cd4 effector memory t cells miltenyi biotech  (Miltenyi Biotec)

Journal: bioRxiv

Article Title: Post-COVID impairment of memory T cell responses to community-acquired pathogens can be rectified by activating cellular metabolism

doi: 10.64898/2025.12.31.697156

Figure Lengend Snippet: A.) Experimental design. B.) Statistical information about variance in pre– vs. post-COVID gene signatures are contained in principal components 25-31. C.) Isolating principal components 25-31 effectively separates samples based on pre– vs. post-COVID gene signatures. D.) Differential gene expression hits in pre– vs. post-COVID CD4 memory T cells. E.) Top 25 differentially expressed genes in pre– vs. post-COVID samples. F.) Gene set enrichment analysis (GSEA) shows significantly decreased transcription factor binding genes and elevated ATP synthase, oxidoreductase, and mitochondrial respirasome pathway genes in post-COVID CD4 memory T cells. Pre-hi: pathway expression higher in pre-COVID samples. Post-hi: pathway expression higher in post-COVID samples. G.) Significantly altered gene expression pathways enriched in mitochondrial function-related cellular processes in post-COVID relative to pre-COVID CD4 memory T cells. DEGs were calculated based on p adj =0.05 using a Bonferroni correction for multiple comparisons. Log 2 MeanDiff= mean of gene expression difference, log 2. N=16 matched pre– and post-COVID samples.

Article Snippet: CD4+CD45RO+ memory T cells were isolated by negative selection using the CD4 memory T cell isolation kit from Miltenyi Biotec.

Techniques: Gene Expression, Binding Assay, Expressing

Journal: bioRxiv

Article Title: Post-COVID impairment of memory T cell responses to community-acquired pathogens can be rectified by activating cellular metabolism

doi: 10.64898/2025.12.31.697156

Figure Lengend Snippet: A.) Baseline levels of active mitochondrial mass (MTT), mitochondrial electron flux (TMRM), and mitochondrial reactive oxygen species production (SOX) in immune cell subsets are unchanged pre– and post-COVID. B.) VZV antigen-specific (AIM+) CD4 memory T cell numbers are unchanged after COVID, while AIM+ CD8 memory T cell numbers are elevated. C-D.) Bimodal phenotype of mitochondrial ROS and mitochondrial flux post-COVID in VZV antigen-specific memory T cells. A majority of study subjects produced less mitochondrial ROS and displayed lower electron flux post-COVID. E.) Levels of SA antigen-specific memory T cells are unchanged post-COVID. F-G.) Deficiency in electron flux and mitochondrial ROS production in SA antigen-specific memory T cells in a majority of subjects. H.) Unchanged percentages of IAV antigen-specific memory T cells post-COVID. I-J.) Similar to VZV and SA, bimodal phenotype of mitochondrial ROS and mitochondrial flux is evident post-COVID in IAV antigen-specific memory T cells. K.) Heatmap of mitochondrial ROS and mitochondrial flux expression across all samples. L.) Flow diagram showing that 92.8% of subjects had ROS and/or flux deficiency to at least one set of antigens. Graphs show mean ±SEM. *p<0.05, **p<0.01, ***p<0.005, ****p<0.0001 by paired Student’s t test or Wilcoxon test from n=28 individuals, matched samples. C, F, I: representative data from 1/28 individuals; dashed histogram represents FMO.

Article Snippet: CD4+CD45RO+ memory T cells were isolated by negative selection using the CD4 memory T cell isolation kit from Miltenyi Biotec.

Techniques: MTT Mitochondrial, Produced, Expressing

Journal: bioRxiv

Article Title: Post-COVID impairment of memory T cell responses to community-acquired pathogens can be rectified by activating cellular metabolism

doi: 10.64898/2025.12.31.697156

Figure Lengend Snippet: A.) Metabolic enzyme targets quantified in flow cytometry (MetFlow). Specific targets are in red boxes. B-C.) Post-COVID elevations in HK1 (glycolysis) and ACAC (fatty acid synthesis) and decreased expression of ATP5a (OXPHOS) in memory T cells after VZV antigen stimulation. D-E.) Higher HK1 expression in SA antigen-stimulated CD4 memory T cells post-COVID. F-G). Elevated HK1 expression and TKT expression (both glycolysis enzymes) in IAV-stimulated memory T cells after COVID. H-I.) Connectivity between metabolic pathways (% enzyme or activation marker positive memory T cells) is lost post-COVID in both CD4 (H) and CD8 (I) memory T cells. The loss of connectivity is more pronounced in CD4 memory T cells. Blue arcs: positive correlation; red arcs: negative correlation. J.) Eigenspectrum neural network analysis of statistical connections within CD4 and CD8 memory T cells finds a group-specific pre– vs. post-COVID signature. K.) Feature distribution map differentiates pre– vs. post-COVID memory T cell phenotypes. Blue: post-COVID; red: pre-COVID. The top 13 features explain the majority of statistical variation between pre– and post-COVID groups (overlay). Filled histograms: post-COVID; open histograms: pre-COVID. Graphs show mean ±SEM. *p<0.05, **p<0.01 by paired Student’s t test in n=24 samples. H, I: chord diagrams of Spearman correlations in % of memory T cells positive for the specified marker. J, K: data from B-I used to generate feature maps using Boltzmann Brain analysis. Feature maps show clear segregation of biomarkers differentiating pre-COVID (CD137 lo , HLA-DR hi , PD1 lo , GLUT1 hi ) from post-COVID (CD137 hi , HLA-DR lo , PD1 hi , GLUT1 lo ) T cell states.

Article Snippet: CD4+CD45RO+ memory T cells were isolated by negative selection using the CD4 memory T cell isolation kit from Miltenyi Biotec.

Techniques: Flow Cytometry, Expressing, Activation Assay, Marker

Journal: bioRxiv

Article Title: Post-COVID impairment of memory T cell responses to community-acquired pathogens can be rectified by activating cellular metabolism

doi: 10.64898/2025.12.31.697156

Figure Lengend Snippet: A.) Decreased glycolysis (GLUT1, HK1) but elevated fatty acid synthesis (ACAC) and phosphor-mTOR in SA and IAV antigen-specific memory T cells post-COVID. B.) Deficits in glycolysis and fatty acid oxidation in VZV antigen-specific CD4 memory T cells can be partly rescued by modulation of mitochondrial complex I (Met, dotted filled histogram) or complex III (Ubq, dotted open histogram). C.) Expression of CPT1A, HK1, and ATP5a in VZV-specific CD4 memory T cells is partly rescued by exposure to Met or Ubq. Data are representative of n=16 samples. D.) Eigenspectrum neural network of VZV antigen-specific CD4 T cells after discovery of a pre– vs. post-COVID (“Group”) MetFlow signature. Bar to the right represents 1D UMAP representation of data where blue dots are pre-COVID samples and red dots are post-COVID samples. Red and blue windows represent areas with the greatest feature divergence between pre– and post-COVID VZV-specific CD4 memory T cells. Feature maps in 5E were derived from information contained within these windows. E.) Left: Feature distribution map of pre– vs. post-COVID VZV-specific CD4 memory T cells showing higher glycolysis (GLUT1, HK1), lower immunosuppression (pMTOR), and higher fatty acid oxidation (CPT1A) in pre-COVID samples relative to post-COVID samples. Right: Feature distribution map of post-COVID VZV-specific T cells treated with Met or Ubq shows higher expression of glycolytic enzymes (HK1), activation markers (CD134, HLA-DR), and lower pMTOR expression compared to untreated T cells. Graphs show mean ±SEM. *p<0.05, **p<0.01 by paired Student’s t test in n=16 samples.

Article Snippet: CD4+CD45RO+ memory T cells were isolated by negative selection using the CD4 memory T cell isolation kit from Miltenyi Biotec.

Techniques: Expressing, Derivative Assay, Activation Assay

Journal: Cell Reports Medicine

Article Title: L-Phenylalanine is a metabolic checkpoint of human Th2 cells

doi: 10.1016/j.xcrm.2025.102466

Figure Lengend Snippet: Metabolomics of circulating human memory CD4 + T effector and T regulatory cells reveals distinct metabolic profiles, enriched in phenylalanine and arginine metabolic pathways (A and B) Intermediate gate depicting memory (CD45RA − ) and naive (CD45RA + ) CD3 + CD4 + T cells (A) and final sorting gate (B) of circulating memory CD4 + T effector and T regulatory cells. (C) Venn diagram representing intracellular metabolites ( n = 295) detected by untargeted mass spectrometry metabolomics and lipidomics in memory CD4 + Teff (red) and Treg (blue) cells from healthy individuals. (D) PCA model of memory CD4 + Teff and Treg cells, based on all (shared and unique) metabolites. Data were logarithmic transformed and pareto scaled (log x Par). (E) Pie charts representing biochemical composition of all (shared and unique) metabolites detected in Teff and Treg cells, ordered by abundance. (F) Metabolic pathways analysis in memory CD4 + Teff and Treg cells. Significant (−log 10 ( p value) > 1.3) and corresponding pathways ( n = 25) are shown for either Teff, Treg, or both. Over-representation analysis was performed by IMPaLA including shared and unique metabolites. Pathways related to Phe and Arg metabolism are highlighted in bold. (G) PCA model of memory CD4 + Teff and Treg cells of shared metabolites only ( n = 133). Data were log x Par. (H) Heatmap (left) and bar graph of fold changes (Log 2 FC) (right) of identified shared metabolites in memory CD4 + Teff vs. Treg cells. Data were logarithmic transformed and unit variance scaled. ∗ p < 0.05. Metabolites related to Phe and Arg metabolism are highlighted in bold. (A–H) Analysis done in n = 6 different healthy donors. (E) Metabolites are organized in main biochemical classes according to Human Metabolome Database (HMDB v.2022). Examples of metabolites are shown in major classes (>5%). See also and and , , , , , , and .

Article Snippet: Next, total CD3 + CD4 + T cells or memory CD3 + CD4 + T cells were isolated using the human CD4 + T cell Isolation Kit or Memory CD4 + T cell Isolation Kit (Miltenyi Biotec, Bergisch Gladbach, Germany), for respective cell types, according to manufacturer instructions on the autoMACS Pro Separator (Miltenyi Biotec, Bergisch Gladbach, Germany).

Techniques: Mass Spectrometry, Transformation Assay

Journal: Cell Reports Medicine

Article Title: L-Phenylalanine is a metabolic checkpoint of human Th2 cells

doi: 10.1016/j.xcrm.2025.102466

Figure Lengend Snippet: High level of L-phenylalanine enhances activation-induced glycolysis but inhibits OXPHOS, while arginine enhances activation-induced glycolysis and OXPHOS in human CD4 + T and memory CD4 + T cells (A) Representative glycolytic proton efflux rate (glycoPER) graph of Seahorse glycolytic rate assay (left); quantification of inducible and compensatory glycolysis (right) of CD4 + T cells treated in full medium (containing 1.149 mM Arg) with additional 0.1 (blue) and 1 mM (red) Arg supplementation or vehicle (gray) for 72 h with/without acute CD2, CD3, and CD28 activation. (B) Representative oxygen consumption rate (OCR) graph of Seahorse Mito Stress test (left); quantification of maximum respiratory capacity (right) of CD4 + T cells treated with Arg as in (A). (C) Representative glycoPER graph of Seahorse glycolytic rate assay (left); quantification of inducible and compensatory glycolysis (right) of CD4 + T cells treated in full medium (containing 90.9 μM of Phe) additionally supplemented Phe at concentrations of 0.1 (violet) and 1 mM (green) or vehicle (gray) for 72 h, with/without acute CD2, CD3, and CD28 activation. (D) Representative OCR graph of Seahorse Mito Stress test (left); quantification of maximum respiratory capacity (right) of CD4 + T cells treated with Phe as in (C). (E) Quantification of induced glycolysis, compensatory glycolysis, and maximum respiratory capacity of memory CD4 + T cells treated with Phe as in (C) and (D). (A–D) Data are representative of three independent experiments in three different donors or (E) in one donor. Data were analyzed by one-way ANOVA with Fisher LSD test. Bar graphs represent mean ± SEM. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, and ∗∗∗∗ p < 0.0001. Arg, L-arginine; Phe, L-phenylalanine; Rot/AA, rotenone/antimycin A; 2DG, 2-deoxyglucose; FCCP, carbonyl cyanide- p -trifluoromethoxyphenylhydrazone. All Seahorse measurements were normalized to total protein concentration.

Article Snippet: Next, total CD3 + CD4 + T cells or memory CD3 + CD4 + T cells were isolated using the human CD4 + T cell Isolation Kit or Memory CD4 + T cell Isolation Kit (Miltenyi Biotec, Bergisch Gladbach, Germany), for respective cell types, according to manufacturer instructions on the autoMACS Pro Separator (Miltenyi Biotec, Bergisch Gladbach, Germany).

Techniques: Activation Assay, Protein Concentration

Journal: Cell Reports Medicine

Article Title: L-Phenylalanine is a metabolic checkpoint of human Th2 cells

doi: 10.1016/j.xcrm.2025.102466

Figure Lengend Snippet: L-phenylalanine inhibits proliferation of human memory CD4 + T cells by induction of interleukin 4 induced gene 1 enzyme (A) Proliferation of memory CD4 + T cells incubated in full medium (containing 90.9 μM of Phe) supplemented with vehicle or 1 mM Phe and activated with CD2, CD3, and CD28 antibody-coated beads for 72 h. n = 3 different subjects. (B) Frequency of live memory CD4 + T cells in the same experiments as in (A). (C) Expression of IL4I1 mRNA in memory CD4 + T cells following similar treatment as in (A). Data from 6 independent experiments in 6 different subjects. (D) IL4I1 mRNA expression (left) and representative WB image of IL4I1 (right) in siRNA knockdown experiments in memory CD4 + T cells. Data show 3 independent experiments in 6 different subjects. One outlier was identified using Grubbs’ test with α = 0.05. One donor was included in two experiments. (E) Proliferation of control siRNA (Ctrl)- and IL4I1 siRNA-treated memory CD4 + T cells from 2 independent experiments in 5 different subjects. One donor was included in both experiments. (F) Viability of control siRNA (Ctrl)- and IL4I1 siRNA-treated memory CD4 + T cells in the same experiments as in (E). (G) Expression of IL4I1 mRNA in in vitro -differentiated human Th1, Th2, Th17, and Treg cells in siRNA knockdown experiments following similar treatment as in (D) ( n = 3 different donors). (H) Proliferation of control siRNA (Ctrl)- and IL4I1 siRNA-treated Th1, Th2, Th17, and Treg cells, incubated in full medium (containing 90.9 μM of Phe) with 1 mM additional Phe and treated with CD2, CD3, and CD28 activation antibody-coated beads for 48 h before flow cytometry ( n = 3 different donors). (A–H) Each dot represents one donor. (E and F) Bar graph shows fold change as compared to activated vehicle-treated cells. Paired t test was used in (A), (B), (C), (G), and (H); Wilcoxon test was used in (D)–(F). All data are presented as mean ± SEM. ∗ p < 0.05, ∗∗ p < 0.01, and ∗∗∗ p < 0.001. See also , , and and .

Article Snippet: Next, total CD3 + CD4 + T cells or memory CD3 + CD4 + T cells were isolated using the human CD4 + T cell Isolation Kit or Memory CD4 + T cell Isolation Kit (Miltenyi Biotec, Bergisch Gladbach, Germany), for respective cell types, according to manufacturer instructions on the autoMACS Pro Separator (Miltenyi Biotec, Bergisch Gladbach, Germany).

Techniques: Incubation, Expressing, Knockdown, Control, In Vitro, Activation Assay, Flow Cytometry

Journal: Cell Reports Medicine

Article Title: L-Phenylalanine is a metabolic checkpoint of human Th2 cells

doi: 10.1016/j.xcrm.2025.102466

Figure Lengend Snippet: L-phenylalanine inhibits Th2 cell proliferation and mTOR and STAT6 phosphorylation as well as expression of type 2 transcription factors, cytokines, activation, and pathogenicity markers (A) Phe uptake into Th2 cells. In vitro -differentiated Th2 cells from 3 different donors were incubated in indicated conditions for 6 h, and intracellular Phe was colorimetrically quantified in lysates. (B and C) Proliferation (B) and viability (C) of in vitro differentiated Th2 cells subjected to high doses of additional Phe. Bar graphs show fold changes compared to vehicle-treated, activated cells. n = 3 different donors. (D and E) IL4I1 mRNA expression (D) and representative WB image of IL4I1 protein expression (E) in in vitro -differentiated Th2 cells following incubation in increasing doses of Phe with/without concurrent activation. mRNA ( n = 6–8 different donors) and protein expression ( n = 3 different donors). (F) Volcano plot of differentially expressed genes (DEGs, raw p value < 0.05) between activated Th2 cells treated with Phe (1mM) vs. vehicle for 24 h, obtained by RNA-seq analysis ( n = 5 different donors). Genes related to STAT6/mTOR/AMPK signaling, critical for T cell activity, are highlighted in boxes. (G and H) Significantly enriched downregulated (G) and upregulated (H) GO processes in Th2 cells following treatment as in (F). STRING analysis was conducted with significantly changed DEGs (raw p value < 0.05), and relevant enriched pathways are presented. (I–M) Representative WB image (I and K) and quantification (J, L, and M) of phosphorylation of STAT6 and mTOR, respectively, in in vitro -differentiated Th2 cells ( n = 3 different donors) treated with CD2, CD3, and CD28 activation antibodies with/without additional supplementation of 1 mM of Phe for indicated time points. (N) Heatmap of mRNA expression of critical transcription factors, cytokines, and activation markers in activated in vitro -differentiated Th2 cells treated with increasing doses of Phe. mRNA expression was determined using RT-qPCR. n = 6–8 different donors. Data are analyzed using one-way ANOVA with Dunnett’s correction. Z scores were determined and plotted as heatmap with different genes mentioned as rows. Data are row normalized. (O) Frequency of activated IL4 + Th2 cells with/without additional supplementation of 1 mM of Phe ( n = 4 different donors). (P) Frequency of activated CD3 + CD4 + CCR4 + GATA3 + CD161 + Th2 cells following incubation with/without supplementation of 1 mM Phe for 24 h ( n = 3 different donors). (A–D, J, L, M, N, O, and P) Each dot represents one donor. (A–C, J, L, M, O, and P) Paired t test was used for analysis. Bars represent mean ± SEM. ∗ p < 0.05, ∗∗ p < 0.01, and ∗∗∗ p < 0.001. See also and , , and .

Article Snippet: Next, total CD3 + CD4 + T cells or memory CD3 + CD4 + T cells were isolated using the human CD4 + T cell Isolation Kit or Memory CD4 + T cell Isolation Kit (Miltenyi Biotec, Bergisch Gladbach, Germany), for respective cell types, according to manufacturer instructions on the autoMACS Pro Separator (Miltenyi Biotec, Bergisch Gladbach, Germany).

Techniques: Phospho-proteomics, Expressing, Activation Assay, In Vitro, Incubation, RNA Sequencing, Activity Assay, Quantitative RT-PCR

Journal: Cell Reports Medicine

Article Title: L-Phenylalanine is a metabolic checkpoint of human Th2 cells

doi: 10.1016/j.xcrm.2025.102466

Figure Lengend Snippet: Low intracellular L-phenylalanine levels in pathogenic memory CD4 + T effector cell populations in severe allergic patients (A–C) Representative flow cytometry dot plots of Th2a cells (A-left) and ILC1, ILC2, and ILC3 (C-left). Number of Th2a cells (A-right); memory CRTH2 + Treg cells and PD1 + Treg cells (B); and ILC1, ILC2, and ILC3 (C-right) in controls ( n = 9) and patients with mild ( n = 7) and severe ( n = 11) allergy (Cohort A). (D) Differentially expressed proteins in serum of controls ( n = 10) and mild ( n = 9) and severe ( n = 10) allergic patients (Cohort A) assessed with PEA technology and presented as NPX. (E) Heatmaps with hierarchical clustering analysis of all metabolites measured in memory CD4 + Teff ( n = 195, left) and Treg ( n = 233, right) cells in controls ( n = 6) and allergic ( n = 11) subjects. A, controls; B, mild allergy; C, severe allergy (from Cohort A). (F) Normalized abundance of Phe in Teff cells in group 1 (control, n = 1; severe allergy, n = 4) and 2 (control, n = 5; mild allergy, n = 1, severe allergy, n = 6) (from Cohort A). (G) t-distributed stochastic neighbor embedding (tSNE) plot of unbiased 2-dimensional flow cytometric analysis of memory CD4 + Teff cells (CD3 + CD4 + CD45RA − CD127 + CD25 − ) from patients with severe allergy (subset of cohort A, n = 9) identifying seven subpopulations based on CD161 and PD-1. (H) Pearson correlation of normalized abundance of intracellular Phe, in memory CD4 + Teff cells from patients with severe allergy ( n = 9), with counts of CD161 + populations within memory CD4 + Teff cells (from Cohort A). Mann-Whitney U test (A–C), one-way ANOVA with Fisher’s LSD test (D), and unpaired t test (F) were used to compare differences among groups. Graphs represent mean ± SEM. ∗ p < 0.05, ∗∗ p < 0.01, and ∗∗∗ p < 0.001. Clinical characteristics of Cohort A are shown in and . NPX, normalized protein expression; Pop, population. See also and , , , , , , , , , and .

Article Snippet: Next, total CD3 + CD4 + T cells or memory CD3 + CD4 + T cells were isolated using the human CD4 + T cell Isolation Kit or Memory CD4 + T cell Isolation Kit (Miltenyi Biotec, Bergisch Gladbach, Germany), for respective cell types, according to manufacturer instructions on the autoMACS Pro Separator (Miltenyi Biotec, Bergisch Gladbach, Germany).

Techniques: Flow Cytometry, Control, MANN-WHITNEY, Expressing

Journal: Cell Reports Medicine

Article Title: L-Phenylalanine is a metabolic checkpoint of human Th2 cells

doi: 10.1016/j.xcrm.2025.102466

Figure Lengend Snippet: Decreased expression of large amino acid transporters in Th2 cells of allergic patients correlates with elevated serum levels of L-phenylalanine (A–C) Top significantly enriched pathways (A) and upregulated (B) and downregulated (C) metabolic networks within differentially expressed genes (DEG, p < 0.05) in allergic asthma patients compared to controls (control n = 15, allergic asthma n = 37) from GEO: GSE75011 (Cohort B). Black line represents ratio of genes in experiment over complete pathway set. (D) Phe metabolism and transport pathway heatmap showing fold change (Log 2 FC) of DEGs in allergic asthma patients ( n = 37) compared to controls ( n = 15) from GEO: GSE75011 (Cohort B). ∗ p < 0.05. Pathway curated and adapted from GSEA and MSigDB Database . (E) Phe metabolism and transport schematic highlighting DEGs in Th2 cells of allergic asthma and controls (GEO: GSE75011 ) (Cohort B). Significantly upregulated (red) and downregulated (blue) genes; detected but not significantly different (black); not detected in original dataset (black and underlined). Adapted from KEGG pathway. (F) Serum Phe concentration in controls ( n = 8) and mild ( n = 30) and severe ( n = 37) allergic patients (Cohort D) quantified by targeted metabolomics. Kruskal-Wallis test was used for analysis. (G) SLC7A5 (LAT1), SLC7A8 (LAT2), and SLC3A2 (CD98; LAT3) mRNA expression in in vitro -differentiated Th2 cells treated with additional Phe with/without CD2, CD3, and CD28 activation for 24 h. Following incubation, mRNA expression was determined using RT-qPCR ( n = 6–8 different donors). (H and I) Representative WB image of LAT1 expression (H) and LAT1 protein quantification in 8 different donors (I) in in vitro -differentiated Th2 cells treated with additional Phe with/without CD2, CD3, and CD28 activation for 24 h. Expression of LAT1 presented as relative ratio normalized to β-actin. (J) Phe uptake into in vitro -differentiated Th2 cells was quantified colorimetrically. Cells were incubated in full medium with/without SLC7A5 inhibitor (KYT0353) and activation of CD2, CD3, and CD28 for 6 h. Data were analyzed using paired t test ( n = 3 different donors). (K) Spearman correlation of serum Phe concentration and relative LAT1 expression in CD4 + T cells in allergic asthma patients (left) and controls (right) (Cohort E). (G–I) Data are analyzed by one-way ANOVA with Dunnett’s correction. (F–J) Bars represent mean ± SEM. Each dot represents one donor. ∗ p < 0.05, ∗∗ p < 0.01, and ∗∗∗ p < 0.001. See also and and , , , , , , , , and .

Article Snippet: Next, total CD3 + CD4 + T cells or memory CD3 + CD4 + T cells were isolated using the human CD4 + T cell Isolation Kit or Memory CD4 + T cell Isolation Kit (Miltenyi Biotec, Bergisch Gladbach, Germany), for respective cell types, according to manufacturer instructions on the autoMACS Pro Separator (Miltenyi Biotec, Bergisch Gladbach, Germany).

Techniques: Expressing, Control, Concentration Assay, In Vitro, Activation Assay, Incubation, Quantitative RT-PCR

Journal: The Journal of Experimental Medicine

Article Title: Human CD4 + T cells recognize Mycobacterium tuberculosis –infected macrophages amid broader responses

doi: 10.1084/jem.20250460

Figure Lengend Snippet: Subset of memory CD4 + T cells lack recognition for Mtb-infected macrophages. (A) Schematic of experimental workflow to coculture infected macrophages with autologous memory CD4 + T cells for flow cytometry or sorting. Created in BioRender. Carpenter, S. (2025) https://BioRender.com/v53j172 . (B and C) Flow cytometry plots from a representative experiment comparing activation marker co-expression of CD69 with CD40L (top row) or IFNγ (bottom row), (B) gated on CD45RA Lo CD4 + T cells after 16–18 h coculture with Mtb-infected macrophages ± treatment with MTB300 or lysate, and (C) in the presence of α-MHC-II blocking antibodies. Data are representative of 10 (CD69 vs. CD40L) and 6 (CD69 vs. IFNγ) experiments and participants. (D and E) Summary bar graphs compare (D) median (and IQR) co-expression of CD69 and CD40L, and (E) the difference in activation when MTB300 is added to infected macrophages (10 LTBI and 7 non-LTBI participants). (F and G) Summary bar graphs compare (F) median (and IQR) CD69 and IFNγ co-expression, and (G) change in activation when MTB300 is added (6 LTBI and 6 non-LTBI participants). Each symbol represents the mean of one to three replicates from independent experiments. Statistical significance was determined by the Wilcoxon matched-pairs signed rank test.

Article Snippet: Immunomagnetic selection was performed per the manufacturer’s instructions using the human memory CD4 T cell isolation kit (Miltenyi Biotec) for negative selection of memory (CD45RA Lo ) CD4 + T cells. autoMACS Rinsing solution with 5% MACS BSA Stock Solution (Miltenyi Biotec) was used to wash cells, hereafter termed “Rinse Buffer.” After selection, CD4 + T cells were then added at ∼4:1 ratio to the infected macrophages in 24-well plates.

Techniques: Infection, Flow Cytometry, Activation Assay, Marker, Expressing, Blocking Assay

Journal: The Journal of Experimental Medicine

Article Title: Human CD4 + T cells recognize Mycobacterium tuberculosis –infected macrophages amid broader responses

doi: 10.1084/jem.20250460

Figure Lengend Snippet: CD69 and CD25 co-expression reveals a subset of memory CD4 + T cells that lack recognition of Mtb-infected macrophages. Related to and . (A and B) (A) Flow cytometry plots comparing the co-expression of CD69 and CD25, gated on CD45RA Lo CD4 + T cells after 16–18 h coculture with Mtb-infected (MOI 4–5) macrophages either alone or with addition of exogenous antigens (MTB300 or lysate) and (B) with and without α-MHC-II blocking antibodies. Plots are concatenated from three replicates from one experiment; data are representative of 10 independent experiments each with two to three replicates per condition. (C and D) (C) Summary bar graphs compare mean (± SEM) co-expression of CD69 and CD25 (10 participants), and (D) the difference in activation when MTB300 is added to Mtb-infected macrophages for samples from 10 LTBI and 6 non-LTBI participants. (E) Representative flow plots showing the gating of memory CD4 + T cells activated in response to Mtb-infected macrophages (or controls). After gating on lymphocytes (SSC Area [SSC-A] vs. FSC Area [FSC-A]) and single cells (FSC Height (FSC-H] vs. FSC-A), live CD4 + 7-AAD Lo T cells were identified. Co-expression of CD69 and either CD25 or CD40L was used to identify activated T cells for sorting.

Article Snippet: Immunomagnetic selection was performed per the manufacturer’s instructions using the human memory CD4 T cell isolation kit (Miltenyi Biotec) for negative selection of memory (CD45RA Lo ) CD4 + T cells. autoMACS Rinsing solution with 5% MACS BSA Stock Solution (Miltenyi Biotec) was used to wash cells, hereafter termed “Rinse Buffer.” After selection, CD4 + T cells were then added at ∼4:1 ratio to the infected macrophages in 24-well plates.

Techniques: Expressing, Infection, Flow Cytometry, Blocking Assay, Activation Assay