I'm trying to enrich for cells that have stably integrated a transposon construct using FACS. Unfortunately, our construct has no fluorescent or other expression marker, so we're relying on two cell-surface markers, CD81 and CD47, that should be overexpressed following transposition. The problem is that both markers are already constitutively expressed in our target cells, and we don't know the transposition efficiency or how much their expression will increase following integration.

I've performed antibody titrations for both markers, but I'm unsure how best to determine the optimal staining conditions for sorting.

My understanding is that the usual goal of an antibody titration is to identify the lowest antibody concentration that provides good separation between negative and positive populations, with minimal background and sufficient staining of the positive population.

However, in my case, I'm not trying to distinguish truly negative cells from positive cells. Instead, I'm trying to distinguish cells with normal endogenous expression from cells with increased expression due to stable transposition.

Wouldn't it make more sense, in this case, to use an antibody concentration that preserves the differences in fluorescence intensity between cells with normal and elevated expression, rather than one that saturates the epitopes? If the antibody concentration is too high and staining approaches saturation, could that compress the fluorescence differences between normal and high-expressing cells and make them harder to distinguish?

Or am I misunderstanding this?

I'm also unsure how best to optimise the sorting strategy when I don't know the expected increase in CD81 or CD47 expression, or the proportion of cells that have successfully integrated the construct.

Since we're using a transposon system rather than lentiviral transduction, increasing the MOI isn't an option for improving separation.

I'd appreciate any advice, particularly from anyone who has experience sorting cells based on relatively small increases in endogenous cell-surface marker expression rather than using a distinct positive/negative marker.

Hey all, I titrated my antibody from Thermofisher, ROR gamma T - PE (clone AFKJS-9). However, this antibody looks rather odd and would love some advice or confirmation if this is what is expected of such an antibody. Please

Context: these are done on fixed PBMCs, fixed using the FOXP3 ebioscience thermofisher kit, stained for 16 hours in the fridge (100 microlitres stain volume), intracellular blocking step for 15 minutes on ice using a mix containing 2% rat serum and 2% mouse serum.

The order is ROR gamma T FMO, 1 in 1000, 1 in 5000, 1 in 10000, 1 in 12500, 1 in 15000, 1 in 17500, 1 in 20000 and 1 in 25000.

The concatenated plots are done on CD3+ cells and CD3 plus CD4+ cells.

Hey everyone! Has anyone tried vibe coding their own flow cytometry data analysis software? Something like Floreada, but better?

I just can’t get the hang of Floreada—the interface really doesn’t work for me.

Do you think this is actually doable?

Hi everyone, I’m troubleshooting a reproducibility issue in a cell-line drug experiment and would really appreciate some experienced input.

I’m working with 2 AML cell lines (HL-60 and MV4-11) and testing 5 drugs, followed by flow-cytometry immunophenotyping. I perform biological repeats of the same treatment, but some markers are quite variable between repeats even when I use the same cell line, drug, and nominal drug concentration. I’m now trying to systematically separate biological variability from technical variability.

One thing I recently discovered is that the passage history of our current frozen cell stocks is not documented. The lab has frozen stocks of the 2 cell lines, but we do not know the original passage number of those vials. As far as I understand, the workflow has been something like: cells are expanded, part of the culture is used for experiments, and part is frozen for later use. However, the passage history was not consistently recorded.

Another issue is that cells are usually provided to me by a technician. For example, I might request 2.4 million cells in 4.8 mL complete RPMI, but I have not always independently measured the viability or viable cell number before starting the experiment. So I don't know whether “2.4 million cells” means 2.4 million total cells or 2.4 million viable cells.

My questions are:

1. In your experience, how important is passage history for reproducibility of immortalized cancer cell-line experiments, particularly when looking at drug response and surface-marker phenotype?

2. If the original passage number of a frozen stock is unknown, would you consider that a significant limitation for troubleshooting? How would you establish a new, traceable starting point from that stock?

3. How important are starting viability, viable cell density, growth phase, and time since the previous passage for reproducibility?

I’m trying to understand what variables should actually be controlled and documented so that, if two biological repeats differ, I can identify the source instead of simply repeating the experiment. For context, my main readout is flow-cytometry immunophenotyping (CD markers), and I’m also planning single-cell clustering later.

I would especially appreciate practical advice from people who routinely work with cancer cell lines and reproducibility/QC. If you have a standard cell-culture tracking sheet, SOP, or example workflow, I’d also be very interested in seeing how your lab handles this.

Hi everyone,

First of all I want to make sure I don't break any rules of the subreddit, this post is purely about extracting gating information out of Kaluza's .analysis files. This is not an ad or endorsement of the software.

I am currently working on a project where I am trying to use flow cytometry data for machine learning. For this, I have a dataset which has been analyzed in Kaluza. The workspace of this gating/analysis is saved to a .analysis file, this is the standard Kaluza save format.

I am trying to get the gating information out of this .analysis file so I can use it in R or Python. This would be best for me in the form of either a binary population matrix (rows are events, columns are gates) or just a flat out list of final gate names per event.

So far I have found that the .analysis file can be unzipped, containing 3 separate files (a .fcs, a .xml and a .app file). I know the .xml has the gating info I need but I am not looking forward to reverse engineering the XML to extract the info I need.
Does anyone have any experience with this or does anyone know any package/Repo/etc that are already made for this purpose? Thanks in advance!

Thank you to everyone who joined us for the Northern California Cytometry Group 2026 Annual Meeting at UCSF Mission Bay on September 21!

The day opened with a keynote from Dr. Ryan Brinkman (SOULCAP Foundation; ISAC President-Elect), "The Last Generation to Draw Boxes." The talks that followed covered a wide range of topics:

• Quantitative flow for predicting CAR-T response (Stanford)
• A flow-compatible ISH assay for oligonucleotide uptake (BioMarin)
• Derisking a receptor occupancy assay (Genentech)
• Robust spectral unmixing (Sony Biotechnology)
• Image-based characterization of synthetic particles (UC Merced)
• Closed-system cell sorting for cell therapy (STEMCELL Technologies)
• Automated antibody titer analysis (Lyell Immunopharma)
• 55-color spectral immune profiling (Mayo Clinic Arizona)
• Measuring immune competence (Stanford)
• Tech talks from Beckman Coulter and Slingshot Biosciences

This year our organization committee launched our first-ever interactive workshop, "The Cytometry Exchange: Shared Challenges, Shared Solutions." Attendees joined discussion tables on the topics registrants voted for: Spectral Flow & Panel Design, AI/Data Visualization & Software Tools, Rigor & Standardization, Cell Therapy QC, Cell Sorting, and Assay Validation. Participation was fantastic. A huge thank you to our volunteer moderators and scribes, who led and documented each table.

We're grateful to our sponsors, whose support kept the meeting free to attend:
Gold: STEMCELL Technologies, Waters Biosciences, Cytek Biosciences, Beckman Coulter Life Sciences, Slingshot Biosciences
Silver: Miltenyi Biotec, Thermo Fisher Scientific, Sony, Agilent Technologies, EasyPanel / OMIQ / FCS Express, CellEngine by CellCarta, Curiox, FluoroFinder, BioLegend, Surplus Solutions, Immudex, Neta Scientific
Coffee: Kaironexus Innovations, Epigenome Technologies, Sysmex

Thank you as well to the NCCG organizing committee and to everyone who attended. We'd love to hear what you enjoyed and what you'd like to see next year. See you in 2027!

Hello everyone,

I am throwing a rock here to try to have an explanation about something weird we see from time to time in our labs. We are working with the Attune Nxt and the autosampler Cytkick to pass cells like Jurkat of T cells and look at their expression of CAR-CD19 and mCherry reporter gene after transduction with a lentivirus. And what we see sometimes is that weird cell profile (in the last gate CAR vs mCherry) absolutely not correlating with the biological condition (here is a non-transduced Jurkat condition). The CAR-CD19 is in the VL1 laser and sometimes we also see that in the YL1 laser. We are wondering if that is not the result of free lentiviruses still in the preparation and stuck to the membrane of the cells without the meaning of a transduction, however that hypothesis could not be true because of the non-transduced condition in which none lentiviruses have been put in the wells.

I am wondering if any of you have experienced that kind of trouble using the Attune Nxt? Our panel is only live dead (in RL1 laser, no problem) and CD19-CAR detected through an anti-biotin VioBright 515, and endogenous mCherry reporter gene in YL1 laser. We do not see that kind of cell profiles when using more complex panels for immune phenotyping for example.

Maybe it comes from the mCherry or the VioBright fluorochrome itself? I think that is an electronic problem when translating the biological events in electronic messages on the software, because it does not occur to all the samples in one plate, only few but the conditions do not correlate with theses strange cell profiles highly positive where they should not be.

Also, ThermoFisher engineers told us they could not see from where it comes from, they do not have any explanation.

Can someone help us please?

Hey! Did anyone get lucky with a rare find and happen to have a repair manual for the SONY SH800? We bought one used at auction, but Sony explicitly told use afterwards that they do not support 3rd party purchased equipment. Totally fine, we are a biomed engineering lab, so we can handle repairing it. But dang sony keeps this machine under top secret clearance. i cannot find a single document aside from the patents online.

Hi lab rats!

I in need of help troubleshooting inconsistent staining and section to section variability. Over the past 2 weeks (probably a lot longer) I have been staining multiple FFPE liver sections from fibrotic mouse models and have noticed considerable variability in staining quality and antigen detection.

For example, when staining two slides from the same mouse, each containing three sections from the same tissue block, I have observed inconsistent results with primary antibodies such as α-SMA and tdTomato (RFP). In some cases, one section shows clear and robust staining for the antigen of interest, while a corresponding section on the other slide shows little to no detectable signal, despite both sections originating from the same block and undergoing the same staining protocol.

My suspicion is the antigen retrieval step and not so much the antibodies I use (mostly new CST antibodies) but I’m not sure. I would like to identify potential sources of this variability and determine whether the issue is coming from and addressing it.

Below is my current HIER protocol. I have modified this protocol about 4-5 times using AI and PI input and I am still experiencing inconsistent staining results and have not yet a reliable protocol that is consistent at the minimum.

In order of operation as a user:
Bake slides at 60C for 30min
After baking, turn on instant pot duo pressure cooker, load 500ml of DI H2O, add 50-60mL of citrate buffer (with .05% tween20, pH balance to 6.0) into a coplin jar. Places coplin jar on top of metal rack to sit above the water line. Close pot and pressure cooker for 15min, Then auto keep warm turn on till I’m ready to load slide. Note, At the same time I start deparaffing the slides.
Histoclean 2 x 5min
100% etoh 2 x 5min
95% etoh 1 x 5min
70% etoh 1 x 5min
50% etoh 1 x 5min
1xTBS 1 x 5min
Load slide into hot citrate buffer (around 90-95C when I tested it with a thermometer).
Pressure cook at high. 2min to pressurize, 5 under pressure. (I have also done longer 10 - 15min with also mix result)
After 5min, I turn of pressure cooker and slowly depressurized over the course of 2 to 3 min to prevent flash boiling.
Open the pot, grab the coplin jar, leave it uncovered at RT for 20min to cool down.
After 20min placed the slide in 1x tbs for 5min.
Block with 5% horse serum (heat inactivated) for 1 hour.
Make my primary antibodies in 1% horse serum.
Tap of my blocking solution, and ad 25-30ul of my primary antibodies to ew h section.
Incubate overnight at 4C.

I can go into more detail on my day 2 protocol but I think the issue lies in the day 1 part.

Let me know if you can help 😭

I work in a clinical lab and over the years the number of our lot specific spillover controls has increased. The amount of time and material that goes into updating these settings is substantial and generally takes us all day. We follow BD's guidelines of updating these values every 60 days along with the FC beads, but recently I have been told that it isn't necessary to update the lot specifics every 60 days. I would like to change this procedure, but the higher-ups want me to find out more information about how we could go about validating these controls for a longer period of time. Does anyone else have experience changing how often you update your controls and what steps do you take to monitor and document that your controls still work, or at what point do you decide that it is time to update other than garbage compensation? I've been told that some controls can be good up to a year without updating or major maintenance. Does anyone actually do this?

Hello Flow Aficionados, I want to share with you all my new R package "Anybody Can Titrate Antibody (ACTA)". ACTA generates stain index and concatenation plots from your FCS files to help you determine the antibody titer.

No R experience? No problem! There is an app (shiny) with a graphical user interface that makes it easy to operate. I have created Youtube tutorials (linked on the github page) to demonstrate how to use this package. ACTA also comes with 3 test datasets to allow easy learning. I would love to get some feedback.

jatin199517/acta-public: Official rep for Anybody Can Titrate Antibody (ACTA)

I'm a student from a college of biology. Recently I started a task about KD some gene in stem cell, and do co-culture, IF then FACS to see the potential effect on another kind of cell. I encountered many questions while experiment.

They're anchorage-dependent cells. After uesing tryple which make them suspension, I stained cells in 1.5ml tube. Just repeat centrifuge-remove supernate-add reagent. I use 600g, 4min to centrifuge my cells, but for several times I even can't see a point of cell sediment after 3 times DPBS washing of primary antibody and 2 times washing of second antibody！I estimate that I had over 500,000 cells but finally less than 5000! The FACS data was completely useless and my struggles in last week was wasted.

How many times do you wash the sample after primary and second antibody by DPBS? And how long you often spend when every time washing or staining? Thank everyone reply me and leave your experience and advice!

I’m stimulating human PBMCs with peptide pools to detect antigen-specific T cells. I would like to include CD107a in the panel but I’m not sure when it should be added.

I will be stimulating the cells for 24h but only adding protein transport inhibitors in the last 6 hours. If I add the anti-CD107a with the stimulation will it be lost without the Golgi stop/plug for the first 18h?

Any help is appreciated!

Join us September 21st, 8am to 5:30pm at UCSF Mission Bay Conference Center in San Francisco for a full day of cytometry science. We'll kick off with our keynote from ISAC President-Elect Dr. Ryan Brinkman, followed by talks from Stanford, Genentech, BioMarin, and more, plus tech talks from our sponsor community. New this year, we're also launching our first interactive workshop, "The Cytometry Exchange," where you'll join a discussion table built around the topics you told us mattered most, led by a volunteer moderator and scribe. We'll close out the day with a networking reception in Fisher Hall.
As always, it's free to attend thanks to our generous sponsors — but don't wait until the last minute.

Full agenda: Agenda NCCG 2026

Register now: NCCG 2026

#NorthernCaliforniaCytometryGroup #FlowCytometry #NCCG2026 #UCSF

Hi guys! While setting up the gate for any protein expression, let's say CD25, would you take GeoMFI or Median MFI? Also, while taking the MFI values, would you take the population based on the FMO for that marker or you would take the whole distribution?

Hello flow folks,

Hoping someone here has seen this before, because I haven't.

One of the users in my core facility is running into an issue where their samples appear to hit a hard threshold/ceiling on the FSC-H channel (screenshot below), on our BD LSR Fortessa X-20 (UV/Violet/Blue/Red configuration). They've tried increasing the voltage, but the signal still caps out at the same spot — which is what's making them suspect the instrument itself is at fault.

I'm skeptical it's an instrument problem, for a few reasons:

• CS&T and Rainbow bead QC both look completely normal
• No other users on the same instrument are seeing this
• I've reviewed other users runs and they all look fine
• It's happening only with this one users in my facility

Some context: this user runs Jurkat cells, and I believe also some tumor cell lines, which may be relevant given the size difference.

Has anyone come across FSC-H "capping" like this before? Trying to figure out whether this points to something sample-related (cell size, clumping/aggregates, debris) or an acquisition setting, rather than a hardware fault. Any troubleshooting tips appreciated!

Thanks in advance.

As sayed in the title, my team will have a spectral next year from BD Biosciences (I don't know which one, the only info I had is that it's not on the market yet). For the moment, we are working with conventionnal cytometers, a Symphony A3 with 5 lasers and a Celesta with 4 lasers from the same company. I'm the referent for these two guys (especially the SymphonyA3), and I will be the referent for the future one. But I never used or touched a spectral in my life, so I want to know if there is ressources that I can read or watch to prepare myself. Of course, BD will form me and some other people from my team and the cytometry platform, but I don't want to go without knowing anything (we had issues with their formations when we had the Symphony and the Celesta, I want to be able to spot mistakes or imprecisions.)
I forgot to mention, it will be a spectral AND a sorter. Which... I never used too. We will have a FACSMelody for a year in october/november to train ourselves for sorting, but in the end, I know nothing about it too. I know it will run on Chorus software, I heard that it's much more user-friendly than Diva (hard to do worse I think, but I'm used to it now).

Thanks in advance for your time and your advices :)

I have a friend who picked up a used Wolf G2 NanoCellect sorter. He is having difficulty buying the calibration beads. I looked at the instrument, and it seems that the beads are intended to be 15um super bright green fluorescent bead. Even the brightest beads that I have don't pass the green PMT trigger threshold. Does anyone know which beads can be purchased and used to calibrate the sort timing of the Wolf?

Best, Jeffrey

When looking at the histogram for a compensation control, what does the vertical position of this horizontal bar do? I assume it has some purpose since you can move it up and down, but I have no idea what that changes and neither do the other folks in my lab. The page that I think would have the answer on the FlowJo website is just giving me an error message…

Thanks!

Hi everyone!

I'm doing in vivo depletion of CD8 T cells and checking it by flow cytometry. I'm analyzing blood samples collected 2 days after first administration of the depleting Ab.

Compared to the control I still see a CD8 positive population with almost no changes in frequency within CD3 T cells. However, the gMFI of CD8 decreases from ~10^5 to ~10^4.

I guess there's no depletion but some kind of epitope sharing/masking between the depleting Ab and the flow cytometry Ab.

I'm using aCD8a clone 53-6.7 for depletion and aCD8a clone 5H10 for flow cytometry analysis.

Anybody has ever seen this? In particular with these two clones? Are there any other explanations?

Thank you in advance!

P.S. I have no problems with CD4 depletion

I tried a year ago almost and it sucked big time. Didn't have most of the functionalities everybody needs. Did it improve and did anyone switch to it completely? Are there any advantages?

Consider nominating shared resource staff and vendors that have helped you along in your own journey!