{"id":493,"date":"2017-05-02T14:04:48","date_gmt":"2017-05-02T18:04:48","guid":{"rendered":"https:\/\/geiselmed2.dartmouth.edu\/dartlab\/flow-cytometry\/"},"modified":"2017-05-02T14:04:48","modified_gmt":"2017-05-02T18:04:48","slug":"flow-cytometry","status":"publish","type":"page","link":"https:\/\/geiselmed.dartmouth.edu\/dartlab\/services\/flow-cytometry\/","title":{"rendered":"Flow Cytometry"},"content":{"rendered":"<ul><li class=\"page_item page-item-486\"><a href=\"https:\/\/geiselmed.dartmouth.edu\/dartlab\/services\/flow-cytometry\/pre-sort-questionnaire\/\">Pre-sort Questionnaire<\/a><\/li>\n<li class=\"page_item page-item-451\"><a href=\"https:\/\/geiselmed.dartmouth.edu\/dartlab\/services\/flow-cytometry\/sorting-recovery-calculations\/\">Sorting Recovery Calculations<\/a><\/li>\n<li class=\"page_item page-item-464\"><a href=\"https:\/\/geiselmed.dartmouth.edu\/dartlab\/services\/flow-cytometry\/cell-surface-staining\/\">Cell Surface Staining<\/a><\/li>\n<li class=\"page_item page-item-460\"><a href=\"https:\/\/geiselmed.dartmouth.edu\/dartlab\/services\/flow-cytometry\/antibody-titration\/\">Antibody Titration<\/a><\/li>\n<li class=\"page_item page-item-448\"><a href=\"https:\/\/geiselmed.dartmouth.edu\/dartlab\/services\/flow-cytometry\/tubes\/\">Tubes<\/a><\/li>\n<li class=\"page_item page-item-466\"><a href=\"https:\/\/geiselmed.dartmouth.edu\/dartlab\/services\/flow-cytometry\/solutions\/\">Solutions<\/a><\/li>\n<li class=\"page_item page-item-444\"><a href=\"https:\/\/geiselmed.dartmouth.edu\/dartlab\/services\/flow-cytometry\/useful-links\/\">Useful Links<\/a><\/li>\n<li class=\"page_item page-item-421\"><a href=\"https:\/\/geiselmed.dartmouth.edu\/dartlab\/services\/flow-cytometry\/flow-cytometry-software\/\">Flow Cytometry Software<\/a><\/li>\n<li class=\"page_item page-item-442\"><a href=\"https:\/\/geiselmed.dartmouth.edu\/dartlab\/services\/flow-cytometry\/qc\/\">Quality Control<\/a><\/li>\n<\/ul>\n<ul>\n<li><a href=\"https:\/\/geiselmed.dartmouth.edu\/dartlab\/wp-content\/uploads\/sites\/22\/2017\/05\/flowbasics.pdf\">Flow Cytometry Basics<\/a> (Givan)<\/li>\n<li><a href=\"https:\/\/geiselmed.dartmouth.edu\/dartlab\/wp-content\/uploads\/sites\/22\/2017\/05\/DNA.pdf\">DNA Overview<\/a> (Givan)<\/li>\n<li><a href=\"http:\/\/www.drmr.com\/compensation\/\">Compensation<\/a> (Roederer)<\/li>\n<\/ul>\n<h2>Three Rules for Compensation Controls<\/h2>\n<h3 class=\"date-header\">(from TreeStar Daily Dongle 10 Sep 2011)<\/h3>\n<p>First and foremost, there must be a single stained control for every parameter in the experiment!<\/p>\n<p>In addition, there are three <em>rules<\/em> for \u201cgood\u201d compensation controls:<\/p>\n<p>1) Controls need to be at least as bright or brighter than any sample to which the compensation will be applied<\/p>\n<p>2) Background fluorescence should be the same for the positive and negative control<\/p>\n<p>3) Compensation controls MUST match the exact experimental fluorochrome<\/p>\n<p>\u00a0<\/p>\n<p>1) Controls need to be at least as bright or brighter than any sample to which the\u00a0compensation will be applied<\/p>\n<p>An important consideration is to select the sample with the brightest  fluorescence of the experiment. \u201cDimness\u201d is relatively irrelevant.  Only brightest matters, and that is so that low spillovers can be  accurately estimated. For example, if a spillover is so low that a MFI  of 10,000 doesn't cause enough spillover to be above autofluorescence,  then the system assumes no compensation is necessary. At a MFI of  100,000, the spillover becomes apparent and then compensation value can  be accurately assessed. Compensation is only about estimating the slope.  The bottom line is that because the compensation coefficients are  computed based on the <strong>RATIO of the DIFFERENCE<\/strong> in MFI's  (of the spillover channel and the primary channel), so small absolute  errors in the position of the negative control become irrelevant as the  positive controls become brighter. The error in the compensation  coefficient is the sum of the absolute errors in the MFI's of both the  negative and the positive control; the latter has an inherently much  larger absolute error than the former.<\/p>\n<p>2) Background fluorescence should be the same for the positive and negative control<\/p>\n<p>Any carrier for binding fluorochromes can be used for single stain  compensation controls, such as cells or particles. However, the positive  and negative carrier of a parameter must have the same  autofluorescence. This is because compensation is a subtraction  algorithm. It is imperative to NOT include autofluorescence in the  compensation calculation, so if the positive and negative have the same  autofluorescence, then the autofluorescence contribution to the  compensation spillover calculation will be zero. If this is met, one can  apply the compensation matrix to any population. For example, one can  compensate on particles and apply that to cells.<\/p>\n<p>3) Compensation control fluorochromes MUST match the exact experimental fluorochrome<\/p>\n<p>Each flurochrome has a unique emission profile.\u00a0 Therefore, the  amount of spillover will be different, even for fluorochromes that emit  light at about the same wavelength (e.g. FITC and Alexa Fluor 488)<\/p>\n<p>This rule is even more restrictive when applied to tandem dyes.\u00a0 Each <strong>lot<\/strong> of tandem dye (PE-TR, PE-Cy5, PerCP-Cy5.5, APC-Cy7, etc.) should be  considered unique and require its own single stain control. If a user is  using two different lots of PE-Cy7 in an experiment, then they need to  have two PE-Cy7 compensation single stain controls, one from each lot.  Different lots will have different conjugation ratios, i.e. more Cy7  conjugates to PE or less.<\/p>\n<p>One final note<\/p>\n<p>Finally, compensation controls must be treated in the same manner as  experimental samples. This is because exposure to light and treatments  like fixation\/permeabilization may alter the fluorochrome, particularly  the tandem conjugation ratio, i.e. lose some Cy7 on each PE molecule.<\/p>\n<p><em>Compensation particles versus cells for single stain controls<\/em><\/p>\n<p>There is no difference in the accuracy of the two approaches for  compensation. However, compensation particles do have numerous benefits  over using cells. First and foremost, precious sample does not need to  be wasted on single stain controls. All the cells can then be used for  the experimental samples. In addition, compensation particles typically  provide the brightest signal possible for any given parameter.  Compensation particles are also more precise. The reason that particles  are more precise for compensation is fairly straightforward. Cells have a  large variance in background fluorescence (a high CV), higher than  particles. This means that the spillover computation has significant  error for compensation coefficients where the measurement of spillover  fluorescence on cells is dominated by the error in the autofluorescence  measurement. On the other hand, the particles have a much smaller error  in the distribution of background fluorescence, meaning that the  spillover computation is far more precise.<\/p>\n<p>Of course, particles have some limitations.<\/p>\n<p>1) Compensation particles cannot be used for dyes like PI, DAPI, or  EMA -- but they can be used with amine-reactive viability dyes.  \u00a0(Also, some manufacturers are now providing specific dyes preloaded  into particles to use as single stain compensation controls).<\/p>\n<p>2)\u00a0 Particles do not bind all antibody reagents and in some cases they simply are not bright enough.<\/p>\n<p>3) For some experimental conditions using tandems (e.g.  permeabilization\/fixation), one must ensure that the fluorescence  spectrum of the experiment does not alter the emission spectrum of the  tandems attached to particles in a different manner than it would the  tandems attached to cells.<\/p>\n<p><strong>So, in fact, in many experiments, a user may have one or two  cell-based compensation controls for some parameters used together with  bead based compensation controls for the other parameters.<\/strong><\/p>\n<h2 class=\"entry-header\">FMO vs. Isotype Controls<\/h2>\n<h3 class=\"date-header\">(from TreeStar Daily Dongle 10 Sep 2011)<\/h3>\n<p>In addition to compensation controls, there are several other  controls that can, and in most cases, should be used to help resolve  issue in staining. Fluorescence Minus One (FMO) controls can help  identify gating boundaries, isotype controls can help identify staining  issues and unstained controls show you the background or  autofluorescence of the system.<\/p>\n<p><a href=\"http:\/\/flowjo.typepad.com\/.a\/6a00d8341c0ebb53ef0154354e8e60970c-pi\"><img loading=\"lazy\" decoding=\"async\" class=\"asset  asset-image at-xid-6a00d8341c0ebb53ef0154354e8e60970c image-full\" title=\"Picture 1\" src=\"https:\/\/geiselmed2.dartmouth.edu\/dartlab\/wp-content\/uploads\/sites\/26\/2017\/05\/6a00d8341c0ebb53ef0154354e8e60970c-800wi\" border=\"0\" alt=\"Picture 1\" width=\"617\" height=\"282\" \/><\/a><\/p>\n<p>FMO controls are ideal for showing gating boundaries, even with  compensation issues. FMO controls contain every stain in the panel  except the one you are controlling for in that sample. For example, a  FITC FMO control would contain all fluorochromes except FITC. (You can  include isotype controls in FMO controls if you would like, but isotype  controls DO NOT accurately show staining boundaries.) The following  figure shows how a gate on an unstained or isotype would be set  incorrectly as compared to an FMO control. Furthermore, the second pane  demonstrates how FMO controls can resolve gating boundaries even with  improper compensation:<\/p>\n<p><a href=\"http:\/\/flowjo.typepad.com\/.a\/6a00d8341c0ebb53ef0154354e8fbb970c-pi\"><img loading=\"lazy\" decoding=\"async\" class=\"asset  asset-image at-xid-6a00d8341c0ebb53ef0154354e8fbb970c image-full\" title=\"Picture 2\" src=\"https:\/\/geiselmed2.dartmouth.edu\/dartlab\/wp-content\/uploads\/sites\/26\/2017\/05\/6a00d8341c0ebb53ef0154354e8fbb970c-800wi\" border=\"0\" alt=\"Picture 2\" width=\"624\" height=\"306\" \/><\/a><\/p>\n<p>Isotype controls do not provide gating controls. Every antibody has  specific and nonspecific binding properties. Isotype controls are  different antibodies than antigen specific antibodies and will have  different activity. Isotype controls are good staining controls to  identify potential problems in staining, particularly if a primary and  secondary antibody are used. However, isotypes do not reliably identify  what is negative and what is positive. If users insist on using isotype\u00a0controls, they must also titrate them as well, since nonspecific activity  at super saturating levels will increase total measured binding and skew  the \u201cnegative\u201d population more positive.<\/p>\n<p>*Images courtesy of Mario Roederer<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Flow Cytometry Basics (Givan) DNA Overview (Givan) Compensation (Roederer) Three Rules for Compensation Controls (from TreeStar Daily Dongle 10 Sep 2011) First and foremost, there must be a single stained control for every parameter in the experiment! In addition, there are three rules for \u201cgood\u201d compensation controls: 1) Controls need [\u2026] <\/p>\n<div class=\"clear\"><\/div>\n<p><a class=\"more_link clearfix\" href=\"https:\/\/geiselmed.dartmouth.edu\/dartlab\/services\/flow-cytometry\/\" rel=\"nofollow\">Read More<\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"parent":452,"menu_order":1,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-493","page","type-page","status-publish","hentry","author-2"],"jetpack_shortlink":"https:\/\/wp.me\/P9HkEC-7X","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/geiselmed.dartmouth.edu\/dartlab\/wp-json\/wp\/v2\/pages\/493","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/geiselmed.dartmouth.edu\/dartlab\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/geiselmed.dartmouth.edu\/dartlab\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/geiselmed.dartmouth.edu\/dartlab\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/geiselmed.dartmouth.edu\/dartlab\/wp-json\/wp\/v2\/comments?post=493"}],"version-history":[{"count":0,"href":"https:\/\/geiselmed.dartmouth.edu\/dartlab\/wp-json\/wp\/v2\/pages\/493\/revisions"}],"up":[{"embeddable":true,"href":"https:\/\/geiselmed.dartmouth.edu\/dartlab\/wp-json\/wp\/v2\/pages\/452"}],"wp:attachment":[{"href":"https:\/\/geiselmed.dartmouth.edu\/dartlab\/wp-json\/wp\/v2\/media?parent=493"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}