Human Plasma-like Medium Improves T Lymphocyte Activation

Summary

T lymphocytes are critical for effective immunity, and the ability to study their behavior in vitro can facilitate major insights into their development, function, and fate. However, the composition of human plasma differs from conventional media, and we hypothesized that such differences could impact immune cell physiology. Here, we showed that relative to the medium typically used to culture lymphocytes (RPMI), a physiologic medium (human plasma-like medium; HPLM) induced markedly different transcriptional responses in human primary T cells and in addition, improved their activation upon antigen stimulation. We found that this medium-dependent effect on T cell activation is linked to Ca²⁺, which is six-fold higher in HPLM than in RPMI. Thus, a medium that more closely resembles human plasma has striking effects on T cell biology, further demonstrates that medium composition can profoundly affect experimental results, and broadly suggests that physiologic media may offer a valuable way to study cultured immune cells.

Graphical Abstract

Highlights

• •Activation of T lymphocytes in plasma-like medium is much more efficient
• •RPMI is severely hypocalcemic relative to human plasma and this impacts activation
• •Non-physiological levels of nutrients in RPMI alter lymphocyte metabolism

Biological Sciences; Immunology; Immunological Methods

Introduction

Adaptive immune systems involve the movement of immune cells throughout the internal milieu of the blood and interstitial spaces to recognize foreign agents and respond to ensure the health of the host. T lymphocytes are central effectors of immunity in infectious diseases, autoimmunity, and cancer. T cell activation by cognate antigen is a complex process influenced by both intrinsic and extrinsic factors. Ligation of the αβ-T cell receptor by peptide antigens bound to major histocompatibility complex (MHC) class I/II initiates a number of signaling events culminating in the activation of a robust transcriptional program, which is key for an appropriate response.

The extracellular environment of the T lymphocyte has increasingly been recognized as a major influence on the characteristics and magnitude of the immune response. Namely, the availability of nutrients/second messengers in the environment, and the consequent changes in the metabolic status of the cell, are critical for shaping an appropriate T cell response. Recent publications have highlighted the influence of lipids, glucose, and amino acid metabolism on both the magnitude and characteristics of T cell responses (Pearce et al., 2009, van der Windt and Pearce, 2012, Sinclair et al., 2013, O'Sullivan et al., 2014, Buck et al., 2017, Ma et al., 2017, Werner et al., 2017, Jacobs et al., 2018). In addition to metabolic changes, ligation of the T cell receptor also induces the influx of extracellular calcium ions via the STIM/Orai channel, leading to activation of downstream transcription factors such as NFAT (Smith-garvin et al., 2010, Derler et al., 2016). Although a complete deficiency of this process has been studied in multiple contexts, the influence of subtler variations in extracellular calcium levels on T cell activation remain unclear (Feske et al., 2006, Prakriya et al., 2006).

Formulations of common cell culture media such as RPMI-1640 were developed in the mid-20^th century to optimize in vitro growth of cell lines and have since undergone remarkably little change (Eagle, 1955, McCoy et al., 1959, Moore et al., 1966). Despite a growing focus on the effects of metabolic changes during T cell activation and proliferation, culture conditions that more closely resemble the in vivo milieu have not been studied. Recently, several studies in non-immune cells have described the use of modified traditional media or new systematically constructed synthetic media designed to either improve growth in cell culture or to better model the in vivo environment (Favaro et al., 2012, Schug et al., 2015, Pan et al., 2016, Cantor et al., 2017, Vande Voorde et al., 2019). Among these is human plasma-like medium (HPLM), which contains a cocktail of 31 components that are absent from the defined formulations of RPMI and other commonly used basal culture media (Cantor et al., 2017). HPLM further contains at physiologically relevant concentrations other typical media components such as glucose, amino acids, and salt ions. It is worth noting that all of these defined components may be otherwise present at non-physiological levels in fetal bovine serum (FBS), the most widely used tissue culture supplement (Cantor et al., 2017). And therefore, HPLM is instead supplemented with 10% dialyzed FBS (HPLM^dFBS). Here, we asked how HPLM^dFBS influences gene expression and activation of cultured primary human T lymphocytes.

Results

Transcriptome Analysis Reveals Extensive Differences in T Lymphocytes Activated in HPLM^dFBS Compared with RPMI^dFBS

T lymphocytes in vivo undergo broad transcriptional re-programming following TCR activation, and this process occurs in the context of a rich internal milieu containing high levels of amino acids, lipids, and a variety of small organic metabolites (Crabtree, 1989). In contrast, typical in vitro methods used to study these same processes are based on T cells cultured in RPMI, which contains a collection of nutrients at non-physiologic concentrations (Moore et al., 1967). Therefore, we evaluated activation in naive CD4/CD8⁺ T cells stimulated in HPLM^dFBS compared with RPMI analogously supplemented with 10% dialyzed serum (RPMI^dFBS) to restrict our downstream analysis of potential phenotypic differences to defined media components only (Figure 1A, Table S1). We then activated purified human naive T lymphocytes from three individual donors with plate-bound anti-CD3/CD28 antibodies for 48 or 120 h in either HPLM^dFBS or RPMI^dFBS, isolated polyadenylated mRNAs, and characterized the transcriptional differences between these two conditions via deep sequencing. Principal component analysis revealed changes between 48 and 120 h of activation independently of the medium used. Nonetheless, the 2^nd and 3^rd principal components divided each group of samples (RPMI^dFBS-48 h, RPMI^dFBS-120 h, HPLM^dFBS-48 h, and HPLM^dFBS-120 h) into clear clusters revealing the transcriptional differences between HPLM^dFBS and RPMI^dFBS (Figure 1C). We next used gene set enrichment analysis (GSEA) to identify statistically significant differences in 29 different Kyoto encyclopedia of genes and genomes (KEGG) pathways (Kanehisa and Goto, 2000, Kanehisa et al., 2019). Nine pathways were significantly different at 48 h, 19 significantly different at 120 h, and one pathway was shared between both timepoints (Figure S1). Among these we observed a striking enrichment of pathways involved in DNA replication and cell cycle in HPLM^dFBS at 120 h post-activation and an enrichment of pathways involved in T cell activation at 48 h (Figure S1). In particular, essentially every gene in the KEGG DNA replication pathway exhibited increased expression in HPLM^dFBS relative to RPMI^dFBS (Figure 1D). Thus, T cell activation in HPLM^dFBS was superior to RPMI^dFBS, and this difference was readily apparent as early as 48 h post activation.

Figure 1.

Transcriptomic Analysis Reveals Major Differences between Human Lymphocytes Activated in HPLM^dFBS Relative to RPMI^dFBS

(A) Schematic of the comparative compositions of RPMI^dFBS, HPLM^dFBS, and HPLM^dFBS-Min. Detailed composition can be found in Table S1.

(B) Experimental outline for T cell activation in either HPLM^dFBS or RPMI^dFBS and downstream transcriptome analysis.

(C) Transcriptional differences between primary naive human mixed CD4⁺ and CD8⁺ T cells from three different donors activated in HPLM^dFBS or RPMI^dFBS as depicted in (B) were measured via RNA-sequencing. These data were used to generate PCA plots showing principal components 2 and 3 at the indicated timepoints.

(D) Heatmap showing the Log₂(fold change) in transcript abundance for genes involved in the KEGG DNA replication pathway using the RNA-sequencing data generated as described in (B).

There were also marked medium-dependent transcriptional differences across several metabolic pathways (Table 1). For instance, we found that HPLM^dFBS induced large increases in the expression of genes involved in amino acid metabolism, including the KEGG annotated pathways: arginine/proline metabolism; glycine/threonine/serine metabolism; and alanine, aspartate, and glutamate metabolism. These differences may be driven as a result of the roughly 2–10 fold differences in availability of arginine, aspartate, serine, and glutamate between the two media (Table S1). We also found that HPLM^dFBS induced increased relative expression of genes involved in the p53 signaling pathway as well as in various nucleic acid metabolism pathways (e.g. DNA repair, pyrimidine metabolism, RNA polymerase, spliceosome, and homologous recombination). In contrast, HPLM^dFBS also induced a relative decrease in the expression of genes associated with several other pathways, including glycerophospholipid and cytochrome p450 metabolism, cell adhesion, allograft rejection, graft vs. host disease, type 1 diabetes, cytokine receptor interactions, and autoimmune thyroid disease. Taken together, these results suggest that HPLM^dFBS promotes a T cell expression signature that is more to promote proliferation and to restrain autoimmunity.

Table 1.

Transcriptional Differences in Metabolic Genes in T Cells Cultured in HPLM^dFBS

	Fold Change in Expression in HPLMdFBS
Serine Biosynthesis
PHGDH	6.10
PSAT1	5.30
PSPH	1.25
Glycine, Arginine, Proline Biosynthesis
SHMT1	1.80
SHMT2	1.33
PYCR1	4.32
ASS1	81.00
Aspartate Biosynthesis
GOT1	1.45
Cholesterol Biosynthesis
HMGCS1	0.38
HMGCR	0.49
MVD	0.48
FDFT1	0.47

HPLM^dFBS Is Superior to RPMI^dFBS in Supporting Naive Human CD4/CD8⁺ T Cell Activation

Guided by our RNA-Seq data, we hypothesized that T cell activation and proliferation would be more efficient in HPLM^dFBS. Thus, we went on to measure markers of activation in antigen-stimulated naive human T cells (Figure 1). In both CD4⁺ and CD8⁺ T cells from five different healthy donors, we observed a significant increase in CD25 and CD69 in HPLM^dFBS compared with RPMI^dFBS (Figure 2A). We also carried out time courses spanning multiple days and the differences in this case were robust at every time point examined (Figure S2A). In addition, the use of increased anti-CD3/CD28 antibody concentrations during the activation led to a nearly equivalent maximal response rate in both conditions (i.e. >90% positive for both CD25 and CD69) (Figure 2A). This result suggests that HPLM^dFBS effectively reduces the activation threshold, as further supported both by the relatively unique appearance of large activated T cell clusters in the HPLM^dFBS cultures, as well as a marked difference in cell size between the two conditions (Figure 2B). Given that the T cells activated in RPMI^dFBS exhibited both a bimodal size distribution and much larger absolute size within the unstimulated population, this relative cell size difference was likely driven by defective activation. Furthermore, as anticipated from the transcriptional differences described earlier, we also found that the rapid proliferation of activated T cells in HPLM^dFBS was far less apparent in RPMI^dFBS (Figure 2C). Lastly, although HPLM was not designed to mimic the in vivo milieu of mice, we also tested activation of murine T cells in HPLM^dFBS versus RPMI^dFBS, as this is a popular model used in the field. Again, we observed greatly improved activation in HPLM^dFBS, suggesting that the mechanism responsible is evolutionarily conserved. In addition, these results would suggest that HPLM is better suited to the in vitro culture of both murine and human T cells.

Figure 2.

Primary Human T Cell Activation Is Superior in HPLM^dFBS Compared with RPMI^dFBS

(A) Flow cytometric measurement of T cell activation markers CD25 and CD69 on purified naive human T cells following stimulation with either 1 or 10 μg of plate-bound anti-CD3 (αCD3)/CD28 in HPLM^dFBS or RPMI^dFBS for 16 h. Data shown are representative of four different experiments each conducted with cells isolated from a different healthy donor (Student's t test; paired; two-tails; *p < 0.05, **p < 0.01, ***p < 0.001).

(B) Bright-field microscopy images of naive T cells stimulated with 1 μg of plate-bound anti-CD3/CD28 in either HPLM^dFBS or RPMI for 16 h.

(C) Flow cytometry histograms of CellTrace Violet staining of naive T cells stimulated in either HPLM^dFBS or RPMI^dFBS (left) with quantitation of the fraction of CD4⁺ T cells that have undergone at least one division (right). Columns represent the mean of three experiments, each done with cells isolated from a different healthy donor (Student's t test; unpaired; two-tails; *p < 0.05). Error bars represent the SEM.

Physiological Calcium Availability Augments T Cell Activation

We next asked which component(s) of HPLM^dFBS dictated the relative differences in T cell activation. To do so, we first compared T cell activation HPLM^dFBS, HPLM-Min (which contains only the defined amino acids, glucose, vitamins, salts, and 10% dialyzed serum; see Table S1), and (Cantor et al., 2017) and RPMI^dFBS (Figure 1A, Table S1). Further, we also included a medium derivative in which we supplemented all HPLM-specific polar metabolites to RPMI^dFBS (RPMI-Metabolites). We ultimately observed an equivalent extent of activation in the HPLM^dFBS and HPLM-Min conditions and a significantly reduced relative extent of activation in both RPMI^dFBS and RPMI-metabolites (Figure 3A). These results suggest that in this context, the relative differences in activation between HPLM^dFBS and RPMI^dFBS were instead due to concentration differences in amino acids, glucose, or salt ions. And indeed, one striking concentration difference among these is that of calcium (Ca²⁺), which is provided by HPLM at a defined concentration of 2.4 mM but is instead present in RPMI at a defined level of 0.4 mM, (Table S1), which is markedly hypocalcemic relative to the in vivo milieu (2–2.5 mM) (Goldstein, 1990). In turn, we in fact found that supplementing RPMI^dFBS with 2 mM CaCl₂ (RPMI+Ca²⁺) was sufficient to achieve T cell activation to an extent equivalent to that seen in HPLM^dFBS (Figure 3A).

Figure 3.

RPMI^dFBS Is Severely Hypocalcemic Relative to Human Plasma and HPLM^dFBS

(A) Measurement of activation marker CD25 on CD4⁺ T cells comparing RPMI^dFBS and HPLM^dFBS-min supplemented with various metabolite components unique to HPLM^dFBS. Columns represent the mean with error bars showing the standard error (one-way ANOVA comparing other conditions to HPLM^dFBS with p values calculated by Dunnett test; *p < 0.05).

(B) Measurement of activation marker CD25 on CD4⁺ T cells activated in HPLM^dFBS, RPMI^dFBS, or RPMI^cFBS. Experiment was repeated four times with each repeat using a different healthy human donor (one-way ANOVA; Tukey's test; *p < 0.05).

(C) Flow cytometric plots of calcium flux following primary stimulation of isolated human CD8⁺ T lymphocytes in either RPMI^dFBS or HPLM^dFBS (left) as well as quantification of the area under the curve (right). Quantification shows data from five experiments each done with a different individual donor, and error bars show standard error (one-way ANOVA; Tukey's test; **p < 0.01, ***p < 0.001).

(D) Flow cytometric plots of calcium flux following primary stimulation of isolated human CD8⁺ T lymphocytes in RPMI^dFBS supplemented with the indicated concentrations of calcium chloride. Quantification shows data from five experiments each done with a different individual donor, and error bars show standard error (one-way ANOVA; Tukey's test; **p < 0.01, ***p < 0.001).

It is worth noting that basal media used to culture T lymphocytes (often RPMI) are instead typically supplemented with 10% unmodified FBS (RPMI^FBS), and so we next wanted to determine the Ca²⁺ concentration of RPMI^FBS and ask how this particular complete medium influenced relative T lymphocyte activation as well. We found that [Ca²⁺] was approximately 3.9 mM in our typical stock FBS, and thus, a 10% supplement to basal RPMI would result in a RPMI^FBS Ca²⁺ concentration of ∼0.8 mM, a value that is still considered hypocalcemic although is closer to physiologic levels. We next found that TCR stimulation of naive T cells in RPMI^FBS induced activation to an extent nearly equivalent to that in HPLM^dFBS (Figure 3B), suggesting that 10% unmodified FBS provides RPMI sufficient Ca²⁺ to achieve comparable activation. We next examined Ca²⁺ flux following TCR stimulation in RPMI^dFBS, RPMI^Ca2+, and HPLM^dFBS. It is worth noting that most calcium flux protocols are carried out in Hank's balanced salt solution or Ringer's solution; however, some studies have described a decreased Ca²⁺ flux in RPMI relative to these solutions (Prakriya et al., 2006, Gwack et al., 2008, Bertin et al., 2014). We observed a striking decrease in the amount of Ca²⁺ entering T cells following activation in RPMI^dFBS, as compared with either HPLM^dFBS or RPMI^Ca2+ (Figure 3C). Taken together, our results suggest that the relatively greater threshold for T cell activation in RPMI^dFBS resulted from lower Ca²⁺ availability.

Our results also raise the possibility that in vivo Ca²⁺ levels can influence T cell activation and that hypocalcemic (or hypercalcemic) patients may be more prone to immunodeficiency (or autoimmunity), and in fact others had previously shown that extracellular [Ca²⁺] can influence cytokine production in murine T cells (Zimmermann et al., 2015). Moreover, our observations indicated that RPMI^dFBS poorly recapitulates in vivo conditions, given the hypocalcemic conditions it provides to cells. Thus, we next titrated Ca²⁺ levels in basal RPMI in 0.5 mM increments, up to a maximum of 2.2 mM, and then measured TCR-induced Ca²⁺ flux. We again observed that basal RPMI induced a meager Ca²⁺ flux, but the supplementation of [Ca²⁺] from 0.7 to 2.2 mM yielded Ca²⁺ fluxes that were virtually identical in both magnitude and kinetics (Figure 3D), suggesting that even at the lower end of physiologically reported levels, the Ca²⁺ flux rates can reach achieve maximum levels and that greater Ca²⁺ levels likely do not affect the propensity of in vivo T cell activation. Nonetheless, the [Ca²⁺] in basal RPMI is insufficient to promote full Ca²⁺ flux or T cell activation.

HPLM^dFBS Promotes CD8⁺ T Cell Effector Cytokine Production

We next evaluated cytokine production in CD8⁺ T cells activated in HPLM^dFBS or HPLM^dFBS-Min. We activated T cells in RPMI^dFBS and grew them for 14 to 21 days supplemented with IL-2 prior to restimulation and measurement of cytokine production. We find that TNFα and IFNγ production was similar in HPLM^dFBS or HPLM^dFBS-Min but substantially greater than RPMI^dFBS (Figure 4A). Similar results were obtained with phorbol myristate acetate (PMA) and ionomycin or anti-CD3 antibodies cross-linked with protein A. IFNγ production was slightly reduced in HPLM^dFBS compared with HPLM^dFBS-min although this did not reach statistical significance. We next examined whether this difference was due to the media composition during the initial stimulation or the subsequent restimulation by activating and expanding the cells in HPLM^dFBS or RPMI^dFBS and then switching them to other media just prior to restimulation (Figure 4B). Under these conditions, we observed robust cytokine production in cells that were activated in HPLM^dFBS or RPMI^dFBS and then transferred to HPLM^dFBS or RPMI^dFBS supplemented with 2mM Ca²⁺ (Figure 4B). However, irrespective of the initial activation medium, cells instead transferred to RPMI^dFBS exhibited reduced cytokine production levels, suggesting that [Ca²⁺] is a critical factor at the time of restimulation.

Figure 4.

T Cells Activated in HPLM^dFBS Produce Higher Levels of Effector Cytokines

(A) Levels of cytokines produced in primary human T lymphocytes following restimulation after being expanded in the indicated medium. T lymphocytes from 5 to 14 individuals were tested across two to three experiments, with the error bars representing standard deviation (one-way ANOVA; Tukey's test; *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001).

(B) Quantification of cytokine production in primary human T lymphocytes expanded in the indicated medium, switched to fresh medium of the indicated type, and then restimulated. Columns represent the mean of measurements from three experiments each with two individuals, with the error bars representing the standard error (one-way ANOVA; Tukey's test; *p < 0.05, **p < 0.01, ***p < 0.001).

CD19 CAR-T Cell Transduction Efficiency in HPLM^dFBS Is Similar to Other Commonly Used Media

T lymphocytes have become a central focus in the cancer immunotherapy field, and many clinical protocols require in vitro culture and expansion of human T cells engineered with chimeric antigen receptors (CAR-T cell) (Newick et al., 2018). Therefore, we wanted to ask whether pan naive T cells cultured in HPLM^dFBS exhibit improved transduction efficiency for lentiviruses that express CAR-T cell receptors. To do so, we first evaluated how HPLM^dFBS affected activation relative to that in two other synthetic media commonly used in clinical CAR-T expansion protocols: a mixture of AIM V and RPMI (supplemented with 5% human serum, referred to as AIM V here) and X-VIVO 15 (serum free). Following stimulation with plate bound anti-CD3/CD28 antibodies, we observed equivalent CD25 expression levels in HPLM^dFBS, HPLM^dFBS-Min, and AIM V, which were ultimately greater than those induced by culture in X-VIVO 15 (Figure 5A). We then observed that the lentiviral transduction efficiencies of both CD4⁺ and CD8⁺ T cells were equivalent in HPLM^dFBS, HPLM^dFBS-Min, and AIM V media and greater than those in X-VIVO 15 (Figure 5B). Taken together, HPLM^dFBS performs comparably or better than commonly used culture media that have been used to generate CAR-expressing T cells.

Figure 5.

Lentiviral Transduction Rates Are Equivalent in T Cells Cultured in HPLM^dFBS and Conventional Culture Media

(A) Quantification of levels of activation markers in CD4⁺ (left panel) and CD8⁺ T cells following activation in the indicated medium. Columns represent the mean of measurements from three experiments each conducted with cells from a different individual, with error bars representing the standard error (one-way ANOVA; Tukey's test; *p < 0.05, **p < 0.01).

(B) Quantification of transduction efficiency human CD4⁺ (left panel) and CD8⁺ T cells (right panel) with CD19-CAR expressing lentiviruses activated in the indicated media. Columns represent the mean of measurements from three experiments each conducted with cells from a different individual, with error bars representing the standard error (one-way ANOVA; Tukey's test).

Discussion

The development of cell culture techniques in the mid 20^th century heralded an enormous advance in life sciences research by permitting tissue-free in vitro studies of cell physiology. However, media formulations developed in the 1960s remain almost universally used today. Here, we took advantage of a recent effort to systematically develop a new cell culture medium that was designed to more closely model human plasma (HPLM) by extending the use of HPLM to the study of primary human lymphocytes. We show that compared to RPMI^dFBS, HPLM^dFBS induces a much more robust activation of naive T cells and a marked increase in the section of effector cytokines. Further, comparative RNA-Seq methods revealed a large number of medium-dependent T cell transcriptional differences across several metabolic pathways.

Through the use of HPLM, we also find that calcium is a rate-limiting component for lymphocyte activation, a result that corroborates recent work that describes the induction of acute Ca²⁺ flux following TCR engagement (Zhang et al., 2005, Prakriya et al., 2006). Others have also described a relative increase in effector cytokine secretion for murine T cells cultured in IMDM ([Ca²⁺] = 1.5 mM) or calcium supplemented-RPMI^dFBS compared with basal RPMI (Zimmermann et al., 2015). Similarly, we found in primary human T cells that relative activation, proliferation, and effector cytokine secretion are reduced in RPMI^dFBS lacking any additional Ca²⁺ supplementation. It is likely that the use of 10% FBS as a common supplement to basal media sufficiently augments the defined calcium concentration of RPMI, as we measured the Ca²⁺ levels of stock FBS as approximately 3.9 mM. Although our current study suggests that the resultant RPMI^FBS Ca²⁺ concentration (∼0.8 mM), which still corresponds to a severely hypocalcemic condition, is sufficient to achieve maximal TCR-induced Ca²⁺ flux and activation, it is now clear that calcium level is an independent parameter that should be considered in studies of T cell biology. For instance, it is possible that the cross-linking of anti-CD3 antibodies used in the calcium flux methods masks an underlying defect that would be present in response to physiological antigens. Further, the calcium flux assay only assesses calcium changes for the first several minutes of a response, whereas the activation process is much more dynamic and can extend over the course of h/day in vivo.

Although our results comparing HPLM^dFBS with a derivative containing only amino acids, glucose, vitamins, salts, and 10% dialyzed serum (HPLM-min) did not suggest an induction of dramatically different phenotypic outputs, a caveat of our study is that prior work with HPLM^dFBS described a much more robust serum dialysis procedure (Cantor et al., 2017). Thus, it is possible that our commercial source of this supplement was far less stringently dialyzed, and in turn, perhaps still contained appreciable levels of several polar metabolites, which would mask any putative differences between the two HPLM derivatives.

This study was primarily focused on the impact of the extracellular milieu on early T cell activation events. As we observed significant differences in the activation efficiency of human T lymphocytes cultured in either HPLM^dFBS or RPMI^dFBS, we restricted our subsequent analyses to these early timeframes. We would speculate that culturing T lymphocytes in physiologic medium for longer time frames would have major impacts on the proliferation, activation, and metabolic state of the T cells. Similarly, metabolic status has been shown to have an impact on T cell differentiation and type of effector cytokines being secreted (Buck et al., 2015). It is likely that culture in HPLM would impact these processes as well; however, it was outside the purview of our study.

We also found that HPLM^dFBS had a large relative impact on the transcriptional response of activated human T cells, revealing major differences that led to our subsequent focus on extracellular [Ca²⁺]. However, many of the most significant differentially regulated genes in our dataset were associated with metabolic pathways. In particular, we found that HPLM^dFBS induced large increases in the expression of genes involved in several amino acid metabolism pathways, including significant upregulation of genes that encode various rate-limiting enzymes in such pathways (ASS1, PHGDH, PYCR1, GOT1). It is likely that such differences result from marked differences in the availability of several amino acids between HPLM^dFBS and RPMI^dFBS. For instance, arginine, which is present at nearly 10-fold greater levels in basal RPMI compared with human blood and (HPLM), have been suggested to be critical for T cell proliferation, differentiation, and survival, and previous studies have described improved T cell survival upon arginine supplementation to 3 mM (Rodriguez et al., 2007, Geiger et al., 2016). Thus, it is likely that in the in vivo environment arginine is even more limiting than previously thought.

Our data broadly highlight the fact that commonly used conditions used to culture and examine T lymphocytes in vitro may not be ideal for metabolic studies, and we also specifically identify one extracellular component (calcium) that can be easily considered by others in the field. Our approach also further demonstrates the value of using HPLM to improve the modeling capacity of in vitro cell culture systems.

Limitations of the Study

In this work we characterize for the first time the impact of physiologic media on the metabolism and activation of human T cell in vitro culture and highlight the drawbacks of conventional media formulations. Although we did observe significant transcriptional changes in multiple critical metabolic pathways, we did not explore the mechanisms behind this nor the downstream impacts on longevity, memory/effector differentiation or differentiation to different subsets such as Th1, Th2, Tregs, and others. It is known that the metabolic state has a critical impact on these processes (van der Windt and Pearce, 2012, Berod et al., 2014, Lochner et al., 2015), and it is likely that physiologic media is a superior model of the in vivo condition; however this hypothesis remains to be tested. In addition to this, our analysis was restricted to the transcriptome and effector/proliferative functions of T lymphocytes rather than direct investigation of the metabolic state of primary cells cultured in HPLM relative to conventional media. Lastly, although we focused exclusively on T lymphocytes, it is likely that B cells, myeloid cells, and other lineages are likely to be similarly affected, although again this remains to be tested.

Methods

All methods can be found in the accompanying Transparent Methods supplemental file.

Published: January 24, 2020

Data and Code Availability

The RNA-Seq data from this study were uploaded to GEO and may be accessed at: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE135936.