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Research Article

Transdifferentiation of human adult peripheral blood T cells into neurons

Koji Tanabe, Cheen Euong Ang, Soham Chanda, Victor Hipolito Olmos, Daniel Haag, Douglas F. Levinson, Thomas C. Südhof, and Marius Wernig
  1. aDepartment of Pathology, Stanford University, Stanford, CA 94305;
  2. bInstitute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA 94305;
  3. cDepartment of Bioengineering, Stanford University, Stanford, CA 94305;
  4. dDepartment of Molecular and Cellular Physiology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305;
  5. eDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305

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PNAS June 19, 2018 115 (25) 6470-6475; first published June 4, 2018; https://doi.org/10.1073/pnas.1720273115
Koji Tanabe
aDepartment of Pathology, Stanford University, Stanford, CA 94305;
bInstitute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA 94305;
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Cheen Euong Ang
aDepartment of Pathology, Stanford University, Stanford, CA 94305;
bInstitute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA 94305;
cDepartment of Bioengineering, Stanford University, Stanford, CA 94305;
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Soham Chanda
aDepartment of Pathology, Stanford University, Stanford, CA 94305;
bInstitute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA 94305;
dDepartment of Molecular and Cellular Physiology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305;
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Victor Hipolito Olmos
aDepartment of Pathology, Stanford University, Stanford, CA 94305;
bInstitute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA 94305;
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Daniel Haag
aDepartment of Pathology, Stanford University, Stanford, CA 94305;
bInstitute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA 94305;
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Douglas F. Levinson
eDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305
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Thomas C. Südhof
dDepartment of Molecular and Cellular Physiology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305;
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  • For correspondence: tcs1@stanford.edu wernig@stanford.edu
Marius Wernig
aDepartment of Pathology, Stanford University, Stanford, CA 94305;
bInstitute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA 94305;
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  • For correspondence: tcs1@stanford.edu wernig@stanford.edu
  1. Contributed by Thomas C. Südhof, May 3, 2018 (sent for review November 21, 2017; reviewed by Thomas Graf and Hideyuki Okano)

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Significance

Recent advances in genomics have revealed that many polygenetic diseases are caused by complex combinations of many common variants with individually small effects. Thus, building informative disease models requires the interrogation of many patient-derived genetic backgrounds in a disease-relevant cell type. Current approaches to obtaining human neurons are not easy to scale to many patients. Here we describe a facile, one-step conversion of human adult peripheral blood T cells directly into functional neurons using episomal vectors without the need for previous in vitro expansion. This approach is more amenable than induced pluripotent stem cell-based approaches for application to larger cohorts of individuals and will enable the development of functional assays to study complex human brain diseases.

Abstract

Human cell models for disease based on induced pluripotent stem (iPS) cells have proven to be powerful new assets for investigating disease mechanisms. New insights have been obtained studying single mutations using isogenic controls generated by gene targeting. Modeling complex, multigenetic traits using patient-derived iPS cells is much more challenging due to line-to-line variability and technical limitations of scaling to dozens or more patients. Induced neuronal (iN) cells reprogrammed directly from dermal fibroblasts or urinary epithelia could be obtained from many donors, but such donor cells are heterogeneous, show interindividual variability, and must be extensively expanded, which can introduce random mutations. Moreover, derivation of dermal fibroblasts requires invasive biopsies. Here we show that human adult peripheral blood mononuclear cells, as well as defined purified T lymphocytes, can be directly converted into fully functional iN cells, demonstrating that terminally differentiated human cells can be efficiently transdifferentiated into a distantly related lineage. T cell-derived iN cells, generated by nonintegrating gene delivery, showed stereotypical neuronal morphologies and expressed multiple pan-neuronal markers, fired action potentials, and were able to form functional synapses. These cells were stable in the absence of exogenous reprogramming factors. Small molecule addition and optimized culture systems have yielded conversion efficiencies of up to 6.2%, resulting in the generation of >50,000 iN cells from 1 mL of peripheral blood in a single step without the need for initial expansion. Thus, our method allows the generation of sufficient neurons for experimental interrogation from a defined, homogeneous, and readily accessible donor cell population.

  • induced neuronal cells
  • direct conversion
  • transdifferentiation
  • disease modeling
  • iN cells

Advances in cell reprogramming and genome editing tools have provided new ways to interrogate human gene function in various human cellular contexts, such as neurons. In particular, genetic engineering of embryonic or induced pluripotent stem (iPS) cells has proven powerful for dissecting the specific consequences of disease-associated mutations in controlled genetic backgrounds (1, 2). However, these methods cannot be expected to provide fully adequate cellular models of diseases for which highly polygenic mechanisms underlie risk. For example, large-scale genome-wide association study data suggest that 30–50% of the genetic risk for each of the neuropsychiatric disorders that have been studied to date can be explained by the joint effects of thousands of common genetic variants with small individual effects, such that individual patients are likely to be carrying a unique combination of many contributory variants (3).

One way to study such complex genetic backgrounds in human neurons is by reprogramming patient cells to iPS cells (4). However, iPS cells have significant line-to-line variability in terms of differentiation capacity, presumably due to variations in their epigenetic and pluripotent state (5⇓–7). Moreover, iPS cells are often karyotypically unstable when grown in feeder-free conditions, and their growth and formation is labor-intensive and difficult to scale from a large number of individuals.

Another way to obtain neurons is by deriving induced neuronal (iN) cells from fibroblasts in a single conversion step, which in principle would greatly facilitate their derivation from many patients (8). However, unlike neonatal human fibroblasts, adult human fibroblasts have proven difficult to reprogram into synaptically competent iN cells (9⇓⇓⇓⇓–14). Moreover, fibroblasts are heterogeneous and ill-defined and must be expanded in vitro from invasive and painful skin biopsies to obtain sufficient numbers, increasing the risk of acquiring random genetic mutations during an extended culture period. Here we report that functional synapse-forming human iN cells can be induced from freshly isolated and stored adult peripheral T cells using nonintegrating episomal vectors. Previous studies have shown the conversion of blood and urinary cells into various neural progenitor cells that only inefficiently gave rise to functional neurons (15⇓⇓⇓⇓⇓–21). The described conversions were accomplished with transient expression of iPS cell reprogramming factors, an approach recently shown to induce a pluripotent intermediate state (22).

Results

Direct Induction of iN Cells from Peripheral Blood Mononuclear Cells.

To investigate whether blood cells can be transdifferentiated to iN cells, we collected fresh blood from an adult healthy individual. We then isolated peripheral blood mononuclear cells (PBMCs) using gradient centrifugation and electroporated these cells with episomal vectors encoding the four transcription factors Brn2, Ascl1, Myt1l, and Ngn2, collectively termed the BAMN pool, which was previously found to generate iN cells from human fibroblasts (9), and enhanced green fluorescent protein (EGFP) into 3 million PBMCs. Transfected cells were then cultured in IL-2 and CD3/CD28 antibodies containing media supporting T cell growth (Fig. 1A). On day 3, we placed the nonadherent, transfected blood cells on different substrates, including primary mouse glia, mouse fibroblast SNL cell line, human primary fibroblasts, Matrigel, Polyornithine, or laminin-coated dishes. BAMN-transfected cells attached well on primary mouse glia cells and human fibroblasts, but on no other substrate. Cells transfected with EGFP alone did not attach to any substrate (SI Appendix, Fig. S1 B and C). On day 5, we changed the hematopoietic medium to the neuronal medium N3. Remarkably, after seeding of the human blood cells on murine glial cells, we noticed that glial cells deteriorated quickly. We reasoned that the nontransfected, activated human T cells presumably began to attack the mouse glia. Withdrawal of IL-2 and the T cell activators after day 3 not only mitigated this problem, but also improved reprogramming by 2.7- to 3.6-fold. Switching to neuronal media on day 3 also rescued glial viability but improved reprogramming only slightly (Fig. 1C and SI Appendix, Fig. S1E).

Fig. 1.
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Fig. 1.

Generation of neuronal cells from peripheral blood cells. (A) Experimental outline of iN cell induction from PBMCs. (B) Morphological changes during iN cell induction from PBMCs. (Scale bars: 50 μm.) (C) The relative number of iN cells from T cells with or without T cell activator (anti-CD3/CD28), with or without IL-2, or a change to N3 media on day 3. n = 3 individuals. (D) Efficiency of iN cell induction of transduced cells from 35 individual donors without inhibitors at day 21. n = 1 for each donor. The number of iN cells on day 21 was divided by the number of total EGFP+ cells counted on day 1. (E and F) Relative iN cell induction (E) and efficiency of electroporation (F) from PBMCs of three individual donors that were kept at −80 °C or at 4 °C for 2 d relative to the fresh sample. *P < 0.05, paired t test. (G) Transdifferentiation efficiency of PBMCs from three individual donors kept at −80 °C or at 4 °C for 2 d relative to the fresh sample. Error bars represent SD.

To test the general applicability of our protocol, we obtained blood from a total of 35 healthy adult donors of various ages and ethnicities and both sexes. Surprisingly, the electroporation efficiencies varied significantly (SI Appendix, Fig. S1A), but nonetheless we were able to generate morphologically complex iN cells from all tested blood samples (Fig. 1D). The reprogramming efficiency varied as well, but the electroporation rate did not correlate with the reprogramming efficiency (SI Appendix, Fig. S1D). Unlike iPS cell reprogramming, reprogramming to iN cells was consistently lower in aged donors (Fig. 1D).

Because most biorepositories freeze patient samples, we next tried to induce iN cells from short- and long-term stored PBMCs at cold temperature. We isolated PBMCs from a fresh whole-blood sample, reprogrammed a fraction of the cells, and froze the remaining cells at −80 °C. Another fraction of the whole-blood sample was maintained at 4 °C for 2 d before subsequent PBMC isolation. We then reprogrammed the PBMCs isolated from the stored blood sample and the frozen PBMCs. There were no significant differences in the reprogramming efficiency and electroporation efficiency between fresh and frozen PBMCs, but the iN cell yield was substantially lower from PBMCs stored at 4 °C due to decreased transfection efficiency (Fig. 1 E–G). Thus, storage of freshly isolated cells at −80 °C did not affect reprogramming.

Combined BMP and TGF-β Pathway Inhibition and PKA Activation Improved Reprogramming Efficiency.

We next sought to further increase the induction efficiency of iN cells using small molecules. Blockade of BMP and TGF-β pathways have been shown to promote neural induction during normal development, during ES cell differentiation, and from fibroblasts (23⇓–25). Moreover, cAMP has been reported to facilitate neuronal survival and maturation (26). Therefore, we treated reprogramming blood cells with compounds regulating these three pathways from day 5 to day 21 (Fig. 2A). Indeed, the number of iN cells was significantly increased by the adenylyl cyclase activator forskolin (1.9-fold), the BMP pathway blocker dorsomorphin (3.7-fold), and the TGF-β pathway inhibitor SB431542 (4.6-fold) when analyzed on day 21 (Fig. 2B). The combination of the three inhibitors (forskolin, dorsomorphin, and SB431542; 3sm) showed an additive effect on the number of iN cells relative to the cells seeded (8.7-fold) (Fig. 2 A and B). These combined improvements yielded a reprogramming efficiency of up to 6.2%, which translates into 54,265 iN cells from 1 mL of blood (Fig. 2B).

Fig. 2.
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Fig. 2.

Small molecule treatment improves iN cell conversion efficiency and maturation. (A) Immunofluorescence analysis of iN cells with and without small molecules (3sm, three small molecules: forskolin, dorsomorphin, and SB431542; Cont, DMSO). (Scale bars: 50 µm.) (B) Fold change of improved iN cell formation on day 21 following various small molecule treatments as indicated. Do, dorsomorphin; Fo, forskolin; SB, SB431542. Data shown are average fold changes of three independent experiments using PBMCs from three different donors. The fold change over the control condition was plotted because the absolute reprogramming efficiency was variable among the three donors, but the fold change was consistent. *P < 0.05, paired t test. The error bars indicate SDs. Similar results were obtained with PBMCs from another set of three different donors. (C) Example traces of action potential firing recorded from PBMC-derived iN cells with or without 3sm at days 21 and 42 (n represents the number of cells patched that shows action potentials over the total number of cells patched). The experiment was performed with cells from three different donors, yielding similar results. (D) Sample traces (Left) and average values (mean ± SEM; Right) demonstrating the presence of voltage-gated Na+ and K+ channels in blood iN cells cocultured with glia with 3sm for 42 d. (Inset) Expanded view of the dotted boxed area. (E) Intrinsic properties of membrane potential (Vrest), capacitance (Cm), and input resistance (Rm) approach more mature values over time. (F) Maturation of blood iN cells on extended coculture with glia in 3sm from day 21 to day 42 as determined by increased action potential (AP) height and threshold. Bar graphs represent mean ± SEM. *P < 0.05; **P < 0.01. ns, not significant.

Blood iN Cells Exhibit Passive and Active Neuronal Membrane Properties.

We then tested the functional properties of blood iN cells that were generated with and without addition of the three inhibitors. Patch-clamp recordings of blood iN cells showed their ability to fire action potentials on step-current injection at 21 and 42 d after infection and expressed functional voltage-gated Na+ and K+ channels (Fig. 2 C and D). As expected, 3sm treatment and longer culture periods (day 42) yielded cells with parameters of more mature action potentials (height, threshold, faster depolarization and repolarization kinetics) and more mature intrinsic properties, such as increased capacitance and decreased input resistance, compared with control-treated cells and day 21 cells, respectively (Fig. 2 C, E, and F).

ROCK Inhibition Substantially Improves Formation of Neuronal Morphologies but Does Not Improve Functional Properties.

In an attempt to increase the reprogramming efficiencies even further, we screened six additional compounds—IWP2, DAPT, retinoic acid, SU5402, Y26732, and SP600125—targeting pathways previously implicated in neural differentiation in combination with forskolin, dorsomorphin, and SB431542. Of the single compounds tested, we found that ROCK inhibition increased both the relative number of iN cells and the morphological complexity of reprogramming cells compared with the DMSO control (Fig. 3 A–D). Other combinations of small molecules did not have additional effects (Fig. 3E). Moreover, the addition of neurotrophic factors did not substantially increase the formation of iN cells, but long-term drug treatment yielded more iN cells than transient small molecule treatment (Fig. 3F).

Fig. 3.
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Fig. 3.

ROCK inhibition improves morphological maturation, but not functional maturation. (A) Relative number of TUJ1-positive (yellow bars) or MAP2-positive (blue bars) cells with 3sm (forskolin, dorsomorphin, and SB431542) and additional small molecules from PBMCs from three individual donors on day 21, normalized to the no treatment control condition (Cont). n = 3 individuals. *P < 0.05 relative to DMSO (only with 3sm). (B) Relative average length of neurites with small molecules from PBMCs from three individual donors. The length was normalized to the no treatment control (Cont). n = 3 individuals. *P < 0.05 relative to the DMSO. (C) Example pictures of iN cells with indicated inhibitors. Green, EGFP fluorescence (Scale bars: 50 µm.). (D) iN cells generated with 3sm plus ROCK inhibitor express neuronal markers, including MAP2. (Scale bars: 50 µm.) (E) The effect of indicated small molecule combinations on reprogramming efficiency. *P <0.05, paired t test. n = 3 individuals. (F) The effect of the duration of 3sm plus ROCK inhibitor with (yellow bars) or without (blue bars) GDNF and BDNF on reprogramming efficiency. n = 3 individuals. (G) Representative traces of action potential responses of PBMC-derived iN cells under control condition (N3 only; Top) and in the presence of 3sm plus ROCK inhibitor when cocultured with glia for 21 d (Left) or 42 d (Right). (H) Graph showing the total number of neurons in four conditions: DMSO control (black line), 3sm treatment for 21 d (blue line), 3sm plus ROCK inhibitor for 21 d (red line), and 3sm plus ROCK for 14 d and 3sm for 7 d. n = 3 individuals. *P < 0.05.

Importantly, however, when we tested their functional properties, cells generated in the presence of ROCK inhibition were not able to generate mature action potentials, unlike cells grown without the ROCK inhibitor (Fig. 3G). The lack of mature action potentials suggests that ROCK inhibition simply affects cytoskeletal rearrangements but perturbs functional neuronal maturation. To assess whether transient ROCK inhibition is sufficient to increase conversion efficiency and still allow for functional maturation, we removed the ROCK inhibitor and 2 wk after 3sm plus ROCK inhibitor treatment and found no beneficial effect (Fig. 3H).

Molecular Characterization of Blood-Derived iN Cells.

To assess the transcriptional changes induced by reprogramming, we performed RNA-sequencing (RNA-seq) on the donor PBMCs as well as on EGFP+ and PSA-NCAM+ blood iN cells purified by magnetic cell sorting. A total of 6,941 genes were differentially expressed between the PBMCs and blood iN cells (Fig. 4A). The up-regulated genes were enriched for Gene Ontology terms such as nervous system development and synaptic transmission, while the down-regulated genes were enriched for cellular defense responses (Fig. 4A). Pan-neuronal markers (TAU, TUBB3, MAP2, and NCAM) were up-regulated while blood surface markers (CD8, CD45, and CD3) were silenced (Fig. 4 B and C). As expected, proproliferative genes were down-regulated and negative cell cycle regulators were induced (Fig. 4 D and E). These results suggest that blood iN cells have silenced hematopoietic transcriptional programs and have adopted a pure neuronal identity.

Fig. 4.
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Fig. 4.

Blood iN cells express genes characteristic of excitatory, postmitotic neurons. (A) Heatmap showing 6,941 genes differentially expressed between PBMC and blood iN cells. Two biological replicates per population, greater than twofold change and P < 0.05. Shown are the seven most significant (P < 0.05, Bonferroni-corrected) Gene Ontology terms among up- and down-regulated genes using PANTHER. (B) Induction of pan-neuronal markers. (C) Suppression of blood cell genes. (D) Down-regulation of cell cycle activators. (E) Induction of antiproliferative cyclin-dependent kinase inhibitors. (F) Immunofluorescence of blood iN cells showing expression of the excitatory marker vGLUT and subtype markers SATB2 and CTIP2 at 21 d after infection and cultured with 3sm on glia (Scale bars: 50 µm.). (G) Quantification of day 21 blood iN cells grown on glia in 3sm conditions by immunofluorescence for indicated markers. (H) Expression of region-specific markers by the PBMC-derived iN cells by RNA-seq. (I) Validation of the neurotransmitter-specific markers by RNA-seq. (J) Validation of the cortical subtype-specific markers by RNA-seq.

To characterize the regional and neurotransmitter identity of PBMC-derived iN cells, we performed immunofluorescence and considered the results in conjunction with the RNA-seq data. The two methods yielded very consistent results. We found that blood iN cells expressed the vesicular glutamate transporter (VGLUT) but not the vesicular GABA transporter, GAD65, or tyrosine hydroxylase, suggesting that blood iN cells are excitatory neurons similar to fibroblast iN cells and Ngn2-ES iN cells (8, 9, 27) (Fig. 4 F, G, and I). Based on the RNA-seq results, we found expression of forebrain markers and cortical layers II–V but not layers I, IV, and VI (Fig. 4 H and J). Immunofluorescence analysis demonstrated that in fact almost all blood iN cells were positive for SATB2 and CTIP2 but negative for REELIN, as suggested by the RNA results (Fig. 4 F and G). SATB2/CTIP2 double-positive cells are found in layer V of the mouse cortex (28).

The Blood-to-Neuron Conversion Does Not Involve a Proliferative Neural Progenitor State.

Several groups have reported the conversion of blood cells into proliferative neural cells using subsets of iPS cell reprogramming factors (20, 21). In contrast, our reprogramming factors are not proproliferative and our approach yields postmitotic neurons directly. Nevertheless, it may be possible that even our reprogramming process involves a proliferative intermediate progenitor. To address this question, we decided to stain the cells at different time points between days 3 and 21 during reprogramming with the neural progenitor marker Sox1 and the proliferation marker Ki67 (SI Appendix, Fig. S2). To our surprise, Ki67-positive cells decreased only after the first week of reprogramming. Nonetheless, all Ki67-positive cells were Sox1-negative, and the number of proliferative cells declined rapidly after day 7. Thus, no proper neural progenitor cells are formed as transient intermediates. The initial persistence of proliferative cells is likely due to the cytokines that we used to activate lymphocytes.

Blood iN Cells Are Stable Without Persistent Transgene Expression.

To examine whether the neuronal identity is dependent on continued transgene expression, we first examined whether the transgenes were perhaps already silenced in our original transfection protocol (Fig. 1A). We had used a bicistronic delivery of Ngn2 and Ascl1 linked by the T2A self-cleaving peptide. After cleavage, the T2A peptide sequence is predicted to be fused in frame with Ascl1 and thus can serve as a tag of the exogenous Ascl1. Immunostaining with T2A antibodies showed that as many as 40% of blood iN cells were T2A-Ascl1 negative, and FACS analysis demonstrated that approximately the same fraction of cells had silenced the EGFP transgene, which was co-electroporated together with the reprogramming factors (SI Appendix, Fig. S3 A and B). Because we used the mouse cDNAs for all four reprogramming factors to reprogram human cells, we could accurately distinguish the exogenous (mouse) factors from the endogenous (human) ASCL1, NGN2, BRN2, and MYT1L genes in our RNA-seq dataset. This analysis clearly demonstrates that the exogenous factors were effectively silenced in the EGFP−/PSA-NCAM+ iN cell population (SI Appendix, Fig. S3C). Thus, blood iN cells can adopt a stable neuronal identity without the need for continued expression of exogenous reprogramming factors.

Synaptically Competent iN Cells Can Be Derived from CD3+ T Cells.

PBMCs consist of fairly heterogenous hematopoietic cell populations. We wondered whether iN cells could be established from a more defined cell type. After characterizing freshly transfected cells, we found that our electroporation conditions greatly favor CD3+ T cells, suggesting that the vast majority of PBMC iN cells are in fact T cell-derived (SI Appendix, Fig. S4 A and B). To more specifically test whether T cells can be converted, we introduced the BAMN factors into four defined cell populations purified based on CD3 and CD4 expression. Indeed, morphologically complex iN cells were induced from CD3+/CD4− and CD3+/CD4+ cells, but not from CD3− cells (Fig. 5A). T cell iN cells showed passive and active neuronal membrane properties when cocultured with glia for 18 d and recorded on day 21 (Fig. 5 B and C and SI Appendix, Fig. S4E). Finally, we confirmed the T cell origin of PSA-NCAM FACS-purified iN cells, by demonstrating genomic VDJ rearrangements at TCR-β locus (SI Appendix, Fig. S4 C and D).

Fig. 5.
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Fig. 5.

Generation of synaptically competent iN cells from T cells. (A) Relative reprogramming efficiency of iN cells from the four indicated PBMC populations. The plotted efficiency was normalized by the electroporation efficiency and the efficiency of the CD3+/CD4− cell population was set to 1 (n = 3 individuals). (B) Recording configuration of EGFP-labeled blood iN cells cocultured with unlabeled iPS cell-derived neurons. The recording electrode (Rec) was placed onto an EGFP-positive blood iN cell (white arrowhead) surrounded by nonfluorescent human iPS cell-derived neurons (black arrowheads). (Scale bar: 50 µm.) (C) Example traces of action potential firing recorded from iN cells derived from CD3+/CD4− (red) or CD3+/CD4+ (blue) T cells. N represents the number of cells patched that show action potentials over the total number of cells patched. (D) Representative traces of AMPA receptor-mediated spontaneous network activity (Top, black) recorded from a T cell-derived iN cell, indicating successful integration into the human synaptic network. The trace in red (Bottom) represents an expanded view of the boxed area. Spontaneous PSCs recorded from a T cell-derived iN cell (Top, black) and subsequently blocked by CNQX and picrotoxin (Bottom, black). The trace in red (Middle) represents and expanded view of the boxed area. This pattern was observed in 2 of the 27 cells patched. (E) Evoked PSCs (five trials) in response to extracellular field stimulation recorded from a blood iN cell (Top), which was subsequently blocked by CNQX and picrotoxin application (Bottom).

The defining property of a neuron is its ability to make synaptic connections. Therefore, we asked whether BAMN-induced T cell iN cells would be able to form functional synapses. Local administration of GABA and AMPA on the soma and proximal dendrites of day 21 T cell iN cells recorded in voltage-clamp mode yielded prominent GABAA receptor-mediated inhibitory postsynaptic currents (PSCs) and AMPA receptor-mediated excitatory PSCs, respectively (SI Appendix, Fig. S4 G and H), demonstrating the presence of functional neurotransmitter receptors. To address whether the T cell iN cells have the capacity to form synapses and functionally integrate into existing neuronal networks, we plated EGFP-labeled iN cells at 14 d postinduction onto unlabeled human iPS cell-derived neurons. At 21 d after coculture, we performed voltage-clamp recordings from EGFP-positive cells and observed synaptic AMPA receptor-mediated spontaneous network activities, indicating their successful integration into the synaptic network (Fig. 5D). In addition, spontaneous PSCs could also be observed in these cells, as confirmed by application of the specific AMPA and GABAA receptor antagonists CNQX and picrotoxin, respectively (Fig. 5D). Finally, evoked PSCs could also be elicited by activating surrounding axons via extracellular field stimulation of the vicinity (Fig. 5E), unambiguously demonstrating that blood iN cells can receive functional synaptic inputs from other neurons.

Discussion

Our demonstration that adult human peripheral T cells can be directly converted to neurons has both conceptual and practical implications. During normal development, the only cells with the potential to change lineage identity are uncommitted stem and progenitor cells. Most reprogramming studies use heterogeneous fibroblasts as donor cells, raising the question as to whether the transdifferentiation capability is limited to undifferentiated progenitor cells (29). Our results unequivocally show that terminally differentiated cells can be transdifferentiated into another, distantly related somatic lineage.

The derivation of neurons from adult peripheral blood cells also has important practical implications. Unlike fibroblasts, whose derivation requires an invasive and painful skin punch biopsy, lymphocytes can be obtained in large numbers from a simple venipuncture, a procedure performed in almost every hospitalized patient, often on a daily basis. Moreover, blood samples are stored in biorepositories in much larger numbers than skin fibroblasts. Of relevance for blood iN cell applications using such repositories, we observed that iN cells can be obtained from fresh and frozen blood cells with similar efficiency. Therefore, our blood iN cell conversion described here enables the generation of human neurons from virtually any individual, unlike the use of fibroblasts as donor cells, which have proven difficult to obtain from certain populations, such as children and mentally ill persons. In addition, the greater accessibility allows for scalability of donor individuals, which will be instrumental in assessing how common, low-risk–conferring genetic variants contribute to cellular function in complex genetic diseases. Another advantage over fibroblasts as donor cells is that fibroblasts need to be expanded in vitro to obtain sufficient numbers, which may lead to accumulation of deleterious mutations.

From a mechanistic standpoint, it was unexpected to find that—unlike iN cell transdifferentiation from fibroblasts—the early coculture of glia was critical for transdifferentiation of blood cells. The effect of glia seems to be fundamentally different here than in fibroblast reprogramming, where glial coculture does not substantially impact conversion efficiency rather than synaptic maturation (8, 9). In contrast, the role of glial factors affected the generation of iN cells in general when transdifferentiated from blood cells. Since transfected PBMCs also attached onto a layer of fibroblasts but did not reprogram, we assume that the monolayer of glial cells provides secreted or cell contact-dependent factors to the blood cells that are essential for transdifferentiation in addition to enabling their attachment.

While this paper provides a clear proof of concept that human adult peripheral T cells can be converted to iN cells with all key biochemical and functional properties of neurons, we note that—similar to human fibroblast iN cells—these cells exhibit less mature synaptic properties compared with primary mouse or iPS cell-derived iN cells (20, 21, 30, 31), and using the current protocol, our blood iN cells are exclusively excitatory. While many cell biological processes, such as transcription, polarization, migration, and subcellular transport, can already be studied in these cells, future efforts will need to focus on improving synaptic maturation and deriving additional neuronal subtypes.

Materials and Methods

PBMCs were isolated from fresh blood donations obtained through the Stanford Blood Bank from individuals of various ethnic backgrounds (Caucasian, Japanese, Indian, South American, and African), various ages (16–78 y), and both sexes using density gradient centrifugation with Ficoll-Paque PLUS (GE Healthcare) according to the manufacturer’s instructions. PBMCs were frozen by a stem cell banker (ZENOAQ). Then 3 μg of vectors (PcxLE-Ngn2-2A-Ascl1, Brn2, and Myt1L: 0.666 µg; pCXLE-GFP: 0.5 µg; pCXWB-Ebna1: 0.5 µg) or nonreplicative vectors (pCXWB-Brn2, Ascl1, v5Myt1l, flagNgn2 and GFP: 0.5 µg) were electroporated into 3 × 106 isolated PBMCs with the Nucleofector 2b Device (Lonza) with the Amaxa Human T-Cell Nucleofector Kit, program V-024 (Lonza).

Transduced cells were cultured for 3 d in six-well plates in X-VIVO 10 medium (Lonza) supplemented with 30 U/mL IL-2 (PeproTech) and 3.4 µL/mL Dynabeads Human T-Activator CD3/CD28 (Life Technologies). At 3 d after electroporation, 0.1–1 × 106 transduced cells were seeded on primary glia culture in a well of a 12-well plate. Glia (1.5 × 105) were seeded in a well of a 12-well plate coated with Matrigel (Corning). At 2 d after seeding, the medium was replaced with DMEM/F12 (Invitrogen) including N2 supplement (Gibco), B27 supplement (Gibco), and insulin (5 µg/mL; Sigma Aldrich). The medium was changed every 7 d. The RNA-seq files are available in the National Center for Biotechnology Information’s Gene Expression Omnibus database (accession no. GSE113804). Virus generation, electrophysiology, RNA-sequencing, TCR recombination and generation of human embryonic stem cell-derived neurons are described in detail in SI Appendix.

Acknowledgments

We thank Dr. Keisuke Okita, Dr. Kazutoshi Takahashi, and members of the M.W. laboratory for important suggestions. This project was supported by National Institutes of Health Grants R01 MH092931 and U19 MH104172, the New York Stem Cell Foundation (NYSCF)–Robertson Prize, and the Stanford Schizophrenia Genetics Research Fund established by an anonymous donor. C.E.A. was supported by California Institute of Regenerative Medicine Training Grant and the Siebel Foundation. M.W. is a NYSCF–Robertson Stem Cell Investigator, a Howard Hughes Medical Institute Faculty Scholar, and a Tashia and John Morgridge Faculty Scholar. T.C.S. is a Howard Hughes Medical Institute Investigator.

Footnotes

  • ↵1K.T. and C.E.A. contributed equally to this work.

  • ↵2To whom correspondence may be addressed. Email: tcs1{at}stanford.edu or wernig{at}stanford.edu.
  • Author contributions: K.T., C.E.A., T.C.S., and M.W. designed research; K.T., C.E.A., S.C., and V.H.O. performed research; D.H. and D.F.L. contributed new reagents/analytic tools; K.T., C.E.A., S.C., T.C.S., and M.W. analyzed data; and K.T., C.E.A., T.C.S., and M.W. wrote the paper.

  • Reviewers: T.G., Center for Genomic Regulation; and H.O., Keio University School of Medicine.

  • The authors declare no conflict of interest.

  • Data deposition: The sequences reported in this paper have been deposited in the Gene Expression Omnibus (GEO) database, https://www.ncbi.nlm.nih.gov/geo (accession no. GSE113804).

  • This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1720273115/-/DCSupplemental.

Published under the PNAS license.

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Transdifferentiation of human adult peripheral blood T cells into neurons
Koji Tanabe, Cheen Euong Ang, Soham Chanda, Victor Hipolito Olmos, Daniel Haag, Douglas F. Levinson, Thomas C. Südhof, Marius Wernig
Proceedings of the National Academy of Sciences Jun 2018, 115 (25) 6470-6475; DOI: 10.1073/pnas.1720273115

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Transdifferentiation of human adult peripheral blood T cells into neurons
Koji Tanabe, Cheen Euong Ang, Soham Chanda, Victor Hipolito Olmos, Daniel Haag, Douglas F. Levinson, Thomas C. Südhof, Marius Wernig
Proceedings of the National Academy of Sciences Jun 2018, 115 (25) 6470-6475; DOI: 10.1073/pnas.1720273115
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