Research Article

Immunology and Inflammation

Functionally specialized human CD4⁺ T-cell subsets express physicochemically distinct TCRs

Center of Life Sciences, Skolkovo Institute of Science and Technology, Russian Federation
Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Russian Federation
Division of Infection and Immunity, Cardiff University School of Medicine, United Kingdom
Adaptive Immunity Group, Central European Institute of Technology, Czech Republic
Institute of Translational Medicine, Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Russian National Research Medical University, Russian Federation
Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Russian Federation
Systems Immunity Research Institute, Cardiff University School of Medicine, United Kingdom

Dec 8, 2020

https://doi.org/10.7554/eLife.57063

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Version of Record: December 30, 2020
Accepted Manuscript: December 8, 2020

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Sofya A Kasatskaya

Kristin Ladell

Evgeniy S Egorov

Kelly L Miners

Alexey N Davydov

Maria Metsger

Dmitry B Staroverov

Elena K Matveyshina

Irina A Shagina

Ilgar Z Mamedov

Mark Izraelson

Pavel V Shelyakin

Olga V Britanova

David A Price

Dmitriy M Chudakov

(2020)
Functionally specialized human CD4⁺ T-cell subsets express physicochemically distinct TCRs

eLife 9:e57063.

https://doi.org/10.7554/eLife.57063
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Figures
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Additional files

8 figures, 4 tables and 1 additional file

Figures

Figure 1 with 1 supplement

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Experimental overview.

Top: schematic representation of the general questions addressed in this study. Bottom: schematic representation of the experimental pipeline. Naive and effector/memory CD4⁺T-cell subsets were …

Figure 1—figure supplement 1

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Gating strategy for the identification of effector/memory CD4⁺T-cell subsets.

Single lymphocytes were identified in a forward scatter-area (FCS-A) *versus* forward scatter-height (FSC-H) plot. Viable CD3⁺CD14⁻CD19⁻ cells were gated in the CD4⁺ lineage, and naive cells were …

Figure 2 with 1 supplement

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Averaged physicochemical characteristics of CDR3β repertoires from effector/memory CD4⁺T-cell subsets.

(**A–F**) Averaged physicochemical characteristics were measured for the five amino acids in the middle of the CDR3β sequences obtained from each effector/memory CD4⁺T-cell subset (n = 8) from each …

Figure 2—figure supplement 1

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Averaged physicochemical characteristics of CDR3α repertoires from effector/memory CD4⁺T-cell subsets.

(**A–F**) Averaged physicochemical characteristics were measured for the five amino acids in the middle of the CDR3α sequences obtained from each effector/memory CD4⁺T-cell subset (n = 8) from each …

Figure 3

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Clonality and diversity of effector/memory CD4⁺T-cell subsets.

Observed diversity (top), the Chao1 estimator (middle), and the normalized Shannon-Wiener index (bottom) were calculated for each TCRα (left) and TCRβ repertoire (right) obtained from each …

Figure 4

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Clonotype overlap among effector/memory CD4⁺T-cell subsets.

(A) Relative overlap between nucleotide-defined CDR3β repertoires obtained from donor-matched pairs of effector/memory CD4⁺T-cell subsets. Clonotypes were matched on the basis of identical *TRBV* …

Figure 5 with 4 supplements

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Clonal relatedness among effector/memory CD4⁺T-cell subsets.

Cytoscape network analysis schemes represent the number and size (frequency) of nucleotide-defined clonotype variants shared among the top 2000 most frequent CDR3β clonotypes in each subset. Each …

Figure 5—figure supplement 1

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Clonal relatedness among the Th17, Th22, Th2a, and Th2 subsets of effector/memory CD4⁺ T-cells.

Cytoscape plots for each donor represent the number and size (frequency) of nucleotide-defined clonotype variants shared among the top 2000 most frequent CDR3β clonotypes in each subset. Details as …

Figure 5—figure supplement 2

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Clonal relatedness among the Th1, Th1-17, and Th17 subsets of effector/memory CD4⁺ T-cells.

Cytoscape plots for each donor represent the number and size (frequency) of nucleotide-defined clonotype variants shared among the top 2000 most frequent CDR3β clonotypes in each subset. Details as …

Figure 5—figure supplement 3

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Clonal relatedness among Tregs and other subsets of effector/memory CD4⁺ T-cells.

Cytoscape plots for each donor represent the number and size (frequency) of nucleotide-defined clonotype variants shared among the top 2000 most frequent CDR3β clonotypes in each subset. Only …

Figure 5—figure supplement 4

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Clonal relatedness among Tfh cells other subsets of effector/memory CD4⁺ T-cells.

Cytoscape plots for each donor represent the number and size (frequency) of nucleotide-defined clonotype variants shared among the top 2000 most frequent CDR3β clonotypes in each subset. Only …

Figure 6 with 2 supplements

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Averaged physicochemical characteristics of CDR3β repertoires from naive CD4⁺T-cell subsets.

(A) Repertoire analysis of RTEs (CD25⁻CD31⁺), mature naive T cells (mNaive; CD25⁻CD31⁻), and naive Tregs (nTreg; CD25^high) from healthy donors (n = 12). Matched letters in the key indicate twin …

Figure 6—figure supplement 1

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Averaged physicochemical characteristics of CDR3α repertoires from naive CD4⁺T-cell subsets.

Repertoire metrics are shown for RTEs (CD25⁻CD31⁺), mature naive T cells (mNaive; CD25⁻CD31⁻), and naive Tregs (nTreg; CD25^high) from healthy donors (n = 7). Matched letters in the key indicate twin …

Figure 6—figure supplement 2

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Gating strategy for the identification of naive CD4⁺T-cell subsets.

Lymphocytes were identified in a forward scatter-area (FSC-A) *versus* side scatter-area (SSC-A) plot, and single cells were identified in FSC-A *versus* forward scatter-height (FSC-H) and FSC-A *versus* …

Author response image 1

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Author response image 2

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Tables

Table 1

Gating strategy for the identification of effector/memory CD4⁺T-cell subsets.

Gates 1 and 2	Gate 3	Gate 4	Gate 5	Gate 6	Gate 7	Gate 8	Subset
Live single CD3⁺ CD14⁻ CD19⁻ lymphocytes	CD4⁺	Exclude CCR7⁺ CD45RA⁺	CD25^high CD127^low				Treg
			CD25^low CD127⁺	CXCR5⁺			Tfh
				CCR10⁺			Th22
				CXCR5⁻ CCR10⁻	CXCR3⁺ CCR6⁻	CCR4⁻	Th1
					CXCR3⁻ CCR6⁺	CCR4⁺	Th17
					CXCR3⁺ CCR6⁺	CCR4⁻	Th1-17
					CXCR3⁻ CCR6⁻	CCR4⁺ CRTh2⁻	Th2
					CXCR3⁻ CCR6⁻	CCR4⁺ CRTh2⁺	Th2a

See also Figure 1—figure supplement 1.

Table 2

Frequencies of sorted effector/memory CD4⁺T-cell subsets.

Donor	Tfh	Th1	Th1-17	Th17	Th22	Th2a	Th2	Treg
D1	5.44	1.91	1.44	3.06	2.60	1.04	4.86	3.99
D2	5.82	3.29	3.50	3.14	6.64	1.53	9.24	6.92
D3	2.05	0.19	0.31	1.31	0.81	0.26	1.93	1.84
D4	6.70	2.33	2.11	4.22	2.02	0.57	7.19	3.95
D5	4.39	1.16	1.17	3.32	2.12	0.82	3.96	3.99
Mean	4.88	1.78	1.71	3.01	2.84	0.84	5.44	4.14
SD	1.79	1.17	1.19	1.06	2.23	0.48	2.84	1.81

Shown as % of live CD3⁺CD4⁺CD14⁻CD19⁻ non-naive cells. Details in Figure 1—figure supplement 1.

Table 3

Frequencies of sorted naive CD4⁺T-cell subsets.

Donor	Th1-like CCR4⁻CXCR3⁺	Th2-like CCR4⁺CXCR3⁻	CCR4⁻ CXCR3⁻	CCR4⁺ CXCR3⁺	Treg CD25^high CD127^low
D1	1.75	5.46	44.80	0.23	0.73
D2	0.77	6.77	20.40	0.32	0.57
D3	0.15	5.67	42.60	0.19	1.70
D4	0.16	6.33	33.10	0.05	1.11

Shown as % of live CD3⁺CD4⁺CD8⁻CD14⁻CD19⁻ naive cells. Details in Figure 6—figure supplement 2.

Author response table 1

property	column used	compare to	subset	p adjusted (BH method)	p	signif	test	p adjusted (BH method)	p	signif	test
cdr3_length	zscore	.all.	Th2	5.1e-01	0.43258	ns	T-test	0.600	0.4481	ns	Wilcoxon
cdr3_length	zscore	.all.	Tfh	2.4e-01	0.14003	ns	T-test	0.370	0.2333	ns	Wilcoxon
cdr3_length	zscore	.all.	Th2a	7.4e-01	0.72099	ns	T-test	0.770	0.7726	ns	Wilcoxon
cdr3_length	zscore	.all.	Th1	4.3e-01	0.34963	ns	T-test	0.770	0.7451	ns	Wilcoxon
cdr3_length	zscore	.all.	Th1-17	9.2e-02	0.03070	*	T-test	0.250	0.0829	ns	Wilcoxon
cdr3_length	zscore	.all.	TREG	4.3e-01	0.34053	ns	T-test	0.600	0.4481	ns	Wilcoxon
cdr3_length	zscore	.all.	Th17	7.5e-01	0.75446	ns	T-test	0.670	0.5633	ns	Wilcoxon
cdr3_length	zscore	.all.	Th22	1.1e-01	0.04145	*	T-test	0.120	0.0171	*	Wilcoxon
added_nucleotides	zscore	.all.	Th2	3.1e-01	0.21194	ns	T-test	0.330	0.1935	ns	Wilcoxon
added_nucleotides	zscore	.all.	Tfh	1.4e-01	0.07180	ns	T-test	0.330	0.1699	ns	Wilcoxon
added_nucleotides	zscore	.all.	Th2a	3.7e-01	0.26285	ns	T-test	0.330	0.1935	ns	Wilcoxon
added_nucleotides	zscore	.all.	Th1	2.6e-01	0.16583	ns	T-test	0.540	0.3860	ns	Wilcoxon
added_nucleotides	zscore	.all.	Th1-17	2.2e-02	0.00365	**	T-test	0.120	0.0251	*	Wilcoxon
added_nucleotides	zscore	.all.	TREG	1.1e-01	0.04517	*	T-test	0.310	0.1485	ns	Wilcoxon
added_nucleotides	zscore	.all.	Th17	7.4e-01	0.70804	ns	T-test	0.670	0.5633	ns	Wilcoxon
added_nucleotides	zscore	.all.	Th22	7.6e-02	0.01900	*	T-test	0.073	0.0060	**	Wilcoxon
strength	zscore	.all.	Th2	1.1e-02	0.00135	**	T-test	0.160	0.0362	*	Wilcoxon
strength	zscore	.all.	Tfh	1.8e-06	7.3e-08	****	T-test	0.049	0.0021	**	Wilcoxon
strength	zscore	.all.	Th2a	4.3e-01	0.34108	ns	T-test	0.470	0.3118	ns	Wilcoxon
strength	zscore	.all.	Th1	3.9e-01	0.28682	ns	T-test	0.610	0.4700	ns	Wilcoxon
strength	zscore	.all.	Th1-17	2.6e-01	0.16136	ns	T-test	0.370	0.2333	ns	Wilcoxon
strength	zscore	.all.	TREG	1.5e-02	0.00219	**	T-test	0.310	0.1386	ns	Wilcoxon
strength	zscore	.all.	Th17	1.0e-02	0.00104	**	T-test	0.310	0.1292	ns	Wilcoxon
strength	zscore	.all.	Th22	1.0e-01	0.03680	*	T-test	0.190	0.0556	ns	Wilcoxon
surface	zscore	.all.	Th2	9.2e-02	0.03016	*	T-test	0.120	0.0251	*	Wilcoxon
surface	zscore	.all.	Tfh	2.0e-06	1.3e-07	****	T-test	0.049	0.0019	**	Wilcoxon
surface	zscore	.all.	Th2a	2.4e-01	0.14789	ns	T-test	0.330	0.1935	ns	Wilcoxon
surface	zscore	.all.	Th1	1.2e-01	0.05902	ns	T-test	0.670	0.5392	ns	Wilcoxon
surface	zscore	.all.	Th1-17	5.5e-02	0.01270	*	T-test	0.310	0.1485	ns	Wilcoxon
surface	zscore	.all.	TREG	3.1e-01	0.21607	ns	T-test	0.430	0.2785	ns	Wilcoxon
surface	zscore	.all.	Th17	1.1e-01	0.04722	*	T-test	0.330	0.1814	ns	Wilcoxon
surface	zscore	.all.	Th22	1.6e-01	0.08850	ns	T-test	0.190	0.0603	ns	Wilcoxon
volume	zscore	.all.	Th2	5.5e-02	0.01168	*	T-test	0.120	0.0208	*	Wilcoxon
volume	zscore	.all.	Tfh	4.6e-03	0.00039	***	T-test	0.120	0.0229	*	Wilcoxon
volume	zscore	.all.	Th2a	7.8e-02	0.02114	*	T-test	0.310	0.1485	ns	Wilcoxon
volume	zscore	.all.	Th1	1.4e-01	0.06982	ns	T-test	0.310	0.1120	ns	Wilcoxon
volume	zscore	.all.	Th1-17	1.2e-01	0.05435	ns	T-test	0.190	0.0603	ns	Wilcoxon
volume	zscore	.all.	TREG	5.3e-01	0.46185	ns	T-test	0.670	0.6131	ns	Wilcoxon
volume	zscore	.all.	Th17	2.3e-01	0.13201	ns	T-test	0.480	0.3294	ns	Wilcoxon
volume	zscore	.all.	Th22	3.8e-02	0.00721	**	T-test	0.120	0.0140	*	Wilcoxon
kf4	zscore	.all.	Th2	6.3e-01	0.56570	ns	T-test	0.770	0.7726	ns	Wilcoxon
kf4	zscore	.all.	Tfh	3.5e-07	7.3e-09	****	T-test	0.049	0.0031	**	Wilcoxon
kf4	zscore	.all.	Th2a	6.3e-01	0.57609	ns	T-test	0.680	0.6387	ns	Wilcoxon
kf4	zscore	.all.	Th1	5.0e-01	0.41381	ns	T-test	0.670	0.6131	ns	Wilcoxon
kf4	zscore	.all.	Th1-17	4.3e-01	0.32935	ns	T-test	0.670	0.5879	ns	Wilcoxon
kf4	zscore	.all.	TREG	9.2e-02	0.02848	*	T-test	0.170	0.0431	*	Wilcoxon
kf4	zscore	.all.	Th17	1.2e-01	0.05305	ns	T-test	0.310	0.1386	ns	Wilcoxon
kf4	zscore	.all.	Th22	7.1e-01	0.66248	ns	T-test	0.670	0.5879	ns	Wilcoxon

Additional files

Transparent reporting form: https://cdn.elifesciences.org/articles/57063/elife-57063-transrepform-v2.docx
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Figures

Experimental overview.

Gating strategy for the identification of effector/memory CD4⁺T-cell subsets.

Averaged physicochemical characteristics of CDR3β repertoires from effector/memory CD4⁺T-cell subsets.

Averaged physicochemical characteristics of CDR3α repertoires from effector/memory CD4⁺T-cell subsets.

Clonality and diversity of effector/memory CD4⁺T-cell subsets.

Clonotype overlap among effector/memory CD4⁺T-cell subsets.

Clonal relatedness among effector/memory CD4⁺T-cell subsets.

Clonal relatedness among the Th17, Th22, Th2a, and Th2 subsets of effector/memory CD4⁺ T-cells.

Clonal relatedness among the Th1, Th1-17, and Th17 subsets of effector/memory CD4⁺ T-cells.

Clonal relatedness among Tregs and other subsets of effector/memory CD4⁺ T-cells.

Clonal relatedness among Tfh cells other subsets of effector/memory CD4⁺ T-cells.

Averaged physicochemical characteristics of CDR3β repertoires from naive CD4⁺T-cell subsets.

Averaged physicochemical characteristics of CDR3α repertoires from naive CD4⁺T-cell subsets.

Gating strategy for the identification of naive CD4⁺T-cell subsets.

Tables

Gating strategy for the identification of effector/memory CD4⁺T-cell subsets.

Frequencies of sorted effector/memory CD4⁺T-cell subsets.

Frequencies of sorted naive CD4⁺T-cell subsets.

Additional files

Transparent reporting form

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Cite this article

Experimental overview.

Gating strategy for the identification of effector/memory CD4+ T-cell subsets.

Averaged physicochemical characteristics of CDR3β repertoires from effector/memory CD4+ T-cell subsets.

Averaged physicochemical characteristics of CDR3α repertoires from effector/memory CD4+ T-cell subsets.

Clonality and diversity of effector/memory CD4+ T-cell subsets.

Clonotype overlap among effector/memory CD4+ T-cell subsets.

Clonal relatedness among effector/memory CD4+ T-cell subsets.

Clonal relatedness among the Th17, Th22, Th2a, and Th2 subsets of effector/memory CD4+ T-cells.

Clonal relatedness among the Th1, Th1-17, and Th17 subsets of effector/memory CD4+ T-cells.

Clonal relatedness among Tregs and other subsets of effector/memory CD4+ T-cells.

Clonal relatedness among Tfh cells other subsets of effector/memory CD4+ T-cells.

Averaged physicochemical characteristics of CDR3β repertoires from naive CD4+ T-cell subsets.

Averaged physicochemical characteristics of CDR3α repertoires from naive CD4+ T-cell subsets.

Gating strategy for the identification of naive CD4+ T-cell subsets.

Gating strategy for the identification of effector/memory CD4+ T-cell subsets.

Frequencies of sorted effector/memory CD4+ T-cell subsets.

Frequencies of sorted naive CD4+ T-cell subsets.

Transparent reporting form

Gating strategy for the identification of effector/memory CD4⁺T-cell subsets.

Averaged physicochemical characteristics of CDR3β repertoires from effector/memory CD4⁺T-cell subsets.

Averaged physicochemical characteristics of CDR3α repertoires from effector/memory CD4⁺T-cell subsets.

Clonality and diversity of effector/memory CD4⁺T-cell subsets.

Clonotype overlap among effector/memory CD4⁺T-cell subsets.

Clonal relatedness among effector/memory CD4⁺T-cell subsets.

Clonal relatedness among the Th17, Th22, Th2a, and Th2 subsets of effector/memory CD4⁺ T-cells.

Clonal relatedness among the Th1, Th1-17, and Th17 subsets of effector/memory CD4⁺ T-cells.

Clonal relatedness among Tregs and other subsets of effector/memory CD4⁺ T-cells.

Clonal relatedness among Tfh cells other subsets of effector/memory CD4⁺ T-cells.

Averaged physicochemical characteristics of CDR3β repertoires from naive CD4⁺T-cell subsets.

Averaged physicochemical characteristics of CDR3α repertoires from naive CD4⁺T-cell subsets.

Gating strategy for the identification of naive CD4⁺T-cell subsets.

Gating strategy for the identification of effector/memory CD4⁺T-cell subsets.

Frequencies of sorted effector/memory CD4⁺T-cell subsets.

Frequencies of sorted naive CD4⁺T-cell subsets.