The procedure to analyze and sort Streptomyces pellets from a two-day-old liquid-grown culture is schematically represented in Figure 1. Details for the method are given below.
1. Growth (Including Preparation of Media and Buffers)
<ol>
	<li>Prepare 1 L of 10x&#160;phosphate buffered saline (PBS; 80 g NaCl, 2 g KCl, 14.4 g Na2HPO4, 2.4 g KH2PO4 in 1 L of distilled water adjusted to pH 7.4). At time of use add 100 ml of 10x&#160;PBS to 900 ml of distilled water to obtain 1 L of PBS.</li>
	<li>Prepare 1 L of YEME medium (3 g Difco yeast extract, 5 g Bacto peptone, 3 g Oxoid malt extract, 10 g glucose, 340 g sucrose, distilled water up to 1 L) and 100 ml of 2.5 M MgCl2. Sterilize both solutions by autoclaving. Note that also other Streptomyces media can be used4,14.</li>
	<li>Add 100 ml YEME medium and 0.2 ml 2.5 M MgCl2 to a sterile 250 ml Erlenmeyer flask equipped with metal coiled springs. Prepare as many flasks as bacterial samples to study.</li>
	<li>Inoculate each flask with 108 spores of Streptomyces to obtain a spore concentration of 106 spores/ml. Grow the bacteria for 2 days at 30 &#176;C while shaking at 180 rpm.</li>
</ol>
2. Sampling
<ol>
	<li>Transfer a 5 ml sample from each culture to a 15 ml Falcon tube using a sterile 5 ml pipette. Gently shake the culture while taking the sample to ensure that the sample is representative for the whole culture.</li>
	<li>When samples are analyzed immediately with COPAS no sample preparation steps are necessary. Keep the sample on ice and proceed to step 3.1 of this protocol. When samples are analyzed at a later time point, fix the pellets as described in steps 2.3-2.5 of this protocol. Note that fixation also prevents growth of the bacteria in the tubing system when not properly cleaned after analyses. Ensure that fixation with formaldehyde is not hampering downstream analyses. For instance, RNA could not be isolated from fungal pellets after fixation with formaldehyde. In contrast, RNA was successfully isolated after fixation with 70% ethanol12.</li>
	<li>Add 600 &#956;l of 37% formaldehyde to 5 ml of sample and mix by inverting the tube 3x. Fix the samples on ice for 30 min.</li>
	<li>Centrifuge the samples at 2,500 x g in a fixed rotor at 4 &#176;C for 10 min. Carefully remove the supernatant and wash the pellets with 5 ml of PBS.</li>
	<li>Repeat step 2.4 so that the pellets are washed with PBS 2x. The samples can be stored in PBS at 4 &#176;C for several weeks.</li>
</ol>
3. COPAS Analysis
<ol>
	<li>Make sure the COPAS Plus, the pump, the computer and the 488 nm argon laser are turned on and start the Biosort software. Although turned on, the laser will still be in standby modus.</li>
	<li>Check if the sheath fluid bottle is full and the waste bottle is empty.</li>
	<li>Click &#39;START&#39; and then &#39;RUN&#39; to switch the 488 nm argon laser from standby to on. After approximately 60 sec, when the laser is on, click &#39;DONE&#39;.</li>
	<li>Check the pressure gauges. The pressures for &#39;Sheath&#39;, &#39;Sample&#39;, &#39;Sorter&#39; and &#39;Clean&#39; should read around 4.0, 0.5, 2.7, and 10.9 respectively.</li>
	<li>Click the checkbox next to &#39;Pressure OK&#39;. The system then primes the flow cell and is ready for use.</li>
	<li>Standard settings are assumed with &#39;Delay&#39; at 11 and &#39;Width&#39; 7. Thresholds are set at 50 for &#39;Signal&#39; and 40 for &#39;TOF Minimum&#39;, with TOF representing the time-of-flight. (For completeness: all &#39;Gains&#39; are set at 1, the trigger is set at EXT (Extinction) and in the &#39;Configuration&#39; tab under &#39;Select scan rate&#39; 2.50 MHz is chosen. Coincidence is set to &#39;Enhanced&#39;).</li>
	<li>Remove leftover water from the sample cup and add 0.1 ml of Streptomyces sample from step 2.2 or 2.5 in the cup together with PBS (around 50 ml). Make sure the sample cup is closed properly.</li>
	<li>Click &#39;Acquire&#39; to start collecting data. Manage the flow speed to obtain between 30-50 events per second. If the flow is too high, add PBS to the sample cup. If the flow speed is too low, add more sample.</li>
	<li>When at least 2,500 events are collected click &#39;STOP&#39;. To save all data click &#39;Store&#39; and save your file for subsequent statistical analysis. The Biosort software will save the data in four files, of which only the .txt file will be used for the subsequent analysis.</li>
	<li>Clean the sample cup by removing the sample with a 50 ml syringe and washing with water 2x.</li>
	<li>Repeat steps 3.7-3.10 until all samples are analyzed.</li>
</ol>
4. Data Analysis
<ol>
	<li>Open the .txt file and discard data with an EXT lower than 25 (using for instance MS Excel). This corresponds to debris and loose hyphal fragments (for Aspergillus niger all data with an EXT lower than 150 are discarded)4,12. Then, save all TOFs in one column in a plain &#39;.txt&#39; file (for many data files this can be automated in the programming language R, available from: <a href="http://www.r-project.org">http://www.r-project.org</a>).</li>
	<li>Make sure SciLab (version 5.3.2 or newer from http://www.scilab.org/) is installed together with the &#39;fittools&#39; library, which is available, together with the manual, from: 
	http://web.science.uu.nl/microbiology/images/fung/fittools.zip 
	http://web.science.uu.nl/microbiology/images/fung/manual%20fittools.pdf</li>
	<li>Start SciLab and run the necessary functions of the fittools library to model the data. In short: Install the fittools library as shown in the manual (only needed once).
	<ol>
		<li>Load the fittools library.</li>
		<li>Read the data (&#39;.txt&#39; file) into SciLab.</li>
		<li>Log transform the data (natural log is the default log function).</li>
		<li>Fit the model of 2 populations to the data.</li>
		<li>Plot a graph with the histogram and model (optional).</li>
		<li>Bootstrap the data (1,000 replicates).</li>
		<li>Fit the model to the bootstrapped datasets.</li>
		<li>Get the confidence intervals estimates of the 5 parameters. This will provide information on the participation fraction (p) of the populations, their 2 means (&#956;1 and &#956;2) and the accompanying standard deviations (&#945;1 and &#945;2). Furthermore, the 95% confidence intervals are determined by refitting with the model after bootstrapping (1,000 replicates)12,13,15. When the confidence intervals of the means do not overlap and the confidence interval of p is between 0.025-0.975 the dataset can be explained as a combination of two populations of normal distributions. (Note that the participation fraction of small pellets is p, whereas the participation of large pellets is 1-p.) The relationship between TOF and the diameter of a Streptomyces pellet equals 0.57 &#215; TOF + 159 &#956;m4.</li>
	</ol>
	</li>
	<li>In the case two populations are found use the average TOFs as sorting parameters in the COPAS as the upper and lower bound to sort the small and large pellets subsequently. Note that also other sorting parameters can be selected depending on the demands of the user.</li>
</ol>
5. Pellet Sorting
<ol>
	<li>Load the Streptomyces sample that needs to be sorted as described in step 3.7.</li>
	<li>Set &#39;Sorting Limits&#39; and provide details about the minimal (Lo) and maximal (Hi) TOF values. Alternatively, set an area by selecting &#39;Regions&#39; and then &#39;Define Gate Region&#39; to select the pellets with the desired dimensions or properties.</li>
	<li>Place a 50 ml tube to collect multiple pellets that meet the sorting parameters. Alternatively, a micro-titer plate can be used to sort individual pellets. Multiple pellets (104-105) are needed for DNA and protein extraction. A single pellet is sufficient for qPCR analysis of gene expression, but multiple pellets are needed for RNA sequencing.</li>
	<li>Decide and set the number of pellets that need to be sorted and click &#39;Sort Manually&#39; to sort for the selected parameters. When the set amount of pellets is reached, the sorting ends automatically.</li>
	<li>Remove left over sample with a 50 ml syringe from the sample cup and wash the cup with water 2x. Repeat steps 5.1-5.5 if other samples need to be sorted.</li>
	<li>Before shutting down the COPAS rinse the sample cup with water to remove the remaining pellets and clean the sample cup with 70% EtOH and/or 2% hypochlorite in water. Run a sample of chlorinated water to clean the entire system and repeat this with water. Empty the overflow container and clean or replace the filter that resides in this container.</li>
	<li>When finished, click &#39;STOP&#39; to release the pressure from the system. When the motor stops close the program and click &#39;Shutdown without purging&#39;. Then switch off the computer, the COPAS, the laser, and the pump.</li>
</ol>

<ol>
	<li>Hopwood, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Streptomyces in nature and medicine: the antibiotic makers. , (2007).</li><li>van Wezel, G. P., McDowall, K. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+regulation+of+the+secondary+metabolism+of+Streptomyces:+new+links+and+experimental+advances.">The regulation of the secondary metabolism of Streptomyces: new links and experimental advances.</a> Nat. Prod. Rep. 28, 1311-1333 (2011).</li><li>Ann&#233;, J., Maldonado, B., Van Impe, J., Van Mellaert, L., Bernaerts, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Recombinant+protein+production+and+streptomycetes.">Recombinant protein production and streptomycetes.</a> J. Biotechnol. 158, 159-167 (2012).</li><li>van Veluw, G. 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=Analysis+of+two+distinct+mycelial+populations+in+liquid-grown+Streptomyces+cultures+using+a+flow+cytometry-based+proteomics+approach.">Analysis of two distinct mycelial populations in liquid-grown Streptomyces cultures using a flow cytometry-based proteomics approach.</a> Appl. Microbiol. Biotechnol. 96, 1301-1312 (2012).</li><li>Veening, J. W., Smits, W. K., Bistability Kuipers, O. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=epigenetics,+and+bet-hedging+in+bacteria.">epigenetics, and bet-hedging in bacteria.</a> Annu. Rev. Microbiol. 62, 193-210 (2008).</li><li>Davey, H. M., Winson, M. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Using+flow+cytometry+to+quantify+microbial+heterogeneity.">Using flow cytometry to quantify microbial heterogeneity.</a> Curr. Issues Mol. Biol. 5, 9-15 (2003).</li><li>Betz, J. W., Aretz, W., H&#228;rtel, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Use+of+flow+cytometry+in+industrial+microbiology+for+strain+improvement+programs.">Use of flow cytometry in industrial microbiology for strain improvement programs.</a> Cytometry. 5, 145-150 (1984).</li><li>Bell, P. 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=A+flow+cytometric+method+for+rapid+selection+of+novel+industrial+yeast+hybrids.">A flow cytometric method for rapid selection of novel industrial yeast hybrids.</a> Appl. Environ. Microbiol. 64, 1669-1672 (1998).</li><li>Pulak, R., Strange, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Techniques+for+analysis,+sorting,+and+dispensing+of+C.+elegans+on+the+COPAS+flow-sorting+system.">Techniques for analysis, sorting, and dispensing of C. elegans on the COPAS flow-sorting system.</a> C. elegans: methods and applications. , 275-286 (2006).</li><li>Buszczak, 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=The+carnegie+protein+trap+library:+a+versatile+tool+for+Drosophila+developmental+studies.">The carnegie protein trap library: a versatile tool for Drosophila developmental studies.</a> Genetics. 175, 1505-1531 (2007).</li><li>Carvalho, R., 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+high-throughput+screen+for+tuberculosis+progression.">A high-throughput screen for tuberculosis progression.</a> PLoS One. 6, (2011).</li><li>de Bekker, C., van Veluw, G. J., Vinck, A., Wiebenga, L. A., W&#246;sten, H. A. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Heterogeneity+of+Aspergillus+niger+microcolonies+in+liquid+shaken+cultures.">Heterogeneity of Aspergillus niger microcolonies in liquid shaken cultures.</a> Appl. Environ. Microbiol. 77, 1263-1267 (2011).</li><li>van Veluw, G. 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=Heterogeneity+in+liquid+shaken+cultures+of+Aspergillus+niger+inoculated+with+melanised+conidia+or+conidia+of+pigmented+mutants.">Heterogeneity in liquid shaken cultures of Aspergillus niger inoculated with melanised conidia or conidia of pigmented mutants.</a> Stud. Mycol. 74, 47-57 (2013).</li><li>Kieser, T., Bibb, M. J., Buttner, M. J., Chater, K. F., Hopwood, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Practical Streptomyces Genetics. , (2000).</li><li>Vinck, 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=Hyphal+differentiation+in+the+exploring+mycelium+of+Aspergillus+niger.">Hyphal differentiation in the exploring mycelium of Aspergillus niger.</a> Mol. Microbiol. 58, 693-699 (2005).</li><li>Reichl, U., King, R., Gilles, E. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+of+pellet+morphology+during+submerged+growth+of+Streptomyces+tendae+by+image+analysis.">Characterization of pellet morphology during submerged growth of Streptomyces tendae by image analysis.</a> Biotechnol. Bioeng. 39, 164-170 (1992).</li></ol>

The authors declare that they have no competing financial interests.

Flow cytometry has enabled the high-speed analysis of large numbers of single cells, which contributed to our understanding of heterogeneity in clonal populations6. Regular flow cytometry is not feasible for analysis of the multicellular mycelial pellets of streptomycetes and fungi. Our work has demonstrated that high-throughput analysis of Streptomyces pellets is feasible using COPAS. The procedure outlined here is simple, fast, and highly reproducible. The critical parameter to keep in mind during operation of the instrument is the flow speed, which should not exceed 100 events/sec&#160;(step 3.8 of this protocol). If the pellet concentration, and therefore also the flow speed, becomes too high, the TOF values will be miscalculated because the instrument fails to detect individual pellets. Sufficiently diluting the sample by the addition of PBS overcomes this problem.
Limitations 
The COPAS Plus used here has a nozzle diameter of 1 mm, which is suitable for measuring particles with a size ranging from 30-700 &#956;m. This nozzle therefore enables measuring pellets formed by streptomycetes. In the case of filamentous fungi the micro-colonies may be larger, which limits the general applicability of the COPAS Plus. The COPAS XL can measure particles up to 1,500 &#956;m in size but its sensitivity in the lower range of diameter is less compared to that of the COPAS Plus. Both the COPAS Plus and the COPAS XL cannot analyze particles smaller than 30 &#956;m. This implies that individual microbial spores or cells cannot be analyzed. In addition, the COPAS may not accurately analyze small aggregates of spores and cells or the very small micro-colonies. For this, regular cell analyzers should be used. This limitation is overcome by the Biosorter of Union Biometrica, which can analyze particles in the range of 1-1,500 &#956;m. The purchase prize however is higher.
Troubleshooting 
The COPAS is a robust instrument that is easy to operate. However, sometimes pellets are not detected after loading a sample into the sample cup and starting the measurement. The cause is typically a clogged entry tube, which can easily be solved by pressing the &#39;clean&#39; command. This will force the pellets back from the tubing system into the sample cup. An alternative reason might be that the lid is not properly placed on the sample cup. This leads to pressure loss and the concomitant failure to detect pellets.
Significance and future directions 
We here focused on the analysis of pellet size but the COPAS setup is also able to analyze and sort based on fluorescence and density. Fluorescence detection enables us to analyze gene expression based on reporters such as GFP. Furthermore, the composition of cells can be evaluated. Even more powerful is the option to separate pellets according to these parameters. Sorted pellets can be used for downstream analyses, including all -omics studies. Indeed, we previously sorted 60,000 large and 200,000 small pellets, and demonstrated that the proteome was significantly different between large and small pellets4. This technology therefore provides new leads to improve streptomycetes as cell factories.
The key benefit of the COPAS technology is time. Previous studies on cell pellets were performed using microscopy, and this limits the number of pellets that can be analyzed up to several hundreds16. Microscopy studies already suggested the existence of two populations of pellets in liquid-grown Streptomyces cultures16. Indeed, two populations of pellets were detected regardless of culture conditions in a large number of different streptomycetes4. This size heterogeneity is not restricted to filamentous streptomycetes, but was also observed in filamentous fungi12. In all cases, the underlying mechanisms of heterogeneity are not yet known. The possibility to sort pellets according to size and fluorescence enables us to unravel such mechanisms.

Streptomycetes are filamentous soil bacteria that are well known for their proficiency to make antibiotics, as well as compounds that can be used as immunosuppressants or to combat fungal infections or cancer1,2. In addition, these organisms produce enzymes that are of interest for a wide range of industrial applications3. Most of these commercially interesting compounds are produced in bioreactors. Growth of streptomycetes in bioreactors is characterized by the formation of complex structures of interconnected hyphae, known as clumps or pellets. These multicellular structures are highly heterogeneous with respect to size4 and can reach sizes that are more than a million times larger than a single-celled bacterium such as Escherichia coli or Bacillus subtilis. Although heterogeneity is regarded as a beneficial trait in natural biological systems5, it is considered a production pitfall in industry. Bioreactor cultivations have to be reproducible and controllable to obtain the highest possible yields. A detailed understanding of the role of each of the pellet types in a bioreactor is therefore crucial to improve streptomycetes as a cell factory.
Flow cytometry is commonly used to analyze individual cells in a population6. Flow cytometers can acquire multiparametric information by simultaneously measuring characteristics of the cells (such as size, density, and multicolor fluorescence). In this way, cell properties can be correlated thereby contributing to our understanding of heterogeneity within a culture and the existence of distinct populations of cells6. More specialized instruments have made it possible to sort cells according to user-defined parameters. For instance, mutants can be screened. Following sorting, such mutant cells can be cultivated for further characterization. This has already proven to be useful, amongst others, to improve productivity of strains7,8. The nozzles of flow cytometers typically allow for the passage of cells with a maximal diameter of approximately 10 &#956;m. Therefore, pellets of streptomycetes cannot be analyzed with regular flow cytometers. They, however, can be analyzed with the Complex Object Parametric Analyzer and Sorter (COPAS). Like regular flow cytometers, COPAS can acquire multiparametric data of particles in a high throughput manner. Depending on the type of COPAS 10-1,500 &#956;m sized particles can be analyzed. In addition, it allows for sorting of individual particles that can be used for cultivation or downstream analyses, such as the isolation of DNA, RNA, or proteins. COPAS was initially designed for the analysis and sorting of small multicellular organisms, such as the nematode Caenorhabditis elegans9, and Drosophila embryos and larvae10. The instruments have also been used for zebrafish11 and for filamentous fungi12,13. The latter organisms also form mycelial pellets that are even larger than those formed by filamentous bacteria. We have recently demonstrated that the use of COPAS is also feasible for streptomycetes4. We here describe the experimental procedure for using the COPAS to assess pellet heterogeneity in Streptomyces coelicolor, including details on the methodology to sort pellets according to size. Please note, however, that this method can also be used for the analysis of other pellet-forming streptomycetes.

<table><tbody><tr><td>COPAS Plus</td><td>Union Biometrica</td><td>PLUS</td><td>Large particle flow cytometer including lasers and software</td></tr><tr><td>NaCl</td><td>Sigma Aldrich</td><td>S3014</td><td>PBS component</td></tr><tr><td>KCl</td><td>Sigma Aldrich</td><td>P9541</td><td>PBS component</td></tr><tr><td>Na&lt;sub&gt;2&lt;/sub&gt;HPO&lt;sub&gt;4&lt;/sub&gt;</td><td>Sigma Aldrich</td><td>S3264</td><td>PBS component</td></tr><tr><td>KH&lt;sub&gt;2&lt;/sub&gt;PO&lt;sub&gt;4&lt;/sub&gt;</td><td>Sigma Aldrich</td><td>P9791</td><td>PBS component</td></tr><tr><td>Difco Yeast Extract</td><td>BD Biosciences</td><td>210933</td><td>Media component</td></tr><tr><td>Bacto Peptone</td><td>BD Biosciences</td><td>211677</td><td>Media component</td></tr><tr><td>Oxoid Malt Extract</td><td>Fisher Scientific</td><td>OXLP0039B</td><td>Media component</td></tr><tr><td>Glucose</td><td>Sigma Aldrich</td><td>G8270</td><td>Media component</td></tr><tr><td>Sucrose</td><td>Sigma Aldrich</td><td>S9378</td><td>Media component</td></tr><tr><td>MgCl&lt;sub&gt;2&lt;/sub&gt;&amp;bull;6H&lt;sub&gt;2&lt;/sub&gt;O</td><td>Sigma Aldrich</td><td>M2670</td><td>Media components. Add after autoclaving.</td></tr><tr><td>Formaldehyde Solution</td><td>Sigma Aldrich</td><td>F8775</td><td>Fixation of pellets</td></tr><tr><td>Sodium Hypochlorite Solution&amp;nbsp;</td><td>Sigma Aldrich</td><td>71696</td><td>For cleaning of the instrument</td></tr><tr><td>EtOH</td><td>VWR</td><td>20816.367</td><td>For cleaning of the instrument</td></tr><tr><td>Erlenmeyer Flask (250 ml)</td><td>Fisher Scientific</td><td>214-1132</td><td>Culture flask for growing Streptomyces</td></tr><tr><td>Springs</td><td>Verenfabriek De Spiraal</td><td>Custom-Made</td><td>Used in culture flask. RVS1.4401/Length 210 mm/Diameter 17 mm/Pitch 5 mm</td></tr><tr><td>Sterile Centrifuge Tube (15 ml)</td><td>Sarstedt</td><td>62.554.002</td><td></td></tr><tr><td>Syringes (50 ml)</td><td>Sigma</td><td>Z683698</td><td></td></tr></tbody></table>

sorting of streptomyces cell pellets using a complex object parametric analyzer and sorter

Streptomycetes are filamentous soil bacteria that are used in industry for the production of enzymes and antibiotics. When grown in bioreactors, these organisms form networks of interconnected hyphae, known as pellets, which are heterogeneous in size. Here we describe a method to analyze and sort mycelial pellets using a Complex Object Parametric Analyzer and Sorter (COPAS). Detailed instructions are given for the use of the instrument and the basic statistical analysis of the data. We furthermore describe how pellets can be sorted according to user-defined settings, which enables downstream processing such as the analysis of the RNA or protein content. Using this methodology the mechanism underlying heterogeneous growth can be tackled. This will be instrumental for improving streptomycetes as a cell factory, considering the fact that productivity correlates with pellet size.

COPAS measurements of Streptomyces pellets 
Streptomycetes form mycelial pellets in liquid cultures that have a wide range of sizes. To analyze pellet size distribution, a 2-day old liquid grown Streptomyces coelicolor culture was subjected to large particle flow cytometry using a COPAS Plus Profiler equipped with a 1 mm nozzle. A typical COPAS output is a scatter plot such as visualized in Figure&#160;2A. The x-axis represents the time-of-flight (TOF), which correlates with pellet size (i.e. it takes longer for larger pellets to pass the laser beam). The y-axis shows the extinction, which represents the optical density of the object. Each point in the scatter plot corresponds to an individual event, i.e. a single pellet passing the laser beam. Importantly, when the sample is too concentrated (i.e. when the laser detects more than 100 events/sec), the COPAS frequently fails to detect individual pellets. This leads to false TOF values that are too high. Diluting the sample reduces the average TOF values, up to a point where further diluting does no longer impact TOF. This point is reached when approximately 100 pellets/sec&#160;were analyzed.
Plotting the data points into a histogram indicates that the sizes are not normally distributed (Figure&#160;2B). The distribution appears to be skewed to the right. Log transforming the data set also did not lead to a normal distribution (Figure&#160;2C). To assess whether the size distribution can be explained by assuming a mixture of two normal distributions the data was mathematically modeled12,15. Modeling indeed indicated that the size distribution can be explained by assuming the existence of two distinct populations of pellets. The population of small pellets consisted of 92% of all pellets with an average size of 248 &#956;m, while the population of large pellets (8% of all pellets) had an average size of 319 &#956;m (note that two populations are assumed to exist when the participation fraction is between 2.5-97.5%). 
Sorting of Streptomyces pellets according to size
Micro-colonies from the populations of large and small pellets were sorted. To this end, the average pellet sizes of the two populations were used to define the boundaries for sorting. Pellets smaller than 248 &#956;m were considered to be from the small pellet population, whereas pellets larger than 319 &#956;m were considered to be from the large pellet population (Figure&#160;3), so as to limit sorting of pellets from the overlapping portion of the two size distributions. Microscopic analysis of sorted pellets showed their distinct sizes (Figure&#160;3). The collected pellets can be further used for DNA, RNA, or protein isolations.
<img alt="Figure 1" fo:content-width="5in" fo:src="/files/ftp_upload/51178/51178fig1highres.jpg" src="/files/ftp_upload/51178/51178fig1.jpg" /> 
Figure 1. Schematic representation of the experimental setup to measure and analyze Streptomyces pellets using COPAS. For details, see experimental procedures.&#160;<a href="https://www.jove.com/files/ftp_upload/51178/51178fig1highres.jpg" target="_blank">Click here to view larger image.</a>
<img alt="Figure 2" fo:content-width="5in" fo:src="/files/ftp_upload/51178/51178fig2highres.jpg" src="/files/ftp_upload/51178/51178fig2.jpg" /> 
Figure 2. Pellet size heterogeneity in liquid-grown Streptomyces cultures. COPAS analysis of a 2-day-old S. coelicolor YEME culture (A) indicates that pellet sizes (indicated as Time of Flight values) are not normally distributed (B), and neither become so when log-transformed (C). Instead, two populations of pellets that differ in TOF (and thus size) were detected. <a href="https://www.jove.com/files/ftp_upload/51178/51178fig2highres.jpg" target="_blank">Click here to view larger image.</a>
<img alt="Figure 3" fo:content-width="5in" fo:src="/files/ftp_upload/51178/51178fig3highres.jpg" src="/files/ftp_upload/51178/51178fig3.jpg" /> 
Figure 3. Fractionation of Streptomyces pellets according to size. Pellets with a size smaller than 248 &#956;m (indicated in pink) were considered to be small pellets, whereas pellets with a size larger than 319 &#956;m (indicated in blue) were considered to be large pellets. Microscopic analysis confirmed the difference in size. Note that these sizes were calculated from the log-transformed data using the described relationship between TOF and the diameter of a Streptomyces pellet, which equals 0.57 &#215; TOF + 159 &#956;m. <a href="https://www.jove.com/files/ftp_upload/51178/51178fig3highres.jpg" target="_blank">Click here to view larger image.</a>

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Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter

Liquid-grown Streptomyces cultures are characterized by mycelial pellets that are heterogeneous in size. We here describe a method to analyze and sort such pellets in a high-throughput manner. These pellets can be used for further analyses, which will provide leads to understand and control growth heterogeneity.

Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter

Streptomycetes are filamentous soil bacteria that are used in industry for the production of enzymes and antibiotics. When grown in bioreactors, these ...

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10.9K Views.  Leiden University. Liquid-grown Streptomyces cultures are characterized by mycelial pellets that are heterogeneous in size. We here describe a method to analyze and sort such pellets in a high-throughput manner. These pellets can be used for further analyses, which will provide leads to understand and control growth heterogeneity.

Video: Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter

Purification of Specific Cell Population by Fluorescence Activated Cell Sorting (FACS)

Experimental and clinical studies often require highly purified cell populations.  FACS is a technique of choice to purify cell populations of known phenotype.  Other bulk methods of purification include panning, complement depletion and magnetic bead separation.  However, FACS has several advantages over other available methods.  FACS is the preferred method when very high purity of the desired population is required, when the target cell population expresses a very low level of the identifying marker or when cell populations require separation based on differential marker density.  In addition, FACS is the only available purification technique to isolate cells based on internal staining or intracellular protein expression, such as a genetically modified fluorescent protein marker.  FACS allows the purification of individual cells based on size, granularity and fluorescence.  In order to purify cells of interest, they are first stained with fluorescently-tagged monoclonal antibodies (mAb), which recognize specific surface markers on the desired cell population (1).  Negative selection of unstained cells is also possible.  FACS purification requires a flow cytometer with sorting capacity and the appropriate software.  For FACS, cells in suspension are passed as a stream in droplets with each containing a single cell in front of a laser.  The fluorescence detection system detects cells of interest based on predetermined fluorescent parameters of the cells.  The instrument applies a charge to the droplet containing a cell of interest and an electrostatic deflection system facilitates collection of the charged droplets into appropriate collection tubes (2).  The success of staining and thereby sorting depends largely on the selection of the identifying markers and the choice of mAb.  Sorting parameters can be adjusted depending on the requirement of purity and yield.  Although FACS requires specialized equipment and personnel training, it is the method of choice for isolation of highly purified cell populations.

Purification of Specific Cell Population by Fluorescence Activated Cell Sorting FACS

For many scientific studies requiring a biological and chemical analysis of cell populations the cells must be in a high state of purity. Fluorescence activated cell sorting (FACS) is a superior method in which to obtain pure cell populations.

Experimental and clinical studies often require highly purified cell populations.  FACS is a technique of choice to purify cell populations of known ...

Immunology and Infection

Step-specific Sorting of Mouse Spermatids by Flow Cytometry

The differentiation of mouse spermatids is one critical process for the production of a functional male gamete with an intact genome to be transmitted to the next generation. So far, molecular studies of this morphological transition have been hampered by the lack of a method allowing adequate separation of these important steps of spermatid differentiation for subsequent analyses. Earlier attempts at proper gating of these cells using flow cytometry may have been difficult because of a peculiar increase in DNA fluorescence in spermatids undergoing chromatin remodeling. Based on this observation, we provide details of a simple flow cytometry scheme, allowing reproducible purification of four populations of mouse spermatids fixed with ethanol, each representing a different state in the nuclear remodeling process. Population enrichment is confirmed using step-specific markers and morphological criterions. The purified spermatids can be used for genomic and proteomic analyses.

We describe a sorting strategy for mouse spermatids using flow cytometry. Spermatids are sorted into four highly pure populations, including round (spermiogenesis steps 1-9), early elongating (spermiogenesis steps 10-12), late elongating (spermiogenesis steps 13-14) and elongated spermatids (spermiogenesis steps 15-16). DNA staining, size and granulosity are used as selection parameters.

The differentiation of mouse spermatids is one critical process for the production of a functional male gamete with an intact genome to be transmitted to ...

Developmental Biology

Semi-automated Biopanning of Bacterial Display Libraries for Peptide Affinity Reagent Discovery and Analysis of Resulting Isolates

Biopanning bacterial display libraries is a proven technique for peptide affinity reagent discovery for recognition of both biotic and abiotic targets. Peptide affinity reagents can be used for similar applications to antibodies, including sensing and therapeutics, but are more robust and able to perform in more extreme environments. Specific enrichment of peptide capture agents to a protein target of interest is enhanced using semi-automated sorting methods which improve binding and wash steps and therefore decrease the occurrence of false positive binders. A semi-automated sorting method is described herein for use with a commercial automated magnetic-activated cell sorting device with an unconstrained bacterial display sorting library expressing random 15-mer peptides. With slight modifications, these methods are extendable to other automated devices, other sorting libraries, and other organisms. A primary goal of this work is to provide a comprehensive methodology and expound the thought process applied in analyzing and minimizing the resulting pool of candidates. These techniques include analysis of on-cell binding using fluorescence-activated cell sorting (FACS), to assess affinity and specificity during sorting and in comparing individual candidates, and the analysis of peptide sequences to identify trends and consensus sequences for understanding and potentially improving the affinity to and specificity for the target of interest.

Biopanning bacterial display libraries is a proven technique for discovery of peptide affinity reagents, a robust alternative to antibodies. The semi-automated sorting method herein has streamlined biopanning to decrease the occurrence of false positives. Here we illustrate the thought process and techniques applied in evaluating candidates and minimizing downstream analysis.

Biopanning bacterial display libraries is a proven technique for peptide affinity reagent discovery for recognition of both biotic and abiotic targets. ...

Biochemistry

Kinetic Measurement and Real Time Visualization of Somatic Reprogramming

Somatic reprogramming has enabled the conversion of adult cells to induced pluripotent stem cells (iPSC) from diverse genetic backgrounds and disease phenotypes. Recent advances have identified more efficient and safe methods for introduction of reprogramming factors. However, there are few tools to monitor and track the progression of reprogramming. Current methods for monitoring reprogramming rely on the qualitative inspection of morphology or staining with stem cell-specific dyes and antibodies. Tools to dissect the progression of iPSC generation can help better understand the process under different conditions from diverse cell sources. 
This study presents key approaches for kinetic measurement of reprogramming progression using flow cytometry as well as real-time monitoring via imaging. To measure the kinetics of reprogramming, flow analysis was performed at discrete time points using antibodies against positive and negative pluripotent stem cell markers. The combination of real-time visualization and flow analysis enables the quantitative study of reprogramming at different stages and provides a more accurate comparison of different systems and methods. Real-time, image-based analysis was used for the continuous monitoring of fibroblasts as they are reprogrammed in a feeder-free medium system. The kinetics of colony formation was measured based on confluence in the phase contrast or fluorescence channels after staining with live alkaline phosphatase dye or antibodies against SSEA4 or TRA-1-60. The results indicated that measurement of confluence provides semi-quantitative metrics to monitor the progression of reprogramming.

The protocol presented in this study describes methods for the real-time monitoring of reprogramming progression via the kinetic measurement of positive and negative pluripotent stem cell markers using flow cytometry analysis. The protocol also includes the imaging-based assessment of morphology, and marker or reporter expression during iPSC generation.

Somatic reprogramming has enabled the conversion of adult cells to induced pluripotent stem cells (iPSC) from diverse genetic backgrounds and disease ...

A Standardized Approach for Multispecies Purification of Mammalian Male Germ Cells by Mechanical Tissue Dissociation and Flow Cytometry

Fluorescence-activated cell sorting (FACS) has been one of the methods of choice to isolate enriched populations of mammalian testicular germ cells. Currently, it allows the discrimination of up to 9 murine germ cell populations with high yield and purity. This high-resolution in discrimination and purification is possible due to unique changes in chromatin structure and quantity throughout spermatogenesis. These patterns can be captured by flow cytometry of male germ cells stained with fluorescent DNA-binding dyes such as Hoechst-33342 (Hoechst). Herein is a detailed description of a recently developed protocol to isolate mammalian testicular germ cells. Briefly, single cell suspensions are generated from testicular tissue by mechanical dissociation, double stained with Hoechst and propidium iodide (PI) and processed by flow cytometry. A serial gating strategy, including the selection of live cells (PI negative) with different DNA content (Hoechst intensity), is used during FACS sorting to discriminate up to 5 germ cell types. These include, with corresponding average purities (determined by microscopy evaluation): spermatogonia (66%), primary (71%) and secondary (85%) spermatocytes, and spermatids (90%), further separated into round (93%) and elongating (87%) subpopulations. Execution of the entire workflow is straightforward, allows the isolation of 4 cell types simultaneously with the appropriate FACS machine, and can be performed in less than 2 h. As reduced processing time is crucial to preserve the physiology of ex vivo cells, this method is ideal for downstream high-throughput studies of male germ cell biology. Moreover, a standardized protocol for multispecies purification of mammalian germ cells eliminates methodological sources of variables and allows a single set of reagents to be used for different animal models.

This work describes the standardization of a method to obtain purified germ cell populations from testicular tissue of different mammalian species. It is a straightforward protocol that combines mechanical testis dissociation, staining with Hoechst-33342 and propidium iodide, and FACS sorting, with wide applications in comparative studies of male reproductive biology.

Fluorescence-activated cell sorting (FACS) has been one of the methods of choice to isolate enriched populations of mammalian testicular germ cells. ...

Bromodeoxyuridine (BrdU) Labeling and Subsequent Fluorescence Activated Cell Sorting for Culture-independent Identification of Dissolved Organic Carbon-degrading Bacterioplankton

Microbes are major agents mediating the degradation of numerous dissolved organic carbon (DOC) substrates in aquatic environments. However, identification of bacterial taxa that transform specific pools of DOC in nature poses a technical challenge. 
Here we describe an approach that couples bromodeoxyuridine (BrdU) incorporation, fluorescence activated cell sorting (FACS), and 16S rRNA gene-based molecular analysis that allows culture-independent identification of bacterioplankton capable of degrading a specific DOC compound in aquatic environments. Triplicate bacterioplankton microcosms are set up to receive both BrdU and a model DOC compound (DOC amendments), or only BrdU (no-addition control). BrdU substitutes the positions of thymidine in newly synthesized bacterial DNA and BrdU-labeled DNA can be readily immunodetected 1,2. Through a 24-hr incubation, bacterioplankton that are able to use the added DOC compound are expected to be selectively activated, and therefore have higher levels of BrdU incorporation (HI cells) than non-responsive cells in the DOC amendments and cells in no-addition controls (low BrdU incorporation cells, LI cells). After fluorescence immunodetection, HI cells are distinguished and physically separated from the LI cells by fluorescence activated cell sorting (FACS) 3. Sorted DOC-responsive cells (HI cells) are extracted for DNA and taxonomically identified through subsequent 16S rRNA gene-based analyses including PCR, clone library construction and sequencing.

Bromodeoxyuridine BrdU Labeling and Subsequent Fluorescence Activated Cell Sorting for Culture-independent Identification of Dissolved Organic Carbon-degrading Bacterioplankton

Environmental bacterioplankton are incubated with a model dissolved organic carbon (DOC) compound and a DNA labeling reagent, bromodeoxyuridine (BrdU). Afterward, DOC-degrading cells are separated from the bulk community based on their elevated BrdU incorporation using fluorescence activated cell sorting (FACS). These cells are then identified by subsequent molecular analyses.

Microbes are major agents mediating the degradation of numerous dissolved organic carbon (DOC) substrates in aquatic environments. However, identification ...

BEST: Barcode Enabled Sequencing of Tetrads

Tetrad analysis is a valuable tool for yeast genetics, but the laborious manual nature of the process has hindered its application on large scales. Barcode Enabled Sequencing of Tetrads (BEST)1 replaces the manual processes of isolating, disrupting and spacing tetrads. BEST isolates tetrads by virtue of a sporulation-specific GFP fusion protein that permits fluorescence-activated cell sorting of tetrads directly onto agar plates, where the ascus is enzymatically digested and the spores are disrupted and randomly arrayed by glass bead plating. The haploid colonies are then assigned sister spore relationships, i.e. information about which spores originated from the same tetrad, using molecular barcodes read during genotyping. By removing the bottleneck of manual dissection, hundreds or even thousands of tetrads can be isolated in minutes. Here we present a detailed description of the experimental procedures required to perform BEST in the yeast Saccharomyces cerevisiae, starting with a heterozygous diploid strain through the isolation of colonies derived from the haploid meiotic progeny.

Barcode Enabled Sequencing of Tetrads (BEST) replaces the manual processes of isolating, disrupting and spacing tetrads. BEST isolates tetrads by fluorescence-activated cell sorting onto agar plates, separates the spores by agitation with glass beads, and determines which randomly arrayed colonies were derived from the same original tetrad using molecular barcodes.

Tetrad analysis is a valuable tool for yeast genetics, but the laborious manual nature of the process has hindered its application on large scales. ...

Low-Input Metabolic Studies in Mice Cell Types

Targeted Metabolomics on Rare Primary Cells

Cellular function critically depends on metabolism, and the function of the underlying metabolic networks can be studied by measuring small molecule intermediates. However, obtaining accurate and reliable measurements of cellular metabolism, particularly in rare cell types like hematopoietic stem cells, has traditionally required pooling cells from multiple animals. A protocol now enables researchers to measure metabolites in rare cell types using only one mouse per sample while generating multiple replicates for more abundant cell types. This reduces the number of animals that are required for a given project. The protocol presented here involves several key differences over traditional metabolomics protocols, such as using 5 g/L NaCl as a sheath fluid, sorting directly into acetonitrile, and utilizing targeted quantification with rigorous use of internal standards, allowing for more accurate and comprehensive measurements of cellular metabolism. Despite the time required for the isolation of single cells, fluorescent staining, and sorting, the protocol can preserve differences among cell types and drug treatments to a large extent.

Author Spotlight: Advancing Metabolomics Analysis of Rare Hematopoietic Stem Cells 

Here, we present a protocol to accurately and reliably measure metabolites in rare cell types. Technical improvements, including a modified sheath fluid for cell sorting and the generation of relevant blank samples, enable a comprehensive quantification of metabolites with an input of only 5000 cells per sample.

Cellular function critically depends on metabolism, and the function of the underlying metabolic networks can be studied by measuring small molecule ...

Multi-enzyme Screening Using a High-throughput Genetic Enzyme Screening System

The recent development of a high-throughput single-cell assay technique enables the screening of novel enzymes based on functional activities from a large-scale metagenomic library1. We previously proposed a genetic enzyme screening system (GESS) that uses dimethylphenol regulator activated by phenol or p-nitrophenol. Since a vast amount of natural enzymatic reactions produce these phenolic compounds from phenol deriving substrates, this single genetic screening system can be theoretically applied to screen over 200 different enzymes in the BRENDA database. Despite the general applicability of GESS, applying the screening process requires a specific procedure to reach the maximum flow cytometry signals. Here, we detail the developed screening process, which includes metagenome preprocessing with GESS and the operation of a flow cytometry sorter. Three different phenolic substrates (p-nitrophenyl acetate, p-nitrophenyl-&#946;-D-cellobioside, and phenyl phosphate) with GESS were used to screen and to identify three different enzymes (lipase, cellulase, and alkaline phosphatase), respectively. The selected metagenomic enzyme activities were confirmed only with the flow cytometry but DNA sequencing and diverse in vitro analysis can be used for further gene identification.

This work presents a method of high-throughput screening using a universal genetic enzyme screening system that can be theoretically applied to over 200 enzymes. Here, the single screening system identifies three different enzymes (lipase, cellulase, and alkaline phosphatase) by simply changing the substrate used (p-nitrophenyl acetate, p-nitrophenyl-&#946;-D-cellobioside, and phenyl phosphate).

The recent development of a high-throughput single-cell assay technique enables the screening of novel enzymes based on functional activities from a ...

Fluorescence-Activated Single-Cell Sorting of Human Mesenchymal Stem Cells

Single-Cell Sorting of Immunophenotyped Mesenchymal Stem Cells from Human Exfoliated Deciduous Teeth

The mesenchymal stem cells (MSCs) of an organism possess an extraordinary capacity to differentiate into multiple lineages of adult cells in the body and are known for their immunomodulatory and anti-inflammatory properties. The use of these stem cells is a boon to the field of regenerative biology, but at the same time, a bane to regenerative medicine and therapeutics owing to the multiple cellular ambiguities associated with them. These ambiguities may arise from the diversity in the source of these stem cells and from their in vitro growth conditions, both of which reflect upon their functional heterogeneity.
This warrants methodologies to provide purified, homogeneous populations of MSCs&#160;for therapeutic applications. Advances in the field of flow cytometry have enabled the detection of single-cell populations using a multiparametric approach. This protocol outlines a way to identify and purify&#160;stem cells from&#160;human exfoliated deciduous teeth (SHEDs) through fluorescence-assisted single-cell sorting. Simultaneous expression of surface markers, namely, CD90-fluorescein isothiocyanate (FITC), CD73-peridinin-chlorophyll-protein (PerCP-Cy5.5), CD105-allophycocyanin (APC), and CD44-V450, identified the &#34;bright,&#34; positive-expressors of MSCs&#160;using multiparametric&#160;flow cytometry. However, a significant drop was observed in percentages of quadruple expressors of these positive markers from passage 7 onwards to the later passages.
The immunophenotyped subpopulations were sorted using the single-cell sort mode where only two positive and one negative marker constituted the inclusion criteria. This methodology ensured the cell viability of the sorted populations and maintained cell proliferation post sorting. The downstream application for such sorting can be used to evaluate lineage-specific differentiation for the gated subpopulations. This approach can be applied to other single-cell systems to improve isolation conditions and for acquiring multiple cell surface marker information.

Author Spotlight: Importance of Single Cell Sorting in Isolating Purified Populations of Mesenchymal Stem Cells 

This protocol describes the use of fluorescence-activated cell sorting of human mesenchymal stem cells using the single-cell sorting method. Specifically, the use of single-cell sorting can achieve 99% purity of the immunophenotyped cells from a heterogeneous population when combined with a multiparametric flow cytometry-based approach.

The mesenchymal stem cells (MSCs) of an organism possess an extraordinary capacity to differentiate into multiple lineages of adult cells in the body and ...

Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter

Summary

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Chapters in this video

Purification of Specific Cell Population by Fluorescence Activated Cell Sorting (FACS)

Step-specific Sorting of Mouse Spermatids by Flow Cytometry

Semi-automated Biopanning of Bacterial Display Libraries for Peptide Affinity Reagent Discovery and Analysis of Resulting Isolates

Kinetic Measurement and Real Time Visualization of Somatic Reprogramming

A Standardized Approach for Multispecies Purification of Mammalian Male Germ Cells by Mechanical Tissue Dissociation and Flow Cytometry

Bromodeoxyuridine (BrdU) Labeling and Subsequent Fluorescence Activated Cell Sorting for Culture-independent Identification of Dissolved Organic Carbon-degrading Bacterioplankton

BEST: Barcode Enabled Sequencing of Tetrads

Targeted Metabolomics on Rare Primary Cells

Multi-enzyme Screening Using a High-throughput Genetic Enzyme Screening System

Single-Cell Sorting of Immunophenotyped Mesenchymal Stem Cells from Human Exfoliated Deciduous Teeth