BioLegend Web Updates
Podcast Episode - Kissing Disease Autoimmunity, Nipah Virus, and Premature Births
In our newest podcast, we talk about autoimmune diseases linked to the Kissing Disease, concerns over the emerging Nipah Virus, and how fetal immunity may be causing babies to be born early.


Epstein-Barr Virus and Autoimmunity (2:20-12:00)
Nipah Virus Outbreaks (12:01-20:35)
Bacteria Coats itself with IgA for Protection (23:23-32:23)
Out of Whack Fetal Immune Systems Prompt Preterm Labor (35:45-43:33)

Keywords: autoimmunity, kissing disease, mononucleosis, Nipah Virus, herpes, Epstein-barr virus, cancer, bats, reservoir, Bacteroides fragilis, IgA, gut, mucosa, bacteria, pregnancy, premature birth, fetal immunity, preterm

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Blog - Rule the Magnet! Tips on improving your magnetic cell separation results

Obtain good purity and yield from your magnetic separation experiments.
Become Magneto (of the bench). Marvel Enterprises.

Our MojoSort™ magnetic cell separation reagents, as well as others in the market, offer convenient, efficient, and cost-effective ways to obtain purified cells of interest. But, as with any other procedure, you may run into some difficulty with your separation experiment. Perhaps your cells are not as pure as you'd want/expect, and you don't know how to get rid of the cells you don't want? Or, maybe the resulting number of cells you get out in the end (i.e. yield) is not very high, as if you're somehow losing a lot of cells in the process? In this blog, we'll discuss some of the common issues that can yield suboptimal results from a magnetic separation experiment, how to overcome them, and how you can bring some mojo back to your experiment!

Types of MojoSort™ Products

First, let's clarify some terminology that will be referred to in this entry, as well as in the nomenclature of some our MojoSort™ products. You can also refer to our previous blog to review some of the terminology being used below:

Positive vs. Negative Selection:

After positive selection, the final cells of interest will be bound to the magnet. Our "Selection Kits" include cell type-specific antibodies, along with nanobead-conjugated secondary reagents (e.g. Streptavidin-nanobeads) to purify the cells of interest as advertised. You can find an example of one of our selection kits with the MojoSort™ Human CD14 Selection Kit. In a negative selection (or isolation) experiment, the cells of interest are not bound by the magnet and are ultimately eluted out in the negative fraction. All other unwanted cells are depleted out in the magnetic-bound fraction via the use of antibody-nanobead cocktails. One major advantage of using negative selection is the cells of interest in the end are not bound to magnetic particles. This may be preferable if there are any concerns about the interference of magnetic particles in a sensitive downstream bioassay or application. The difficulty in designing this on your own is that you must be able to efficiently deplete all other cells in a given sample in order to get good purity, which might be difficult to do comprehensively without trial and error. Our isolation kits are optimized to deplete out all other cells in a given sample except for the cells advertised. For instance, our MojoSort™ Human NK Cell Isolation Kit contains a cocktail of antibodies to deplete out all other cells from healthy PBMC samples except NK cells, as analyzed by CD56+CD3- surface marker phenotype shown on the product webpage.

Direct vs. two-step isolation:

Direct separation refers to the use of magnetic particles that are directly conjugated to the antibodies. Two-step utilizes antigen-specific primary antibodies, followed by Streptavidin-magnetic particles (in the case where antibodies are biotinylated), or other magnetically-bound secondary reagents, such as our anti-PE and anti-APC nanobeads. MojoSort™ products that are labeled as "nanobeads" contain antibodies that are directly conjugated to magnetic particles, and our "selection kits" or "isolation kits" contains reagents for a two-step selection method.
Suppose you perform a magnetic isolation experiment for B cells on murine splenocytes, stain and analyze using PE anti-mouse CD19, and you obtain the following result (under "reality"):
So, how can you break down your result and make improvements to your experiment?

Identify the perpetrator. 

With low purity, the source of "contamination" is likely originating from one cell population. Try and identify this population. When assessing purity via flow, analyze the plots using multiple markers and parameters instead of just looking at a marker associated with the cells of interest in a histogram. Knowledge of the starting cell populations/contents is useful here, as is having a good set of controls to identify them. If you are using a "home-made" magnetic depletion cocktail instead of a pre-optimized kit from manufacturers, honing into particular cell populations allow you to pinpoint where you need to optimize your experiment, such as adding markers specifically for those cells to better deplete, and titrating associated reagents.

A couple of additional tips here:
  • Back-gate: when analyzing the sample via flow cytometry for the marker pertaining to your cells of interest, gate the contaminating cells for analysis. For instance, if you're isolating human CD3+ T cells and you're finding a lot of CD3- cells from your PBMC preparation, gate the CD3- cells to see if you can find any parameters, such as FSC/SSC scatter profiles, to possibly identify the contaminating cells. By looking at the scatter profile, you may be able to distinguish the contaminating population is actually from monocytes or dead cells. 
  • Anticipate failure: This sounds pessimistic, but if you're trying a separation protocol for the first time, it can help you save some steps, samples, and time getting a working protocol for you in the long run. Based on your knowledge of the starting material, you can pre-plan a multicolor panel of general phenotyping markers to co-stain, not just to label the final cells of interest but also the anticipated contaminants. Ask yourself - If my purified sample was to be contaminated by another cell type, who would it likely be, based on the sample? Do you need tips on how to identify some of these cells, and what the expected cell frequencies are in a starting material? You can take a look at our essential phenotyping markers page to get a quick idea for a panel, and a previous blog entry on expected cell populations. Of course, you should also carry an unsorted, starting material cell population as well for comparison after separation.

Co-staining a sample and analyzing on a two-dimensional bivariate plot instead of a histogram can reveal a lot of information. In the B Cell isolation example above, co-staining with APC anti-mouse CD3 suggests that the remaining CD19- population (red box) is primarily T cells (~32%). Perhaps this is where you can optimize your experiment, to try and remove more T cells from your sample:

The cells are too concentrated in the separation experiment

A common issue leading to poor magnetic cell separation is a staining reaction with a sample that is too highly concentrated with cells. I know that sometimes it's cumbersome to count out the cells you have in your sample, and just taking 100 µL straight out of your original sample suspension allows you to cut so much time and hassle! However, this step is crucial - if your sample is too concentrated, it can affect antibody (and any other secondary reagent) binding its target antigen sufficiently and/or increase non-specific binding, causing more cell aggregation, amongst other unwanted consequences. Ultimately, this can affect both purity and yield. If using a column, applying too many cells per run can also clog it. Make sure you are following manufacturers instructions on how many cells can be subjected to each cell separation assay. Also verify the column manufacturer's recommendation so samples are diluted to a sufficient volume before they're added to the columns, and pre-equilibrate columns with proper buffers as necessary.

For most MojoSort™ reagents, a standard test consists of 1 x 10^7 cells in a 100 µL reaction volume. You can always scale up as needed, but try to always keep the same cell/volume ratio. When starting with less than 10^7 cells, I'd recommend staying with the 100 µL reaction volume. Manual cell counting can yield variability, so make sure you have a relatively precise number. If you're concerned about precision, try counting a couple of replicates.
Don't get too physical

Take your time, and be gentle. If using our MojoSort™ magnetic separator (or equivalent), if you rotate the tube while inside the magnet during incubation, it can cause the magnetically-bound cells to come loose from the magnet. So, during this incubation step, leave the tube alone. Don't aggressively shake the tube to get your unbound samples out- use a smooth, decanting motion to take out your negative fraction. If using a column, let gravity do the work and allow time for samples to naturally drip through. Don't plunge the bound samples out until all of the negative fraction has dripped through.

Pour out cells in one smooth motion. Just like Dr. Evil. Naturally, he has great MojoSort™ technique.
New Line Cinema.
Low yield? Labeling too much... or too little?

The likely cause for your yield being lower than expected is that your cells are ending up in the wrong fraction. In a positive selection experiment, the cells are likely being washed away. For negative isolation, you're depleting out too many of your cells of interest. You can confirm this by taking both positive/negative fractions for flow analysis, but in either case, the first thing you can try is to optimize reagent use:
  • Positive selection - to make sure you're not losing your cells of interest in the washed out fractions, try increasing the amount of antibody/secondary reagents for selection. Too many cells in the reaction (discussed above) can also cause this.
  • Isolation - titrate down antibody/secondary reagents. The likelihood is that the excess reagents are depleting out too many cells non-specifically.

For MojoSort™ reagents, contact our tech support team ( to get sample yields obtained from our in-house testing. Also note that increasing yield can potentially concomitantly compromise purity. The key here is to find a "sweet-spot" that has a good balance of both.

Follow recommended protocol! 

This one's relatively straightforward - if you are using one of our pre-designed kits, we’ve developed optimized protocols, which are available on their respective product webpages or you can view our Protocol tables on our MojorSort™ page. It's best to start with what's been validated to work in BioLegend labs first, before proceeding to optimize and modify steps and reagents as desired in your future experiments. To see how our MojoSort™ reagents and magnets are used, check out our awesome protocol video below:

The points mentioned here are by no means comprehensive as there are numerous other factors and considerations not covered here that can affect your magnetic separation outcome. However, if you encounter low purity and/or yield, hopefully some of the tips and suggestions above may help as your first steps to success. You can check out the MojoSort™ webpage for an overview on our reagents, FAQs, and protocols by clicking on the various available tabs. For any additional suggestions on how to design and improve your magnetic separation experiments, contact us at!
Contributed by Kenta Yamamoto, PhD.

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Blog - A Guide to Tandem Dyes and Degradation
In this blog, we'll describe the common characteristics of tandem dyes, discuss their advantages in multicolor flow cytometry, and address a common myth about tandem degradation.

What is a tandem dye?

A tandem dye is composed of two covalently attached fluorescent molecules. One of these molecules is either a protein-based (i.e., PE, APC) or synthetic dye (i.e., BV421™) characterized by a large extinction coefficient (capacity to absorb energy) that serves as a donor, while the second molecule is a small synthetic dye that serves as an acceptor (i.e., Cy5, Cy7).

Why do we use tandem dyes?

As you may already know, the number of fluorophores one is able to use at the same time is limited by the number of lasers and detectors on the cytometer (Table 1). The most advanced cytometer instruments on the current market have 5 lasers including ultraviolet (355 nm), violet (405 nm), blue (488 nm), green (532 nm) or yellow-green (561 nm), and red (633 nm) and the potential to integrate 8 parameters off of each laser. However, there are not currently enough spectrally distinct fluorophores yet to fill out this configuration. Without tandem fluorophores, each laser would only be suitable to discretely excite a small number of fluorophores, thus severely limiting the total number of parameters able to be detected.

Table 1. Example of multicolor flow panel diversification based on available lasers, detectors, and instrument.

Further expansion of the number of detectors off of each laser has allowed us to increase flow panels up to 21 colors /23 parameters (Table 1). It is possible to achieve because the tandem dyes use the same excitation characteristics as the donor dye but possess emission properties of the acceptor. Therefore, though donor dyes and their tandems are excited by the same laser, they can be used in the same panel by utilizing different detectors to readout their emission. As an example, Figure 1 demonstrates the excitation and emission spectrum of BV421™ and its tandems.

The further expansion of multicolor panels can be achieved by using a spectral cytometer, such as Cytek's Aurora™ Spectral Cytometer. This instrument has 48 fluorescent channels with three lasers. Theoretically, it can detect 42 fluorophores as long as those fluorophores have distinct emission profiles. A spectral detection system does not utilize traditional methods of compensation calculation and allows a simultaneous use of fluorophores with significant overlapping emission spectrum (i.e. BV750™ and BV785™) while having minimal compensation concerns.

Figure 1. Excitation and emission spectra of BV421™ and its tandems, BV570™, BV605™, BV650™, BV711™, BV750™, BV785™.

How do tandem dyes work?

The donor fluorophore absorbs light energy of the specific wavelength. Upon excitation, energy is transferred from the donor to the acceptor through a phenomenon called Förster resonance energy transfer (FRET), also known as fluorescence resonance energy transfer. The acceptor emits the transferred energy as fluorescent light. When FRET efficiency is high, a strong signal will be observed in the acceptor channel and a weaker signal in the donor channel. Please note, the FRET efficiency is never 100%, which means that some spillover or bleeding in the donor channel is expected.

I see a fluorescence signal in the donor channel. Is my tandem degrading?

NO. This is a common myth. The donor and acceptor dyes are covalently conjugated and don't typically fall apart. As mentioned earlier some spillover or bleeding into the donor channel is expected since FRET efficiency is not 100%. To accurately compensate spillover, it is important to use the same antibody used in the multicolor sample as the single color compensation control and to treat them identically as the multicolor sample especially in light and fixative exposure. However, if you observe a strong signal in the donor channel and a weak signal in the acceptor channel, this is an indication of low FRET efficiency that is caused by one of the following factors:
  • Photobleaching. Always protect tandem dyes from light or other sources of oxidative stress as they are highly susceptible to photobleaching resulting from oxidation.

  • Exposure to freezing temperature. Do not freeze tandem dye antibody conjugates as it might result in denaturation of the protein-based donor fluorophore.

  • Fixation and Permeabilization. Don't leave your cells in fixative for long periods of time as it will result in increase of the autofluorescence and cause greater harm to the tandems. It is strongly advised to wash the cells after fixation and replace the buffer with the FluoroFix™ Buffer. You can also perform surface staining after fixation. However, be sure to check our Fixation page for compatibility of our antibody clones with fixation.
As an example of how different fixatives may affect the fluorescence signal of tandem dyes, Figure 2 demonstrates the fluorescence signal from cells stained with a PerCP/Cy5.5-conjugated antibody and exposed to 1%PFA or True-Phos™ Perm buffer. Exposure to the True-Phos™ Perm buffer, which is methanol-based, leads to the denaturation of PerCP since this is a protein based dye. It results in the loss of signal for PerCP but not for its acceptor, Cy5.5 whose fluorescence can be detected in the Alexa Fluor® 700 channel.

Figure 2. A) Fluorescence intensity of PerCP/Cy5.5 anti-CD14 antibody staining upon exposure to 1% PFA or True-Phos™ Perm buffer solution. B) Dot plots demonstrating appearance of signal in Alexa Fluor® 700 channel upon exposure of PerCP/Cy5.5 to True-Phos™ Perm buffer.

Hopefully, now you have a better understanding of tandem dyes and are familiar with guidelines on their use and handling when planning and doing your experiments. As always, if you have any questions while planning your experiments, feel free to reach out to our technical services team at You can learn more about these fluorophores with our tandem dyes webpage.
Contributed by Ekaterina Zvezdova, PhD.
View a full listing of Trademarks and Patents.

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Podcast Episode - 8-Bit Science: Level One
In our new podcast, we look at the science behind popular video game franchises like Resident Evil, Final Fantasy VII, and The Last of Us!


Final Fantasy VII (Podcast from 2:35-14:20)
Resident Evil (Podcast from 14:20-26:50)
The Last of Us (Podcast from 31:50 to 44:00; Spoilers from 41:20 to 42:18)
Viruses in the Resident Evil Series
The Last of Us Part II
Stages of Infection in the Last of Us
Cordyceps: Attack of the Killer Fungi-Planet Earth with David Attenborough

Intro music “The Pirate and the Dancer” by artist Rolemusic at the Free Music Archive.

Keywords: video games, science, podcast, resident evil, final fantasy VII, Jenova, CRISPR, gene splicing, Sephiroth, virus, T-virus, mitochondria, retrovirus, reverse transcriptase, Ebola, Atari, playstation, The Last of Us, Cordyceps, fungus

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Video - Simultaneous Proteomics and Transcriptomics - the future of single cell analysis
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Blog - Expected Cell Frequencies
While designing an experiment there are a number of important factors to take into account. One of these factors may be the expected frequency of cells in a given sample. This information can help dictate your fluorophore choices when building a multicolor panel, help you determine a sufficient number of events to collect in your experiment, and potentially predict how long you'll need to run the instrument. It could even help you better determine the expected yield of a magnetic cell separation experiment.

Sometimes (though it can seem rare) your results can meet or even exceed your expectations.
Comic from PhD Comics.

Of course, the exact frequency of any cell type that you see in your experiment will vary depending on a number of factors including the antibody clone/fluorophore chosen, gating strategy, sample processing or treatment, and donor/strain variability (just to name a few). The charts below describe cell compositions of common sample types in both human and mouse and can be used as a helpful reference to better plan your experiments. Given the caveats mentioned above, they shouldn't cause alarm if your results don't align perfectly as this should only be used as a guide or first step in planning your experiments.
Two common sample types when studying human immune cell subsets are peripheral blood mononuclear cells (PBMCs) and lysed whole blood. Typically, PBMCs are isolated using density gradient separation methods (such as our Lymphopure™ reagent) in which other cell types, such as erythrocytes and granulocytes, are removed from the sample. In the charts below, the frequency of CD4+ and CD8+ T cells is represented as a percentage of total T cells. We also offer Veri-Cells™ products, which are lyophilized control cells that you can use as a reference point for your samples.
In addition to in-house data, the following publications were used to compile the data.
  • Lepone LM, et al. 2013. J Circ Biomark. 10:5.
  • Maecker H, et al. 2012. Nav Rev Immunol. 12: 191-200.
  • Corkum CP, et al. 2015. BMC Immunol. 16:48.

Lysed Whole Blood:
  • Mijeong IM, et al. 2011. Korean J Lab Med. 31: 148-153.
  • Autissier P, et al. 2010. Cytometry A. 77:410-9
When studying mice, there are a number of tissues or cell compartments that you can analyze. Below, we've presented common cell frequencies in two of these populations - spleen and bone marrow. Given the vast number of mouse models and strains available, these frequencies may vary and these compositions were based on data collected from C57BL/6 mice. Note that the frequencies represented in the spleen chart represent a cell composition of a spleen sample following red cell lysis and the CD4+ and CD8+ percentages are listed as a percentage of total T cells.
In addition to in-house data, the following publications were used to compile the data.
  • The Jackson Laboratory MPD:JaxPheno6. Mouse Phenome Database website.

Bone Marrow:
  • Chen Z, et al. 2017. Sci Rep. 7:40508.
  • Yang M, et al. 2013. Ann of Hem. 92;5:587-594.

These guides may help give you a better idea of the expected cell composition in your sample to better help you plan your experiments, especially if you are working in a new species or sample type. While building your flow panel, you may also want to check out our recent blogs focusing on other sample considerations and using the ideal compensation controls. As always, if you have any questions while planning your experiments, feel free to reach out to our technical services team at

Contributed by Kelsey Swartz, PhD.

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Video - 360 Video - Immunologic Networks
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New Web Page: Growth Factors

Growth factors regulating important signaling pathways cell processes including proliferation.  Learn more about the different growth factor families and BioLegend reagents can be used to study these important signaling molecules. BioLegend develops and manufactures world-class, cutting-edge immunological reagents for biomedical research, offered at an outstanding value.

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Blog - BioLegend at IMMUNOLOGY 2018™
Each year, the American Association of Immunologists gathers for an annual meeting to discuss their latest findings. This year's IMMUNOLOGY 2018™ meeting takes place in Austin, Texas. As a platinum sponsor, we'll be hosting and supporting a number of events, including the Service Appreciation Reception (by invite only), which honors AAI's volunteers, and the IMMUNOLOGY 2018™ Gala. The Gala will be hosted at Stubb's Bar-B-Q and will come complete with live music from a local band, The Nightowls. You can sample some of their soulful music here.
Image from The Nightowls Website.
In addition to these social gatherings, we'll be sponsoring academic awards, like the AAI-BioLegend Herzenberg Award, which pays tribute to Leonard Herzenberg and honors a researcher's developments in the field of B cells. This year's winner is Jason G. Cyster of UCSF. His lab focuses on leukocyte migration, immune surveillance, antibody affinity maturation, and the prevention of autoimmune antibody production. We also sponsor the AAI-Lefrançois-BioLegend Award, in honor of Leo Lefrançois, to shine the spotlight on a rising star in mucosal immunology. This year, the honor goes to Neil Surana of the Boston Children's Hospital. Dr. Surana works on the identification of immuno-modulating bacteria and their influence on immunity overall.
(Left) Jason G. Cyster. Image from UCSF. (Right) Neil Surana. Image from Boston Children's Hospital.
You can also attend our exhibitor workshops, which will have three drawings a piece for $50 Amazon gift cards. We'll examine the role of the Ubiquitin pathway in controlling melanoma by regulating immune checkpoints and BioLegend's TotalSeq™ reagents in single-cell analysis. We also have a number of poster sessions where you'll get to directly interact with our scientists to discuss their work with recombinant proteins, multiplexing, and more.

One of the best parts of conferences? The swag.
Be sure to swing by to visit us at Booth #303, where we'll have plenty of new literature and giveaways, like our upgraded Immunologic Networks Poster, Immunology Handbook, and more. We'll also have a Quiz Game, where high scores can earn you a sweet prize! You'll also get to learn about our newest products, some of which will be unveiled specifically at the conference.
If you're still looking for a little funding for your travel, be sure to check out our Junior Investigator Travel Award, which provides $500 to help offset the cost of attending a scientific conference. We hope to see you soon to show you all the new things we've been working on.

If you're seeking out activities while in Austin, check out this article from CNN for some inspiration. And, you can browse these Austin fun facts while you're planning your itinerary!
Austin Fun Facts:
  • It was originally named Waterloo when chosen as the capital of the Republic of Texas. It was later renamed to Austin to honor Stephen F. Austin.

  • The South by Southwest Festival started here in 1987. It showcases films and music, drawing huge crowds. In 2017, it was estimated 421,900 people attended SXSW.

  • It's the fastest growing city in the United States. It's also America's most populous city without a sports franchise.

  • Austin is known as the Live Music Capital of the World and the Violet Crown City due to the purple hue the hills take on during winter nights. BioLegend approves of the color scheme!

No, not that Steve Austin.
Image from WWE.
Contributed by Ken Lau, PhD.

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Video - BioLegend MojoSort™ Protocol Video
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Video - The Wild Wild Western
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Blog - Tired Eyes: The Nuclear Era and Some Good Ole Ingenuity, The Story of FACS
Fluorescently activated cell sorting (FACS) is used around the world to subdivide heterogeneous populations of live cells often derived from blood. This flexible application, often utilized by immunologists, would not have been possible if it had not been for Leonard Herzenberg's willingness to be a life-long student.

Leonard was born November 5, 1931 in Flatbush Brooklyn, where he attended Brooklyn College and majored in Biology. He later earned his PhD at Cal Tech in Biochemistry and Immunology. Herzenberg then completed his American Cancer Society postdoc in Paris. He then joined Stanford's newly opened medical school in the department of genetics.

Leonard Herzenberg, Stanford University School of Medicine.
During a long session of counting fluorescently-labeled cells, Leonard longed for an instrument that could expedite this highly mundane task. It turned out he was asking that question at the perfect time, as several other scientists were beginning to develop machines that could sort cells and particulates by volume. The need for this type of device had grown out of the atomic era, as many scientists were investigating the effects of nuclear radiation on the lung cells of rats.
SpongeBob SquarePants, Nickelodeon Animation Studios.
Per usual, curiosity drove Herzenberg to Los Alamos. While there, he convinced the team that had developed the "volume sorters" to lend him blueprints. Herzenberg, a Biochemist by training, understood the need for interdisciplinary collaboration in order to develop this device into a cross-functional cell sorter. With the addition of a laser, a droplet technique borrowed from the ink-jet printer, and electrostatic charging, the team cobbled together the first FACS instrument by 1971.
Diagram of FACS
At this time, the only antibodies available to scientists were polyclonal and were highly variable leading to very inconsistent results. Herzenberg understood that the value of FACS hinged on a labeling mechanism that was both consistent and repeatable. Polyclonal antibodies lacked the specificity and reproducibility Leonard's new tool demanded. Luckily at that time, Herzenberg was collaborating with César Milstein and Georges J. F. Köhler at Cambridge, who were developing a mechanism to fuse a B cell to a myeloma cell which came to be known as a hybridoma. This "marriage" allowed for the continued production of an antibody that would only recognize a singular epitope.
Diagram of Hybridoma Development
The creation of these monoclonal antibodies acted as the backbone for FACS and provided the necessary specificity to fuel FACS into the clinical research field. As such, Herzenberg was able to identify and characterize the T and B lymphocytes in the mammalian immune system through FACS-based detection. Leonard understood the importance of this technology and readily shared both his expertise and cell lines and tools with the scientific community.

Leonard's Tesla-like approach, which valued knowledge and discovery over profit, spurred researchers and biotech companies alike.

The Simpsons, 20th Century Fox Television
Unfortunately in October of 2013, Herzenberg passed away. He left behind a legacy of FACS and his valuable work on CD4+ T cells, which is still in clinical use to this day. In light of his major scientific contributions, BioLegend honors Leonard through an annual American Association of Immunologists award.

  1. PNAS Biography
  2. Stanford's Faculty Biography
  3. Leonard Herzenberg's Wikipedia page
  4. Wikipedia FACS Diagram
  5. Flow Chart Hybridoma
Contributed by Sean Cosgriff.

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Podcast Episode - Understanding Malaria with Jason Lehmann
In our new podcast, we welcome guest Jason Lehmann to discuss his work with malaria, his new LEGENDplex™ promotion at BioLegend, and how class timing can influence your grades.


The Undersea LEGENDplex™ Adventure
LEGENDplex™ Plush Plexy Promotion
New human antibody prevents malaria in mice
Class time affects grades
School starts too early according to CDC

Keywords: malaria, Jason Lehmann, mosquito, parasite, infectious disease, plasmodium falciparum, vivax, Haiti, cytokines, multiplexing, LEGENDplex, CIS43, social jetlag, Beatles, octopus

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New Web Page: Knockout and Knockdown Validation

Learn more about how BioLegend is addressing reproducibility in research, by using CRISPR/CAS9-mediated knockout/knockdown and siRNA-mediated knockdown models to validate antibody specificity.

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Video - LEGENDplex™ Undersea Adventure
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Blog - Brain Organoids: Heads in a Jar
Early attempts to culture brain organoids yielded mixed results.
Futurama, 20th Century Fox Television

Lately, the scientific community has expressed a growing interest in a new take on an old discipline. Organoids, or the complex result of three-dimensional cell culture, were recently named the 2017 Nature Method of the year. While we have covered organoids before, we decided it was high time to revisit the topic in light of recent developments in the field.

For years, scientists have made incredible discoveries by observing how cells behave in two dimensions. Traditional cell culture techniques often rely on the propensity of cell lines or tissue samples to adhere and propagate on flat surfaces like glass or plastic. The ability to isolate tissue and grow it under carefully controlled conditions in the lab has led to game-changing advances, like the development and maintenance of genetically-stable, immortalized cell lines that serve as a benchmark for world-wide studies.
But as 3D printers and James Cameron proved in his 2009 sci-fi romp Avatar, sometimes 2D just isn't enough. Enter organoids: three-dimensional arrangements of multiple cell-types descended from a stem population, that resemble a particular model organ in composition and function. This basic definition hints at three important features of organoids:

  1. Much like their namesakes, organoids contain a similar mixture of cell types to those found in natural organs. Kidney organoids have been generated that contain as many as 10 distinct types of cells.

  2. Organoids can recapitulate organ function. Single Lgr5+ liver progenitor cells have been coaxed to form functional, transplantable organoids in vitro, with the potential to rescue liver disease related mortality in mouse models1.

  3. Organ-like cell grouping and spatial organization. Organoids self-organize (Get it?) by joining with cells expressing complimentary adhesion molecules (i.e. N-cadherin), in a process termed "cell sorting out." Cell sorting out is then followed by lineage commitment and arrangement into cohesive, 3D structures resembling natural tissue. The mechanisms behind this fascinating phenomenon remain poorly understood.

To date, organoid models have been developed for the liver, kidney, retina, breast, GI tract, and others. In this blog post, we'll explore recent advances in organoid models for what is perhaps the most complicated organ in the body: the brain.

Brain organoids are emerging as a much needed tool for studying brain development and neurodegenerative diseases. Diseases like Alzheimer's disease (AD) and Parkinson’s disease (PD) are difficult to model in mice due to the complex interaction of genetic and non-genetic risk factors that produce pathology. Practical and ethical considerations (anyone want to loan me a piece of their brain?) further limit the availability of healthy and diseased tissue for study. Organoids generated from patient-derived pluripotent stem cells (hPSC) have the potential to be important tools for understanding these disorders.

Earlier 3D culture methodologies using isolated neuroepithelium produced 2D neural tube-like arrangements of progenitors termed neural rosettes2. This method provided an important basis for ongoing work, but ultimately lacked the cytoarchitecture and cellular diversity of true organoids. Brain organoids more closely resembling human brain tissue were developed with a free-floating culture technique, allowing for the spatial polarization of cultured hPSC along rostral-caudal and dorsal-ventral axes using FGF, WNT, and BMP signal gradients3. Modifications to this technique by Lancaster et al., instead using hPSCs suspended in Matrigel® droplets cultured in a spinning bioreactor, produced "mini brains" complete with dorsal cortex, ventral forebrain, retina, hippocampus, and choroid plexus regions4. More recent publications detail cerebral organoids pieced together from independently grown regions, in order to increase reproducibility of cultured organoids5.

So, what is all this good for? Here are some recent examples of exciting applications for brain organoids:
  1. Zika virus research: Infection during pregnancy with the Zika virus is associated with severe birth defects in newborns (microcephaly), but little is known about the mechanisms driving these outcomes. Brain organoids are currently being used as a model system for the effects of viral infection on the developing brain, displaying many of the developmental abnormalities seen clinically. Dang et al. recently found that TLR3 signaling in Zika-infected cerebral organoids was linked to tissue shrinkage and apoptosis6.

  2. Models for neurodegenerative diseases: A modification of the neural rosette method, developed by Kim et al., utilized neural precursors suspended in Matrigel® to model the aggregation of β-amyloid and accumulation of hyperphosphorylated tau seen in AD7. More recently, Raja et al. took it a step further, using β- and γ-secretase inhibitor therapy on an organoid model of early-onset familial AD8.

  3. Autism research: Organoids generated from iPSC isolated from ASD patients serve as an invaluable model for early development of this condition. Studies have implicated FOXG1 and its downstream targets in the accelerated neural progenitor growth and accumulation of GABAergic inhibitory neurons observed in patient-derived organoids9.
While brain organoids continue to advance, they are still a long way off from faithfully replicating the dizzying complexity of the human brain. The lack of vascularization currently hinders organoid development in vitro, and the lack of immune cell populations limits their utility in fields like immuno-oncology. Despite these drawbacks, organoids represent a valuable research tool with exciting future potential. If you work with organoids and would like to know how BioLegend can help, email us at

  1. Huch M, et al. 2013. Nature. 494(7436): 247-250
  2. Elkabetz Y, et al. 2008. Genes Dev. 22(2): 152-165
  3. Eiraku M, et al. 2008. Cell Stem Cell. 3(5): 519-32
  4. Lancaster MA, et al. 2013. Nature. 501(7467): 373-379
  5. Bagley JA, et al. 2017. Nat. Methods. 14: 743-751
  6. Dang J, et al. 2016. Cell Stem Cell. 19(2): 258-265
  7. Kim YH, et al. 2015. Nat. Protoc. 10(7): 985-1006
  8. Raja WK, et al. 2016. PLoS One. 11(9): e0161969
  9. Mariani J, et al. 2015. Cell. 162(2): 375-390
Contributed by Christopher Dougher, PhD.

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