Posts Tagged ‘B and T cell gene rearrangements’

NIH Considers Guidelines for CAR-T therapy: Report from Recombinant DNA Advisory Committee

Reporter: Stephen J. Williams, Ph.D.

UPDATED 5/10/2022

In the mid to late 1970’s a public debate (and related hysteria) had emerged surrounding two emerging advances in recombinant DNA technology;

  1. the development of vectors useful for cloning pieces of DNA (the first vector named pBR322) and
  2. the discovery of bacterial strains useful in propagating such vectors

As discussed by D. S, Fredrickson of NIH’s Dept. of Education and Welfare in his historical review” A HISTORY OF THE RECOMBINANT DNA GUIDELINES IN THE UNITED STATES” this international concern of the biological safety issues of this new molecular biology tool led the National Institute of Health to coordinate a committee (the NIH Recombinant DNA Advisory Committee) to develop guidelines for the ethical use, safe development, and safe handling of such vectors and host bacterium. The first conversations started in 1974 and, by 1978, initial guidelines had been developed. In fact, as Dr. Fredrickson notes, public relief was voiced even by religious organizations (who had the greatest ethical concerns)

On December 16, 1978, a telegram purporting to be from the Vatican was hand delivered to the office of Joseph A. Califano, Jr., Secretary of Health, Education,

and Welfare. “Habemus regimen recombinatum,” it proclaimed, in celebration of the

end of a long struggle to revise the NIH Guidelines for Research Involving

Recombinant DNA Molecules

The overall Committee resulted in guidelines (2013 version) which assured the worldwide community that

  • organisms used in such procedures would have limited pathogenicity in humans
  • vectors would be developed in a manner which would eliminate their ability to replicate in humans and have defined antibiotic sensitivity

So great was the success and acceptance of this committee and guidelines, the NIH felt the Recombinant DNA Advisory Committee should meet regularly to discuss and develop ethical guidelines and clinical regulations concerning DNA-based therapeutics and technologies.

A PowerPoint Slideshow: Introduction to NIH OBA and the History of Recombinant DNA Oversight can be viewed at the following link:


Please see the following link for a video discussion between Dr. Paul Berg, who pioneered DNA recombinant technology, and Dr. James Watson (Commemorating 50 Years of DNA Science):


The Recombinant DNA Advisory Committee has met numerous times to discuss new DNA-based technologies and their biosafety and clinical implication including:

A recent Symposium was held in the summer of 2010 to discuss ethical and safety concerns and discuss potential clinical guidelines for use of an emerging immunotherapy technology, the Chimeric Antigen Receptor T-Cells (CART), which at that time had just been started to be used in clinical trials.

Considerations for the Clinical Application of Chimeric Antigen Receptor T Cells: Observations from a Recombinant DNA Advisory Committee Symposium Held June 15, 2010[1]

Contributors to the Symposium discussing opinions regarding CAR-T protocol design included some of the prominent members in the field including:

Drs. Hildegund C.J. Ertl, John Zaia, Steven A. Rosenberg, Carl H. June, Gianpietro Dotti, Jeffrey Kahn, Laurence J. N. Cooper, Jacqueline Corrigan-Curay, And Scott E. Strome.

The discussions from the Symposium, reported in Cancer Research[1]. were presented in three parts:

  1. Summary of the Evolution of the CAR therapy
  2. Points for Future Consideration including adverse event reporting
  3. Considerations for Design and Implementation of Trials including mitigating toxicities and risks

1. Evolution of Chimeric Antigen Receptors

Early evidence had suggested that adoptive transfer of tumor-infiltrating lymphocytes, after depletion of circulating lymphocytes, could result in a clinical response in some tumor patients however developments showed autologous T-cells (obtained from same patient) could be engineered to express tumor-associated antigens (TAA) and replace the TILS in the clinical setting.

However there were some problems noticed.

  • Problem: HLA restriction of T-cells. Solution: genetically engineer T-cells to redirect T-cell specificity to surface TAAs
  • Problem: 1st generation vectors designed to engineer T-cells to recognize surface epitopes but engineered cells had limited survival in patients.   Solution: development of 2nd generation vectors with co-stimulatory molecules such as CD28, CD19 to improve survival and proliferation in patients

A summary table of limitations of the two types of genetically-modified T-cell therapies were given and given (in modified form) below

                                                                                                Type of Gene-modified T-Cell

Limitations aβ TCR CAR
Affected by loss or decrease of HLA on tumor cells yes no
Affected by altered tumor cell antigen processing? yes no
Need to have defined tumor target antigen? no yes
Vector recombination with endogenous TCR yes no

A brief history of construction of 2nd and 3rd generation CAR-T cells given by cancer.gov:



Differences between  second- and third-generation chimeric antigen receptor T cells. (Adapted by permission from the American Association for Cancer Research: Lee, DW et al. The Future Is Now: Chimeric Antigen Receptors as New Targeted Therapies for Childhood Cancer. Clin Cancer Res; 2012;18(10); 2780–90. doi:10.1158/1078-0432.CCR-11-1920)

Constructing a CAR T Cell (from cancer.gov)

The first efforts to engineer T cells to be used as a cancer treatment began in the early 1990s. Since then, researchers have learned how to produce T cells that express chimeric antigen receptors (CARs) that recognize specific targets on cancer cells.

The T cells are genetically modified to produce these receptors. To do this, researchers use viral vectors that are stripped of their ability to cause illness but that retain the capacity to integrate into cells’ DNA to deliver the genetic material needed to produce the T-cell receptors.

The second- and third-generation CARs typically consist of a piece of monoclonal antibody, called a single-chain variable fragment (scFv), that resides on the outside of the T-cell membrane and is linked to stimulatory molecules (Co-stim 1 and Co-stim 2) inside the T cell. The scFv portion guides the cell to its target antigen. Once the T cell binds to its target antigen, the stimulatory molecules provide the necessary signals for the T cell to become fully active. In this fully active state, the T cells can more effectively proliferate and attack cancer cells.

2. Adverse Event Reporting and Protocol Considerations

The symposium had been organized mainly in response to two reported deaths of patients enrolled in a CART trial, so that clinical investigators could discuss and formulate best practices for the proper conduct and analysis of such trials. One issue raised was lack of pharmacovigilence procedures (adverse event reporting). Although no pharmacovigilence procedures (either intra or inter-institutional) were devised from meeting proceedings, it was stressed that each institution should address this issue as well as better clinical outcome reporting.

Case Report of a Serious Adverse Event Following the Administration of T Cells Transduced With a Chimeric Antigen Receptor Recognizing ERBB2[2] had reported the death of a patient on trial.

In A phase I clinical trial of adoptive transfer of folate receptor-alpha redirected autologous T cells for recurrent ovarian cancer[3] authors: Lana E Kandalaft*, Daniel J Powell and George Coukos from University of Pennsylvania recorded adverse events in pilot studies using a CART modified to recognize the folate receptor, so it appears any adverse event reporting system is at the discretion of the primary investigator.

Other protocol considerations suggested by the symposium attendants included:

  • Plan for translational clinical lab for routine blood analysis
  • Subject screening for pulmonary and cardiac events
  • Determine possibility of insertional mutagenesis
  • Informed consent
  • Analysis of non T and T-cell subsets, e.g. natural killer cells and CD*8 cells

3. Consideration for Design of Trials and Mitigating Toxicities

  • Early Toxic effectsCytokine Release Syndrome– The effectiveness of CART therapy has been manifested by release of high levels of cytokines resulting in fever and inflammatory sequelae. One such cytokine, interleukin 6, has been attributed to this side effect and investigators have successfully used an IL6 receptor antagonist, tocilizumab (Acterma™), to alleviate symptoms of cytokine release syndrome (see review Adoptive T-cell therapy: adverse events and safety switches by Siok-Keen Tey).


Below is a video form Dr. Renier Brentjens, M.D., Ph.D. for Memorial Sloan Kettering concerning the finding he made that the adverse event from cytokine release syndrome may be a function of the tumor cell load, and if they treat the patient with CAR-T right after salvage chemotherapy the adverse events are alleviated..

Please see video below:

http link: https://www.youtube.com/watch?v=4Gg6elUMIVE

  • Early Toxic effects – Over-activation of CAR T-cells; mitigation by dose escalation strategy (as authors in reference [3] proposed). Most trials give billions of genetically modified cells to a patient.
  • Late Toxic Effectslong-term depletion of B-cells . For example CART directing against CD19 or CD20 on B cells may deplete the normal population of CD19 or CD20 B-cells over time; possibly managed by IgG supplementation

Below is a curation of various examples of the need for developing a Pharmacovigilence Framework for Engineered T-Cell Therapies

As shown above the first reported side effects from engineered T-cell or CAR-T therapies stemmed from the first human trial occuring at University of Pennsylvania, the developers of the first CAR-T therapy.  The clinical investigators however anticipated the issue of a potential cytokine storm and had developed ideas in the pre-trial phase of how to ameliorate such toxicity using anti-cytokine antibodies.  However, until the trial was underway they were unsure of which cytokines would be prominent in causing a cytokine storm effect from the CAR-T therapy.  Fortunately, the investigators were able to save patient 1 (described here in other posts) using anti-IL1 and 10 antibodies.  


Over the years, however, multiple trials had to be discontinued as shown below in the following posts:

What does this mean for Immunotherapy? FDA put a temporary hold on Juno’s JCAR015, Three Death of Celebral Edema in CAR-T Clinical Trial and Kite Pharma announced Phase II portion of its CAR-T ZUMA-1 trial

The NIH has put a crimp in the clinical trial work of Steven Rosenberg, Kite Pharma’s star collaborator at the National Cancer Institute. The feds slammed the brakes on the production of experimental drugs at two of its facilities–including cell therapies that Rosenberg works with–after an internal inspection found they weren’t in compliance with safety and quality regulations.

In this instance Kite was being cited for manufacturing issues, apparantly fungal contamination in their cell therapy manufacturing facility.  However shortly after other CAR-T developers were having tragic deaths in their initial phase 1 safety studies.

Juno Halts Cancer Trial Using Gene-Altered Cells After 3 Deaths


Juno halts its immunotherapy trial for cancer after three patient deaths

By DAMIAN GARDE @damiangarde and MEGHANA KESHAVAN @megkesh

JULY 7, 2016

In Juno patient deaths, echoes seen of earlier failed company


JULY 8, 2016


After a deadly clinical trial, will immune therapies for cancer be a bust?

By DAMIAN GARDE @damiangarde

JULY 8, 2016

This led to warnings by FDA and alteration of their trials as well as the use of their CART as a monotherapy

Hours after Juno CAR-T study deaths announced, Kite enrolls CAR-T PhII

Well That Was Quick! FDA Lets Juno Restart Trial With a New Combination Chemotherapuetic

 at Seattle Times

FDA lets Juno restart cancer-treatment trial

Certainly with so many issues there would seem to be more rigorous work to either establish a pharmacovigilence framework or to develop alternative engineered T cells with a safer profile

However here we went again

New paper sheds fresh light on Tmunity’s high-profile CAR-T deaths
Jason Mast
The industry-wide effort to push CAR-T therapies — wildly effective in several blood cancers — into solid tumors took a hit last year when Tmunity, a biotech founded by CAR-T pioneer Carl June and backed by several blue-chip VCs, announced it shut down its lead program for prostate cancer after two patients died.

On a personal note this trial was announced in a Bio International meeting here in Philadelphia a few years ago in 2019

see Live Conference Coverage on this site

eProceedings for BIO 2019 International Convention, June 3-6, 2019 Philadelphia Convention Center; Philadelphia PA, Real Time Coverage by Stephen J. Williams, PhD @StephenJWillia2

and the indication was for prostate cancer, in particular hormone resistant castration resistant.  Another one was planned for pancreatic cancer from the same group and the early indications were favorable.

From Onclive

Source: https://www.onclive.com/view/car-t-cell-therapy-trial-in-solid-tumors-halted-following-2-patient-deaths 

Tmunity Therapeutics, a clinical-stage biotherapeutics company, has halted the development of its lead CAR T-cell product following the deaths of 2 patients who were enrolled to a trial investigating its use in solid tumors.1

The patients reportedly died from immune effector cell-associated neurotoxicity syndrome (ICANS), which is a known adverse effect associated with CAR T-cell therapies.

“What we are discovering is that the cytokine profiles we see in solid tumors are completely different from hematologic cancers,” Oz Azam, co-founder of Tmunity said in an interview with Endpoints News. “We observed ICANS. And we had 2 patient deaths as a result of that. We navigated the first event and obviously saw the second event, and as a result of that we have shut down the version one of that program and pivoted quickly to our second generation.”

Previously, with first-generation CAR T-cell therapies in patients with blood cancers, investigators were presented with the challenge of overcoming cytokine release syndrome. Now ICANS, or macrophage activation, is proving to have deadly effects in the realm of solid tumors. Carl June, the other co-founder of Tmunity, noted that investigators will now need to dedicate their efforts to engineering around this, as had been done with tocilizumab (Actemra) in 2012.

The company is dedicated to the development of novel approaches that produce best-in-class control over T-cell activation and direction in the body.2 The product examined in the trial was developed to utilize engineered patient cells to target prostate-specific membrane antigen; it was also designed to use a dominant TGFβ receptor to block an important checkpoint involved in cancer.

Twenty-four patients were recruited for the dose-escalating study and the company plans to release data from high-dose cohorts later in 2021.

“We are going to present all of this in a peer-reviewed publication because we want to share this with the field,” Azam said. “Because everything we’ve encountered, no matter what…people are going to encounter this when they get into the clinic, and I don’t think they’ve really understood yet because so many are preclinical companies that are not in the clinic with solid tumors. And the rubber meets the road when you get in the clinic, because the ultimate in vivo model is the human model.”

Azam added that the company plans to develop a new investigational new drug for version 2, which they hope will result in a safer product.


  1. Carroll J. Exclusive: Carl June’s Tmunity encounters a lethal roadblock as 2 patient deaths derail lead trial, raise red flag forcing rethink of CAR-T for solid tumors. Endpoints News. June 2, 2021. Accessed June 3, 2021. https://bit.ly/3wPYWm0
  2. Research and Development. Tmunity Therapeutics website. Accessed June 3, 2021. https://bit.ly/3fOH3OR

Forward to 2022

Reprogramming a new type of T cell to go after cancers with less side effects, longer impact

A Sloan Kettering Institute research team thinks new, killer, innate-like T cells could make promising candidates to treat cancers that so far haven’t responded to immunotherapy treatments. (koto_feja)

Immunotherapy is one of the more appealing and effective kinds of cancer treatment when it works, but the relatively new approach is still fairly limited in the kinds of cancer it can be used for. Researchers at the Sloan Kettering Institute have discovered a new kind of immune cell and how it could be used to expand the reach of immunotherapy treatments to a much wider pool of patients.

The cells in question are called killer innate-like T cells, a threatening name for a potentially lifesaving innovation. Unlike normal killer T cells, killer innate-like T cells stay active much longer and can burrow further into potentially cancerous tissue to attack tumors. The research team first reported these cells in 2016, but it’s only recently that they were able to properly understand and identify them.

“We think these killer innate-like T cells could be targeted or genetically engineered for cancer therapy,” said the study’s lead author, Ming Li, Ph.D., in a press release. “They may be better at reaching and killing solid tumors than conventional T cells.”

Below is the referenced paper from Pubmed:

Evaluation of the safety and efficacy of humanized anti-CD19 chimeric antigen receptor T-cell therapy in older patients with relapsed/refractory diffuse large B-cell lymphoma based on the comprehensive geriatric assessment system



Anti-CD19 chimeric antigen receptor (CAR) T-cell therapy has led to unprecedented results to date in relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL), yet its clinical application in elderly patients with R/R DLBCL remains somewhat limited. In this study, a total of 31 R/R DLBCL patients older than 65 years of age were enrolled and received humanized anti-CD19 CAR T-cell therapy. Patients were stratified into a fit, unfit, or frail group according to the comprehensive geriatric assessment (CGA). The fit group had a higher objective response (OR) rate (ORR) and complete response (CR) rate than that of the unfit/frail group, but there was no difference in the part response (PR) rate between the groups. The unfit/frail group was more likely to experience AEs than the fit group. The peak proportion of anti-CD19 CAR T-cells in the fit group was significantly higher than that of the unfit/frail group. The CGA can be used to effectively predict the treatment response, adverse events, and long-term survival.


Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma (NHL), accounting for 30–40% of cases, with the median age of onset being older than 65 years [1]. Although the five-year survival rate for patients with DLBCL has risen to more than 60% with the application of standardized treatments and hematopoietic stem cell transplantation, nearly half of patients progress to relapsed/refractory (R/R) DLBCL. Patients with R/R DLBCL, especially elderly individuals, have a poor prognosis [2,3], so new treatments are needed to prolong survival and improve the prognosis of this population.

As a revolutionary immunotherapy therapy, anti-CD19 chimeric antigen receptor (CAR) T-cell therapy has achieved unprecedented results in hematological tumors [4]. As CD19 is expressed on the surface of most B-cell malignant tumors but not on pluripotent bone marrow stem cells, CD19 has been used as a target for B-cell malignancies, including B-cell acute lymphoblastic leukemia, NHL, multiple myeloma, and chronic lymphocytic leukemia [5]. Despite the wide application and high efficacy of anti-CD19 CAR T-cell therapy, reports of adverse events (AEs) such as cytokine release syndrome (CRS) and immune effector cell-associated neurotoxic syndrome (ICANS) have influenced its use [6]. Especially in elderly patients, AEs associated with anti-CD19 CAR T-cell therapy might be more obvious.

Although anti-CD19 CAR T-cell therapy has been reported in the treatment of NHL, including R/R DLBCL, few studies to date have assessed the safety of anti-CD19 CAR T-cell therapy in elderly R/R DLBCL patients, and its clinical application in the elderly R/R DLBCL population is limited. In ZUMA-1 [7] to R/R DLBCL patients who received CAR T-cell therapy, the CR rate in patients ≥65 years was higher than that of in patients <65 years (75% vs. 53%). Lin et al. [8] reported 49 R/R DLBCL patients (24 patients >65 years, 25 patients <65 years) who received CAR T-cell therapy with a median follow-up of 179 days. The CR rate at 100 days was 51%, while the 6-month progression-free survival (PFS) and overall survival (OS) were 48% and 71%, respectively. Neither of the two studies carried out a comprehensive geriatric assessment (CGA) of fit, unfit, and frail groups of R/R DLBCL patients over 65 years of age and further analyzed the differences in efficacy and side effects in the three groups. The CGA is an effective system designed to evaluate the prognosis and improve the survival of elderly patients with cancer. The CGA system includes age, activities of daily living (ADL), instrumental ADL (IADL), and the Cumulative Illness Rating Score for Geriatrics (CIRS-G) [9].

In this study, elderly R/R DLBCL patients were grouped according to their CGA results (fit vs. unfit/frail) before receiving humanized anti-CD19 CAR T-cell therapy. We then analyzed the efficacy and AEs of anti-CD19 CAR T-cell therapy and compared findings between these groups.


Well it appears that the discriminator was only fitness going into the trial  a bit odd that the whole field appears to be lacking in development of Safety Biomarkers.



However Genentech (subsidiary of Roche) may now be using some data to develop therapies which may combat resistance to CART therapies which may provide at least, for now, a toxicokinetic approach to reducing AEs by lowering the amount of CARTs needed to be administered.


Source: https://www.fiercebiotech.com/research/genentech-uncovers-how-cancer-cells-resist-t-cell-attack-potential-boon-immunotherapy

Roche’s Genentech is exploring inhibiting ESCRT as an anticancer strategy, said Ira Mellman, Ph.D., Genentech’s vice president of cancer immunology. (Roche)

Cancer cells deploy various tactics to avoid being targeted and killed by the immune system. A research team led by Roche’s Genentech has now identified one such method that cancer cells use to resist T-cell assault by repairing damage.

To destroy their targets, cancer-killing T cells known as cytotoxic T lymphocytes (CTLs) secrete the toxin perforin to form little pores in the target cells’ surface. Another type of toxin called granzymes are delivered directly into the cells through those portals to induce cell death.

By using high-res imaging in live cells, the Genentech-led team found that the membrane damage caused by perforin could trigger a repair response. The tumor cells could recruit endosomal sorting complexes required for transport (ESCRT) proteins to remove the lesions, thereby preventing granzymes from entering, the team showed in a new study published in Science.

The following is the Science paper

Membrane repair in target cell defenses

Killer T cells destroy virus-infected and cancer cells by secreting two protein toxins that act as a powerful one-two punch. Pore-forming toxins, perforins, form holes in the plasma membrane of the target cell. Cytotoxic proteins released by T cells then pass through these portals, inducing target cell death. Ritter et al. combined high-resolution imaging data with functional analysis to demonstrate that tumor-derived cells fight back (see the Perspective by Andrews). Protein complexes of the ESCRT family were able to repair perforin holes in target cells, thereby delaying or preventing T cell–induced killing. ESCRT-mediated membrane repair may thus provide a mechanism of resistance to immune attack. —SMH


Cytotoxic T lymphocytes (CTLs) and natural killer cells kill virus-infected and tumor cells through the polarized release of perforin and granzymes. Perforin is a pore-forming toxin that creates a lesion in the plasma membrane of the target cell through which granzymes enter the cytosol and initiate apoptosis. Endosomal sorting complexes required for transport (ESCRT) proteins are involved in the repair of small membrane wounds. We found that ESCRT proteins were precisely recruited in target cells to sites of CTL engagement immediately after perforin release. Inhibition of ESCRT machinery in cancer-derived cells enhanced their susceptibility to CTL-mediated killing. Thus, repair of perforin pores by ESCRT machinery limits granzyme entry into the cytosol, potentially enabling target cells to resist cytolytic attack.
Cytotoxic lymphocytes, including cytotoxic T lymphocytes (CTLs) and natural killer (NK) cells, are responsible for identifying and destroying virus-infected or tumorigenic cells. To kill their targets, CTLs and NK cells secrete a pore-forming toxin called perforin through which apoptosis-inducing serine proteases (granzymes) are delivered directly into the cytosol. Successful killing of target cells often requires multiple hits from single or multiple T cells (1). This has led to the idea that cytotoxicity is additive, often requiring multiple rounds of sublethal lytic granule secretion events before a sufficient threshold of cytosolic granzyme activity is reached to initiate apoptosis in the target (2).
Loss of plasma membrane integrity induced by cytolytic proteins or mechanical damage leads to a membrane repair response. Damage results in an influx of extracellular Ca2+, which has been proposed to lead to the removal of the membrane lesion by endocytosis, resealing of the lesions by lysosomal secretion, or budding into extracellular vesicles (3). Perforin pore formation was initially reported to enhance endocytosis of perforin (4), but subsequent work has challenged this claim (5). Endosomal sorting complexes required for transport (ESCRT) proteins can repair small wounds and pores in the plasma membrane caused by bacterial pore-forming toxins, mechanical wounding, and laser ablation (67). ESCRT proteins are transiently recruited to sites of membrane damage in a Ca2+-dependent fashion, where they assemble budding structures that shed to eliminate the wound and restore plasma membrane integrity. ESCRT-dependent membrane repair has been implicated in the resealing of endogenous pore-mediated plasma membrane damage during necroptosis (8) and pyroptosis (9).

Localization of target-derived ESCRT proteins to the cytolytic synapse

To investigate whether ESCRT-mediated membrane repair might be involved in the removal of perforin pores during T cell killing, we first determined whether ESCRT proteins in cancer-derived cells were recruited to sites of CTL engagement after perforin secretion. We used CTLs from OT-I mice that express a high-affinity T cell receptor (TCR) that recognizes the ovalbumin peptide SIINFEKL (OVA257-264) bound to the major histocompatibility complex (MHC) allele H-2Kb (10). We performed live-cell microscopy of OT-I CTLs engaging SIINFEKL-pulsed target cells that express enhanced green fluorescent protein (EGFP)–tagged versions of Tsg101 or Chmp4b, two ESCRT proteins implicated in membrane repair (6). To correlate recruitment of ESCRT proteins with perforin exposure in time, we monitored CTL-target interaction in media with a high concentration of propidium iodide (PI), a cell-impermeable fluorogenic dye that can rapidly diffuse through perforin pores to bind and illuminate nucleic acids in the cytosol and nucleus of the target (5). EGFP-tagged ESCRT proteins were consistently recruited to the site of CTL engagement within 30 to 60 s after PI influx (Fig. 1, A and B). EGFP-Tsg101 and EGFP-Chmp4b in target cells accumulated at the cytolytic synapse after PI influx in 25 of 27 (92.6%) and 31 of 33 (93.9%) of conjugates monitored, respectively, compared with a cytosolic EGFP control, which was not recruited (Fig. 1C and movies S1 to S3). Notably, ESCRT-laden material, presumably membrane fragments, frequently detached from the target cell and adhered to the surface of the CTL (Fig. 1, D and E, and movie S2). We observed this phenomenon in ~60% of conjugates imaged in which targets expressed EGFP-Tsg101 or EGFP-Chmp4b (17 of 27 and 20 of 33 conjugates, respectively; Fig. 1D). Shedding of ESCRT-positive membrane from the cell after repair occurs after laser-induced plasma membrane wounding (67). Plasma membrane fragments shed from the target cell into the synaptic cleft likely contain ligands for CTL-resident receptors. Target cell death would separate the CTL and target, revealing target-derived material on the CTL surface.
FIG. 1. Fluorescently tagged ESCRT proteins in targets localize to site of CTL killing after perforin secretion.
(A) Live-cell spinning disk confocal imaging of a fluorescently labeled OT-I CTL (magenta) engaging an MC38 cancer cell expressing EGFP-Tsg101 (green) in media containing 100 μM PI (red). Yellow arrowheads highlight ESCRT recruitment. T-0:00 is the first frame of PI influx into the target cell (time in minutes:seconds). Scale bar, 10 μm. (B) Graph of EGFP-Tsg101 and PI fluorescence intensity at the IS within the target over time, from example in (A). AU, arbitrary units. (C and D) Quantification of CTL-target conjugates exhibiting accumulation of EGFP at the synapse after PI influx (C) or detectable EGFP-labeled material associated with CTL after target interaction (D) (EGFP condition: N = 22 conjugates in seven independent experiments; EGFP-Tsg101 condition: N = 27 conjugates in nine independent experiments; EGFP-Chmp4b condition: N = 33 conjugates in 24 independent experiments). (E) Live-cell spinning disk confocal imaging of OT-I CTL (magenta) killing MC38 expressing EGFP-Chmp4b (green), demonstrating the presence of target-derived EGFP-Chmp4b material (yellow arrowheads) associated with CTL membrane after a productive target encounter. T-0:00 is the first frame of PI influx into the target cell. Scale bar, 10 μm.

3D cryo-SIM and FIB-SEM imaging of CTLs caught in the act of killing target cells

Although live-cell imaging indicated that ESCRT complexes were rapidly recruited at sites of T cell–target cell contact, light microscopy alone is of insufficient resolution to establish that this event occurred at the immunological synapse (IS). We thus sought to capture a comprehensive view of the IS in the moments immediately after secretion of lytic granules. We used cryo–fluorescence imaging followed by correlative focused ion beam–scanning electron microscopy (FIB-SEM), which can achieve isotropic three-dimensional (3D) imaging of whole cells at 8-nm resolution or better (1113). To capture the immediate response of target cells after perforin exposure, we developed a strategy whereby cryo-fixed CTL-target conjugates were selected shortly after perforation, indicated by the presence of a PI gradient in the target (fig. S1A). In live-cell imaging experiments, PI fluorescence across the nucleus of SIINFEKL-pulsed ID8 target cells began as a gradient and became homogeneous 158 ± 64 s, on average, after initial PI influx (N = 31 conjugates; fig. S1, B and C, and movie S4). Thus, fixed CTL-target conjugates that exhibited a gradient of PI across the nucleus would have been captured within ~3 min of perforin exposure.
Coverslips of CTL-target conjugates underwent high-pressure freezing and were subsequently imaged with wide-field cryogenic fluorescence microscopy followed by 3D cryo–structured illumination microscopy (3D cryo-SIM) performed in a customized optical cryostat (14). We selected candidate conjugates for FIB-SEM imaging on the basis of whether a gradient of PI fluorescence was observed across the nucleus of the target emanating from an attached CTL (movie S5). FIB-SEM imaging of the CTL-target conjugate at 8-nm isotropic voxels resulted in a stack of >10,000 individual electron microscopy (EM) images. The image stack was then annotated using a human-assisted machine learning–computer vision platform to segment the plasma membranes of each cell along with cell nuclei and various organelles (https://ariadne.ai/).
We captured four isotropic 3D 8-nm-resolution EM datasets of CTLs killing cancer cells moments after the secretion of lytic granule contents (Fig. 2A and movie S6). Semiautomated segmentation of the cell membranes, nuclei, lytic granules, Golgi apparatus, mitochondria, and centrosomes of the T cells allow for easier visualization and analysis of the 3D EM data. All FIB-SEM datasets and segmentations can be explored online at https://openorganelle.janelia.org (see links in the supplementary materials). Reconstructed views of the segmented data clearly demonstrate the polarization of the centrosome, Golgi apparatus, and lytic granules to the IS—all of which are hallmarks of CTL killing [Fig. 2A, i to iii, and movie S6, time stamp (TS) 1:33] (1516). On the target cell side, we noted cytoplasmic alterations consistent with cell damage including enhanced electron density of mitochondria adjacent to the IS (fig. S2A). Close visual scanning of the postsynaptic target cell membrane in the raw EM data failed to reveal obvious perforin pores, which have diameters (16 to 22 nm) close to the limit of resolution for this technique (17).
FIG. 2. Eight-nm-resolution 3D FIB-SEM imaging of whole CTL-target conjugate.
(A) 3D rendering of segmented plasma membrane predictions derived from isotropic 8-nm-resolution FIB-SEM imaging of a high-pressure frozen OT-I CTL (red) captured moments after secretion of lytic granules toward a peptide-pulsed ID8 ovarian cancer cell (blue). (i) Side-on sliced view corresponding to the gray horizontal line within the inset box in (A). Seen here are 3D renderings of the segmented plasma membrane of the cancer cell (blue) as well as the CTL plasma membrane (red), centrosome (gold), Golgi apparatus (cyan), lytic granules (purple), mitochondria (green), and nucleus (gray). (ii and iii) A zoomed-in view from the dashed white box in (i) shows the details of the IS (ii) and a single corresponding FIB-SEM slice docked onto the segmented data (iii). (B) Single top-down FIB-SEM slice showing overlaid target cell (blue) and CTL (red) segmentation. (i) Zoomed-in view from dashed white box in (B) details the intercellular material (IM) (gray) between the CTL and target at the IS. (C) Zoomed-in image of a 3D rendering of the surface of the target cell plasma membrane (white) opposite the intercellular material (IM) at the IS. Yellow arrowheads mark plasma membrane buds protruding into the synaptic cleft. (i and ii) Accompanying images demonstrate the orientation of the view in (C) with the rendering of the CTL (red) present (i) and removed (ii), and the dashed yellow box in (ii) indicates the area of detail shown in (C).
The segmentation of the two cells illustrates the detailed topography of the plasma membrane of the CTL and target at the IS (fig. S2B). The raw EM and segmentation data reveal a dense accumulation of particles, vesicles, and multilamellar membranous materials, which crowd the synaptic cleft between the CTL and the target (Fig. 2B and movie S6, TS 0:40 to 0:50). The source of this intercellular material (IM) was likely in part the lytic granules because close inspection revealed similar particles and dense vesicles located within as-yet-unreleased granules (fig. S2C). To determine whether some of the membranous material within the intercellular space might also have been derived from the target cell, we examined the surface topology of the postsynaptic target cell. We noted multiple tubular and bud-like protrusions of the target cell membrane that extended into the synaptic space; thus, at least some of the membrane structures observed were still in continuity with the target cell (Fig. 2C and movie S6, TS 0:58 to 1:11). ESCRT proteins have been shown to generate budding structures in the context of plasma membrane repair (6), which led us to next assess where target-derived ESCRT proteins are distributed in the context of the postsecretion IS.
To map the localization of target-derived ESCRT proteins onto a high-resolution landscape of the IS, we captured three FIB-SEM datasets that have associated 3D cryo-SIM fluorescence data for mEmerald-Chmp4b localization (Fig. 3A, fig. S3, and movie S7). This correlative light and electron microscopy (CLEM) revealed that mEmerald-Chmp4b expressed in the target cell was specifically recruited to the target plasma membrane opposite the secreted IM (Fig. 3, B and C). The topography of the plasma membrane at the site of ESCRT recruitment was markedly convoluted, exhibiting many bud-like projections (movie S7, TS 0:37 to 0:40). mEmerald-Chmp4b fluorescence also overlapped with some vesicular structures in the intercellular synaptic space (Fig. 3C). Together, the live-cell imaging and the 3D cryo-SIM and FIB-SEM CLEM demonstrate the localization of ESCRT proteins at the synapse that was the definitive site of CTL killing and was thus spatially and temporally correlated to perforin secretion. These data implicate the ESCRT complex in the repair of perforin pores.
FIG. 3. Correlative 3D cryo-SIM and FIB-SEM reveal localization of target-derived ESCRT within the cytolytic IS.
(A) Three example datasets showing correlative 3D cryo-SIM and FIB-SEM imaging of OT-I CTLs (red) captured moments after secretion of lytic granules toward peptide-pulsed ID8 cancer cells (blue) expressing mEmerald-Chmp4b (green fluorescence). (B and C) Single FIB-SEM slices corresponding to the orange boxes in (A), overlaid with CTL and cancer cell segmentation (B) or correlative cryo-SIM fluorescence of mEmerald-Chmp4b derived from the target cell (C).

Function of ESCRT proteins in repair of perforin pores

We next investigated whether ESCRT inhibition could enhance the susceptibility of target cells to CTL-mediated killing. Prolonged inactivation of the ESCRT pathway is itself cytotoxic (9). We thus developed strategies to ablate ESCRT function that would allow us a window of time to assess CTL killing (fig. S4). We used two approaches to block ESCRT function: CRISPR knockout of the Chmp4b gene or overexpression of VPS4aE228Q (E228Q, Glu228 → Gln), a dominant-negative kinase allele that impairs ESCRT function (fig. S4, A to C) (10). We took care to complete our assessment of target killing well in advance of spontaneous target cell death (fig. S4D).
We tested the capacity of OT-I CTLs to kill targets presenting one of four previously characterized peptides that demonstrate a range of potencies at stimulating the OT-I TCR: SIINFEKL (N4), the cognate peptide, and three separate variants (in order of highest to lowest affinity), SIITFEKL (T4), SIIQFEHL (Q4H7), and SIIGFEKL (G4) (1819). Target cells were pulsed with peptide, washed, transferred to 96-well plates, and allowed to adhere before the addition of OT-I CTLs. Killing was assessed by monitoring the uptake of a fluorogenic caspase 3/7 indicator (Fig. 4, A to D, and fig. S5A). Killing was significantly more efficient in ESCRT-inhibited target cells for both CRISPR depletion of Chmp4b (Fig. 4, A to C) and expression of the dominant-negative VPS4aE228Q (Fig. 4D). The difference in killing between the ESCRT-inhibited and control cells was greater when the lower-potency T4, Q4H7, and G4 peptides were used. Nevertheless, ESCRT inhibition moderately improved killing efficiency even in the case of the high-potency SIINFEKL peptide. ESCRT inhibition had no effect on MHC class I expression on the surface of target cells (fig. S5B). Thus, ESCRT inhibition could sensitize target cells to perforin- and granzyme-mediated killing, especially at physiologically relevant TCR-peptide MHC affinities.
FIG. 4. ESCRT inhibition enhances susceptibility of cancer cells to CTL killing and recombinant lytic proteins.
(A) Representative time-lapse data of killing of peptide-pulsed Chmp4b knockout (KO) or control B16-F10 cells by OT-I CTLs. Affinity of the pulsed peptide to OT-I TCR decreases from left to right. Error bars indicate SDs. (B) Images extracted from T4 medium-affinity peptide condition show software-detected caspase 3/7+ events in control and Chmp4b KO conditions. (C and D) Data representing the 4-hour time point of assays measuring OT-I T cells killing either Chmp4b KO (C) or VPS4 dominant-negative (D) target cells with matched controls. Error bars indicate SDs of data. Data are representative of at least three independent experimental replicates. pMHC, peptide-MHC; HA, hemagglutinin. (E and F) Determination of sublytic dose of Prf. B16-F10 cells expressing VPS4a (WT or E228Q) were exposed to increasing concentrations of Prf. Cell viability was determined by morphological gating (E). FSC, forward scatter; SSC, side scatter. (G and H) B16-F10 cells expressing VPS4a (WT or E228Q) were exposed to a sublytic dose of Prf in combination with increasing concentrations of recombinant GZMB (rGZMB). Cell death was determined by Annexin V–allophycocyanin (APC) staining (G). Controls include a condition with no perforin and 5000 ng/ml rGZMB and sublytic perforin with no rGZMB. Graphs in (F) and (H) represent the means of three experiments, and error bars indicate SDs. Statistical significance was determined by multiple unpaired t tests with alpha = 0.05. ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001.
We next directly tested the effects of ESCRT inhibition when target cells were exposed to both recombinant perforin (Prf) and granzyme B (GZMB), the most potently proapoptotic granzyme in humans and mice (20). Prf alone at high concentrations can lyse cells (4), so we first determined a sublytic Prf concentration that would temporarily permeabilize the plasma membrane but permit the cells to recover. B16-F10 cells expressing either VPS4aWT (WT, wild-type) or VPS4aE228Q were exposed to a range of Prf concentrations in the presence of PI, and cell viability and PI uptake were assessed using flow cytometry. Cells that expressed dominant-negative VPS4aE228Q were more sensitive to Prf alone than ESCRT-competent cells (Fig. 4, E and F). At 160 ng/ml Prf, there was no significant difference in cell viability for either condition. Cells in the live gate that were PI+ had been permeabilized by Prf but recovered. Although the percentage of PI+ live cells was similar under both sets of conditions, the mean fluorescence intensity of PI was higher in live ESCRT-inhibited cells (fig. S6). A delay in plasma membrane resealing could account for this difference.
We reasoned that delaying perforin pore repair might also enhance GZMB uptake into the target. ESCRT-inhibited cells were more sensitive to combined perforin-GZMB when cell death was measured by Annexin V staining (Fig. 4, G and H). Similar results were observed when these experiments were repeated with a murine lymphoma cancer cell line (fig. S7). The observation that ESCRT-inhibited target cells are more sensitive to both CTL-secreted and Prf-GZMB supports the hypothesis that the ESCRT pathway contributes to membrane repair after Prf exposure.
Escaping cell death is one of the hallmarks of cancer. Our findings suggest that ESCRT-mediated membrane repair of perforin pores may restrict accessibility of the target cytosol to CTL-secreted granzyme, thus promoting survival of cancer-derived cells under cytolytic attack. Although other factors may contribute to setting the threshold for target susceptibility to killing, the role of active repair of perforin pores must now be considered as a clear contributing factor.


We thank members of the Mellman laboratory for advice, discussion, and reagents; B. Haley for assistance with plasmid construct design; the Genentech FACS Core Facility for technical assistance; S. Van Engelenburg of Denver University for invaluable discussions and guidance; A. Wanner, S. Spaar, and the Ariande AI AG (https://ariadne.ai/) for assistance with FIB-SEM segmentation, CLEM coregistration, data presentation, and rendering; D. Bennett of the Janelia Research Campus for assisting with data upload to https://openorganelle.janelia.org; and the Genentech Postdoctoral Program for support.
Funding: A.T.R. and I.M. are funded by Genentech/Roche. C.S.X., G.S., A.W., D.A., N.I., and H.F.H. are funded by the Howard Hughes Medical Institute (HHMI).

Please look for a Followup Post concerning “Developing a Pharmacovigilence Framework for Engineered T-Cell Therapies”



  1. Ertl HC, Zaia J, Rosenberg SA, June CH, Dotti G, Kahn J, Cooper LJ, Corrigan-Curay J, Strome SE: Considerations for the clinical application of chimeric antigen receptor T cells: observations from a recombinant DNA Advisory Committee Symposium held June 15, 2010. Cancer research 2011, 71(9):3175-3181.
  2. Morgan RA, Yang JC, Kitano M, Dudley ME, Laurencot CM, Rosenberg SA: Case report of a serious adverse event following the administration of T cells transduced with a chimeric antigen receptor recognizing ERBB2. Molecular therapy : the journal of the American Society of Gene Therapy 2010, 18(4):843-851.
  3. Kandalaft LE, Powell DJ, Jr., Coukos G: A phase I clinical trial of adoptive transfer of folate receptor-alpha redirected autologous T cells for recurrent ovarian cancer. Journal of translational medicine 2012, 10:157.

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Larry, H. Bernstein, MD, FCAP, Author and Curator


Picking the Lock on Pluripotency

Kevin Eggan, Ph.D.
N Engl J Med 28 Nov 2013; 369:2150-2151 http://dx.doi.org/10.1056/NEJMcibr1311880

Induced pluripotent stem (iPS) cells are obtained by reprogramming somatic cells. This powerful disease-modeling research tool is central to certain experimental approaches to therapy. A recent study showed that iPS cells can be generated with a very high degree of efficiency.

FIGURE 1  http://dx.doi.org/nejmcibr1311880_f1

nejmcibr1311880_f1   A Potent Provision of Induced Pluripotent Stem Cells.

A Potent Provision of Induced Pluripotent Stem Cells

Generation of Induced Pluripotent Stem Cells from CD34+ Cells across Blood Drawn from Multiple Donors with Non-Integrating Episomal Vectors

AA Mack, S Kroboth,  D Rajesh,  Wen Bo Wang
Published: November 22, 2011  PLoS ONE 6(11): e27956   http://dx.doi.org/10.1371/journal.pone.0027956

The methodology to create induced pluripotent stem cells (iPSCs) affords the opportunity to generate cells specific to the individual providing the host tissue. However, existing methods of reprogramming as well as the types of source tissue have significant limitations that preclude the ability to generate iPSCs in a scalable manner from a readily available tissue source. We present the first study whereby iPSCs are derived in parallel from multiple donors using episomal, non-integrating, oriP/EBNA1-based plasmids from freshly drawn blood. Specifically, successful reprogramming was demonstrated from a single vial of blood or less using cells expressing the early lineage marker CD34 as well as from unpurified peripheral blood mononuclear cells. From these experiments, we also show that proliferation and cell identity play a role in the number of iPSCs per input cell number. Resulting iPSCs were further characterized and deemed free of transfected DNA, integrated transgene DNA, and lack detectable gene rearrangements such as those within the immunoglobulin heavy chain and T cell receptor loci of more differentiated cell types. Furthermore, additional improvements were made to incorporate completely defined media and matrices in an effort to facilitate a scalable transition for the production of clinic-grade iPSCs.

Citation: Mack AA, Kroboth S, Rajesh D, Wang WB (2011) Generation of Induced Pluripotent Stem Cells from CD34+ Cells across Blood Drawn from Multiple Donors with Non-Integrating Episomal Vectors. PLoS ONE 6(11): e27956. doi:10.1371/journal.pone.0027956


Fibroblasts have been a predominate source material for the development of the process to generate induced pluripotent stem cells (iPSCs) given their ability to expand, endure for multiple passages in culture, and receptiveness to efficient infection by viruses expressing a combination of transcription factors for reprogramming [1]–[6]. However, fibroblasts from skin biopsies require invasive surgical procedures, are labor intensive and isolating a sufficient number for reprogramming takes time. In addition, the ability to generate iPSCs from skin appears inversely correlated with the age of the donor likely due to increasing exposure to external mutagens [7]. There is value, therefore, in alternative tissue sources to generate iPSCs that minimize the risk for additional mutation, involve less invasive procedures, and are amenable to industrialization to increase availability across an extensive population range.


A blood draw is an ideal starting point to generate donor-specific iPSCs because it is minimally invasive and established procedures are already in place for acquisition and handling [8]. Lymphocytes comprise a large fraction of the peripheral blood mononuclear cell (PBMC) population but pose at least two potential limitations. First, they are subject to intrinsic DNA rearrangements such as those that occur in B and T cells at the V, D, and J gene segments as well as T cell receptor (TCR) loci to generate a diverse repertoire of antigen-specific surface immunoglobulins. These rearrangements are subsequently perpetuated in iPSCs generated from them and their impact on iPSC function is currently unknown [9], [10]. Second, some research has indicated that host cell types may influence functional properties of iPSCs [11], [12]. For example, while embryonic stem (ES) cells and progenitor cells derived from bone marrow successfully differentiate into B cells, iPSCs derived from B cells have demonstrated resistance to this ability [13], [14], [15]. Therefore, choosing an early lineage cell type that lacks DNA rearrangements alleviates the potential risk of reduced ability to differentiate.

Somatic cells that are characteristically more progenitor-like with respect to the expression of early lineage markers, such as CD34, appear more susceptible to reprogramming, and they too can be isolated from blood [16]. For example, Haase and colleagues successfully isolated and reprogrammed early progenitor cells isolated from cord blood. The ability to reprogram cells from peripheral blood, however, expands the range of host cells available for reprogramming especially when acquisition of cord blood-derived material is not an option. However, the amount of CD34+ cells represents less than 0.1% of the population of PBMCs thus limiting the amount of source material available for reprogramming. To generate enough starting material to perform reprogramming trials, Loh and colleagues relied on patients treated with granulocyte-colony stimulating factor (G-CSF) to expand the number of CD34+ cells in circulating peripheral blood and ultimately generated iPSCs from these cells [17]. The acquisition of blood that does not require donors to receive these agents would be more desirable to avoid the negative side effects associated with them [18]. Studies have also shown that cells from mobilized blood demonstrate functional differences when compared with cells from non-mobilized samples indicating changes to properties intrinsic to the cell [19]. For example, epigenetic and genetic anomalies (i.e. aneuploidy) have been detected in cells derived from patients mobilized with G-CSF [20], [21]. These observations increase the likelihood that similar genetic modifications would carry over into iPSCs generated from mobilized CD34+ cells and potentially impact their function.

The method to generate iPSCs from cord and mobilized peripheral blood has predominately relied on viral-based methods to introduce reprogramming factors [16], [17]. Resulting clones thus have transgenes integrated into their genomes that may alter the function of iPSCs, increase the risk of cancer, and hinder their potential for clinical application. Improvements to reprogramming methods have been made to eliminate integrated transgenes including a recent study examining the reprogramming potential of blood-derived cells using a previously described episomal, oriP/EBNA1-based transfection method [2], [22], [23]. We capitalized on the oriP/EBNA1-method but made modifications to accommodate the reprogramming of CD34+ cells derived from actual vials of blood collected across multiple donors. The oriP/EBNA1-based vectors contribute to the replication and retention of plasmids during each cell division long enough for reprogramming to occur and are lost over time resulting in cells free of transfected DNA and integrated transgenes [24], [25]. Importantly, reprogramming can be achieved through a single transfection. Herein we demonstrate the ability to generate iPSCs from a single vial of blood or less using an improved process of reprogramming that incorporates fully defined conditions to generate iPSCs free of gene rearrangements and transgene elements.



Hematopoietic progenitor cells from non-mobilized, peripheral blood are expandable


Hematopoietic progenitor cells expressing CD34 represent a small fraction of the population and limit the number of cells available for reprogramming; therefore, a modified formulation of a media used to expand cord blood cells was tested on CD34+ cells isolated from peripheral blood [26]. CD34+ cells from two non-mobilized, peripheral (PB.1 and PB.2) blood donors were tested in comparison to CD34+ cells from two cord blood donors (CB.1 and CB.2). Cells were placed into untreated, 24-well culture plates at 1.2×104 per ml of expansion media (StemSpan basal medium; 300 ng/ml each of SCF, Flt3, TPO; 100 ng/ml IL-6; 10 ng.ml IL-3) and fed 3 to 4 days later. The total number of cells from peripheral blood expanded 170-fold and 680-fold from cord blood after 10 to 14 days in culture (Figure 1A, left hand panel). The percentage of CD34+ cells in the peripheral and cord blood samples peaked in less than 1 week (CB data not shown; Figure 1A, right hand panel). The expression profile of expanding populations was determined by flow cytometry for all donors examined herein (Figure 1B). Phenotypic analysis of the resulting peripheral blood culture PB.2 after 10 days of expansion revealed predominately early progenitor cells expressing CD43, CD45, CD33, CD44, CD15, and CD117 and marginal levels of T (CD3, CD4, CD8), NK (CD56, CD94), B (CD19), macrophage (CD163), megakaryocyte (CD41), and monocyte (CD14) cells (Figure 1C).

Figure 1. Hematopoietic cells enriched for CD34 expression are expandable.

journal.pone.0027956.g001  Figure 1. Hematopoietic cells enriched for CD34 expression are expandable


A. Graphs depict the expansion of purified cells from either two peripheral (PB.1 and PB.2) or cord (CB.1 or CB.2) blood donors over time (lefthand panel) along with the percentages of the total population that are CD34+ (righthand panel). B. Representative profile of a purified population of cells after 6 days of expansion by flow cytometry on cells isolated from Donor 3002. Flow cytometry plots from control staining using IgG antibodies (upper plots) are compared to plots with antibodies specific to lineage markers (lower plots). C. The graph represents an extended analysis by flow cytometry of the characteristic profile of PB.2 cells after 10 days of expansion. The % positive indicates the fraction of the population expressing the cell surface markers on the x-axis. D. The total number of CD34+ cells across 16 different donors was assessed beginning at 0 and 6 days of expansion (left side y-axis). The fold expansion (right side y-axis, orange squares) was determined by dividing the total number of cells at day 6 divided by the number of cells at day 0 after purification. The average percent of CD34 expression across all 16 donors was 48+/−19%.     http://dx.doi.org/10.1371/journal.pone.0027956.g001

These expansion conditions were then applied to cells acquired from a single vial of blood collected from multiple donors. PBMCs were isolated, frozen down immediately, or directly purified for CD34+ cells and seeded for expansion. On average, 1×107 PBMCs were recovered per 8 ml vial of blood and yielded approximately 2×104 cells after purification for CD34-expressing cells (data not shown). Although the magnitude of expansion was variable, cells from all of the donors demonstrated expansion ranging from 3 to 83-fold after 6 days in culture and approximately 48+/−19% of that population expressed CD34 (Figure 1D).

Optimizing the generation of iPSCs with small molecules and a defined matrix

The total number of purified cells isolated from a single, 8 ml vial of blood can be as little as 2×104 CD34+ cells; therefore, a range of CD34+ cell numbers was tested to determine transfection efficiency from low cell numbers. The efficiency of transfection was determined by transfecting an oriP/EBNA1-containing plasmid encoding GFP into expanded CD34+ cells and assessing them by flow cytometry. Viability was determined by identifying the fraction of viable cells that did not stain positively for trypan blue the day after transfection divided by the total number of input cells. Viability was approximately 30% when 1×104 to 1×105 input cells were used for transfection (data not shown). Cell numbers at 1×104 and 3×104 resulted in an efficiency of 30% and was 40% when using 6×104 and 1×105 cells (Figure 2A). Cells expanded for only 3 days demonstrated a two-fold increase in transfection efficiency. Over 90% of those cells also co-expressed GFP and CD34 while only 18% of the cells transfected after 6 days of expansion co-expressed both markers (Figure 2B, C). These results support the notion that the conditions selected for this protocol favor the transfection of CD34+ cells present in the population.

Figure 2. Identifying optimal transfection conditions for CD34+ cells.

journal.pone.0027956.g002   Figure 2. Identifying optimal transfection conditions for CD34+ cells.

A. PBMCs (donor GG) were isolated and purified for CD34-expression and expanded for 6 days. A range of cell numbers were transfected with a control, oriP/EBNA1-based plasmid expressing GFP. Transfection efficiency was determined by calculating the percentage of viable cells expressing GFP detectable by flow cytometry (n = 6). B. PBMCs (donor A2389) were isolated, purified for CD34-expression and expanded for 3 or 6 days. 6×104 to 1×105 cells were transfected with the control, GFP-expressing plasmid. The graph depicts the percent of the total population that is GFP-positive along with the absolute number of total cells (n = 3). C. The graph represents the fraction of cells in B that co-express GFP and CD34 when transfected at 3 or 6 days of expansion (n = 3).    http//dx.doi.org/10.1371/journal.pone.0027956.g002

We anticipated variability in reprogramming efficiency given the differences already observed across donors for other cell types tested and with other methods of reprogramming. Therefore, we optimized the matrix, media, and plasmid combinations used for reprogramming. Firstly, a common source of variation occurs when MEFs or matrigel are used because both are undefined, cumbersome to prepare, and vary from lot-to-lot. Therefore, we established a defined matrix by testing a variety of commercially available possibilities. Recombinant protein fragments containing the active domains of human fibronectin (RetroNectin) or vitronectin consistently supported iPSC formation the best among those tested. Second, the efficiency of colony formation on RetroNectin-coated plates improved significantly when used in combination with StemSpan SFEM media, N2, B27, and a cocktail of small molecules that included PD0325901, CHIR99021, A-83-01, and HA-100 (Figure 3A). These molecules have been described previously as inhibitors of MEK, GSK3β, TGFβ, and ROCK pathways, respectively [27], [28]. Patches of adherent cells appeared within one week and became a positive indicator for progression into iPSCs since hematopoietic cells are typically cultured in suspension. The following week many of the colonies exhibited overt characteristics typical of an iPSC and stained positively for the common pluripotency markers Tra-1-81 and alkaline phosphatase (AP) (Figure 3A). The borders of the colonies were compact and the nucleoli more visible when cultures were transitioned to defined, TeSR2 media without small molecules 1.5 to 2 weeks following transfection. Thirdly, episomal oriP/EBNA1-based plasmids were used to deliver Oct4, Sox2, Klf4, C-myc, Nanog, Lin28, and SV40 Large T-antigen as previously described (Set 1; Figure 3B) [2]. Different combinations of reprogramming plasmids were also tested to determine whether a boost in reprogramming efficiency was possible. Based on previous reports indicating the benefit of L-myc in reprogramming trials, we modified plasmid combination Set 1 and substituted L-myc in place of C-myc (Set 2, Figure 3B) [29], [30]. While an improvement was not observed when C-myc was substituted for L-myc in the combination of plasmids represented in Set 1 (data not shown), an equal to or two-fold improvement was observed with plasmid Set 2 expressing L-myc (Figure 3C). Optimizing a range of input cell numbers for transfection also revealed more consistent generation of iPSCs when transfecting greater than 5×104 cells (Figure 3D).

Figure 3. Plasmid transfections to optimize reprogramming efficiency.

journal.pone.0027956.g003  Figure 3. Plasmid transfections to optimize reprogramming efficiency.

A. Representative reprogramming trial from freshly drawn blood (donor 3002) using combination plasmid Set 2 for transfection. A single well is shown from a 6-well plate that contains colonies staining positively for AP activity (i). The white arrowhead highlights the colony magnified in panel ii that also stained positively for Tra-1-81 expression (green), panel iii. B. Schematic of the plasmid sets successfully used for reprogramming trials. Set 1 contains a combination of two plasmids for transfection whereby a 20 kb plasmid that either contains C- or L-myc is depicted. Set 2 includes a three plasmid combination for transfection. C. CD34+ cells purified from four different donors were expanded for 6 days and transfected using the plasmid combination that expresses either Set 1 or Set 2 plasmid sets to compare the total number of resulting iPSCs. D. Reprogramming trials were performed using plasmid Set 2 to transfect a range of cell numbers expanded for 6 days (donor GG, n = 6).  http://dx.doi.org/10.1371/journal.pone.0027956.g003


Optimization of iPSCs generated from CD34+ cells isolated from fresh, whole blood across multiple donors

The next step was to confirm iPSCs could be generated from actual vials of human blood, ensure cell numbers optimized for expansion and transfection are applicable across multiple donors, and determine whether the starting volume of blood can be minimized. Colonies emerging during reprogramming were scored positive by their ability to express Tra1-81 and exhibit a classic embryonic stem (ES) cell-like morphology. After colonies were picked from the reprogramming cultures, a subset of them were further characterized to confirm their pluripotency. Reprogramming efficiency was calculated in two ways 1) the number of iPSCs divided by the total volume of blood collected from each donor and 2) the total number of iPSCs divided by the number of cells for transfection multiplied by 1×105 cells. The first calculation incorporates the whole process beginning from the blood collection to the generation of an iPSC. The second calculation removes the variability incurred during the isolation of PBMCs, purification, and expansion and focuses on the number of iPSCs generated per number of cells placed into transfection.

We tested blood collected across donors spanning a range of ethnicities, ages, and genders to confirm iPSCs could be generated from CD34+ cells purified from fresh blood draws (Table 1). Six of these donors provided up to 55 ml of blood, and PBMCs from them were either isolated and used directly for purification, expansion, and reprogramming or frozen down after isolation. iPSCs were successfully generated from all six donors regardless of whether they were from fresh or frozen cells despite the lower efficiency of reprogramming, less than 1 iPSC per ml of blood (Table 2). Next, smaller volumes of blood representative of a single vial were obtained from six different donors to test parameters established in earlier experiments such as the number of cells for transfection and plasmid combinations. The cell numbers used for transfection from donors 3052, 3233, and 3373 ranged from 2×104 to 4×104 which fall below the minimum, 5×104 cells, established with our optimization studies. These experiments resulted in less than one iPSC per ml of blood (Table 2). Also, transfections with cells from donors 2583, 2970, and 3185 represent early trials performed with plasmid Set 1 expressing C-myc before Set 2 plasmids expressing L-myc were fully optimized which may have resulted in more iPSCs.

Table 1. Diversity across the set of donors used for reprogramming trials to generate iPSCs.

Table 2. Optimizing reprogramming from a range of blood volumes across multiple donors.

The next step was to then extend the insights acquired from these donors and verify the robustness of our protocol against ten new donors. The average number of iPSCs per ml of blood and per 1×105 cells across these donors indeed improved after incorporating experience with handling and the testing performed on the earlier donor samples (Table 3). Furthermore, these experiments were extended to test even smaller volumes of blood from a subset of the same donors in Table 3. CD34+ cells purified from approximately 4 ml of blood were sufficient to generate iPSCs from all six donors tested, and CD34+ cells from approximately 2 ml of blood from four out of six of these donors generated iPSCs (Table 4). These results demonstrate that iPSCs can be generated from CD34+ isolated from tractable volumes of blood using this non-intergrating and feeder-free method of reprogramming.

Table 3. Improved reprogramming across multiple donors from a single vial of blood.


Table 4. The efficiency of reprogramming CD34+ cells beginning from 4 ml of blood or less.


iPSCs derived from peripheral blood are pluripotent and free of transgene elements

Multiple iPSCs from each of the donors that were reprogrammed from Tables 2, 3, and 4 were selected for further characterization to confirm their pluripotency. The clones exhibited a normal karyotype, were positive for Tra-1-81 and SSEA-4 expression by flow cytometry as well as endogenous genes DNMT3B, REX1, TERT, UTF1, Oct4, Sox2, Nanog, Lin28, Klf4, and C-myc (Table 5, Figure 4A–C). Clones did not exhibit integrated transgene or episomal elements and loss of episomal DNA occurred, on average, within 7–10 passages (Table 5, Figure 4D,E). A PCR screen did not reveal rearrangements pertaining to immunoglobulin heavy chain (IgH) or a subset of T cell receptor (TCR) gene segments (Table 5, Figure 4F). The lack of rearrangements supports the notion that the protocol selectively favors the production of iPSCs from hematopoietic progenitors rather than more differentiated cell types. When used for in vitro directed differentiation at passage 15, donor 2939 iPSC clones 4 and 5, which have lost episomal plasmids, were competent to form neurons (Figure 5G). Furthermore, five iPS clones from three different donors also formed teratomas after injection into immunodeficient (SCID) mice (Figure 4G). Interestingly, the presence of residual episomal plasmids did not appear to hinder the ability to form teratomas since clone 6 from donor 2970 did not lose transfected plasmids until passage 18, well after injection into mice for teratoma studies.

Figure 4. Characterization of iPSCs derived from CD34+ blood cells.

journal.pone.0027956.g004  Figure 4. Characterization of iPSCs derived from CD34+ blood cells.

A subset of iPSC clones were characterized for pluripotency. The experiments demonstrated in this figure provide representative examples of the types of results observed for characterization studies using iPS clones 4 and/or 5 derived from donors 2939 and 3389. A. Cytogenetic analysis on G-banded metaphase cells from iPS clone 4 exhibiting a normal karyotype. B and C. RT-PCR confirms the endogenous expression of classic pluripotency genes and the absence of expression from transgenes. A standard in-house iPS line served as the positive control k. D. Clones were deemed free of episomal (E) DNA and genomic integration (G) by PCR. E. PCR was used to track the loss of oriP/EBNA1-based plasmids at multiple passages using primers that amplify EBNA1. A control plasmid at 1 and 20 copies per genome was used to establish the sensitivity of the PCR at 1 copy per 3,000 cells. F. PCR screen using primers specific for the joining region and all three of the conserved framework regions (FR1, FR2 and FR3) to amplify immunoglobulin heavy chain (IgH) gene rearrangements and two assays with primers specific to the T cell receptor (TCR) gamma gene rearrangement. G. Representative image of donor 2939 clone 5 differentiated in vitro into neurons (i). Clone 5 also demonstrated differentiation into all three germ layers: ii) epithelium iii) endoderm iv) mesoderm v) ectoderm vi) endoderm from teratomas formed when iPSCs were injected into immunodeficient, SCID mice.

Figure 5. The presence of CD34+ cells correlates with reprogramming efficiency.

journal.pone.0027956.g005  Figure 5. The presence of CD34+ cells correlates with reprogramming efficie

A. CD34+ cells from four different blood donors were expanded for 3, 6, 9, or 13 days. A large volume of blood was collected from donors 3096, 2849, and 3389 to ensure sufficient cell numbers to perform these studies. Expanding CD34+ cells using plasmid DNA combination Set 2. The efficiency of reprogramming was calculated as the total number of iPSCs exhibiting morphological features characteristic of an ES cell and an ability to stain positively for Tra-1-81 divided by the total number of cells used for transfection. Black Squares depict the percentage of the population expressing CD34 at the indicated days of expansion. B. Representative reprogramming trial whereby both the positive (i) and negative (ii) fraction following purification were used for reprogramming. Panel (i) shows one well of a 6-well plate that contains successfully reprogrammed colonies from donor 2939 based on their ability to demonstrate AP activity. The CD34-depleted fraction from donor 2939 was unable to form colonies as indicated by the lack of AP staining when performed in parallel with the purified population panel, ii. Panels iii and iv magnify the colony in panel (i) marked by a white arrowhead and demonstrates expression of Tra-1-81 (green), panel iv.

Table 5. Characterization of insert-free iPS clones derived from fresh blood.

Reprogramming efficiency correlates with the amount of CD34-expression

The isolation of CD34+ cells from PBMCs creates an additional step in our process and others have demonstrated successful reprogramming directly from PBMCs without the need for purification [22]. Therefore, several experiments to determine whether a correlation exists between CD34+ cells and reprogramming efficiency were performed. First, the expanding CD34+ populations were screened by flow cytometry for characterization prior to transfection. T, B, and NK cells were undetectable after 3 and 6 days of expansion demonstrated by their lack of CD3, 19, and 56 expression, respectively. The percentage of CD34 expression during expansion ranged from 30 to 100%, thus increasing the likelihood of reprogramming more of an early lineage cell type (n = 9, data not shown). Second, samples were taken from the purified populations during expansion at different timepoints as they lost CD34 expression to determine their receptiveness to reprogramming. A decrease in reprogramming efficiency was observed in correlation with decreasing percentages of CD34 expression across populations of cells from four independent donors (Figure 5A). For example, donor 3096 exhibited only 1 iPSC per 1×105 input cells when beginning from cells expanded for 13 days (31% CD34+) compared to 91.5 iPSCs per 1×105 cells following 3 days when levels of CD34 expression were much higher, 98% (Figure 5B). Third, populations depleted of CD34+ cells were tested for their ability to reprogram in parallel with their CD34+ cell counterparts. These CD34-depleted populations were not receptive to reprogramming as the CD34+ cells even when the same media and transfection conditions were used (n = 3, Figure 5B). Finally, a side-by-side comparison of reprogramming efficiency was performed between unpurified PBMCs and CD34+ cells isolated from 10 different donors. A medium described previously for the expansion of erythroblasts and for successful reprogramming studies was used to ensure media would not be a limiting factor for reprogramming the PBMCs in our protocol [22], [31]. Reprogramming trials beginning from either PBMCs or CD34+ cells were launched in parallel using their respective media for expansion. The efficiency of reprogramming was approximately 2 to 8 fold higher when beginning with cells purified for CD34 expression in 9 out of the 10 donors compared to those from PBMCs (p = 0.007; Figure 6). A significant fraction of the PBMC population was comprised of lymphocytes (~79+/−14% CD3/CD19) at the time of transfection (data not shown); therefore, PCR was performed to screen for potential IgH and TCR gene rearrangements to determine whether both protocols promoted the generation of iPSCs free of gene rearrangements. Interestingly, screened clones from either cell type were free of IgH and TCR gene rearrangements indicating that both protocols favor the reprogramming of early progenitor cells. The lower efficiency of reprogramming from the PBMC population may reflect the dilution of early progenitor blood cells by a predominately lymphocytic population.

Figure 6. Comparing the efficiency of reprogramming between PBMCs and CD34+ cells.

PBMCs and CD34+ cells were isolated from single tubes of blood provided from 10 different donors. The efficiency of reprogramming following transfection with DNA Combination Set 2 was determined for each donor and each method. “Total colonies” refers to all iPS colonies derived from either CD34+ or PBMC populations that stain positively for Tra1-60 and “iPS-like” colonies are those that stain positively for Tra1-60, exhibit clear iPS morphology, and are large enough to pick for expansion. Input cells refer to the number of CD34+ cells or PBMCs were used for transfection. The efficiencies across all donors from both methods were compared using the Wilcoxon signed rank test (two-sided), p = 0.007.

Generation of iPSCs from CD34+ cells using completely defined reagents

Additional reprogramming trials were performed using completely defined conditions to enable the production of clinic-grade iPSCs. A large pool of CD34+ cells mixed from multiple donors was used for multiple tests and resulted in a successful expansion of 113+/−11 fold in defined media compared to 83+/−32 fold for cells in standard conditions after 6 days of expansion (Figure 7A). Despite the 30-fold difference between the two conditions, the absolute number of CD34+ cells is similar between the two populations when multiplied by the percentage of the population expressing CD34 by flow cytometry. For example, 42+/−13% of the population expanded in standard conditions expressed CD34 and 26+/−16% expressed CD34 using completely defined conditions (Figure 7A). There were no detectable CD3+, CD19+, or CD56+ cells after 6 days in culture consistent with our earlier expansion trials (data not shown). The media used for reprogramming is completely defined with the exception of the supplement B27 which contains bovine serum albumin (BSA). However reprogramming was still achieved in the presence or absence of B27 (Figure 7B). These improvements coupled with a defined matrix enables the production of iPSCs in a completely defined process.

Figure 7. The generation of iPSCs from blood using completely defined conditions.


A. Fold expansion of CD34+ cells pooled from multiple blood donors in standard (n = 13) and completely defined conditions (n = 2) after 6 days of expansion. Fold expansion was calculated from the total number of cells at day 6 divided by the number of cells the day after purification. Percentages indicate the fraction of cells expressing CD34 in the total population as assessed by flow cytometry. B. Reprogramming trials were performed on CD34+ cells obtained by leukapheresis from donors GG and A2389 with and without the B27 supplement.


CD34+ cells possess characteristics that make them an ideal blood cell to reprogram: they are readily identified, highly receptive to reprogramming, and free of gene rearrangements characteristic of more differentiated cell types. However, their low numbers in circulating blood have made them a less desirable cell type for reprogramming because large volumes of blood were predicted to be required for the generation of iPSCs. We describe a method to generate insert-free iPSCs from CD34+ cells beginning from a single vial of blood or less. In some cases, the number of CD34+ cells that expanded exceeded that required for a single transfection after 6 days in culture making it possible to transfect after only 3 days of expansion, shorter than the amount of time Chou and colleagues used to reprogram unpurified PBMCs [22].

Proliferation contributes to reprogramming efficiency; therefore, choosing a culture medium that promotes proliferation will effectively promote reprogramming. Data presented in our manuscript supports this assertion because all four donor populations examined were almost 100% positive for CD34 expression after 3 days in culture, but they were not equally receptive to reprogramming (Figure 5A). Cells from donor 3096 demonstrated the highest fold expansion following purification as well as the highest efficiency of reprogramming. However, we go on to demonstrate that proliferation is not the only contributor to efficient reprogramming. In our experiments, the purity of the cell population diminishes over time following purification, but the cells within the culture continue to expand despite low CD34 expression. Figure 1C shows that this expanding population 10 days following purification consists primarily of early lineage progenitor cells. This result indicates that our medium has the capacity to stimulate the proliferation of non-T and non-B cells that have never been or are no longer CD34+. If proliferation were the primary force driving the efficiency of reprogramming, then it would be expected that proliferating non-T/non-B cells within our population would be equally receptive to reprogramming regardless of their time in culture. Our results are contrary to this hypothesis, however, because the efficiency of reprogramming decreases as the magnitude of CD34 expression decreases. This is observed across four independent donor cell populations and is consistent with dependence of reprogramming on CD34 expression (see Figure 5A). These results, taken together, support our hypothesis that both proliferation and cell identity contribute to the efficiency of reprogramming.

We have also outlined a protocol that begins to systematically address some of the challenges in the generation of clinical-grade iPSCs in an effort to advance their use from research lab to clinic. iPSCs must not only be manufactured consistently from a tractable tissue source but also satisfy safety requirements. The core of these requirements includes the use of completely defined culture conditions and a standardized reprogramming method that results in the removal of the potentially oncogenic transgenes employed to reprogram the cells. The starting point of the protocol is the actual patient sample, a single vial of blood. The ability to begin from frozen rather than fresh starting material allows flexibility to launch multiple reprogramming trials in parallel. We demonstrate that either CD34+ cells or PBMCs may be used as the source population for reprogramming. The iPSCs generated by this method are free of transfected DNA as well as B and T cell gene rearrangements. Several challenges remain, however, before routine production of clinical-grade iPSCs can be completely performed. First, there is considerable variation in the efficiency of reprogramming from donor to donor. Some of this variation is likely due to the inherent differences among the donors, but a careful examination of external sources of variation at each step from blood to iPSCs may well reveal areas in addition to those we have uncovered that can be better controlled. For example, we demonstrate potential in the ability to produce iPSCs using completely defined reagents to minimize variation. Second, an automated method for screening and selecting iPSCs during reprogramming would facilitate high throughput production of iPSCs. Third, a robust production protocol must also include a method for the rapid screening of iPSCs to identify those that both lack potentially harmful mutations and are readily differentiated into various cell types. In sum, the generation of iPSCs using a standardized process beginning from early progenitor cells isolated from routine blood draws minimizes this variation and is a good starting point to provide a more comparable baseline for analysis. We present the first steps towards a standardized process to make the generation of clinical-grade iPSCs a reality.

Materials and Methods

Ethics Statement

All human primary cells were generated in vitro from tissue samples from human donors with appropriate written informed consent given to the commercial providers.

All animal work was conducted according to relevant national and international guidelines under the approval of the Cellular Dynamics International Animal Care and Use Committee. As a private company, our animal facility does not provide a permit number or approval ID since mouse is not a protected species.

Processing whole blood samples

Peripheral (PB.1 and PB.2) and cord (CB.1 and CB.2) blood-derived CD34+ cells were obtained from AllCells (Emeryville, CA USA). Blood collections were performed at AllCells and Meriter Laboratories (Madison, WI USA) using standard, 8 ml Vacutainer Cell Processing Tubes (both sodium citrate and sodium heparin-based tubes are acceptable; BD Biosciences; Franklin Lakes, NJ USA). Appropriate documentation for informed consent was completed prior to blood collection (Meriter Laboratories). Vacutainers were processed within 24 hours of collection. Briefly, the PBMC-containing upper phase was collected and washed with ice-cold PBS (Invitrogen; Carlsbad, CA USA). Cells were either frozen down or used directly for purification with the CD34 MicroBead Kit (Miltenyi; Auburn, CA USA) and used according to the manufacturer’s protocol. Some samples were treated with Histopaque (Sigma Aldrich; St. Louis, MO USA) to minimize the number of red blood cells (RBCs) and centrifuged at 2000 rpm for 20 minutes without braking. The interface containing the PBMCs was removed if samples were treated with histopaque, cells washed again with chilled PBS, centrifuged at 600× g for 15 minutes and either frozen down with CryoStor10 (StemCell Technologies; Vancouver, BC Canada) or used directly for purification. CD34+ cell expansion media: StemSpan SFEM (StemCell Technologies), Flt3, SCF, TPO each at a final concentration of 300 ng/ml, IL-6 (100 ng/ml) and IL-3 (10 ng/ml) (Peprotech; Rocky Hill, NJ USA), supplemented with DNaseI (final concentration at 20 U/ml), and 1× Antibiotic-antimycotic (Invitrogen) for overnight recovery. Defined expansion media: serum-free StemSpan H3000 (StemCell Technologies), animal-free IL-6 (R&D Systems Minneapolis, MN USA), and recombinant human IL-3, TPO, Flt3, and SCF (Peprotech) at the same concentrations listed above. PBMC expansion media: StemSpan SFEM, ExCyte Medium Supplement (Millipore; Billerica, MA), Glutamax (Invitrogen), SCF (250 ng/ml), IL-3 (20 ng/ml), Erythropoietin (2 U/ml; Prospec; Rehovot, Israel), IGF-1 (40 ng/ml; Prospec), and Dexamethasone (1 µM; Fisher; Waltham, MA). PBMCs were resuspended at 1×106 cells/ml for expansion.

Flow cytometry

Cell surface staining of hematopoietic cells was performed with CD45-PE, CD34-APC, CD19-APC and CD56-PE (BD Biosciences) and CD3-PE (eBioscience; San Diego, CA USA) antibodies. iPSCs were processed directly for antibody staining for the presence of Tra-1-81 (Stemgent; Cambridge, MA USA) and SSEA-4 (BD Pharmingen; San Diego, CA USA). Propidium Iodide (Sigma Aldrich) was added for dead cell exclusion, and all stained cells were analyzed in combination with their respective isotype controls using a flow cytometer (Accuri; Ann Arbor, MI USA).

Reprogramming cells enriched for CD34-expression

The CD34 nucleofection kit and device (Lonza; Allendale, NJ USA) were used for transfections. For CD34+ cells, 3.5 µg of each plasmid in Combination Set 1 and 3 ug of each plasmid for Combination Set 2 except for the L-myc containing plasmid where 2 µg was transfected using program U-08. Cells were seeded onto RetroNectin-coated 6-well plates (Takara Bio, Inc; Otsu, Shiga Japan). Seeding density ranged from 5×104 to 1×105 cells/ml. Reprogramming media: StemSpan SFEM (StemCell Technologies) supplemented with non-essential amino acids (NEAA; Invitrogen), 0.5× Glutamax, N2B27 (Invitrogen), 0.1 mM β-mercaptoethanol (Sigma-Aldrich), 100 ng/mL zebrafish basic fibroblast growth factor (zbFGF), 0.5 µM PD0325901, 3 µM CHIR99021, 0.5 µM A-83-01 (all molecules from Stemgent), and 10 µM HA-100 (Santa Cruz; Santa Cruz CA USA). Conditions for PBMC reprogramming relied on 1×106 cells per transfection, program T-16, and DNA from Combination Set 2 at the concentrations described for CD34+ cells. Reprogramming media for PBMCs was the same with the exception of the small molecule cocktail which contained recombinant human LiF (Millipore), 3 uM CHIR99021, and 0.5 uM A-83-01. In general, cultures were fed with fresh medium every other day for 9 to 14 days then transitioned to TeSR2 (Stem Cell Technologies) without the addition of small molecules. iPSC colonies were scored with Tra-1-81 antibody (StainAlive™ DyLight™ 488 Mouse anti-Human Tra-1-81 antibody; Stemgent) or mouse-anti-Tra-1-60 IgM antibody (R&D) in combination with goat anti-mouse IgM Alexa 488 (Invitrogen), and alkaline phosphatase expression (Vector Blue Alkaline Phosphatase Substrate Kit III, Vector Laboratories; Burlingame, CA USA).

Detecting endogenous expression of pluripotency markers

Total RNA was isolated using the RNeasy Mini Plus kit (Qiagen; Valencia, CA USA) per the manufacturer’s protocol. Approximately 1 µg of total RNA was used for cDNA synthesis using the SuperScript III First-Strand Synthesis system for RT-PCR (Invitrogen). RT-PCR was performed using previously described primers and those listed in Table 6 [2]. cDNA was diluted 1:2 and 1 µl was used in reactions with GoTaq Green Master Mix (Promega; Madison, WI USA).

Table 6. Primer sequences for the detection of endogenous gene expression.

journal.pone.0027956.t006  Table 6. Primer sequences for the detection of endogenous gene expression.

Episomal and Genomic DNA isolation

Immunoglobulin heavy chain and T cell gene rearrangements


In Vitro Differentiation and Teratoma Studies


Author Contributions


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Analysis of Human and Mouse Reprogramming of Somatic Cells to Induced Pluripotent Stem Cells. What Is in the Plate?

Stéphanie Boué, Ida Paramonov,  María José Barrero,  Juan Carlos Izpisúa Belmonte
Published: September 17, 2010  http://dx.doi.org/10.1371/journal.pone.0012664

After the hope and controversy brought by embryonic stem cells two decades ago for regenerative medicine, a new turn has been taken in pluripotent cells research when, in 2006, Yamanaka’s group reported the reprogramming of fibroblasts to pluripotent cells with the transfection of only four transcription factors. Since then many researchers have managed to reprogram somatic cells from diverse origins into pluripotent cells, though the cellular and genetic consequences of reprogramming remain largely unknown. Furthermore, it is still unclear whether induced pluripotent stem cells (iPSCs) are truly functionally equivalent to embryonic stem cells (ESCs) and if they demonstrate the same differentiation potential as ESCs. There are a large number of reprogramming experiments published so far encompassing genome-wide transcriptional profiling of the cells of origin, the iPSCs and ESCs, which are used as standards of pluripotent cells and allow us to provide here an in-depth analysis of transcriptional profiles of human and mouse cells before and after reprogramming. When compared to ESCs, iPSCs, as expected, share a common pluripotency/self-renewal network. Perhaps more importantly, they also show differences in the expression of some genes. We concentrated our efforts on the study of bivalent domain-containing genes (in ESCs) which are not expressed in ESCs, as they are supposedly important for differentiation and should possess a poised status in pluripotent cells, i.e. be ready to but not yet be expressed. We studied each iPSC line separately to estimate the quality of the reprogramming and saw a correlation of the lowest number of such genes expressed in each respective iPSC line with the stringency of the pluripotency test achieved by the line. We propose that the study of expression of bivalent domain-containing genes, which are normally silenced in ESCs, gives a valuable indication of the quality of the iPSC line, and could be used to select the best iPSC lines out of a large number of lines generated in each reprogramming experiment.

Citation: Boué S, Paramonov I, Barrero MJ, Izpisúa Belmonte JC (2010) Analysis of Human and Mouse Reprogramming of Somatic Cells to Induced Pluripotent Stem Cells. What Is in the Plate? PLoS ONE 5(9): e12664.  http://dx.doi.org/10.1371/journal.pone.0012664

Figure 2. Human protein-protein interaction networks of genes with higher expression levels in ESCs and iPSCs compared to somatic cells.

journal.pone.0012664.g002  Figure 2. Human protein-protein interaction networks of genes with higher expression levels in ESCs and iPSCs compared to somatic cells.


The human protein-protein interaction networks of genes most consistently highly expressed in ESCs and iPSCs, compared to the starting cell populations, have been created from the lists of the biggest changes in expression, using String[71] with high confidence interactions (min score 0.7) and have been edited in Medusa[72]. They show a central, highly interconnected network of genes in which the most famous pluripotency transcription factors are to be found and which is likely to represent the core pluripotency network. They also highlight a number of genes whose functions relate to cell-cell communication, cell cycle, DNA repair and other metabolisms.


Figure 3. Mouse protein-protein interaction networks of genes with higher expression levels in ESCs and iPSCs compared to somatic cells.

journal.pone.0012664.g003  Figure 3. Mouse protein-protein interaction networks of genes with higher expression levels in ESCs and iPSCs compared to somatic cells.

The mouse protein-protein interaction networks of genes most consistently highly expressed in ES and iPSCs, compared to the starting cell populations, have been created from the lists of biggest changes in expression, using String[71] with high confidence interactions (min score 0.7) and have been edited in Medusa[72]. They show a central, highly interconnected network of genes in which the most famous pluripotency transcription factors are to be found and which is likely to represent the core pluripotency network. They also highlight a number of genes those functions relate to cell-cell communication, cell cycle, DNA repair and other metabolisms.



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