1. Immunology and Inflammation

Neurotrophic factor Neuritin modulates T cell electrical and metabolic state for the balance of tolerance and immunity

  1. Hong Yu  Is a corresponding author
  2. Hiroshi Nishio
  3. Joseph Barbi
  4. Marisa Mitchell-Flack
  5. Paolo DA Vignali
  6. Ying Zheng
  7. Andriana Lebid
  8. Kwang-Yu Chang
  9. Juan Fu
  10. Makenzie Higgins
  11. Ching-Tai Huang
  12. Xuehong Zhang
  13. Zhiguang Li
  14. Lee Blosser
  15. Ada Tam
  16. Charles Drake
  17. Drew Pardoll
  1. Bloomberg-Kimmel Institute for Cancer Immunotherapy, Immunology and Hematopoiesis Division, Department of Oncology, Johns Hopkins University School of Medicine, United States
  2. The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, United States
  3. Institute of Cancer Stem Cell, Cancer Center, Dalian Medical University, China
https://doi.org/10.7554/eLife.96812.3
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Cite this article
  1. Hong Yu
  2. Hiroshi Nishio
  3. Joseph Barbi
  4. Marisa Mitchell-Flack
  5. Paolo DA Vignali
  6. Ying Zheng
  7. Andriana Lebid
  8. Kwang-Yu Chang
  9. Juan Fu
  10. Makenzie Higgins
  11. Ching-Tai Huang
  12. Xuehong Zhang
  13. Zhiguang Li
  14. Lee Blosser
  15. Ada Tam
  16. Charles Drake
  17. Drew Pardoll
(2024)
Neurotrophic factor Neuritin modulates T cell electrical and metabolic state for the balance of tolerance and immunity
eLife 13:RP96812.
https://doi.org/10.7554/eLife.96812.3
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6 figures, 1 table and 1 additional file

Figures

Figure 1 with 3 supplements
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Nrn1 expression and function in anergic T cells.

(A) Experimental scheme identifying Nrn1 in anergic T cells and qRT-PCR confirmation of Nrn1 expression in HA-specific CD4 cells recovered from HA-expressing host vs WT host activated with Vac_HA virus. (B) qRT-PCR and western blot detecting Nrn1 expression in naïve CD4+CD62LhiCD44lo Tn cell, CD4 effector CD4+FOXP3-CD44hiCD73-FR- Te cells and CD4 anergic CD4+FOXP3-CD44hiCD73+FR+ Ta cells. (C) Nrn1 expression was measured by qRT-PCR and western blot among naive CD4+ T cells, CD4+FOXP3+ nTreg, and in vitro generated iTregs. (D) Nrn1 expression was detected by qRT-PCR and flow cytometry among WT naïve CD4+ cells and activated CD4+ cells on days 1, 2, and 3 after activation. Nrn1-/- CD4 cells were also stained for NRN1 3 days after activation. qPCR Data are presented as average ± SEM. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Triplicates were used. Ordinary one-way ANOVA was performed for multi-comparison. (E–J). Anergy induction in vivo. (E) Experimental outline evaluating anergy development in vivo: 2x106 Thy1.1+ Nrn1-/- or ctrl CD4 OTII T cells were co-transferred with 5x105 Thy1.2+Thy1.1- WT Treg cells into TCRα-/-mice. Cells were recovered on day 13 post-transfer. (F) Proportions and numbers of OTII cells recovered from recipient spleen; (G) IL2 secretion from OTII cells upon ex vivo stimulation with OVA peptide. (H) FOXP3+ cell proportion among Thy1.1+ Nrn1-/- or ctrl CD4 cells. (I & J) Nrn1-/- vs ctrl OTII cells recovered from the peptide-induced anergy model were subjected to bulk RNASeq analysis. GSEA comparing the expression of signature genes for anergy (I) and Treg (J) among ctrl and Nrn1-/- OTII cells. Data are presented as mean ± SEM and representative of three independent experiments (N>4 mice per group). *p<0.05, **p<0.01, ***p<0.001. Unpaired Student’s t-tests were performed.

Figure 1—source data 1

PDF file containing the Figure original western blot for Figure 1B, indicating the relevant bands and cell types.

https://cdn.elifesciences.org/articles/96812/elife-96812-fig1-data1-v1.zip
Figure 1—source data 2

Original files for western blot analysis displayed in Figure 1B.

https://cdn.elifesciences.org/articles/96812/elife-96812-fig1-data2-v1.zip
Figure 1—source data 3

PDF file containing the original western blot for Figure 1C, indicating the relevant bands and cell types.

https://cdn.elifesciences.org/articles/96812/elife-96812-fig1-data3-v1.zip
Figure 1—source data 4

Original files for western blot analysis displayed in Figure 1C.

https://cdn.elifesciences.org/articles/96812/elife-96812-fig1-data4-v1.zip
Figure 1—figure supplement 1
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Nrn1 expression in T cells from tumor environment and during early T cell activation.

(A–B) Nrn1 expression in tumor infiltrates. (A) Comparison of Nrn1 expression by qRT-PCR among Tregs and non-Treg CD44hiCD4+ cells recovered either from B16 melanoma infiltrates or from peripheral blood of FOXP3DTRgfp mice bearing subcutaneous B16 melanomas. (B) Comparison of Nrn1 expression in breast tumor-infiltrating Treg (T-Treg) and Te (T-CD4+FOXP3-) cells vs. peripheral blood Treg (P-Treg) and Te (PBMC CD4+Foxp3-) cells. Data derived from the ‘Regulatory T Cells Exhibit Distinct Features in Human Breast Cancer’ report (Plitas et al., 2016). (C) NRN1 cell surface detection on day 2 activated CD4 and CD8 cells by flow cytometry. (D) Detection of NRN1 expression in nTreg cells by qRT-PCR and cell surface Nrn1 staining.

Figure 1—figure supplement 2
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Nrn1-/- mice body weight and immune cell profile analysis compared to Nrn1+/-, and WT mice.

(A) Average body weight of 10–12 week old age and sex-matched Nrn1-/-, Nrn1+/- and WT mice. (B) Thymus and peripheral lymphoid tissue total cell count. (C–D) Immune cell frequencies in the thymus and spleen. (E) Proportion of CD4+FOXP3-CD44+FR4hi CD73hi anergic T cells among splenocytes CD4 cell population. (F) FOXP3+ cell frequency among CD4 cells in the spleen. The immune profile assessment used n>3 mice/group of Nrn1-/- and control mice. p values were calculated by one-way ANOVA. *p<0.05. **p<0.01.

Figure 1—figure supplement 3
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Compromised T cell activation in Nrn1-/- cells.

(A) Cell tracker dye violet (CTV) dilution in Nrn1-/- or ctrl CD4 cells after stimulation with plate-bound aCD3 (5 µg/ml) and soluble aCD28 (2 µg/ml); (B) Cell surface activation markers CD25, CD44, CD69, and PD1 expression day 2 after naive CD4+ cell activation. Unpaired student’s t-test, *p<0.05, **p<0.01. Data represent three independent experiments. (C) Store-operated Ca++ entry (SOCE) was examined on day 2 activated CD4+ cells labeled with Fluo-4 dye. Representative graph and mean ± SEM of SOCE induced by CD4 cell stimulation with 1 uM thapsigargin (TG) in Ca++ free HBSS (0 mM Ca++) followed by addition of 2 mM Ca++. Representative graphs of Ca++ influx from three independent experiments (****p<0.0001).

Figure 2
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Reduced proliferation and suppression function in Nrn1-/- Treg cells.

(A) Proportion of FOXP3+ cells 3 days after in vitro iTreg differentiation. (B–D) iTreg cell expansion after restimulation. (B) The number of live cells from day 1 to day 3 after iTreg cell restimulation with anti-CD3. (C) Ki67 expression among CD4+FOXP3+ cells day 3 after restimulation. (D) FOXP3+ cell proportion and number among live CD4+ cells day 3 after restimulation. Triplicates in each experiment, data represent one of four independent experiments. (E–M) Nrn1-/- or ctrl nTreg cells expansion and suppression in vivo. (E) The experimental scheme. CD45.2+ nTreg T cells from Nrn1-/- or ctrl were transferred with CD45.1+ FDG splenocytes devoid of Tregs into the Rag2-/- host. Treg cell expansion and suppression toward FDG CD45.1+ responder cells were evaluated on day 7 post cell transfer. Alternatively, B16F10 tumor cells were inoculated on day 7 after cell transfer and monitored for tumor growth. (F–J) CD45.2+ cell proportion (F), FOXP3 retention (G), and Ki67 expression among FOXP3+ cells (H) at day 7 post cell transfer. (I) CD45.1+ cell proportion and number in the spleen of Nrn1-/- or ctrl Treg hosts day 7 post cell transfer. (J–L) Treg cell suppression toward anti-tumor response. (J) Tumor growth curve and tumor size at harvest from Nrn1-/- or ctrl nTreg hosts. (K) CD45.1+ cell count in tumor draining lymph node (LN) and spleen. (L) the proportion of CD45.1+ cells among CD45+ tumor lymphocyte infiltrates (TILs). (M) IFNγ% among CD8+ T cells in TILs. n>5 mice per group. (F–I) represents three independent experiments, (J–M) represents two independent experiments. Data are presented as mean ± SEM *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Unpaired Student’s t-tests were performed.

Figure 3 with 2 supplements
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Nrn1 expression impacts Treg cell electrical and metabolic state.

(A–C). Gene sets clusters enriched in Nrn1-/- and ctrl iTreg cells. Gene sets cluster analysis via Cytoscape was performed on Gene ontology Molecular Function (GO_MF) gene sets. The results cutoff: pvalue <0.05 and FDR q-value <0.1. (A) Gene sets cluster in Nrn1-/- iTreg cells cultured under resting conditions (IL2 only; Figure 3—source data 1). (B) Gene sets clusters in Nrn1-/- and ctrl iTreg cells reactivated with anti-CD3 (Figure 3—source data 2). (C) Comparison of enriched gene sets in Nrn1-/- under resting vs. activating condition (Figure 3—source data 3). (D–F) Changes relating to cell electric state. (D) Enrichment of ‘GOMF_Neurotransmitter receptor activity involved in the regulation of postsynaptic membrane potential’ gene set and enriched gene expression heatmap. (E) Membrane potential was measured in Nrn1-/- and ctrl iTreg cells cultured in IL2 or activated with anti-CD3 in the presence of IL2. Data represent three independent experiments. (F) Enrichment of ‘GOMF_Metal ion transmembrane transporter activity’ gene set and enriched gene expression heatmap (Figure 3—figure supplement 1A). (G–K) Metabolic changes associated with Nrn1-/- iTreg. (G) Heatmap of differentially expressed amino acid (AA) transport-related genes (from ‘MF_Amino acid transmembrane transporter activity’ gene list) in Nrn1-/- and ctrl iTreg cells. (H) AAs induced MP changes in Nrn1-/- and ctrl iTreg cells. Data represent three independent experiments. (I) Measurement of pmTOR and pS6 in iTreg cells that were deprived of nutrients for 1 hr and refed with RPMI for 2 hr. (J) Hallmark gene sets significantly enriched in Nrn1-/- and ctrl iTreg. NOM p-val <0.05, FDR q-val <0.25. (K) Seahorse analysis of extracellular acidification rate (ECAR) and oxygen consumption rate (OCR) in Nrn1-/- and ctrl iTreg cells. n=6–10 technical replicates per group. Data represent three independent experiments. **p<0.01, ***p<0.001, ****p<0.0001. Unpaired student t-test for two-group comparison. Unpaired t-test (H, K), two-way ANOVA (E, I). ns, not significant.

Figure 3—source data 1

Gene sets enriched in Nrn1-/- iTreg cells cultured under the resting condition.

https://cdn.elifesciences.org/articles/96812/elife-96812-fig3-data1-v1.xlsx
Figure 3—source data 2

Gene sets enriched in Nrn1-/- iTreg cells cultured under the reactivating condition.

https://cdn.elifesciences.org/articles/96812/elife-96812-fig3-data2-v1.xlsx
Figure 3—source data 3

Comparison of gene sets enriched in Nrn1-/- iTreg cells cultured under the resting and TCR restimulation conditions.

https://cdn.elifesciences.org/articles/96812/elife-96812-fig3-data3-v1.xlsx
Figure 3—figure supplement 1
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Heatmap of differentially expressed genes and Hallmark gene set enrichment.

(A) Heatmap of differentially expressed genes in ‘GOMF_Metal ion transmembrane transporter activity’ gene set from Nrn1-/- and ctrl iTreg cells cultured under the resting condition. (B) Heatmap of differentially expressed genes in ‘GOMF_Metal ion transmembrane transporter activity’ gene set from reactivated Nrn1-/- and ctrl iTreg cells. (C) Detection of pmTOR and pS6 in Nrn1-/- and ctrl iTreg cells. Data represents three independent experiments. **p<0.01. Unpaired Student’s t-tests were performed. (D) Enrichment of Hallmark gene set in activated Nrn1-/- and ctrl iTreg cells (p<0.05, FDR q<0.25).

Figure 3—figure supplement 2
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Characterization of Nrn1-/- naïve CD4 T cells and effect of NRN1 blockade on WT iTreg cell differentiation and expansion.

(A) Resting MP in Nrn1-/- and ctrl naive CD4+ T cells. (B) AAs induced MP change in Nrn1-/- and ctrl naïve CD4+ T cells. (C) Seahorse analysis of extracellular acidification rate (ECAR) and oxygen consumption rate (OCR) in Nrn1-/- and ctrl iTreg cells. n=6–10 technical replicates per group. Data represent three independent experiments. (D–F) WT iTreg cells differentiated in the presence of Nrn1 antibody blockade. (D) MP in Nrn1-/- and WT iTreg cells differentiated in the presence or absence of anti-Nrn1 antibody. (E) Live cell number and proportion of Ki67 expressing cells after anti-CD3 restimulation among Nrn1-/- and WT iTreg cells differentiated in the presence or absence of anti-NRN1 antibody. (F) FOXP3+ cell proportion 3 days after anti-CD3 restimulation in Nrn1-/- and WT iTreg cells differentiated and restimulated in the presence or absence of anti-Nrn1 antibody. Data represent three independent experiments. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Ordinary one-way ANOVA was performed for multi-comparison.

Figure 4 with 1 supplement
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Nrn1 deficiency affects Te cell response.

(A) Comparison of cell proliferation and cytokine expression in Nrn1-/- and ctrl Te cells. Data represent one of three independent experiments. (B–E) An enhanced autoimmune response in Nrn1-/- mice in vivo. (B) Experimental scheme. Nrn1-/- mice were crossed with FDG mice and Nrn1-/-_FDG or ctrl_FDG mice were obtained. The autoimmune response was induced by injecting DT i.p. to delete endogenous Treg cells. Mice’s weight change was monitored after disease induction. (C) Relative body weight change after autoimmune response induction. (D) Mice were harvested 6 days after DT injection and assessed for ki67, cytokine TNFα, IL2, and IFNγ expression in CD4+ cells. (E) FOXP3 expression among CD4+ cells day 6 post DT treatment. n>5 mice per group. Data represent four independent experiments. (F–I) Changes relating to ion balances in Te cells. (F) Gene sets clusters from GSEA of GO_MF and GO_Biological process (GO_BP) results in Nrn1-/- and ctrl Te cells (Figure 4—source data 1). (G) Enrichment of ‘GOBP_ membrane repolarization’ gene set and enriched gene expression heatmap. (H) Membrane potential measurement in Te cells. Data represent two independent experiments. (I) Enrichment of ‘GOMF_Metal ion transmembrane transporter activity’ gene set and heatmap of differential gene expression pattern (Figure 4—figure supplement 1B). (J–N) Metabolic changes associated with Nrn1-/- Te cell. (J) Enrichment of ‘GOMF_amino acid transmembrane transporter activity’ gene set and differential gene expression heatmap. (K) AAs induced MP changes in Te cells. Data represent two independent experiments. (L) Measurement of pmTOR and pS6 in Te cells after nutrient sensing. Data represent three independent experiments. (M) Enriched Hallmark gene sets (p<0.05, FDR q<0.25). (N) Seahorse analysis of extracellular acidification rate (ECAR) and oxygen consumption rate (OCR) in Nrn1-/- and ctrl Te cells. n>6 technical replicates per group. Data represent three independent experiments. Error bars indicate ± SEM. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001, unpaired Student’s t-test was performed for two-group comparison.

Figure 4—source data 1

Gene sets enriched in Nrn1-/- and ctrl Te cells.

https://cdn.elifesciences.org/articles/96812/elife-96812-fig4-data1-v1.xlsx
Figure 4—figure supplement 1
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Heatmap of enriched genes in Te cells.

(A) Differentially expressed genes in ‘GOMF_Neurotransmitter receptor activity involved in the regulation of postsynaptic membrane potential’ gene set in Nrn1-/- and ctrl Te cells. (B) Heatmap of differentially expressed genes in ‘MF_metal ion transmembrane transporter activity’ in Nrn1-/- and ctrl Te cells. (C) Detection of pmTOR and pS6 in Nrn1-/- and ctrl iTreg cells. Data represents three independent experiments. **p<0.01, ****p<0.0001. Unpaired Student’s t-tests were performed.

Figure 5
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Nrn1 deficiency exacerbates autoimmune EAE disease.

(A) Aggravated body weight loss and protracted EAE disease in Nrn1-/- mice. (B) CD45+ cell number in the spinal cord infiltrates. (C) CD4+ cell number in the spinal cord infiltrates. (D) Mog38-49/IAb tetramer staining of spinal cord infiltrating CD4 cells. (E) FOXP3+ proportion among CD4+ cells in spinal cord infiltrates. (F) IFNγ+and IL17+ cell proportion among CD4+ cells in draining lymph nodes. n>5 mice per group. Data represent three independent experiments. The p value was calculated by 2way ANOVA for (A). The p-value was calculated by the unpaired student t-test for (B–F). *p<0.05, **p<0.01.

Author response image 1
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Membrane potential change induced by amino acids entry.

a. Nrn1-/- or WT iTreg cells loaded with MP dye and MP change was measured upon the addition of a complete set of AAs. b. Nrn1-/- or WT Th0 cells loaded with MP dye and MP change was measured upon the addition of a complete set of AAs.

Tables

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
AntibodyPurified anti-mouse CD3BiolegendCat. No. 1002025 ug/ml for stimulation
AntibodyAPC anti-mouse CD4BiolegendCat. No. 100516FACS (1:500)
AntibodyFITC anti-mouse CD4BiolegendCat. No. 100706FACS (1:500)
AntibodyPE/Cyanine7 anti-mouse CD25BiolegendCat. No. 102016FACS (1:500)
AntibodyPacific Blue anti-mouse CD45.1BiolegendCat. No. 110722FACS (1:500)
AntibodyAPC anti-mouse CD45.2 AntibodyBiolegendCat. No. 109814FACS (1:500)
AntibodyAPC/Cyanine7 anti-mouse CD62LBiolegendCat. No. 104428FACS (1:500)
AntibodyPE anti-mouse CD73 AntibodyBiolegendCat. No. 127206FACS (1:400)
AntibodyPerCP/Cyanine5.5 anti-mouse CD90.1 (Thy1.1)BiolegendCat. No. 109004FACS (1:500)
AntibodyAPC/Cyanine7 anti-mouse CD90.2 (Thy1.2)BiolegendCat. No. 105328FACS (1:500)
AntibodyPE anti-mouse TCR Vβ5.1, 5.2BiolegendCat. No. 139504FACS (1:500)
AntibodyAPC/Cyanine7 anti-mouse CD279 (PD-1)BiolegendCat. No. 135224FACS (1:500)
AntibodyAlexa Fluor 700 anti-mouse IFN-gBiolegendCat. No. 505824FACS (1:500)
AntibodyPE anti-mouse IL-17ABiolegendCat. No. 506904FACS (1:500)
AntibodyAlexa Fluor 700 anti-mouse TNF-αBiolegendCat. No. 506338FACS (1:500)
AntibodyAlexa Fluor 594 anti-T-betBiolegendCat. No. 644833FACS (1:300)
AntibodyPerCP/Cyanine5.5 anti-mouse Ki-67 ABiolegendCat. No. 652424FACS (1:500)
AntibodyPE Rat Anti-Mouse CD44BD BioscienceCat. No. 561860FACS (1:500)
AntibodyBV605 Rat Anti-Mouse CD45BD BioscienceCat; No. 563053FACS (1:500)
AntibodyPE Hamster Anti-Mouse CD69BD BioscienceCat. No: 553237FACS (1:500)
AntibodyPE FOXP3 Monoclonal Antibody (FJK-16s)ThermoFisher eBioscienceCat. No. 12-5773-82FACS (1:300)
AntibodyBiotin anti-NRN1 (1 A10)custom madeA&G PharmaceuticalFACS (1:200)
Antibodyanti-NRN1 (1D6)custom madeA&G Pharmaceutical10 ug/ml for blocking
Antibodypurified antiCD28Bio-X CellCat. No.BE0015-12 ug/ml ofr stimulation
Antibodypurified anti-mouse IL-4Bio-X CellCat. No.BE00455 ug/ml for blocking
Antibodypurified anti-mouse IFNgBio-X CellCa. No.BE00555 ug/ml for blocking
Chemical compound, drugFluo-4, AM,InvitrogenCat. No.F142012 ug/ml
Chemical compound, drugThapsigarginInvitrogenCat.No.T74581 uM
Chemical compound, drugOligomycinSigmaCat. No.O4876-5MG1 uM
Chemical compound, drug2-Deoxy-D-glucoseSigmaCat. No.D8375-1G50 mM
Chemical compound, drugFCCPSigmaCat. No.SML29592 uM
Chemical compound, drugRotenoneSigmaCat. No.557368–1 GM1 uM
Chemical compound, drugAntimycin ASigmaCat. No.A8674-25MG1 uM
Chemical compound, drugBD Difco AdjuvantsFisherCat. No.DF3114-33-8500 ug/mouse
Peptide, recombinant proteinHuman IL-2 Recombinant ProteinpeproTechCat No.200-02-50UG100 ng/ml
Peptide, recombinant proteinHuman TGF-beta 1 RecombinantpeproTechCat No. 100-21-10UG10 ng/ml
Peptide, recombinant proteinPertussis Toxin from B. pertussis,List LaboratoryCat. No.180400 ng/mouse
Peptide, recombinant proteinOVA323-339GeneScriptCat. No.RP10610100 ug/mouse
Peptide, recombinant proteinMOG35-55GeneScriptCat. No.RP10245200 ug/mouse
Strain, strain backgroundNrn1-/- mice backcrossed to C57/BL6 backgroundThe Jackson LaboratoryRRID:IMSR_JAX:018402
Strain, strain backgroundFOXP3DTRGFP, C57/BL6 backgroundThe Jackson LaboratoryRRID:IMSR_JAX:016958
Strain, strain backgroundTCRa-/-, C57/BL6The Jackson LaboratoryRRID:IMSR_JAX:002116
Strain, strain backgroundOTII, C57/BL6Jonathan Powell, parental strain: The Jackson LaboratoryRRID:IMSR_JAX:004194
Strain, strain backgroundRag2-/-, C57/BL6Pardoll Lab, parental strain:The Jackson LaboratoryRRID:IMSR_JAX:008449
Strain, strain background6.5 TCR transgenic mice, B10.D2Pardoll Lab, parental strain:von Boehmer Lab
Strain, strain backgroundC3HA transgenic mice, B10.D2Pardoll Lab
Sequence-based reagentNrn1 ForwardIDTGCGGTGCAAATAGCTTACCTG
Sequence-based reagentNrn1 ReverseIDTCGGTCTTGATGTTCGTCTTGTC
Software, AlgorithimsSTAR alignerDobin et al., 2013https://www.ncbi.nlm.nih.gov/pubmed/23104886
Software, AlgorithimsHTSeqAnders et al., 2015https://pypi.org/project/HTSeq/
Software, AlgorithimsDESeq2Love et al., 2014https://bioconductor.org/packages/devel/bioc/vignettes/DESeq2/inst/doc/DESeq2.html
Software, AlgorithimsGSEASubramanian et al., 2005https://www.gsea-msigdb.org/gsea/index.jsp
Software, AlgorithimsCytoscapeShannon et al., 2003https://cytoscape.org/
Software, AlgorithimsFlowJo 10.5.3BD Biosciencehttps://www.flowjo.com/solutions/flowjo
Software, AlgorithimsPrism 10GraphPadhttps://www.graphpad.com/

Additional files

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  1. Hong Yu
  2. Hiroshi Nishio
  3. Joseph Barbi
  4. Marisa Mitchell-Flack
  5. Paolo DA Vignali
  6. Ying Zheng
  7. Andriana Lebid
  8. Kwang-Yu Chang
  9. Juan Fu
  10. Makenzie Higgins
  11. Ching-Tai Huang
  12. Xuehong Zhang
  13. Zhiguang Li
  14. Lee Blosser
  15. Ada Tam
  16. Charles Drake
  17. Drew Pardoll
(2024)
Neurotrophic factor Neuritin modulates T cell electrical and metabolic state for the balance of tolerance and immunity
eLife 13:RP96812.
https://doi.org/10.7554/eLife.96812.3