D-Lactate drives cytotoxicity in Th1 cells by limiting mitochondrial ROS production through enhanced glyoxalase system activity

D-Lactate drives cytotoxicity in Th1 cells by limiting mitochondrial ROS production through enhanced glyoxalase system activity | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results D-Lactate drives cytotoxicity in Th1 cells by limiting mitochondrial ROS production through enhanced glyoxalase system activity View ORCID Profile Adrián Madrigal-Avilés , View ORCID Profile Valerie Plajer , View ORCID Profile Sebastian Serve , View ORCID Profile Maria Dzamukova , View ORCID Profile Leticia Soriano-Baguet , View ORCID Profile Dirk Brenner , View ORCID Profile Mir-Farzin Mashreghi , View ORCID Profile Max Löhning doi: https://doi.org/10.1101/2025.04.03.647060 Adrián Madrigal-Avilés 1 Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Rheumatology and Clinical Immunology, Experimental Immunology and Osteoarthritis Research , Berlin, Germany 2 German Rheumatology Research Center (DRFZ), a Leibniz Institute, Pitzer Laboratory of Osteoarthritis Research , Berlin, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Adrián Madrigal-Avilés Valerie Plajer 1 Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Rheumatology and Clinical Immunology, Experimental Immunology and Osteoarthritis Research , Berlin, Germany 2 German Rheumatology Research Center (DRFZ), a Leibniz Institute, Pitzer Laboratory of Osteoarthritis Research , Berlin, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Valerie Plajer Sebastian Serve 1 Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Rheumatology and Clinical Immunology, Experimental Immunology and Osteoarthritis Research , Berlin, Germany 2 German Rheumatology Research Center (DRFZ), a Leibniz Institute, Pitzer Laboratory of Osteoarthritis Research , Berlin, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Sebastian Serve Maria Dzamukova 1 Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Rheumatology and Clinical Immunology, Experimental Immunology and Osteoarthritis Research , Berlin, Germany 2 German Rheumatology Research Center (DRFZ), a Leibniz Institute, Pitzer Laboratory of Osteoarthritis Research , Berlin, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Maria Dzamukova Leticia Soriano-Baguet 3 Luxembourg Institute of Health (LIH), Department of Infection and Immunity, Experimental and Molecular Immunology , Luxembourg, Luxembourg Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Leticia Soriano-Baguet Dirk Brenner 3 Luxembourg Institute of Health (LIH), Department of Infection and Immunity, Experimental and Molecular Immunology , Luxembourg, Luxembourg 4 Immunology & Genetics, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg , Esch-sur-Alzette, Luxembourg 5 Odense Research Center for Anaphylaxis (ORCA), Department of Dermatology and Allergy Center, Odense University Hospital, University of Southern Denmark , Odense, Denmark Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Dirk Brenner Mir-Farzin Mashreghi 6 German Rheumatology Research Center (DRFZ), a Leibniz Institute, Therapeutic Gene Regulation , Berlin, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Mir-Farzin Mashreghi Max Löhning 1 Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Rheumatology and Clinical Immunology, Experimental Immunology and Osteoarthritis Research , Berlin, Germany 2 German Rheumatology Research Center (DRFZ), a Leibniz Institute, Pitzer Laboratory of Osteoarthritis Research , Berlin, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Max Löhning For correspondence: max.loehning{at}charite.de loehning{at}drfz.de Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract L-lactate, long considered a byproduct of the glycolytic shift in activated CD4 + T cells, has been shown to impact T-cell differentiation and cytokine production. However, D-lactate’s role in immunity remains poorly understood. Here we compared the effects of D- and L-lactate supplementation on T-helper-1 (Th1) cells. D- but not L-lactate increased the production of Th1 effector cytokines such as IFN-γ and TNF-α, and enhanced the cytotoxic activity of Th1 cells. This increase was independent of STAT1, STAT4 or T-bet and also of the metabolic and H3 acetylation changes driven by both lactates. Distinct phenotypes induced by either lactate arose from the differential regulation of mitochondrial reactive oxygen species (ROS) production. D- but not L-lactate limited mitochondrial ROS via enhanced activity of the glyoxalase system. Additionally, selective upregulation of mTORC1 and ERK1/2 signaling in D-lactate– treated cells contributed to the production of cytotoxic molecules, while IFN-γ upregulation was rather mediated by a protection from Blimp-1 transcriptional repression through D-lactate. This study highlights the potential of D-lactate in enhancing Th1 differentiation and effector functions, especially under suboptimal conditions such as glucose deprivation. Introduction Upon activation, naïve CD4 + T cells can differentiate into various subsets depending on the cytokine environment. Infections caused by viruses, extracellular bacteria, or the appearance of carcinogenic cells induce Th1 differentiation. The release of interferon-γ (IFN-γ) and interleukin-12 (IL-12) triggers signal transducer and activation of transcription 1 (STAT1) and STAT4 signaling, respectively. Activation of these transcription factors upregulates T-bet, the master-regulator transcription factor of the Th1 differentiation program, leading to the secretion of proinflammatory cytokines such as IFN-γ and tumor necrosis factor-α (TNF-α). Furthermore, in type 1 immune responses, a fraction of the Th1 cells can further differentiate into CD4 + cytotoxic T lymphocytes (CTLs), characterized by the ability to kill target cells by releasing cytotoxic molecules such as granzyme B (GZMB) and perforin-1 (Perf-1) 1 , 2 . Apart from the influence of the cytokine milieu and transcription factors on Th differentiation, also different metabolic adaptations have been shown to govern specific Th differentiation programs. After thymic selection, naïve T cells remain in a quiescent state, maintained by basal mitochondrial oxidative phosphorylation (OXPHOS) activity. This OXPHOS activity results from the combined function of the tricarboxylic acid (TCA) cycle, which supplies reducing equivalents and the electron transport chain (ETC), which produces ATP. The TCA cycle generates metabolic intermediates that the ETC uses as electron donors. The transport of electrons through the ETC, coupled with the pumping of protons, generates the mitochondrial membrane potential (MMP) required for energy production. Abnormal electron transport results in the generation of O - (superoxide), a highly reactive mitochondrial reactive oxygen species (mitoROS) 3 , 4 . Inactivation of superoxide begins with its conversion into H 2 O 2 , which passively diffuses through biological membranes, impacting signaling pathways and activity of transcription factors 5 . Detoxification of mitoROS requires the enzymatic activities of proteins, some of which consume antioxidant molecules like glutathione (GSH). Reactive oxygen species (ROS) have a significant impact on the ability of CD4 + T cells to produce cytokines; their accumulation favors IL-4 production in Th2 cells 6 , 7 , while negatively affecting IFN-γ and IL-10 production in Th1 and regulatory T (Treg) cells 7 , 8 ,respectively. For other subsets such as Th17 cells, ROS feature a more complex regulation, promoting the nuclear recruitment of the master-regulator transcription factor RORγt 6 while limiting translation of IL-22 9 . Currently, very little is known about the metabolic cues promoting CD4 + CTL formation. Upon antigen recognition, T cells increase their metabolic rates and shift their endogenous metabolism toward aerobic glycolysis to support rapid cellular division 10 . The metabolic switch is mediated by the mammalian target of rapamycin complex 1 (mTORC1), which upregulates the transcription of glycolytic genes and initiates protein synthesis by regulating the activities of HIF-1α and S6, respectively 11 , 12 . Consequently, pyruvate is preferentially converted into lactate in the cytoplasm rather than being fully oxidized through OXPHOS in the mitochondria. In nature, lactate can be found in two different enantiomeric forms, D- and L-lactate, differing only in the rotation angle of their asymmetric carbon 13 . Lactate dehydrogenases (LDH) are stereospecific enzymes metabolizing lactate. Cytoplasmic L-LDH (LDHA and LDHB) can interconvert L-lactate into pyruvate, whereas D-LDH (LDHD), located in mitochondria, irreversibly metabolizes D-lactate into pyruvate in the mitochondria 14 , 15 . In higher organisms, the predominant form of lactate is the L-lactate enantiomer, which is the end-product of glycolysis. Increased glycolytic rates produce higher levels of methylglyoxal (MG) as a byproduct 16 , 17 . The accumulation of this dicarbonyl compound is highly deleterious to cells since it binds and alters DNA, proteins and phospholipids 18 . The glyoxalase system, composed by Glo1 and Glo2, detoxifies MG into D-lactate using GSH as a cofactor. In immune cells, MG dampens lymphocyte activation and cytokine production 19 , 20 . Extracellular D-lactate can originate from the incomplete fermentation of glucose by commensal gut bacteria, contributing locally to increased levels of both D- and L-lactate 21 . Far from being a waste-product, lactate plays a pivotal role in chromatin remodeling, influencing gene expression 22 . L-lactate catabolism into pyruvate increases acetyl-CoA pools, which can serve as substrate for histone acetylation and cytokine expression 23 . However, excessive L-lactate accumulation impairs Th1 differentiation and IFN-γ production 24 . Both lactate enantiomers possess intrinsic histone deacetylase (HDAC) inhibitory activity, which preserves histone acetylation 22 . Lastly, the accumulation of intracellular lactate levels can result in non-enzymatic lactylation of histones and glycolytic proteins, a recently described post-translational modification capable of inducing gene transcription and regulating metabolism 24 , 25 . While several studies have addressed the role of L-lactate in CD4 + T cell biology 6 , 23 , 26 , only very few data have been collected regarding the effect of D-lactate in immunity 27 , 28 . In this study, we compared the effects of D- and L-lactate supplementation on processes governing Th1 differentiation. We found a previously unknown role of lactate in the upregulation of killing activity and cytotoxic markers. The induction of cytotoxicity partially relied on D-lactate’s upregulation of mTORC1 and extracellular regulated kinase 1/2 (ERK1/2) signaling pathways. Although lactate supplementation impacted metabolic rates, its ability to modulate cytokine expression rather depended on the levels of mitochondrial ROS generated during restimulation. Results D-lactate increases IFN-γ production independently of STAT1, STAT4, T-bet or epigenetic regulation In our study, we investigated the impact of lactate supplementation on the functionality and differentiation of Th1 cells. We utilized sorted mouse naïve CD4 + T cells (CD4 + CD25 - CXCR3 - CD62L + CD44 - ). These cells were cultured in vitro for 5 days under Th1 polarizing conditions. Some samples received an additional supplement of either Na-D-lactate or Na-L-lactate (referred to as D- and L-lactate), respectively. Addition of D-lactate to Th1 cells resulted in increased frequencies and mean fluorescence intensity (MFI) of IFN-γ and TNF-α producers, while L-lactate supplementation reduced the production of both proinflammatory cytokines ( Figure 1A,B ). T-bet orchestrates the Th1 differentiation program and promotes IFN-γ transcription 29 . Supplementation of L-lactate reduced T-bet expression in Th1 cells, consistent with previous findings 26 . Surprisingly, we also observed decreased T-bet expression upon D-lactate supplementation, making D-lactate’s boosting effect on IFN-γ production more remarkable ( Figure 1C ). Download figure Open in new tab Figure 1. D-lactate increases IFN-γ production independently of STAT1, STAT4, T-bet or epigenetic regulation. (A-E) Naïve CD4 + T cells (CD4 + CD25 - CXCR3 - CD62L + CD44 - ) were sorted from WT, STAT1-, STAT4- or T-bet-deficient mice and cultured under Th1-polarizing conditions with or without lactate supplementation as indicated. Most of the analysis was carried out on day 5 (A-C, and E), except for (D) which was performed on day 7. (A) Representative contour plots of IFN-γ (n=51) and TNF-α (n=45). (B) Quantification of (A), frequencies and MFI. (C) Representative histograms (left) and quantification (right) of intracellular T-bet expression (n=48). (D) Representative histograms (left) and quantification (right) of IFN-γ (n=6). (E) ATAC-seq analysis of the Ifng l ocus. Bands highlighted in yellow indicate the main CNS regions regulating Ifng transcription, and the purple band marks the TSS (n=2). Data are presented as mean ± SD. Each dot represents a biological replicate of normalized pooled data from either 15 or 17 (B), 16 (C) or 2 (D and E) independent experiments. Statistical significance was determined using either Kruskal-Wallis (B and C) or Two-way ANOVA with Bonferroni’s post-tests (D). *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001. In addition to T-bet, transcriptional programs triggered by STAT1 and STAT4 signaling, cooperatively induce Th1 differentiation and IFN-γ production 30 , 31 . While deficiency in Stat1 , Stat4 or Tbx21 dampened IFN-γ production levels, it did not abrogate D-Lactate’s ability to upregulate IFN-γ production, indicating an alternative mechanism for this upregulation than through classically Th1 associated transcription factors ( Figure 1D ). To investigate whether variations in chromatin accessibility contribute to the regulation of IFN-γ production upon lactate supplementation, we performed ATAC-seq analysis across all experimental conditions. Additionally, to assess the kinetics of potential chromatin rearrangements, we briefly pulsed control Th1 cells with either D- or L-lactate during the entire course of the restimulation process (4 hours). Our analysis revealed no significant differences between the control and lactate-treated conditions, either at the transcriptional start site (TSS) or within the conserved non-coding sequences (CNS) known to regulate Ifng transcription 32 ( Figure 1E ). These findings collectively indicate that while the activities of STAT1, STAT4, and T-bet contribute to IFN-γ expression, the boosting effect of D-lactate is mediated through a different mechanism. Furthermore, the observed changes in IFN-γ production levels are likely independent of changes in chromatin accessibility levels. Lactate supplementation drives differentiating Th1 cells towards CD4 + CTLs To further characterize the phenotypical differences exerted by either lactate, RNA-Seq analysis was performed on Th1 cells at day 5, shortly restimulated with plate bound anti-CD3 and anti-CD28 for 4h. Overrepresentation analysis identified GO: 031341 (regulation of cell killing) as one of the most differentially regulated gene sets ( Figure 2A ). Previous studies have shown that during the course of viral infections, CD4 + CTLs arise from terminally differentiated Th1 cells 32 . Hence, we further differentiated the Th1 cells by submitting them to an additional stimulation round under Th1 skewing conditions, moving the day of analysis to day 10. We assessed Eomes expression, as it plays a role in conferring CD8 + T cells the ability to produce GZMB and Perf-1 while additionally contributing to the generation of CD4 + CTLs 33 – 35 . Indeed, D-lactate treatment significantly increased both frequencies of Eomes + cells and their MFI compared to control counterparts, while L-lactate supplementation only mildly upregulated Eomes MFI. T-bet expression levels remained downregulated in response to lactate at this timepoint ( Figure 2B,C ). Additionally, both lactates significantly increased frequencies of GZMB + and Perf-1 + cells, with D-lactate showing a more pronounced effect in the upregulation of both cytolytic molecules ( Figure 2D,E ). We then investigated whether lactate supplementation could enhance MHCII-TCR-dependent cytotoxic activity in Th1 cells using TCR-transgenic SMARTA CD4 + T cells with TCR specificity for the LCMV glycoprotein (GP) 61-80 antigen 36 . In vitro killing assays showed that supplementation with either lactate during Th1 differentiation increased the cytotoxicity of Th1 cells already on day 5 of culture. Notably, D-lactate-treated samples exhibited the highest cytotoxic rates at all effector : target ratios tested ( Figure 2F,G ). Download figure Open in new tab Figure 2. Lactate enhances cytotoxicity of CD4 + T cells without compromising their CD4 cellular identity. (A-E and H,I) Sorted naïve mouse WT CD4 + T cells were cultured for 10 days under Th1-polarizing conditions with or without lactate supplementation as indicated. (A) Heatmap of the differentially expressed genes (DEG) included in GO-031341: regulation of cell killing (n=2). (B) Representative dot plots of intracellular Eomes and T-bet levels, MFIs for T-bet and Eomes are written in bold black and purple, respectively. (C) Quantification of (B) (n=12). (D) Representative contour plots of GZMB and Perf-1 expression. (E) Quantification of (D) (n=15). (F,G) Sorted naïve SMARTA + CD4 + T cells were polarized under Th1 conditions with or without lactate supplementation for 5 days. On day 5, Th1 cells were mixed at different ratios with B cells previously loaded with GP61 peptide or PBS. After 6 hours of incubation, specific cytotoxic activity was determined by FACS. (F) Representative contour plots showing the fraction of living B cells after the killing assay at different effector : target (E:T) ratios. (G) Quantification of (F) (n=6). (H) Representative histograms(left) and quantification (right) of ThPOK, CD4, CD8α and CD8β levels. (I) Representative histograms (top) and quantification (bottom) of RUNX3 expression on day 5 and day 10 (n=24 RUNX3 d5; n= 15, RUNX3 d10). Data are presented as mean ± SD. Each dot represents a biological replicate of normalized pooled data from either 4 (C), 5 (E), 2 (H) or 3 (H) independent experiments. Statistical significance was determined using either Kruskal-Wallis (C), One-way ANOVA with Tukey’s post-tests (A,B, D-H) or Two-way ANOVA with Bonferroni’s post-tests (I). *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001. In the gut, the acquisition of a cytotoxic phenotype occurs through ThPOK downregulation, which leads to the loss of CD4-lineage identity. Suboptimal ThPOK levels result in increased RUNX3 expression, which in turn causes the de-repression of CD8 expression, downregulation of CD4 levels, and upregulation of cytotoxic molecules such as GZMB and Perf-1 32 , 37 – 39 . While ThPOK expression was impaired with lactate supplementation, we observed lower frequencies of CD8β + cells and unchanged CD4 expression levels ( Figure 2H ). Although we did not detect increased CD8 expression upon lactate treatment, significantly higher RUNX3 levels were detected with both lactates on day 5. However, by day 10 only D-lactate-treated samples retained elevated amounts of RUNX3 compared to controls ( Figure 2I ). Thus, lactate supplementation increases cytotoxicity in Th1 cells while preserving their CD4 cellular identity. D-Lactate preferentially supports enhanced mTORC1 signaling and glycolysis, whereas basal OXPHOS activity remains unaffected We observed increased T cell expansion rates upon D- but not L-lactate supplementation in Th1 cells ( Figure 3A ). Activation of mTORC1 signaling rewires cellular metabolism promoting glycolysis, which sustains rapid proliferation 40 , 41 . Therefore, we investigated lactate’s impact on mTORC1 activity. D-lactate treated Th1 cells showed increased frequencies of P-mTORC1 + and P-S6 + cells, whereas L-lactate had no observable effect ( Figure 3B ). Download figure Open in new tab Figure 3. D-Lactate promotes metabolic reprogramming in CD4 + T cells independently of its own catabolism. (A-D) Sorted naïve mouse WT CD4 + T cells were cultured for 5 days under Th1-polarizing conditions with or without lactate supplementation as indicated. (E) On day 5, control and D-lactate-treated cells were replated in RPMI medium containing [U-13C] D-lactate for 24 hours. (A) Expansion factor of Th1 cells on day 5 (n=72). (B) Representative histograms (left) and quantification (right) of P-mTORC1 (S2448) and P-S6 (S240/244) (n=18). (C) Representative SeaHorse kinetics of OXPHOS and glycolysis (left) (n=3) and quantification (right) of basal (top) and maximal (bottom) metabolic activity in each pathway (n=9). (D) Heatmap showing differentially expressed genes (DEGs) identified with an adjusted p-value < 0.05 (n=2). (E) Peak area abundance of unlabeled M+0 metabolites in day 5 control and D-lactate-treated cells after 24-hour treatment with [U-13C] D-lactate (n=3). Data are presented as mean ± SD. Each dot represents a biological replicate of normalized pooled data from either 24 (A), 6 (B), 3 (C) or 1 (E) independent experiments. Statistical significance was determined using either Kruskal-Wallis (A), One-way ANOVA with Tukey’s post-tests (B, E) or Two-way ANOVA with Bonferroni’s post-tests (C). *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001. To determine whether enhanced mTORC1 signaling contributed to the cytokine burst by D-lactate, we inhibited mTORC1 activity by adding rapamycin (100mM) during the cytokine restimulation assay. Rapamycin did not eliminate differences in IFN-γ + frequencies between D-lactate and control samples. However, D-lactate’s boosting effect on IFN-γ MFI was completely abrogated ( Figure suppl. 1A ). Additionally, D-lactate’s upregulation of Perf-1 + frequencies and GZMB MFI was significantly reduced on day 10 in the rapamycin group ( Figure suppl. 1B ). Download figure Open in new tab Figure suppl. 1. Enhanced mTORC1 activity, rather than metabolic activity, is partially responsible for the upregulation of IFN-γ, GZMB, and Perf-1 by D-lactate. (A-G) Sorted naïve WT CD4 + T cells were cultured for 5 (A, C, D, G) or 10 (B) days under Th1-polarizing conditions with or without lactate supplementation as indicated. (D-F) On day 5, control and D-lactate-treated cells were replated in RPMI medium containing [U-13C] D-lactate for 24 hours. (A) Representative histograms (top) and quantification (bottom) of IFN-γ production upon 4h of rapamycin (100nM) treatment on day 5 (n=9). (B) Representative histograms (left) and quantification (right) of Perf-1 (top) and GZMB (bottom) production upon 4h of rapamycin treatment on day 10 (n=9). (C) Ldhd expression assessed by RNA-seq (n=2) or qPCR (n=12) analysis. (D) Percent labeling of [U-13C] D-lactate-derived lactate (M+3), pyruvate (M+3), and citrate (M+2) after 24 hours (n=3). (E) Ldhd expression after 24h of [U-13C] D-lactate treatment (n=3). (F) Representative histograms (left) and quantification (right) of IFN-γ and GZMB production after 24h of [U-13C] D-lactate treatment (n=3). (G) Representative histograms (left) and quantification (right) of IFN-γ and GZMB production after 4h of either 2-DG (10mM) or R/AA (11.5μM and 9μM) treatment (n=6). Data are presented as mean ± SD. Each dot represents a biological replicate of normalized pooled data from either 4 (qPCR C), 3 (A, B, E), 2 (G) or 1 (RNA-seq C, D-F) independent experiments. Statistical significance was determined using either Two-way ANOVA with Bonferroni’s post-tests (A and B) or One-way ANOVA with Tukey’s post-tests (C-G). *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001. Since mTORC1 activation shifts cellular metabolism toward glycolysis 42 , we assessed the metabolic effect of D-lactate by SeaHorse measurements. D-lactate supplementation increased basal glycolytic levels compared to control samples ( Figure 3C ), aligning with the selective upregulation of mTORC1 signaling observed in this experimental group (cf. Figure 3B ). A recent study has shown that both lactates favor mitochondrial oxidative metabolism in detriment of glycolysis by a process that enhances ETC activity 43 .However, basal OXPHOS rates remained unaffected by D-lactate supplementation and only an increase in maximal respiration could be detected ( Figure 3C ). Further dissection of our RNA-seq datasets revealed a significant downregulation of at least 25 genes encoding different subunits of the ETC complexes (16 genes in C-I, 2 genes in C-II, 1 gene in C-III, 1 gene in C-IV and 5 genes in C-V) ( Figure 3D ). However, upon stimulation, transcription of most of the subunits reverted to control levels ( Figure 3D , right). Interestingly, within the downregulated genes, we could find several ETC subunits directly involved in mitoROS generation in C-I ( Ndufv1 and Ndufs1 ) and C-III ( Uqcrc1 ) ( Figure 3D ). D-lactate can be converted to pyruvate, generating energy and serving as a precursor for macromolecule biosynthesis 44 – 46 . This process depends on the activity of the enantiomer-specific enzyme LDHD ( Ldhd ) 45 , 47 . A previous study investigating the effects of D-lactate supplementation on the metabolic activity of various cell lines revealed that, in the absence of Ldhd expression, D-lactate enhances mitochondrial OXPHOS by promoting L-lactate catabolism, without direct consumption of D-lactate in the process. 43 . Our RNA-seq dataset showed that although Ldhd was lowly expressed under all experimental conditions, D-lactate treatment increased its transcription more than sevenfold compared to the control group, a finding further validated by qPCR ( Figure suppl. 1C ), suggesting that D-lactate catabolism could be taking place. To test this hypothesis and investigate how rapidly D-lactate induces metabolic rewiring in Th1 CD4 + T cells, we performed metabolic tracing experiments. Th1 cells were differentiated for five days under control or D-lactate conditions and subsequently pulsed with [U-13C] D-lactate for 24 hours. Surprisingly, as previously reported 43 , no incorporation of traced D-lactate into pyruvate (M+3) or citrate (M+2) pools was detected in either group ( Figure suppl. 1D ). Despite the absence of detectable D-lactate metabolism, we could still observe metabolic differences between the D-lactate and control groups. Treatment with D-lactate for only 24 hours was insufficient to upregulate Ldhd transcription ( Figure suppl. 1E ). Additionally, extracellular glycolytic L-lactate levels remained significantly higher in cells differentiated in the presence of D-lactate for five days ( Figure 3D , right). While most TCA cycle metabolites showed no major changes, α-ketoglutarate levels were significantly elevated in the D-lactate group. Glutamine can serve as an anaplerotic source of carbon for the TCA cycle through glutaminolysis, a pathway involving its conversion into glutamate and subsequently into α-ketoglutarate, a metabolite taking part in the TCA cycle 48 . However, similar levels of glutamine uptake and glutamate were observed between both conditions, ruling out increased flux via glutaminolysis as the source of the elevated α-ketoglutarate levels. Instead, the increased α-ketoglutarate appeared to result from its reduced conversion into GABA ( Figure 3E ). Surprisingly, acute treatment of control cells with D-lactate for 24 hours resulted in a downregulation in IFN-γ and GZMB frequencies, which indicates that full D-lactate metabolic reprogramming and the boost in cytokine production require longer than 24h time-periods to be active ( Figure suppl. 1F ). To explore the link between increased metabolic activity and cytokine upregulation, we inhibited glycolysis and OXPHOS using 2-deoxyglucose (2-DG) or Rotenone/Antimycin A (R/AA), respectively. Interestingly, inhibition of either pathway not only failed to eliminate differences in IFN-γ and GZMB levels but instead amplified the disparity between D-lactate-treated and control samples ( Figure suppl. 1G ). Collectively, these findings indicate that D-lactate supplementation drives profound metabolic reprogramming independent of its own catabolism. However, the elevated metabolic activity does not account for D-lactate’s ability to enhance functionality in Th1 cells. Instead, enhanced mtORC1 signaling contributes partially to the boosting effect. D-lactate preserves differentiation and functionality of Th1 cells in glucose-restricted conditions We had previously observed that D-lactate was able to sustain considerably higher cytokine production levels in conditions where glycolysis was inhibited by 2-DG (cf. Figure suppl. 1G ). However, prolonged glucose deprivation in microenvironments such as tumors, impairs production of proinflammatory cytokines in CD4 + T cells 49 . To study the impact of lactate supplementation in glucose-restricted conditions, we plated day 5 differentiated Th1 cells in a medium containing 1mM glucose for three days. Furthermore, this experimental setting allowed us to assess whether D-lactate could still promote mitochondrial respiration in conditions where glucose-derived L-lactate catabolism is severely impaired due to glucose scarcity. D-lactate-treated Th1 cells retained higher expression of T-bet and Eomes, while L-lactate only partially sustained increased Eomes levels ( Figure 4A ). Moreover, withdrawal of lactate during the glucose-restricted phase reverted T-bet and Eomes expression to control’s baseline. Regarding the production of cytokines and cytolytic molecules, D-lactate supported enhanced expression of IFN-γ, TNF-α, GZMB and Perf-1, whereas L-lactate could only boost GZMB expression. The upregulation of all these molecules was lost when cells were deprived of lactate, arguing against the establishment of cell-intrinsic memory for lactate-induced phenotypic changes ( Figure 4B ). Interestingly, we observed that D-lactate samples not only had considerably more mitochondrial mass (MitoSpy Green FM) but they also had higher MMP/area unit (TMRM/MitoSpy Green FM ratios) ( Figure 4C ), indicating that D-lactate likely fosters mitochondrial fitness independently of L-lactate. Enhanced activation of mTORC1 and S6, could only be observed in D-lactate-treated samples ( Figure 4D ). Importantly, upregulation of phosphorylated mTORC1 and MMP were lost upon lactate removal ( Figure 4C and 4D ). Taken together, these data show that under restrictive metabolic conditions such as glucose scarcity, D-lactate is able not only to preserve expression of key transcription factors essential for the Th1 differentiation program but also sustains production of their signature proinflammatory cytokines, while maintaining mTORC1 signaling and mitochondrial fitness. Moreover, D-lactate likely increases mitochondrial fitness independently of L-lactate. Download figure Open in new tab Figure 4. D-lactate sustains Th1 differentiation and functionality in glucose-restricted conditions. (A-D) Sorted naïve mouse WT CD4+ T cells were cultured for 5 days under Th1-polarizing conditions with or without lactate supplementation as indicated. On day 5 cells were replated in glucose-restricted medium (1mM) for three days, a fraction of the lactate-differentiated samples were removed from the exogenous lactate supplementation. (A) Representative dot plots (left) and quantification (right) of T-bet and Eomes expression on day 8 (n=9). (B) Representative contour plots (left) and quantification (right) of IFN-γ, TNF-α, GZMB and Perf-1 on day 8 (n=9). (C) Representative histograms (top) and calculation (bottom) of TMRM and MitoSpy Green stainings (n=9). (D) Representative histograms (top) and quantification (bottom) of P-mTORC1 (S2448) and P-S6 (S240/S244) (n=9). Data are presented as mean ± SD. Each dot represents a biological replicate of normalized pooled data from 3 independent experiments. Statistical significance was determined using One-way ANOVA with Tukey’s post-tests. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001. D-lactate upregulates cytokine production by limiting mitochondrial ROS production through the glyoxalase system Previous reports have described opposing effects on mitoROS production following D- or L-lactate supplementation. While L-lactate enhances mitoROS production 6 , 50 , D-lactate appears to limit it under conditions of impaired ETC activity due to C-I and C-III inhibition by rotenone or antimycin A, respectively 43 . In our primary CD4 + Th1 cells, samples treated with D-lactate limited superoxide production, whereas L-lactate supplementation resulted in elevated levels ( Figure 5A ). Superoxide quickly reacts with molecules in the vicinity, while H 2 O 2 has a longer half-life and thus the ability to impact several signaling pathways and transcription factors outside of the mitochondria 51 . FACS staining revealed reduced mitochondrial H 2 O 2 accumulation in D-lactate-treated samples and significantly higher levels in L-lactate-supplemented ones ( Figure suppl. 2A-B ). Download figure Open in new tab Figure suppl. 2. D-lactate limits mitoROS activity through the glyoxalase system. (A-G) Sorted CD4 + T cells were cultured under Th1-polarizing conditions for five days with or without lactate supplementation as indicated. (A) Representative histograms of MitoPY1 staining. (B) Quantification of (A) (n=9). (C) Representative histograms (left) and quantification (right) of MitoSOX (top) and IFN-γ (bottom) production (n=9). (D) Normalized RNA-seq reads depicting the relative expression levels of Slc25a39 and Slc25a40 (n=2). (E) Representative histograms of Glo1 and Glo2 staining (F) Quantification of (E) (n=21). (G) Representative histograms (left) and quantification (right) of MG-Lys staining (n=3). Data are presented as mean ± SD. Each dot represents a biological replicate of normalized pooled data from either 7 (F), 3 (B, C) or 1 (D) independent experiments. Statistical significance was determined using either Two-way ANOVA with Bonferroni’s post-tests (B and G) or One-way ANOVA with Tukey’s post-tests (C, E and F). *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001. Download figure Open in new tab Figure 5. D-lactate relies on the glyoxalase system to limit mitoROS and increase cytokine production. (A-G) Sorted naïve mouse WT CD4 + T cells were cultured for 5 days under Th1-polarizing conditions with or without lactate supplementation as indicated. (A) Representative histograms (left) and quantification (right) of MitoSOX MFI (n=12). (B) Representative histograms (left) and quantification (right) of IFN-γ production in Th1 cells (n=9). (C) Heatmap showing differentially expressed genes (DEGs) included in WP_Oxidative_stress_response, KEGG_GSH_metabolism or identified with an adjusted p-value < 0.05 and log2FC ∈ (-1.24, 2.8) (n=2). (D) Representative histograms of MitoSOX stainings upon treatment with either BBGC (1μM) or BBGC (1μM) + AG (100μM) for 30minutes. (E) Quantification of (D) (n=15, DMSO and BBGC; n=9 BBGC+AG). (F) Representative contour plots of IFN-γ and GZMB production after 4h of BBGC (1μM) or BBGC (1μM) + AG (100μM) treatment. (G) Quantification of (F) (n=15). (H) qRT-PCR analysis of Gzmb and Ifng (n=6). Data are presented as mean ± SD. Each dot represents a biological replicate of normalized pooled data from either 5 (E, G) 4 (A), 3 (B), 2 (H) or 1 (C) independent experiments. Statistical significance was determined using One-way ANOVA with Tukey’s post-tests (A, B) or Two-way ANOVA with Bonferroni’s post-tests (E, G and H). *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001. We then investigated how the differential regulation of mitoROS by D-vs. L-lactate could influence cytokine production. By adding H 2 O 2 or mitoTEMPO, we augmented or neutralized ROS levels, respectively. When H 2 O 2 was introduced to D-lactate-treated cells, IFN-γ + frequencies reverted to control levels. Conversely, mitoROS scavenging via mitoTEMPO in L-lactate samples significantly increased IFN-γ levels compared to the control group ( Figure 5B ). Both observations highlight the negative influence of ROS on IFN-γ production. Acute restimulation of control cells in the presence of either D- or L-lactate increased mitochondrial superoxide formation and decreased IFN-γ frequencies, an effect that could be prevented by pre-incubating lactate-treated samples with mitoTEMPO, reinforcing our previous observation ( Figure suppl. 2C ). To investigate how D-lactate maintains basal mitochondrial respiration while limiting superoxide and H₂O₂ formation, we analyzed the expression of genes involved in oxidative stress response and GSH metabolism. Surprisingly, D-lactate-treated samples showed decreased expression of catalase ( Cat ), superoxide dismutase ( Sod2 ), peroxiredoxins ( Prdx1 , Prdx3 ), thioredoxin ( Txn1 ), and thioredoxin reductase ( Txnrd3 )—all key enzymes for H₂O₂ detoxification. Notably, the expression of Nfe2l2 52 , the master oxidative stress transcription factor, was also reduced in this group. Conversely, genes associated with cytoplasmic ROS and NOS production, such as Txnip , Xdh and Nos2 , were upregulated. Additionally, D-lactate-treated cells exhibited decreased expression of Gclc and Gclm , which are essential for GSH synthesis from precursor amino acids ( Figure 5C ). Since neither oxidative stress response mechanisms nor enhanced cytoplasmic GSH biosynthesis could account for the advantage in mitoROS regulation in the D-lactate group, we decided to investigate next whether mitochondrial import of GSH was favored in this experimental condition. Mitochondrial GSH import is primarily mediated by Slc25a39 and Slc25a40 53 . However, we could also not detect major differences in the expression of these genes between different experimental conditions ( Figure suppl. 2 D ). The glyoxalase system, which detoxifies MG into harmless D-lactate, regulates mitochondrial redox state. Once Glo1 binds MG and GSH releasing S-D-lactoylglutathione (SLG) in the cytoplasm, mitochondrial processing of SLG by mGlo2 releases GSH and D-lactate inside the organelle, where it neutralizes mitoROS accumulation 54 . To deplete cells of SLG, we added BBGC to our samples, a well-known Glo1 inhibitor. Accumulation of MG can lead to mitoROS formation 55 . Therefore, some samples were additionally treated with aminoguanidine bicarbonate (AG), which can neutralize MG accumulation 56 . When BBGC was added, D-lactate-treated samples lost their ability to limit mitochondrial ROS and produced higher levels of superoxide compared to the control group. Moreover, D-lactate samples were more sensitive to Glo1 inhibition, showing a greater increase in mitochondrial superoxide levels than any other of the experimental groups ( Figure 5D,E ). To determine whether D-lactate potentiated the glyoxalase system, we measured Glo1 and Glo2 expression. FACS analysis revealed no significant changes in Glo1 expression between control and lactate samples. However, D-lactate supplementation significantly increased Glo2 levels ( Figure suppl. 2E,F ). Unmetabolized MG binds irreversibly to lysine and arginine residues in proteins 25 . Hence, we measured relative MG-Lys levels to assess activity through the glyoxalase system under steady state or after 24 hours of exogenous MG (100μM) addition. Quantification of FACS stainings showed that D-lactate-treated samples tended to keep lower MG-Lys binding than control counterparts ( Figure suppl. 2G ), despite a 40% higher glycolytic activity (cf. Figure 3C ). Regarding the production of cytokines and cytolytic molecules, inhibition of Glo1 activity equalized the frequencies of GZMB + cells in all groups and eliminated D-lactate’s upregulation of IFN-γ production. Neutralization of MG by AG minimally rescued D-lactate’s boosting effect on IFN-γ frequencies while no significant changes could be observed for GZMB production ( Figure 5F,G ). Finally, RT-qPCR analysis revealed that the loss of D-lactate’s boosting effect on IFN-γ and GZMB in samples where Glo1 had been inhibited, occurred primarily at the transcriptional level ( Figure 5H ). Collectively, these results indicate not only that mitoROS levels impact cytokine production in Th1 cells, but also that D-lactate’s boosting effect relies on its ability to limit mitoROS by enhancing the activity of the glyoxalase system. Augmented ERK1/2 signaling triggered by D-lactate sustains GZMB and Perf-1 upregulation Further analysis of the RNA-Seq data showed that the GO:0070371 (ERK1/ERK2 cascade) was strongly upregulated compared with control and L-lactate-treated counterparts ( Figure 6A ). Quantification of phosphorylated ERK levels confirmed a drastic upregulation upon D-lactate supplementation when compared to the other experimental groups ( Figure 6B,C ). ERK1/2 controls expression of Perf-1 and GZMB in CD8 + T cells 57 . Hence, we determined whether an enhancement of ERK signaling contributed to the upregulation of cytolytic molecules in D-lactate-treated samples. Inhibition of ERK1/ERK2 activity by adding UO126 (10μM) substantially impaired D-lactate’s ability to upregulate Perf-1 and GZMB expression in terms of frequencies or MFI, respectively ( Figure 6D,E ). Download figure Open in new tab Figure 6. Enhanced P-ERK1/2 is required to sustain GZMB and Perf-1 upregulation in D-lactate-treated Th1 cells. (A-E ) Sorted naïve mouse WT CD4 + T cells were cultured for 5 (A) or 10 (B-E) days under Th1-polarizing conditions with or without lactate supplementation as indicated. (A) Heatmap of the differentially regulated genes included in GO-0070371: ERK1/ERK2 cascade (n=2). (B) Representative histograms of P-ERK staining. (C) Quantification of (B) (n=9). (D) Representative histograms of Perf-1 and GZMB expression. (E) Quantification of (D) (n=9). Data are presented as mean ± SD. Each dot represents a biological replicate of normalized pooled data from either 1 (A) or 3 (C and E) independent experiments. Statistical significance was determined using Kruskal-Wallis (C) or Two-way ANOVA with Bonferroni’s post-tests (E). *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001. D-lactate protects from Blimp-1-mediated transcriptional repression of Ifng We had previously observed no differences in chromatin accessibility (cf. Figure 1E ) that could account for the increase in Ifng and Gzmb transcription. Hence, we hypothesized that the transcriptional differences should be exerted by a TF (cf. Figure 5H ). Reactome 2022 analysis showed Interleukin-10 Signaling R-HSA-6783783 to be the most differentially regulated process between activated D-lactate and control samples ( Figure 7A ). Although additional transcription factors contribute to IL-10 production in Th1 cells, its expression is Blimp-1 driven 58 . Moreover, Blimp-1 acts as a negative regulator of IFN-γ transcription and it is associated with increased cytotoxicity in CD4 + T cells 59 , 60 . Hence, we used a Blimp-1 eGFP reporter mouse strain to assess its expression in each experimental group. D-lactate-treated samples increased Blimp-1 expression in Th1 cells on both day 5 and day 10 of analysis, whereas L-lactate supplementation had no effect ( Figure 7B ). Download figure Open in new tab Figure 7. D-lactate prevents Blimp-1-mediated transcriptional repression at the Ifng locus. (A-E) Sorted naïve mouse WT, Blimp-1eGFP, Blimp-1 fl/fl and Blimp-1 fl/fl xCre CD4 + T cells were cultured for 5 days under Th1-polarizing conditions with or without lactate supplementation as indicated. (A) Pathway enrichment analysis depicting the top differentially regulated processes using Reactome 2022 (n=2). (B) Representative histograms (left) and quantification (right) of Blimp1 expression levels (n=9). (C) Representative contour plots (left) and quantification (right) of IFN-γ and GZMB production in Blimp-1 fl/fl and Blimp-1 fl/fl xCre Th1 cells on day 5 (n=4, Blimp-1 fl/fl ; n=6 Blimp-1 fl/fl xCre). (D) Representative histogram of GZMB (top) and Perf-1 (bottom) expression in Blimp-1 fl/fl and Blimp-1 fl/fl xCre Th1 cells on day 10. (E) Quantification of (D) (n=4, Blimp-1 fl/fl ; n=6 Blimp-1 fl/fl xCre). Data are presented as mean ± SD. Each dot represents a biological replicate of normalized pooled data from either 3 (B), 2 (D) or 1 (C) or independent experiments. Statistical significance was determined using Two-way ANOVA with Bonferroni’s post-tests. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001. To assess Blimp-1 contribution to IFN-γ, GZMB and Perf-1 production, we employed Blimp-1 deficient CD4 + T cells ( Il7raCrexPrdm-1 fl/fl (Blimp-1 fl/fl xCre from now on)) or their respective control counterparts ( Prdm-1 fl/fl (Blimp-1 fl/fl from now on)). Deletion of Blimp-1 abrogated the differences in IFN-γ production between control and D-lactate-treated samples. While Blimp-1 deletion increased the frequencies of IFN-γ + cells in control and L-lactate samples, D-lactate failed to further upregulate IFN-γ production ( Figure 7C ), despite being the experimental group with highest Blimp-1 expression levels (cf. Fig. 7B ). Additionally, Blimp-1 deletion failed to abrogate the differences in GZMB expression levels between control and lactate-treated samples and rather exacerbated them on day 5 ( Figure 7C ). Analysis on day 10 demonstrated not only that Blimp-1 deletion failed to abrogate the differences in GZMB and Perf-1 expression between the D-lactate and control groups but also that it played no significant role in the overall expression levels of either cytotoxic molecule in any of the experimental groups ( Figure 7D,E ). These results suggest that D-lactate treatment protects IFN-γ production in Th1 cells from Blimp-1-mediated transcriptional repression. Discussion In the last decades, L-lactate has emerged as a versatile signaling molecule that regulates diverse facets of cellular biology. Traditionally, attention has gravitated toward L-lactate due to its prevalence in higher organisms. In this study, we dissected the different phenotypes induced by exogenous D- and L-lactate supplementation in Th1 cells. Exogenous addition of L-lactate resulted in decreased production of proinflammatory cytokines such as TNF-α and IFN-γ, with solely a discrete boosting effect on cytotoxic molecules. In contrast, D-lactate supplementation greatly enhanced the production of IFN-γ, TNF-α, GZMB, and Perf-1. The different effector phenotypes were derived from the distinct ability of D- and L-lactate to regulate and limit mitoROS levels. Extending earlier findings on the adverse effects of high concentrations of L-lactate on T-bet and IFN-γ levels 26 , our study revealed D-lactate’s ability to exacerbate IFN-γ production in cells with relatively low T-bet expression levels. Interestingly, D-lactate treatment retained its ability to upregulate IFN-γ in knockout Th1 cells lacking STAT1, STAT4, or T-bet expression, indicating the involvement of an alternative regulatory mechanism responsible for the burst in IFN-γ production. Beyond orchestrating Th1 cytokines like IFN-γ and TNF-α, lactate supplementation elevated markers associated with cytotoxic immune cell populations. It is noteworthy that D-lactate induced the expression of Class-I MHC-restricted T-cell-associated molecule (CRTAM), which is exclusively expressed in CD4 + CTLs 61 . While both lactates enhanced selective killing of antigen-loaded B cells, D-lactate-treated samples exhibited superior cytotoxic activity, correlating with higher production levels of cytolytic molecules. In the gut, upregulation of cytotoxic features in CD4 + T cells is accompanied by a certain loss of their lineage identity due to ThPOK and CD4 downregulation 37 . Loss of ThPOK de-represses RUNX3 expression and results in the upregulation of CD8β and cytotoxic molecules 38 , 62 . Although we observed a dysregulation of ThPOK and RUNX3 levels in lactate-treated samples, CD4 lineage identity was better preserved than in control cells, where upregulation of CD8 was more prominent. While no specific master-regulator transcription factor for the CD4 + CTL program has been identified, lactate upregulated some transcription factors implicated in the acquisition of cytotoxic features. IL-2 promotes CD4 + cytotoxicity by enhancing Blimp-1 expression, which recruits T-bet to promoter regions of cytolytic genes 60 , 63 . In our study using Th1 cells, D-lactate treatment increased Blimp-1 and downregulated T-bet expression. Experiments with Blimp-1-deficient Th1 cells demonstrated that this transcription factor does not play a role in the upregulation of GZMB and Perf-1 under any of the experimental conditions tested, as both Blimp-1 fl/fl and Blimp-1 fl/fl xCre cells exhibited similar cytokine frequencies within each group. These findings indicate that the D-lactate-induced acquisition of cytotoxicity in our system operates through an alternative mechanism. In Th1 cells, Blimp-1 plays a pivotal role as it regulates transcription of several cytokines. Blimp-1 represses Ifng by binding to CNS-22Kb 59 , a critical region regulating IFN-γ production in T and NK cells 64 . Conversely, in this CD4 + T cell subset, IL-10 production relies on Blimp-1 expression 58 . We detected increased Blimp-1 expression in the D-lactate-treated group. Moreover, the most upregulated process in Reactome 2022 was Interleukin-10 Signaling R-HSA-6783783, correlating with the elevated Blimp-1 levels found in the D-lactate group. Surprisingly, Blimp-1 ablation increased IFN-γ levels in control and L-lactate-treated samples but had no impact on the D-lactate group. These findings suggest that Blimp-1 either preferentially targets alternative chromatin sequences or that D-lactate provides protection against Blimp-1-mediated transcriptional repression at the Ifng locus. In CD8 + T cells, RUNX3 drives Eomes expression and upregulates Blimp-1 levels, and the binding of these three transcription factors to Ifng , Prf1 and Gzmb loci regulate the production of the aforementioned molecules 65 , 66 . Moreover, abrogation of RUNX3 in CD4 + CTLs with a Th1 origin impairs production of cytotoxic molecules 32 . Lactate supplementation enhanced the expression of RUNX3 and Eomes, and the most potent upregulation was induced by D-lactate. Whether RUNX3 is responsible for Eomes and Blimp-1 expression and to which extent it may contribute to GZMB and Perf-1 production in Th1 cells, remains to be addressed in future work. D-lactate supplementation increased mTORC1 activity, basal glycolytic rates and proliferative capacity in Th1 cells, in stark contrast to L-lactate’s minimal modulation. In activated CD4 + T cells, impairment of glycolysis by pharmacological inhibition or low glucose concentration, severely compromises effector functions and cytokine production 67 – 69 . Our data demonstrate that D-lactate supplementation preserves T cell differentiation and overall cytokine production in culture conditions where glucose metabolism is inhibited or glucose availability is restricted, whereas L-lactate only minimally promoted Eomes and GZMB expression. These results indicate that the metabolic and functional effects of D-lactate supplementation are independent of L-lactate catabolism. Experiments selectively inhibiting glycolysis with 2-DG or mTORC1 activity with rapamycin demonstrated that mTORC1 signaling, rather than glycolytic activity, was partially responsible for the increase in IFN-γ, GZMB, and Perf-1 production. Sequencing analysis revealed a broad downregulation of genes encoding ETC subunits across multiple complexes. However, basal mitochondrial respiration rates remained unaffected by this phenomenon. Interestingly, supplementation with either lactate enhanced maximal oxygen consumption in mitochondria or/and MMP in glucose-restricted conditions. However, since only D-lactate sustained elevated cytokine production in this experimental setting, the boosting effect could not be attributed to the lactate-driven increase in MMP. This conclusion was further supported by experiments demonstrating that D-lactate retained its ability to enhance cytokine production even when mitochondrial respiration was inhibited by R/AA treatment. Acute restimulation of control cells in the presence of either lactate rose mitoROS levels hindering IFN-γ production, a phenotype that could be prevented by preincubating the samples with a mitoROS scavenger. Notably, prolonged D-lactate supplementation limited mitoROS levels, whereas L-lactate retained its ability to exacerbate oxidative stress 70 . D-lactate downregulated several ETC genes, including Ndufv1 and Ndufs1 (Complex I) as well as Uqcrc1 (Complex III), all of which are implicated in the aberrant transport of electrons back to the mitochondrial matrix. D-lactate treatment not only impaired mitoROS-ETC forming subunits in mitochondria but also downregulated several key genes implicated in oxidative stress response and GSH biosynthesis. Taken together, these results might collectively indicate a more efficient configuration of ETC complexes where regular OXPHOS rates are maintained while superoxide and H 2 O 2 formation are kept to a minimum, thus turning off several oxidative stress response genes. However, D-lactate-treated samples exhibited increased sensitivity to glyoxalase system inhibition, losing the ability to limit superoxide formation and starting to produce significantly higher mitoROS levels when compared to control samples. These findings argue in favor of an improved mitochondrial redox state in D-lactate-treated cells, which depends on enhanced glyoxalase system activity rather than a diminished capacity to produce mitoROS through the ETC. Importantly, glyoxalase system inhibition not only reversed D-lactate’s control over superoxide formation in mitochondria but also abrogated its boosting effects on GZMB and IFN-γ production. The glyoxalase system plays a pivotal role in mitigating metabolic stress, being not only central to the regulation of mitochondrial redox balance 54 but also bridging glycation stress through its critical role in MG detoxification 71 . D-lactate supplementation increased basal glycolytic rates by more than 40%, while it reduced methylglyoxal (MG) conjugation to protein residues, thereby conferring resistance to glycating stress. This advantage in MG detoxification reinforces our previous observation of a boost in glyoxalase system activity. Neutralizing MG accumulation while inhibiting the glyoxalase system, only minimally restored D-lactate’s boosting effect on IFN-γ production and had no effect on GZMB levels. Collectively, these results suggest that the glyoxalase system’s protective role is mediated by its capacity to shuttle GSH into mitochondria rather than its ability to detoxify MG. Manipulation of mitoROS levels produced during restimulation by either mitoTEMPO or H 2 O 2 addition to Th1 cells, recapitulated the results obtained by glyoxalase system inhibition. Scavenging of superoxide in L-lactate-treated samples was sufficient to upregulate IFN-γ production with respect to the control group and incubation of D-lactate with H 2 O 2 reverted IFN-γ production to control levels, proving not only that the phenotypes induced by each lactate were dependent on their differential ability to regulate mitoROS but also highlighting the pivotal role of oxidative stress in the regulation of Th1 cell functionality 7 . Previous reports have shown that D-lactate rewires metabolic activity toward mitochondrial respiration at the expense of glycolysis. Interestingly, this mechanism depends on intact mitochondrial ETC integrity and L-lactate catabolism, as no Ldhd expression or anaplerotic contribution of D-lactate to TCA cycle metabolites was observed 43 . Although in Th1 cells we noted a selective upregulation of Ldhd expression in D-lactate-treated samples, we could not detect any D-lactate catabolism. Despite increasing MMP and maximal respiration, D-lactate did not alter basal mitochondrial OXPHOS levels. Instead, its primary metabolic effect was the induction of glycolytic rates, likely supported by the enhanced activation of the mTORC1 signaling cascade observed in this experimental group. Moreover, in glucose-restricted experiments, where L-lactate production is severely impaired due to glucose scarcity, D-lactate still increased total mitochondrial mass, MMP, and mTORC1 activity. These findings indicate that D-lactate’s metabolic regulation extends beyond L-lactate or its own catabolism. Whether the downregulation of various mitochondrial ETC subunits redirected D-lactate’s metabolic burst toward glycolysis, or if D-lactate’s effect on metabolic activity is context- or cell type-dependent, remains to be further investigated. Lactate can induce deep chromatin rearrangements by inhibiting HDACs 22 , increasing the Acetyl-CoA 22 pool or through enzyme-independent histone lactylation 72 . However, ATAC-seq analysis revealed similar chromatin accessibility levels for all the experimental conditions tested. These results argue against the contribution of a more accessible chromatin configuration due to lactate’s epigenetic regulation under the experimental settings employed in this study. Inhibition of Glo1 exacerbated mitoROS production and significantly dampened the capacity of D-lactate to increase Ifng and Gzmb transcription, resulting in a total loss of the boosting effect at IFN-γ and GZMB protein levels. These results were further recapitulated by experiments where cytokine production levels were altered by direct manipulation of mitoROS generated in each experimental condition. Taken together, these data suggest that a putative transcription factor responsible for the lactate-induced phenotypes likely is mitoROS sensitive and able to induce transcription of both Ifng and Gzmb . Although previous studies have demonstrated that ROS accumulation can lead to enhanced Prdm1/Blimp-1 expression in cancerous cells 73 , we could not find evidence in the literature describing any direct effects of ROS on the activity or DNA-binding ability of Blimp-1. This suggests that the protection against Blimp-1 transcriptional repression might be mediated by a mitoROS-regulated transcription factor able to antagonize Blimp-1 binding to CNS-22 of Ifng locus. Accumulation of mitoROS has the potential to impact several key cell signaling pathways, among them mTORC1 and ERK1/2. Whether activation of one or both signaling pathways was dependent on the differential mitoROS amounts generated in the distinct experimental groups remains to be assessed in future work. A previous study reported the contribution of enhanced ERK1/2 signaling to the production of IL-6 and IL-8 in fibroblasts supplemented with D-lactate 74 . In our study of the mechanism involved, enhanced ERK1/2 signaling also contributed to D-lactate’s upregulation of GZMB and Perf-1 production. The cytolytic activity of CD4 + CTLs is restricted to professional antigen-presenting cells such as macrophages, dendritic cells, and B cells expressing MHC-II. Hence, the clearance of infected or transformed cells primarily occurs through the cytolytic activity of CD8 + T cells, which recognize peptide-bound MHC-I on all nucleated cells of the body. However, a common trait shared by some viral infections and cancerous processes is the downregulation of MHC-I expression, which impairs CD8 + T cell cytotoxic activity and results in immune surveillance escape 75 , thereby helping to establish the pathogenic process. This mechanism is observed in certain lymphomas, melanomas, breast and colorectal cancers, among others 76 , where cytolytic activity of CD4 + CTLs can be exploited to eradicate the disease 77 . Our results demonstrate that D-lactate not only enhances classical Th1 effector function but also amplifies their cytolytic activity, opening a window for its use either alone or as adjuvant for existing therapies. D-lactate’s therapeutic potential is particularly relevant in immunosuppressive environments where other primary metabolites, such as glucose, are scarce. Our study highlights a novel role for D-lactate in promoting a cytotoxic phenotype in CD4+ T cells. This effect relied on mTORC1 and ERK1/2 signaling and was independent of Blimp-1 repression. D-lactate supplementation enhanced both OXPHOS and glycolysis but primarily augmented cytokine production by limiting mitoROS generation through increased glyoxalase system activation. Materials and Methods Mice C57BL/6J or C57BL/6N mice were used as wild type (WT) controls. In addition, strains carrying the following genetic modifications were used: Stat1 -/- , Stat4 -/- , Tbx21 -/- , Blimp-1eGFP, SMARTA + or Il7raCrexPrdm-1 fl/fl (Blimp-1 fl/fl xCre from now on) and Tcrbd -/- mice. Blimp-1eGFP and Blimp-1 fl/fl xCre mice were obtained from Prof. Thomas Dörner and Prof. Andreas Diefenbach, respectively. SMARTA + and Blimp-1 fl/fl xCre mice were bred in a heterozygous state for their respective transgene (SMARTA and Il7ra Cre, respectively). For all the experiments, male and female mice were used at an age of 8 to 12 weeks. All animals were bred under specific-pathogen free (SPF) conditions in the animal facility of Charité – Universitätsmedizin Berlin. T cell isolation and cell sorting Mouse CD4 + T cells were isolated from spleens. Samples were enriched for CD4 using CD4-biotin (L3T4, BD) and subsequently stained with the following antibody mixes: CD8a (53-6.7, BD), CD25 (pC61.5, DRFZ), CXCR3 (CXCR3-173, eBiosciences), CD62L (MEL-14, eBiosciences), CD44 (IM7, DRFZ) and immediately sorted at an Aria II cell sorter. We defined naïve mouse CD4 + T cells as: CD4 + CD25 - CXCR3 - CD62L + CD44 - . All the samples used for experiments had a post-sort purity of at least 98%. Activation and differentiation of CD4 + T cells with antibodies or antigenic peptide Mouse CD4 + T cells were stimulated for 48h with plate-bound anti-CD3 (OKT3, eBiosciences) and anti-CD28 (CD28.6, eBiosciences). SMARTA + T cells were alternatively stimulated with irradiated splenocytes from TCRβδ-deficient mice loaded with GP61 peptide (GLKGPDIYHGVYQFKSVEFD, 1μM; R.Volkmer, Charitè) at a 4:1 ratio (APC : T cell). All samples were cultured with RPMI 1640+GlutaMax-I (Gibco) containing: 10% (v/v) FCS (Gibco), penicillin (100 U/ml; Gibco), streptomycin (100 μg/ml; Gibco), ß-mercaptoethanol (50 ng/ml; Sigma). For Th1 differentiation, cultures were supplemented with IL-2 (5ng/mL; Miltenyi), IL-12 (5ng/mL; Miltenyi) and anti-IL-4 (11b11; 10μg/mL; DRFZ). Some samples were additionally supplemented with either Na-D-lactate (20mM) or Na-L-lactate (20mM; both from Sigma-Aldrich). Most of the analyses were carried out either after one (5 days) or two rounds (10 days) of in vitro stimulation. For some experiments, MG (100μM; Sigma-Aldrich) was added for 24h from day 4 to 5. In glucose-restricted experiments, day 5 differentiated cells were resuspended in Agilent SeaHorse XF RPMI medium supplemented with 10% (v/v) FCS (Gibco), penicillin (100 U/ml; Gibco), streptomycin (100 μg/ml; Gibco), ß-mercaptoethanol (50 ng/ml; Sigma), glutamine (Gibco, 2mM), Na-pyruvate (Sigma, 1mM), glucose (Sigma, 1mM) and IL-2 (5ng/mL) for three days, during which medium was replenished daily. Cell surface stainings Cells were stained in PBS/BSA containing the following antibody mix: CD4 (RM4-5, eBiosciences), CD8α (53-6.7, BD), CD8β (YTS156.7.7, Biolegend). Restimulation and detection of intracellular cytokines and cytotoxic molecules Intracellular detection of cytokines was performed by stimulating cells in RPMI medium containing PMA (5ng/mL) and ionomycin (500ng/mL, both from Sigma-Aldrich) for 4 hours. After the initial 30 minutes, brefeldin A (5μg/mL, Sigma-Aldrich) was added to the cultures until the end of the restimulation. For some of the experiments, cells were pre-incubated with mitoTEMPO (2μM) prior to stimulation or re-stimulated in the presence of H 2 O 2 (10μM), rapamycin (100nM; Thermo-Fisher), UO126 (10μM; Bio Techne), SAHA (10μM; Bio Techne), BBGC (1μM; Sigma-Aldrich), aminoguanidine bicarbonate (AG, 100μM; Sigma-Aldrich) for the entire re-stimulation time. Samples were stained with combinations of the following antibodies: CD4 (L3T4/GK1.5, BD), IL-2 (JES-5H4, eBiosciences), TNF-α (MP6-XT22, Biolegend), GzmB (QA16A02, Biolegend), Perforin-1 (S1600, Biolegend) and IFN-γ (XMG1.2, eBiosciences). Master-regulator transcription factor staining Cells were fixed and permeabilized with the Foxp3/ Transcription Factor Staining Buffer Set (eBioscience) according to manufacturer’s protocol. Samples were stained in Permeabilization buffer 1X containing antibodies to T-bet (eBio4B10, eBiosciences), CD4 (RM4-5, eBiosciences), mIgG1κ (P3, eBiosciences), rIgG2b (eBio149, eBiosciences); or alternatively: CD4 (RM4-5, eBiosciences), T-bet (4B10, Biolegend), Eomes (Dan11mag, eBiosciences), mouse IgG1 (MOPC-21, Biolegend). For the geometric mean index (GMI) calculations, the geometric mean of the master-regulator transcription factor was divided by the geometric mean of the respective isotype control. ThPOK intracellular staining For intracellular detection of ThPOK, cells were stained, fixed and permeabilized using the Transcription Factor Buffer Set (eBiosciences) according to manufacturer’s instructions. After fixation and permeabilization, cells were stained with the following antibodies diluted in Perm1X buffer: CD4 (RM4-5, eBiosciences), ThPOK (AB_2739268, BD). Intracellular staining of methanol-permeabilized samples For intracellular detection of markers in methanol-permeabilized samples, cells were kept for 4 hours in RPMI medium alone or containing PMA (5ng/mL) and ionomycin (500ng/mL, both from Sigma). After that period, cells were fixed in 4% formaldehyde. Permeabilization was accomplished by adding 100% of ice-cold methanol to the fixed pellet. Samples were stained with different combinations of the following antibodies: Histone H3 (D1H2, CellSignaling), Acetyl-Histone H3 (Lys27) (D5E4, CellSignaling), Acetyl-Histone H3 (Lys9) (C5B11, CellSignaling), Phospho-mTOR(Ser2448) (MRRBY, Thermo-Fisher), mTOR (7C10, CellSignaling), Phospho-S6 (Ser240/244) (D68F8, Cell Signaling), Phospho-ERK (p44,p42) (Thr202/Tyr204) (197G2, CellSignaling), Runx3 (D6E2, Cell Signaling), Glo1 (6F10, abcam), Glo2 (abcam) and CD4 (RM4-5, eBiosciences). For some of the markers a secondary staining was performed containing donkey anti-mouse IgG (AB_2556618; Invitrogen) and donkey anti-rabbit IgG (Polyclonal; Invitrogen) prior to acquisition. Mitochondrial stainings Cells were resuspended in incomplete RPMI medium (lacking FCS) containing the various mitochondrial dyes. Samples were co-stained with MitoSpy Green FM (1μM, BioLegend) and TMRM (30nM, Thermo-Fisher). For O 2 - and H 2 O 2 detection, cells were stained with MitoSOX (3μM, Thermo-Fisher) or MitoPY1 (5μM, Tocris), respectively. In vitro cytotoxic assay SMARTA + Th1 cells were differentiated for 5 days with or without lactate (D- or L-lactate, 20mM) as previously described in this section. On day 3, B cells were isolated from TCRβδ-deficient mice using the same methodology as for the CD4 enrichment, exchanging only the primary antibody used for the positive magnetic selection to CD19 (ID3, BD). B cells were then plated in RPMI supplemented with dextran sulfate (25μg/mL, Merck) and LPS (3.5 μg/mL, Merck) for 2 days of in vitro culture (until d5). On day 5, activated B cells were resuspended in PBS and divided into two fractions, one containing plain PBS and the other additionally supplemented with GP61 peptide (5μM). Cells were kept in the incubator for 1h, after which the fractions were stained with different concentrations of CellTrace Violet (Thermo-Fisher, CTV) (5 μM for GP61-loaded cells; 0.5 μM for unloaded cells). B cells were then counted and mixed back together to a 1:1 ratio. The mixed B cell population was eventually added to Th1 CD4 + T cells at different ratios ranging from 0X to 16X for 6h in the incubator (Th1 cells : B cells). Cells were then stained with the following markers: CD4 (RM4-5, eBiosciences), CD19 (ID3, eBiosciences) and Zombie NIR (Biolegend). Samples were immediately acquired at a FACS Canto II after this step. Calculation of specific killing at every given ratio was done using the following formula: FACS acquisition and analysis of data All the samples were acquired in a Canto II cytometer from BD-Biosciences (unless stated otherwise). For the analysis of the data, FlowJo 10.4.2 or posterior versions were used. Regarding the gating strategy, T cells were selected according to their cell size and granularity with the FSC-A and SSC-A, we excluded duplets by SSC-H vs. SSC-W and FSC-H vs. SSC-W gating. Finally, we excluded dead cells by gating on CD4 + ZombieAqua - cells. For the quantification of frequencies and MFI, statistics were exported to excel files, normalized and transferred to GraphPadPrism for the generation of plots and statistical analysis. SeaHorse analysis Samples were washed and resuspended in Agilent Seahorse XF RPMI Medium pH 7.4 (Agilent) containing glutamine (2mM, Gibco), glucose (10mM, Sigma), Na-pyruvate (1mM, Sigma) and lactate when indicated. Cells were counted, adjusted to a final concentration of 1.1×10 6 cells/mL and seeded in a 96-well utility plate precoated with poly-D-lysine (50μg/mL, Sigma). After a resting period (1h; incubator without CO 2 ), cells were placed in a SeaHorse XFe96 analyzer to track OXPHOS (OCR) and glycolytic (PER) activity. After assessment of the steady-state metabolic activity, oligomycin (Oligo, 10.5μM, Sigma), FCCP (7.74μM, Cayman Chemical) and rotenone/antimycinA (R/AA, 11.5μM and 9μM, Cayman Chemical and Sigma, respectively) were injected in a sequential fashion. A minimum of 4 technical replicates were plated for every sample. Initial analysis was done in Wave for bubble exclusion, final analysis was done in GraphPad Prism, where the technical replicates of every sample were averaged and pooled for every biological sample. Basal OCR and PER were taken from the 4 th measurement point before oligomycin injection, whereas maximal OCR and PER were taken from the first measurement after FCCP injection. Isotopic labeling On day 5, both control and D-lactate-treated cells were plated for 24 hours in the presence of [U-13C 3 ] D-lactate (20mM; Merck). Extraction of intracellular metabolites, GC-MS, MID calculations and determination of fractional carbon contributions were performed as previously described 78 using the Metabolite Detector software package. Glucose, lactate and amino acid concentrations were detected with a YSI 2959D Biochemistry Analyzer (YSI Incorporated). RNA isolation, cDNA synthesis and qPCR analysis RNA was purified and converted to cDNA using a Nucleospin RNA XS kit (Macherey Nagel) and Taqman Reverse Transcription reagent kit (Thermo-Fisher) according to manufacturer’s instructions, respectively. qPCRs were carried out in a Quant Studio 7 Flex Real-time qPCR system (Thermo-Fisher). For every tested gene, 3 technical replicates were generated. The relative expression of every gene was always normalized to the mean value of the house-keeping gene ( Hprt ) on the same sample. The following primer pairs were used: Ldhd : Ldhd-fwd (GAATCGATGCACAGGTGTCAACCTC), Ldhd-rev (CAGCTCCGTGATCTGGTCCATAT); Ifng : Ifng-fwd (GCCACGGCACAGTCATTGA), Ifng-rev (TGCTGATGGCCTGATTGTCTT) 80 ; Gzmb : Gzmb-fwd (TCTCGACCCTACATGGCCTTA), Gzmb-rev (TCCTGTTCTTTGATGTTGTGGG) from Harvard Primers Bank; Hprt : Hprt-fwd (CATAACCTGGTTCATCATCATCGC), Hprt-rev (TCCTCCTCAGACCGCTTTT). RNA-Seq library preparation and analysis Cells were analyzed either under resting conditions or after a short restimulation with plate bound anti-CD3 and anti-CD28 for 4 hours. Isolated RNA quality was assayed with a Fragment Analyzer System (Agilent), and all samples displayed high RNA quality (RQN > 8). cDNA libraries were generated using a Trueseq Stranded Total RNA Library kit (Illumina) according to manufacturer’s instructions. Paired-end sequencing (2×75 bp) was performed on an Illumina NextSeq500 device using a NextSeq500/550 High Output Kit v2. Reads were then displayed to the mm10 genome, and DESeq2 was used for differential gene expression assessment. Only genes with high expression profile (reads > 100) were considered for the analysis. Genes were considered as differentially regulated between different experimental conditions when the following requirements were met: log2FC > 1 and adjusted P < 0.01. ATAC-Seq library preparation and analysis Libraries were prepared using an ATAC-Seq Kit (Active Motif) according to manufacturer’s instructions. Quality of the libraries and fragment sizes were assessed by Fragment Analyzer System, and concentrations were determined using a Kapa Library Quantification Kit (Kapa Biosystems). The ATAC-seq libraries were quantified using Qubit assays and paired-end sequenced (2×76 nt) on an Illumina NextSeq2000 device. Quality control and analysis of the ATAC-seq libraries were performed using the AIAP pipeline 81 . The reads were mapped to the mouse mm10 genome, and peak files generated for each library were annotated using the Homer package 82 . The normalized peaks were visualized with the WashU Epigenome Browser 83 . Normalization of data To pool results from different experiments, data belonging to the same experiment were normalized according to the mean value of the control group (Th1 condition without the addition of any lactate) and subsequently pooled together in GraphPad Prism. Statistical analysis After pooling the data, the different groups were tested for normality by the D’Agostino-Pearson normality test. Data displaying a normal distribution were statistically analyzed using either One Way-ANOVA or Two Way-ANOVA tests. When the data set did not pass the normality test, non-parametric Kruskal-Wallis tests were employed. All the statistical analysis was carried out in GraphPad Prism. Significance was indicated as ∗p < 0.05; ∗∗p < 0.01; ∗∗∗p < 0.001; ∗∗∗∗p < 0.0001. For some parameters that did not reach statistical significance exact p-values were indicated. Author contributions AMA designed the experiments under the supervision of ML. AMA and VP performed the experiments. SS and MD analyzed RNA-Seq and ATAC-Seq data, respectively. AMA analyzed the data. LSB and DB analyzed the D-lactate tracing experiments, provided technical assistance in some experiments, and contributed to scientific discussions. MFM sequenced RNA-Seq and ATAC-Seq samples. AMA wrote the manuscript, and ML reviewed the text. Data availability statement The datasets for raw and processed RNA and ATAC sequencing data generated for this study are available in the gene expression omnibus (GEO) database. Acknowledgments We thank I. Panse, V. Holecska, and C. Rüster for expert technical assistance and M. Villa and D. Zaiss for helpful scientific discussions. Cell sorting was carried out at the Flow Cytometry Core Facility of the DRFZ. This study was supported by the German Research Foundation (DFG grants LO1542/4-1 and LO1542/5-1 to M.L.), the Einstein Center for Regenerative Therapies (ECRT) (EZ-2016-289 to A.M.A. and V.P.), the Willy Robert Pitzer Foundation (Pitzer Laboratory of Osteoarthritis Research, 21-033 to M.L.), and the Dr. Rolf M. Schwiete Foundation (Osteoarthritis Research Program, 2021-035 to M.L.). References 1. ↵ Lancki , D. W. , Hsieh , C. S. & Fitch , F. W . Mechanisms of lysis by cytotoxic T lymphocyte clones. 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Share D-Lactate drives cytotoxicity in Th1 cells by limiting mitochondrial ROS production through enhanced glyoxalase system activity Adrián Madrigal-Avilés , Valerie Plajer , Sebastian Serve , Maria Dzamukova , Leticia Soriano-Baguet , Dirk Brenner , Mir-Farzin Mashreghi , Max Löhning bioRxiv 2025.04.03.647060; doi: https://doi.org/10.1101/2025.04.03.647060 Share This Article: Copy Citation Tools D-Lactate drives cytotoxicity in Th1 cells by limiting mitochondrial ROS production through enhanced glyoxalase system activity Adrián Madrigal-Avilés , Valerie Plajer , Sebastian Serve , Maria Dzamukova , Leticia Soriano-Baguet , Dirk Brenner , Mir-Farzin Mashreghi , Max Löhning bioRxiv 2025.04.03.647060; doi: https://doi.org/10.1101/2025.04.03.647060 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Immunology Subject Areas All Articles Animal Behavior and Cognition (7643) Biochemistry (17717) Bioengineering (13910) Bioinformatics (42016) Biophysics (21477) Cancer Biology (18628) Cell Biology (25536) Clinical Trials (138) Developmental Biology (13392) Ecology (19935) Epidemiology (2067) Evolutionary Biology (24356) Genetics (15617) Genomics (22530) Immunology (17755) Microbiology (40437) Molecular Biology (17200) Neuroscience (88704) Paleontology (667) Pathology (2840) Pharmacology and Toxicology (4832) Physiology (7657) Plant Biology (15171) Scientific Communication and Education (2046) Synthetic Biology (4304) Systems Biology (9828) Zoology (2272)