204 (2015).</li><li>Proa-Coronado, S., S&#233;verac, C., Martinez-Rivas, A., Dague, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Beyond+the+paradigm+of+nanomechanical+measurements+on+cells+using+AFM:+an+automated+methodology+to+rapidly+analyse+thousands+of+cells.">Beyond the paradigm of nanomechanical measurements on cells using AFM: an automated methodology to rapidly analyse thousands of cells.</a> Nanoscale Horizons. , (2019).</li><li>Foncy, J., 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=Comparison+of+polyurethane+and+epoxy+resist+master+mold+for+nanoscale+soft+lithography.">Comparison of polyurethane and epoxy resist master mold for nanoscale soft lithography.</a> Microelectronic Engineering. 110, 183-187 (2013).</li><li>Unsay, J. D., Cosentino, K., Garc&#237;a-S&#225;ez, 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=Atomic+Force+Microscopy+Imaging+and+Force+Spectroscopy+of+Supported+Lipid+Bilayers.">Atomic Force Microscopy Imaging and Force Spectroscopy of Supported Lipid Bilayers.</a> Journal of Visualized Experiments. (101), e52867 (2015).</li><li>Schiavone, 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=A+combined+chemical+and+enzymatic+method+to+determine+quantitatively+the+polysaccharide+components+in+the+cell+wall+of+yeasts.">A combined chemical and enzymatic method to determine quantitatively the polysaccharide components in the cell wall of yeasts.</a> FEMS Yeast Research. 14 (6), 933-947 (2014).</li><li>Formosa, C., 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=Nanoscale+Effects+of+Caspofungin+against+Two+Yeast+Species,+Saccharomyces+cerevisiae+and+Candida+albicans.">Nanoscale Effects of Caspofungin against Two Yeast Species, Saccharomyces cerevisiae and Candida albicans.</a> Antimicrobial Agents and Chemotherapy. 57 (8), 3498-3506 (2013).</li><li>El-Kirat-Chatel, S., 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=Nanoscale+analysis+of+caspofungin-induced+cell+surface+remodelling+in+Candida+albicans.">Nanoscale analysis of caspofungin-induced cell surface remodelling in Candida albicans.</a> Nanoscale. 5 (3), 1105-1115 (2013).</li><li>Peric, O., Hannebelle, M., Adams, J. D., Fantner, G. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microfluidic+bacterial+traps+for+simultaneous+fluorescence+and+atomic+force+microscopy.">Microfluidic bacterial traps for simultaneous fluorescence and atomic force microscopy.</a> Nano Research. 10 (11), 3896-3908 (2017).</li></ol>

The authors have nothing to disclose.

The main improvement provided by this methodology is a significant increase in the number of measured cells in a determined amount of time. The counterpart is a reduction of the number of points measured per cell. It means that this method is not designed to provide a detailed analysis of a single cell. The method only applies to cells that can fit in the wells of the PDMS stamp. The stamp is quite versatile, while it contains wells of 1.5 x 1.5 &#181;m2 up to 6 x 6 &#181;m2. Still it is impossible to immobilize bacillus or much bigger cells. The stamp and capillary convective deposition cannot be used to immobilize mammalian cells that are much bigger (around 100 &#181;m in length).
In this context, Peric et al.19 developed a smart microfluidic device to immobilize bacillus like Escherichia coli and bacillus subtilis. This device makes it possible to immobilize bacillus at defined positions and under physiological conditions. It would be very interesting to adapt the software to the particular size of this device.
Tip contamination can also be a problem in this automated system. In the case of microbial cells, it is not so prevalent, but it is of high importance in the case of mammalian cells. Dujardin et al.11 addressed this issue by adding a cleaning step in their automated protocol. This step consists of checking the laser sum and activating the cleaning procedure if the sum is too low. The clean step consists of immersing the tip in a well filled with water or ethanol.
A question that systematically arises from this automation work has been: &#34;does the heterogeneity comes from the evolution of the cells during the experiment?&#34;. To answer this question, we plotted the stiffness results as a function of time as presented in Figure 8A,B. It clearly demonstrates that heterogeneous stiffness values are recorded at any time during the experiment.
In the same context the question of the tip position during the measure emerged. It could be possible that force curves recorded on the edge of a cell would have a different stiffness from FC recorded on the top of the cells. To avoid this inconvenience, we defined what we called the safe area. It is depicted in Figure 9A,B and represents an area inside the wells where the tip will not touch the well edges during force measurement. Using this &#34;safe area&#34; we could record FC only on cells and at the top of them. As shown in Figure 8C,D the tip position within the safe area is not responsible for the heterogeneity of the results as we found both phenotypes for each position of the tip, in the safe area.
To make sure that the values recorded at each position are homogeneous we plotted the stiffness values as a function of the position as presented in Figure 9C,D. It shows that heterogeneous stiffness values are recorded on each position in the well, which means that the observed heterogeneity is not an artifact due to the tip position in the wells.
The protocol presented in this article represents a conceptual and methodological breakthrough in the field of AFM applied in life science. The large amounts of data generated are compatible with automatic analysis which will undoubtedly allow the classification of cell populations according to new criteria. The application of this protocol to protein or sugar arrays is entirely feasible and requires only a few adaptations to consider the spacing between areas of interest.
It is therefore a versatile protocol that is the result of strong interdisciplinary collaboration.

This work provides a methodology to perform automatic force measurements on hundreds of living cells using an atomic force microscope (AFM). It also provides a method to immobilize microbes on a PDMS microstructured stamp that is compatible with AFM experiments conducted in a liquid environment.
Bio-AFM is a highly specialized technology conceived for applications in biology and then used to study living cells. It requires a trained engineer who can analyze one cell at the time. In these conditions, the number of different cells that can be analyzed is rather small, typical 5 to 10 cells in 4-5 hours. However, the quantity of force measurements recorded on a single cell are usually very high and can easily reach 1000. Thus, the current paradigm of AFM force measurements on living cells is to record hundreds of force curves (FCs) but on a limited number of cells.
Statistically, this approach is questionable, and raises the issue of the representativeness of the sample. Indeed, it is difficult, for example, to evaluate the heterogeneity of a cell population by measuring only a few cells, even if hundreds of measurements are recorded on these few cells. However, it is on the basis of this paradigm that major advances have been made in biophysics, microbiology and nanomedicine1,2,3. Indeed, nanometer analysis at the scale of single cells has provided new information on cellular nanomechanics, on the organization of transmembrane proteins, or the action mechanism of antimicrobial or anticancer drugs4,5,6,7. Recently however, several high-throughput biomechanical tests conducted on cells have emerged8, showing the scientific community&#8217;s interest in changing this paradigm and accessing the cell population heterogeneity. These tests all rely on microfluidic systems to deform cells and optically measure their deformation under stress to obtain an indirect measure of their overall surface elasticity8. However, an important issue with these methods is that they are mono-parametric: only cell elasticity can be probed. Moreover, they do not allow the measurement of the mechanical parameters of adherent cells, which can be limiting for the studies of noncirculating mammalian cells or biofilms for example.
Approaches involving AFM have been developed by the teams of S. Scheuring9 and M. Favre10. Scheuring et al. immobilized cells on fibronectin patterns9, forcing individual cells to take the shape of the pattern9. Then this team mapped the mechanical properties of a few cells to define average data, representative of 14 to 18 cells. The development carried out by Farve et al. aimed at multiplexing the measurements by parallelizing the AFM cantilevers10. To our knowledge, this work in the multiplexing direction has not led to measurements on living cells.
An interesting approach proposed by Dujardin&#8217;s team presents an automated AFM capable of identifying cells and imaging them at the bottom of custom-made wells. Although this method does not allow for the analysis of a large population of cells, it allows the automatic testing of different conditions in each well11.
Our objective in this work is more ambitious since we wanted to measure at least 1000 cells to access not an average cell, but, on the contrary, the heterogeneity between cells. The strategy that we developed here to access cell population heterogeneity using AFM is based on the analysis of hundreds of cells on which a limited number of force curves are recorded. Compared to the &#8220;classical&#8221; approach of recording a large number of force curves on a limited number of cells, this approach should be considered as complementary since it does not provide the same information. Indeed, while the typical method allows one to probe individual cell surface heterogeneity, using our approach, we are able to access the entire cell population heterogeneity. To achieve this objective, we have combined a method that directly immobilizes microbes (here the yeast species Candida albicans) into the wells of a PDMS microstructured stamp12, and develops an original program for moving the AFM tip, automatically, from cell to cell13 and measuring the mechanical properties of each cell.

<table>
	<tbody>
		<tr>
			<td>AFM cantilever</td>
			<td>Bruker AFM probes</td>
			<td>MLCT</td>
			<td>The cantilevers used were the labeled &#8220;C&#8221; with resonant frequency of 7 to 10 kHz and k: 0.01 N/m</td>
		</tr>
		<tr>
			<td>AFM data analysis</td>
			<td>JPK-Bruker</td>
			<td>JPK Data processing version minimum 5.1.8</td>
			<td>Can be downloaded from a JPK-Bruker user acount</td>
		</tr>
		<tr>
			<td>AFM Petri dishes</td>
			<td>WPI</td>
			<td>FluoroDish FD35-100</td>
			<td>The heater was used to monitor the temperature changes during the experiment</td>
		</tr>
		<tr>
			<td>Atomic force Microscope (AFM)</td>
			<td>JPK-Bruker</td>
			<td>Nanowizard II or III</td>
			<td>the AFM should be mounted on an inverted optical microscope with a motorized stage</td>
		</tr>
		<tr>
			<td>Caspofungin</td>
			<td>Sigma-Aldrich</td>
			<td>SML0425-5MG</td>
			<td>Caspofungin was used with a concentration of 4 MIC (Minimum Inhibitor Concentration)</td>
		</tr>
		<tr>
			<td>Code editor</td>
			<td>Microsoft</td>
			<td>Visual Studio Code version 1.40.1</td>
			<td>https://code.visualstudio.com/</td>
		</tr>
		<tr>
			<td>Cryobeads</td>
			<td>IFU</td>
			<td>CB12</td>
			<td></td>
		</tr>
		<tr>
			<td>Dessicator/Degassing chamber</td>
			<td>Fisherbrand</td>
			<td>15594635</td>
			<td>The equipment is used to degassing the PDMS stamps for about 50 minutes any dessicator coupled with a vaccum pump will do.</td>
		</tr>
		<tr>
			<td>Petri dish heater</td>
			<td>JPK-Bruker</td>
			<td>PetriDishHeater</td>
			<td>This is an add-on to the JPK/Bruker AFM. The heater was used to monitor the temperature changes during the experiment</td>
		</tr>
		<tr>
			<td>Sodium acetate buffer pH 5.2</td>
			<td>Sigma-Aldrich</td>
			<td>S7899</td>
			<td>The solution contains 18 mM sodium acetate, 1 mM CaCl2, and 1 mM MnCl2. Adjust the pH with glacial acetic acid. The solution can be stored at 4 &#176;C for 2 months</td>
		</tr>
		<tr>
			<td>Statistical analysis language</td>
			<td>https://www.r-project.org</td>
			<td>R version 3.6.1</td>
			<td>R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment</td>
		</tr>
		<tr>
			<td>Statistical analysis software</td>
			<td>https://rstudio.com</td>
			<td>R studio version 1.1.463</td>
			<td>collaboration between the R Foundation, RStudio, Microsoft, TIBCO, Google, Oracle, HP and others. RStudio and Shiny are affiliated projects of the Foundation for Open Access Statistics</td>
		</tr>
		<tr>
			<td>Sylgard 184</td>
			<td>Sigma-Aldrich</td>
			<td>761028</td>
			<td>Polydimethylsiloxane (PDMS) and curing agent in one set</td>
		</tr>
		<tr>
			<td>Yeast Peptone D Broth</td>
			<td>Difco</td>
			<td>242820</td>
			<td></td>
		</tr>
		<tr>
			<td>YPD Agar</td>
			<td>Difco</td>
			<td>DF0427-17-6</td>
			<td></td>
		</tr>
	</tbody>
</table>

automation of bio-atomic force microscope measurements on hundreds of c. albicans cells

The method presented in this paper aims to automate Bio-AFM experiments and the recording of force curves. Using this method, it is possible to record forces curves on 1000 cells in 4 hours automatically. To maintain a 4 hour analysis time, the number of force curves per cell is reduced to 9 or 16. The method combines a Jython based program and a strategy for assembling cells on defined patterns. The program, implemented on a commercial Bio-AFM, can center the tip on the first cell of the array and then move, automatically, from cell to cell while recording force curves on each cell. Using this methodology, it is possible to access the biophysical parameters of the cells such as their rigidity, their adhesive properties, etc. With the automation and the large number of cells analyzed, one can access the behavior of the cell population. This is a breakthrough in the Bio-AFM field where data have, so far, been recorded on only a few tens of cells.

We used the described protocol to analyze the effect of caspofungin on the biophysical properties of the opportunistic human pathogen C. albicans in its yeast form. Caspofungin is a last chance antifungal molecule used when other drugs are ineffective because of the resistance mechanisms cells develop towards antifungals. Its mechanism of action is based on the inhibition of the subunit Fks2 of the complex fks1/Fks2 responsible for the &#223; glucan synthesis. As &#223; glucans are a major component of the fungal cell wall16,17, we expected modification of the biophysical properties of the cell wall: rigidity and adhesion.
Figure 6 presents typical histograms obtained when all the protocol presented above is applied. The red histogram represents the stiffness repartition recorded on 957 native cells and the blue one on 574 caspofungin treated cells. The first interesting observation is that both histograms demonstrate a bimodal distribution of the values. This observation is possible only because we measured hundreds of cells. On smaller samples, researchers usually observe a single distribution and miss the population heterogeneity.17,18
The second observation concerns the effect of caspofungin. It globally reduces the stiffness of the cells while still two subpopulations exist. In a last step the proposed protocol provides an ANOVA comparison of the native and treated cells as presented in Figure 7. It demonstrates that the two conditions have a different stiffness and that this difference is highly significant (p value &#60; 0.001). This value is reached thanks to the large number of cells analyzed and provides a greater confidence in the obtained results.
The adhesion has also been extracted from the automatically recorded data and we found that the adhesion force between the bare tip and native cells was of 0.64 &#177; 0.6 nN. In this case also two subpopulations were found: the first one has a mean adhesion force of 0.7 &#177; 1.4 nN while the second of 4.5 &#177; 1.5 nN. The treatment with caspofungin had unpredictable effects on the adhesion. In one experiment no effect was observed, but in another experiment, caspofungin induced a decrease in the adhesion to the tip and a reduction of the population adhesion heterogeneity. These results are extracted from Proa et al.13, where they are presented in totality.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/61315/61315fig01.jpg" /> 
Figure 1: Acceptable position of the microstructured stamp on the AFM stage. 
The tilt angle on the left pictures (up to 5&#176;) can be handled by the program but the tilt on the right is important (10&#176;). This figure has been modified from13. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61315/61315fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/61315/61315fig02.jpg" /> 
Figure 2: Typical AFM image of a filled PDMS stamps showing the initial coordinates as W1 and W2, the size of the scanning area (&#916;2), the tilt angle (&#952;). 
This Figure has been modified from13. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61315/61315fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/61315/61315fig03.jpg" /> 
Figure 3: User input section of the script. 
P1 and P2 refers to the coordinates of well 1 (W1) and well 2 (W2) of Figure 2. The other parameters are the pitch in &#181;m, the well size in &#181;m (Ws), the directory path for saving the data, the total square area that will be probed by the automated AFM (totalArea is the length in &#181;m of the side of the total square area) and the number of force-curves per wells (numScans). All units are in &#181;m. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61315/61315fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/61315/61315fig04.jpg" /> 
Figure 4: Optical image providing an example of valuable (green dots) initial wells. 
The black square represents the scanning area and the red spots, initial wells that should better be discarded. This figure has been modified from13. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61315/61315fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/61315/61315fig05.jpg" /> 
Figure 5: Program flowchart showing the 5 steps automatically executed by the AFM. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61315/61315fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/61315/61315fig06.jpg" /> 
Figure 6: Histograms of the median stiffness values. 
(A, B) Show the median results per cell for native and caspofungin treated cell. This figure has been modified from13. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61315/61315fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/61315/61315fig07.jpg" /> 
Figure 7: Box plots comparing native and treated with caspofungin cells. 
The 3 stars represent a significance of p&#60;0.001. The box represents 90% of the results, the central line is the median value and the vertical bars represent the range of all the data. This figure has been modified from13. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61315/61315fig07large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/61315/61315fig08.jpg" /> 
Figure 8: Time-position dependency of values. 
Histograms in the center are the original data which is divided into the different subgroups corresponding to the subpopulations founded (blue/yellow). (A,B) Show the presence of the two sub-populations at every hour in the experiment. (C,D) show the positions of indentation; on each position it is possible to see the presence of the subpopulations (blue/yellow). Subgroup organization was done using the k-means algorithm. This figure has been modified from13. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61315/61315fig08large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 9" class="xfigimg" src="/files/ftp_upload/61315/61315fig09.jpg" /> 
Figure 9: The safe area. 
An area, inside the PDMS well, has been defined as the area where the pyramidal tip does not touche the well edge while reaching the well bottom (in the case of an empty well). This Figure has been modified from13. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61315/61315fig09large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplementary Data.&#160;<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61315/Supplementary_Data.zip" target="_blank">Please click here to down these files.</a>

Watch this Scientific Journal Video about Automation of Bio-Atomic Force Microscope Measurements on Hundreds of C. albicans Cells at JoVE.com

Automation of Bio-Atomic Force Microscope Measurements on Hundreds of C. albicans Cells

This protocol aims to automate AFM measurements on hundreds of microbial cells. First, microbes are immobilized into PDMS stamp microstructures and then force spectroscopy measurements are performed automatically on hundreds of immobilized cells.

Automation of Bio-Atomic Force Microscope Measurements on Hundreds of C. albicans Cells

The method presented in this paper aims to automate Bio-AFM experiments and the recording of force curves. Using this method, it is possible to record ...

automation-bio-atomic-force-microscope-measurements-on-hundreds-c

Nanyang Technological University

Research

JoVE Journal

Bioengineering

3.8K Views.  Université de Toulouse, CNRS, Toulouse, France. This protocol aims to automate AFM measurements on hundreds of microbial cells. First, microbes are immobilized into PDMS stamp microstructures and then force spectroscopy measurements are performed automatically on hundreds of immobilized cells.

Video: Automation of Bio-Atomic Force Microscope Measurements on Hundreds of C. albicans Cells

Multiplexed Single-molecule Force Proteolysis Measurements Using Magnetic Tweezers

The generation and detection of mechanical forces is a ubiquitous aspect of cell physiology, with direct relevance to cancer metastasis1, atherogenesis2 and wound healing3. In each of these examples, cells both exert force on their surroundings and simultaneously enzymatically remodel the extracellular matrix (ECM). The effect of forces on ECM has thus become an area of considerable interest due to its likely biological and medical importance4-7.
	Single molecule techniques such as optical trapping8, atomic force microscopy9, and magnetic tweezers10,11 allow researchers to probe the function of enzymes at a molecular level by exerting forces on individual proteins. Of these techniques, magnetic tweezers (MT) are notable for their low cost and high throughput. MT exert forces in the range of ~1-100 pN and can provide millisecond temporal resolution, qualities that are well matched to the study of enzyme mechanism at the single-molecule level12. Here we report a highly parallelizable MT assay to study the effect of force on the proteolysis of single protein molecules. We present the specific example of the proteolysis of a trimeric collagen peptide by matrix metalloproteinase 1 (MMP-1); however, this assay can be easily adapted to study other substrates and proteases.

In this article we describe the use of magnetic tweezers to study the effect of force on enzymatic proteolysis at the single molecule level in a highly parallelizable manner.

The  generation and detection of mechanical forces is a ubiquitous aspect of cell physiology,  with direct relevance to cancer metastasis1, atherogenesis2 ...

Flexural Rigidity Measurements of Biopolymers Using Gliding Assays

Microtubules are cytoskeletal polymers which play a role in cell division, cell mechanics, and intracellular transport. Each of these functions requires microtubules that are stiff and straight enough to span a significant fraction of the cell diameter. As a result, the microtubule persistence length, a measure of stiffness, has been actively studied for the past two decades1. Nonetheless, open questions remain: short microtubules are 10-50 times less stiff than long microtubules2-4, and even long microtubules have measured persistence lengths which vary by an order of magnitude5-9.
	Here, we present a method to measure microtubule persistence length. The method is based on a kinesin-driven microtubule gliding assay10. By combining sparse fluorescent labeling of individual microtubules with single particle tracking of individual fluorophores attached to the microtubule, the gliding trajectories of single microtubules are tracked with nanometer-level precision. The persistence length of the trajectories is the same as the persistence length of the microtubule under the conditions used11. An automated tracking routine is used to create microtubule trajectories from fluorophores attached to individual microtubules, and the persistence length of this trajectory is calculated using routines written in IDL.
	This technique is rapidly implementable, and capable of measuring the persistence length of 100 microtubules in one day of experimentation. The method can be extended to measure persistence length under a variety of conditions, including persistence length as a function of length along microtubules. Moreover, the analysis routines used can be extended to myosin-based acting gliding assays, to measure the persistence length of actin filaments as well.

A method to measure the persistence length or flexural rigidity of biopolymers is described. The method uses a kinesin-driven microtubule gliding assay to experimentally determine the persistence length of individual microtubules and is adaptable to actin-based gliding assays.

Microtubules are cytoskeletal polymers which  play a role in cell division, cell mechanics, and intracellular transport. Each of these functions requires ...

Biosensor for Detection of Antibiotic Resistant Staphylococcus Bacteria

A structurally transformed lytic bacteriophage having a broad host range of Staphylococcus aureus strains and a penicillin-binding protein (PBP 2a) antibody conjugated latex beads have been utilized to create a biosensor designed for discrimination of methicillin resistant (MRSA) and sensitive (MSSA) S. aureus species 1,2. The lytic phages have been converted into phage spheroids by contact with water-chloroform interface. Phage spheroid monolayers have been moved onto a biosensor surface by Langmuir-Blodgett (LB) technique 3. The created biosensors have been examined by a quartz crystal microbalance with dissipation tracking (QCM-D) to evaluate bacteria-phage interactions. Bacteria-spheroid interactions led to reduced resonance frequency and a rise in dissipation energy for both MRSA and MSSA strains. After the bacterial binding, these sensors have been further exposed to the penicillin-binding protein antibody latex beads. Sensors analyzed with MRSA responded to PBP 2a antibody beads; although sensors inspected with MSSA gave no response. This experimental distinction determines an unambiguous discrimination between methicillin resistant and sensitive S. aureus strains. Equally bound and unbound bacteriophages suppress bacterial growth on surfaces and in water suspensions. Once lytic phages are changed into spheroids, they retain their strong lytic activity and show high bacterial capture capability. The phage and phage spheroids can be utilized for testing and sterilization of antibiotic resistant microorganisms. Other applications may include use in bacteriophage therapy and antimicrobial surfaces.

Lytic phage biosensors and antibody beads are able to discriminate between methicillin resistant (MRSA) and sensitive staphylococcus bacteria. The phages were immobilized by a Langmuir-Blodgett method onto a surface of a quartz crystal microbalance sensor and worked as broad range staphylococcus probes. Antibody beads recognize MRSA.

A structurally transformed lytic bacteriophage having a broad host range of Staphylococcus aureus strains and a penicillin-binding protein (PBP 2a) ...

Measuring the Mechanical Properties of Living Cells Using Atomic Force Microscopy

Mechanical properties of cells and extracellular matrix (ECM) play important roles in many biological processes including stem cell differentiation, tumor formation, and wound healing. Changes in stiffness of cells and ECM are often signs of changes in cell physiology or diseases in tissues. Hence, cell stiffness is an index to evaluate the status of cell cultures. Among the multitude of methods applied to measure the stiffness of cells and tissues, micro-indentation using an Atomic Force Microscope (AFM) provides a way to reliably measure the stiffness of living cells. This method has been widely applied to characterize the micro-scale stiffness for a variety of materials ranging from metal surfaces to soft biological tissues and cells. The basic principle of this method is to indent a cell with an AFM tip of selected geometry and measure the applied force from the bending of the AFM cantilever. Fitting the force-indentation curve to the Hertz model for the corresponding tip geometry can give quantitative measurements of material stiffness. This paper demonstrates the procedure to characterize the stiffness of living cells using AFM. Key steps including the process of AFM calibration, force-curve acquisition, and data analysis using a MATLAB routine are demonstrated. Limitations of this method are also discussed.

This paper demonstrates a protocol to characterize the mechanical properties of living cells by means of microindentation using an Atomic Force Microscope (AFM).

Mechanical  properties of cells and extracellular matrix (ECM) play important roles in many  biological processes including stem cell differentiation, ...

Transplantation of Induced Pluripotent Stem Cell-derived Mesoangioblast-like Myogenic Progenitors in Mouse Models of Muscle Regeneration

Patient-derived iPSCs could be an invaluable source of cells for future autologous cell therapy protocols. iPSC-derived myogenic stem/progenitor cells similar to pericyte-derived mesoangioblasts (iPSC-derived mesoangioblast-like stem/progenitor cells: IDEMs) can be established from iPSCs generated from patients affected by different forms of muscular dystrophy. Patient-specific IDEMs can be genetically corrected with different strategies (e.g. lentiviral vectors, human artificial chromosomes) and enhanced in their myogenic differentiation potential upon overexpression of the myogenesis regulator MyoD. This myogenic potential is then assessed in vitro with specific differentiation assays and analyzed by immunofluorescence. The regenerative potential of IDEMs is further evaluated in vivo, upon intramuscular and intra-arterial transplantation in two representative mouse models displaying acute and chronic muscle regeneration. The contribution of IDEMs to the host skeletal muscle is then confirmed by different functional tests in transplanted mice. In particular, the amelioration of the motor capacity of the animals is studied with treadmill tests. Cell engraftment and differentiation are then assessed by a number of histological and immunofluorescence assays on transplanted muscles. Overall, this paper describes the assays and tools currently utilized to evaluate the differentiation capacity of IDEMs, focusing on the transplantation methods and subsequent outcome measures to analyze the efficacy of cell transplantation.

Induced pluripotent stem cell (iPSC)-derived myogenic progenitors are promising candidates for cell therapy strategies to treat muscular dystrophies. This protocol describes transplantation and functional measurements required to evaluate the engraftment and differentiation of iPSC-derived mesoangioblasts (a type of muscle progenitors) in mouse models of acute and chronic muscle regeneration.

Patient-derived iPSCs could be an invaluable source of cells for future autologous cell therapy protocols. iPSC-derived myogenic stem/progenitor cells ...

Cell Patterning on Photolithographically Defined 
Parylene-C: SiO2 Substrates

Cell patterning platforms support broad research goals, such as construction of predefined in vitro neuronal networks and the exploration of certain central aspects of cellular physiology. To easily combine cell patterning with Multi-Electrode Arrays (MEAs) and silicon-based &#8216;lab on a chip&#8217; technologies, a microfabrication-compatible protocol is required. We describe a method that utilizes deposition of the polymer parylene-C on SiO2&#160;wafers. Photolithography enables accurate and reliable patterning of parylene-C at micron-level resolution. Subsequent activation by immersion in fetal bovine serum (or another specific activation solution) results in a substrate in which cultured cells adhere to, or are repulsed by, parylene or SiO2 regions respectively. This technique has allowed patterning of a broad range of cell types (including primary murine hippocampal cells, HEK 293 cell line, human neuron-like teratocarcinoma cell line, primary murine cerebellar granule cells, and primary human glioma-derived stem-like cells). Interestingly, however, the platform is not universal; reflecting the importance of cell-specific adhesion molecules. This cell patterning process is cost effective, reliable, and importantly can be incorporated into standard microfabrication (chip manufacturing) protocols, paving the way for integration of microelectronic technology.

Cell Patterning on Photolithographically Defined 
Parylene-C: SiO2 Substrates

This protocol describes a microfabrication-compatible method for cell patterning on SiO2. A predefined parylene-C design is photolithographically printed on SiO2 wafers. Following incubation with serum (or other activation solution) cells adhere specifically to (and grow according to the conformity of) underlying parylene-C, whilst being repulsed by SiO2 regions.

Cell patterning platforms support broad research goals, such as construction of predefined in vitro neuronal networks and the exploration of certain ...

From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope

It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the regulation of many cellular functions. However, due to the fast dynamics and the tiny structures involved, a very high spatio-temporal resolution is required to catch the real behavior of molecules. Here we present the experimental protocol for studying the dynamics of fluorescently-labeled plasma-membrane proteins and lipids in live cells with high spatiotemporal resolution. Notably, this approach doesn&#8217;t need to track each molecule, but it calculates population behavior using all molecules in a given region of the membrane. The starting point is a fast imaging of a given region on the membrane. Afterwards, a complete spatio-temporal autocorrelation function is calculated correlating acquired images at increasing time delays, for example each 2, 3, n repetitions. It is possible to demonstrate that the width of the peak of the spatial autocorrelation function increases at increasing time delay as a function of particle movement due to diffusion. Therefore, fitting of the series of autocorrelation functions enables to extract the actual protein mean square displacement from imaging (iMSD), here presented in the form of apparent diffusivity vs average displacement. This yields a quantitative view of the average dynamics of single molecules with nanometer accuracy. By using a GFP-tagged variant of the Transferrin Receptor (TfR) and an ATTO488 labeled 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine (PPE) it is possible to observe the spatiotemporal regulation of protein and lipid diffusion on &#181;m-sized membrane regions in the micro-to-milli-second time range.

Spatial distribution and temporal dynamics of plasma membrane proteins and lipids is a hot topic in biology. Here this issue is addressed by a spatio-temporal image fluctuation analysis that provides conceptually the same physical quantities of single particle tracking, but it uses small molecular labels and standard microscopy setups.

It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the ...

Atomic Force Microscopy Imaging and Force Spectroscopy of Supported Lipid Bilayers

Atomic force microscopy (AFM) is a versatile, high-resolution imaging technique that allows visualization of biological membranes. It has sufficient magnification to examine membrane substructures and even individual molecules. AFM can act as a force probe to measure interactions and mechanical properties of membranes. Supported lipid bilayers are conventionally used as membrane models in AFM studies. In this protocol, we demonstrate how to prepare supported bilayers and characterize their structure and mechanical properties using AFM. These include bilayer thickness and breakthrough force. 
The information provided by AFM imaging and force spectroscopy help define mechanical and chemical properties of membranes. These properties play an important role in cellular processes such as maintaining cell hemostasis from environmental stress, bringing membrane proteins together, and stabilizing protein complexes.

We describe a protocol for preparation of supported lipid bilayers and its characterization using atomic force microscopy and force spectroscopy.

Atomic force microscopy (AFM) is a versatile, high-resolution imaging technique that allows visualization of biological membranes. It has sufficient ...

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Recent advances in modular DNA assembly techniques have enabled synthetic biologists to test significantly more of the available &#34;design space&#34; represented by &#34;devices&#34; created as combinations of individual genetic components. However, manual assembly of such large numbers of devices is time-intensive, error-prone, and costly. The increasing sophistication and scale of synthetic biology research necessitates an efficient, reproducible way to accommodate large-scale, complex, and high throughput device construction.
Here, a DNA assembly protocol using the Type-IIS restriction endonuclease based Modular Cloning (MoClo) technique is automated on two liquid-handling robotic platforms. Automated liquid-handling robots require careful, often times tedious optimization of pipetting parameters for liquids of different viscosities (e.g. enzymes, DNA, water, buffers), as well as explicit programming to ensure correct aspiration and dispensing of DNA parts and reagents. This makes manual script writing for complex assemblies just as problematic as manual DNA assembly, and necessitates a software tool that can automate script generation. To this end, we have developed a web-based software tool, http://mocloassembly.com, for generating combinatorial DNA device libraries from basic DNA parts uploaded as Genbank files. We provide access to the tool, and an export file from our liquid handler software which includes optimized liquid classes, labware parameters, and deck layout. All DNA parts used are available through Addgene, and their digital maps can be accessed via the Boston University BDC ICE Registry. Together, these elements provide a foundation for other organizations to automate modular cloning experiments and similar protocols.
The automated DNA assembly workflow presented here enables the repeatable, automated, high-throughput production of DNA devices, and reduces the risk of human error arising from repetitive manual pipetting. Sequencing data show the automated DNA assembly reactions generated from this workflow are ~95% correct and require as little as 4% as much hands-on time, compared to manual reaction preparation.

Here, an automated workflow to perform modular DNA &#34;device&#34; assembly using a modular cloning DNA assembly method on liquid-handling robots is presented. The protocol uses an intuitive software tool for generating liquid handler picklists for combinatorial DNA device library generation, which we demonstrate using two liquid handling platforms.

Recent advances in modular DNA assembly techniques have enabled synthetic biologists to test significantly more of the available &#34;design space&#34; ...

Power Input Measurements in Stirred Bioreactors at Laboratory Scale

The power input in stirred bioreactors is an important scaling-up parameter and can be measured through the torque that acts on the impeller shaft during rotation. However, the experimental determination of the power input in small-scale vessels is still challenging due to relatively high friction losses inside typically used bushings, bearings and/or shaft seals and the accuracy of commercially available torque meters. Thus, only limited data for small-scale bioreactors, in particular single-use systems, is available in the literature, making comparisons among different single-use systems and their conventional counterparts difficult.
This manuscript provides a protocol on how to measure power inputs in benchtop scale bioreactors over a wide range of turbulence conditions, which can be described by the dimensionless Reynolds number (Re). The aforementioned friction losses are effectively reduced by the use of an air bearing. The procedure on how to set up, conduct and evaluate a torque-based power input measurement, with special focus on cell culture typical agitation conditions with low to moderate turbulence (100 &#60; Re &#60; 2&#183;104), is described in detail. The power input of several multi-use and single-use bioreactors is provided by the dimensionless power number (also called Newton number, P0), which is determined to be in the range of P0 &#8776; 0.3 and P0 &#8776; 4.5 for the maximum Reynolds numbers in the different bioreactors.

The power input in stirred bioreactors can be measured through the torque that acts on the impeller shaft during rotation. This manuscript describes how an air bearing can be used to effectively reduce friction losses observed in mechanical seals and improve the accuracy of power input measurements in small-scale vessels.

The power input in stirred bioreactors is an important scaling-up parameter and can be measured through the torque that acts on the impeller shaft during ...

Automation of Bio-Atomic Force Microscope Measurements on Hundreds of C. albicans Cells

Summary

Explore More Videos

Chapters in this video

Multiplexed Single-molecule Force Proteolysis Measurements Using Magnetic Tweezers

Flexural Rigidity Measurements of Biopolymers Using Gliding Assays

Biosensor for Detection of Antibiotic Resistant Staphylococcus Bacteria

Measuring the Mechanical Properties of Living Cells Using Atomic Force Microscopy

Transplantation of Induced Pluripotent Stem Cell-derived Mesoangioblast-like Myogenic Progenitors in Mouse Models of Muscle Regeneration

Cell Patterning on Photolithographically Defined Parylene-C: SiO₂ Substrates

From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope

Atomic Force Microscopy Imaging and Force Spectroscopy of Supported Lipid Bilayers

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Power Input Measurements in Stirred Bioreactors at Laboratory Scale

Automation of Bio-Atomic Force Microscope Measurements on Hundreds of C. albicans Cells

Summary

Explore More Videos

Chapters in this video

Multiplexed Single-molecule Force Proteolysis Measurements Using Magnetic Tweezers

Flexural Rigidity Measurements of Biopolymers Using Gliding Assays

Biosensor for Detection of Antibiotic Resistant Staphylococcus Bacteria

Measuring the Mechanical Properties of Living Cells Using Atomic Force Microscopy

Transplantation of Induced Pluripotent Stem Cell-derived Mesoangioblast-like Myogenic Progenitors in Mouse Models of Muscle Regeneration

Cell Patterning on Photolithographically Defined Parylene-C: SiO2 Substrates

From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope

Atomic Force Microscopy Imaging and Force Spectroscopy of Supported Lipid Bilayers

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Power Input Measurements in Stirred Bioreactors at Laboratory Scale

Cell Patterning on Photolithographically Defined Parylene-C: SiO₂ Substrates