PT-MPS platform and perfusion system
Nortis microfluidic chips are molded from polydimethylsiloxane, a semi-transparent, flexible, generally bio-compatible, and gas-permeable silicone polymer (Fig. 1). While the footprint of the Nortis Triplex chip is relatively small, the equipment required for perfusion including chip platform, shelves, docking station, and pneumatic pump are relatively large. In order to reduce the footprint of the Triplex chip during perfusion and meet the levels of containment required by the National Aeronautics and Space Administration (NASA), we partnered with BioServe Space Technologies to design, machine, and fabricate a novel perfusion platform as previously described.19
Experimental design and loss of devices to mold contamination
During disassembly of the chips from the housing unit, mold was observed on the exterior of several chips near the matrix port, cell seeding port, and edges. Mold was also observed within the flow path of some devices. Media overflow from the injection port was noted from 9.7% (14/144) of the channels before integration into the BioServe perfusion platform and may have contributed to the contamination. Consequently, channels that had visible mold, issues with RLT perfusion during RNA isolation, or notably discolored effluents were excluded from the analyses. In total, 65.3% (47/72) and 66.7% (48/72) of the ground and flight samples were included for effluent analyses, respectively. 72.2% (39/54) and 61.1% (33/54) of the ground and flight samples were analyzed by RNAseq, respectively. 94.4% (17/18) and 55.6% (10/18) of the ground and flight samples were used for the analysis of vitamin D metabolites, respectively. The number of usable samples for each donor separated by treatment and condition (ground vs flight) is summarized in Table 1.
Table 1
Number of samples usable for effluent analysis and RNAseq analysis. Fractions represent the number of samples included in each analysis over the total number of samples at the beginning of the experiment.
|
|
Effluent Analysis Samples
|
RNAseq Analysis Samples
|
|
|
Donors
|
Donors
|
|
|
M1
|
M2
|
F1
|
F2
|
M1
|
M2
|
F1
|
F2
|
GROUND
|
Media
|
2/9
|
0/9
|
5/12
|
6/6
|
2/6
|
0/3
|
3/6
|
3/3
|
Vitamin D
|
5/6
|
3/3
|
6/6
|
3/3
|
5/6
|
3/3
|
6/6
|
2/3
|
2% Human Serum
|
5/6
|
3/3
|
6/6
|
33
|
5/6
|
2/3
|
6/6
|
2/3
|
FLIGHT
|
Media
|
6/9
|
7/9
|
10/12
|
0/6
|
3/6
|
3/3
|
4/6
|
0/3
|
Vitamin D
|
5/6
|
0/3
|
3/6
|
2/3
|
4/6
|
0/3
|
2/6
|
2/3
|
2% Human Serum
|
5/6
|
2/3
|
6/6
|
2/3
|
6/6
|
2/3
|
5/6
|
2/3
|
Transcriptional response of PTECs to 2% human serum in ground and flight conditions
To characterize the changes induced by serum exposure and identify condition-dependent responses, RNA from multiple replicates of control- or serum-treated PT-MPS was isolated and transcriptomic profiles were measured by RNA-seq. Exposure of PT-MPS to 2% normal human serum resulted in differential expression of 2,389 and 2,220 genes compared to control in the ground and flight conditions, respectively, based on a fold change of at least 1.1 at an adjusted p-value threshold of 0.05. In the ground condition, 1,144 and 1,245 genes were up- and down-regulated, respectively, whereas in the flight condition 1,108 and 1,112 genes were up- and down-regulated, respectively (Fig. 2A). No genes were differentially expressed between 1) ground media vs. flight media, 2) ground serum vs. flight serum, or 3) (ground serum vs. ground media) vs. (flight serum vs. flight media), indicating that 1) flight alone did not impact PTEC gene expression, 2) the relative expression level for a given gene between the ground and flight serum-treated samples was similar, and 3) the flight condition did not affect the magnitude of change in expression of a gene between control treatment and serum treatments (i.e., the difference in differences).
To elucidate the functional networks regulated by serum exposure in PTECs, we performed Advaita gene ontology analyses and iPathwayGuide analyses on the genes differentially expressed between serum and control treatments in the ground and flight conditions. Gene ontology enrichment analysis showed over-representation of the set of DE genes in cellular component terms, such as mitochondrion (GO:0005739), plasma membrane (GO:0005886), extracellular space (GO:0005615), and condensed chromosome (GO:0000793) (Fig. 2B). While the false discovery rate (FDR) adjusted p-value calculated for each cellular component term was different between ground and flight, the number of DE genes within a given term was comparable suggesting the overall response to serum between ground and flight chips was similar (Fig. 2B). Advaita Pathway analysis revealed that several cellular pathways were significantly affected by serum treatment in both the ground and flight conditions including cell cycle (ground: p = 3.19x10− 6 and flight: p = 7.7x10− 6), cytokine-cytokine receptor interaction (ground: p = 6.93x10− 6 and flight: p = 1.12x10− 8), chemokine signaling (ground: p = 0.0337 and flight: p = 0.0039), peroxisome proliferator-activated receptor (PPAR) signaling (ground: p = 1.49x10− 4 and flight: p = 2.54x10− 5), and metabolic pathways (ground: p = 3.96x10− 17 and flight: 8.16x10− 15) (Figs. 2C and 2D). Most of the genes within the cell cycle, cytokine-cytokine receptor interaction and chemokine signaling pathways were upregulated. Examination of the cell cycle pathway showed upregulation of genes that promote progression through the G1, S, G2, and M stages of the cell cycle (Supplemental Figs. 1 and 2). Several members of the CC chemokine, CXC chemokine, and interleukin families were upregulated in the chemokine signaling and cytokine-cytokine receptor interaction pathways (Supplemental Table 1). On the other hand, the PPAR signaling and metabolic pathways were downregulated. More specifically, genes within fatty acid metabolism (ground: p = 7.39x10− 6 and flight: p = 3.79x10− 7), tricarboxylic acid cycle (ground: p = 4.05x10− 3 and flight: p = 4.09x10− 7), and steroid biosynthesis (ground: p = 3.3x10− 5 and flight: p = 1.9x10− 5) pathways were downregulated (Supplemental Table 2). Non-alcoholic fatty liver disease, Alzheimer disease, and Huntington disease pathways were affected only in the ground condition. Inspection of the DE genes within those pathways indicated that the statistical significance was largely driven by a group of mitochondrial genes associated with oxidative phosphorylation (Fig. 1C and 1D). Consistent with this observation, the oxidative phosphorylation pathway was far more impacted by 2% human serum treatment in the ground condition (p = 1.87x10− 24, 63 DE genes) than in the flight condition (p = 2.5x10− 6, 33 DE genes). Overall, these data suggest that serum exposure caused PTECs to activate a proliferative program, shift cellular bioenergetics, and promote a pro-inflammatory extracellular environment.
Next, we focused on gene-level changes to help delineate the biological consequence of exposure of PT-MPS to serum. First, we looked at metabolic reprogramming as it included the largest set of genes and was the most significantly impacted by serum treatment. Adenosine triphosphate (ATP) is a molecule that plays an important role in signal transduction (via being a substrate for kinases) and provides energy to drive a variety of cellular processes including transport of ions and solutes via ATP-binding cassette transporters such as the sodium-potassium-ATPase. PTECs generate the bulk of ATP through mitochondrial oxidative phosphorylation, wherein the transfer of electrons from nicotinamide adenine dinucleotide hydride (NADH) and dihydroflavin adenine dinucleotide (FADH2) to molecular oxygen (O2) through a series of protein complexes (complexes I-IV) in the mitochondrial inner membrane results in pumping of protons across the inner mitochondrial matrix membrane. This creates a transmembrane pH gradient that is subsequently utilized by complex V (or ATP synthase) to create ATP from adenosine diphosphate (ADP) and phosphate (Pi).20 The DE genes within the oxidative phosphorylation pathway were found to be involved in the mitochondrial electron transport chain, with representation of all five of the major respiratory chain protein complexes (Fig. 3). A greater number of genes were identified in the ground condition compared to flight condition (58 vs 27, respectively), though all DE genes in both conditions were downregulated by similar magnitudes suggesting that both ground and flight conditions had reduced mitochondrial respiration following serum treatment. The mitochondrion has its own genome which encodes thirteen proteins that participate in the electron transport chain.20,21 Thirteen of those mitochondrial encoded genes were downregulated in the ground condition, but not the flight condition (Fig. 4B). The expression of four key factors that control mitochondrial gene transcription including RNA polymerase mitochondrial (POLRMT), transcription factor A mitochondrial (TFAM), transcription factor B2 mitochondrial (TFB2M), and transcription elongation factor mitochondrial (TEFM), were unchanged with serum treatment in both the flight and ground conditions (adj. p-value = 1).
To fuel the mitochondrial electron transport chain and oxidative phosphorylation, a steady source of reducing equivalents of NADH and FADH2 are required.20 β-oxidation of fatty acids and intermediary metabolism in the tricarboxylic acid (TCA) cycle, each of which occur in mitochondria, are the primary processes that generate FADH2 and NADH.20 β-oxidation is the stepwise enzymatic process that shortens fatty acid chains by two carbon atoms, producing acetyl coenzyme A (acetyl-CoA), NADH, and FADH2.22 Acetyl-CoA can subsequently be utilized in the TCA cycle, a series of chemical reactions that oxidize acetate (derived from acetyl-CoA) to ultimately produce GTP, NADH, FADH2, and carbon dioxide.20
Serum treatment of the PT-MPS significantly reduced the expression of a set of genes that function in β-oxidation, catabolism, and synthesis of fatty acids including carnitine palmitoyltransferase 1 (CPT1A), a transporter that is rate-limiting in fatty acid β-oxidation, and acetyl-CoA carboxylase alpha (ACACA) and fatty acid synthase (FASN), the rate-limiting enzymes in fatty acid biosynthesis (Fig. 3C). In addition, serum caused a modest, but broad downregulation of genes within the TCA cycle and solute carrier 25 (SLC25) family, that are mitochondrial membrane transporters for a variety of ions and metabolic intermediates (Supplemental Table 1). Expression of the lipogenic enzymes (GPAT3, GPAT4, AGPAT1-5, DGAT1, and DGAT2) were unchanged (data not shown) whereas only lipin 1 (LPIN1) was significantly reduced (Supplemental Table 1). The expression of genes that are targets of the sterol-regulatory element binding transcription factor 2 (SREBF2) were considerably repressed (Supplemental Table 2). Because SREBF2 activity is inhibited in the presence of high cellular cholesterol levels, repression of SREBF2 target genes indicated that serum treatment increased cytosolic cholesterol levels. The transcriptional repression of genes involved in fatty acid metabolism, cholesterol metabolism, and intermediary metabolism (TCA cycle) strongly indicated that serum treatment caused metabolic reprograming in PTECs.
Next, we evaluated genes which could be potential maladaptive effectors in the tubular response to protein challenge. Serum treatment induced the expression of genes that function in the extracellular space and are associated with tissue remodeling. This group of genes included extracellular matrix proteins (e.g., fibronectin 1 (FN1) and transforming growth factor beta induced (TGFBI)), growth factors (e.g., platelet derived growth factor beta (PDGFB)), transcription factors (e.g., mothers against decapentaplegic homolog 3 (SMAD3)), and extracellular matrix modifying enzymes (e.g., matrix metallopeptidase 7 (MMP7), lysyl oxidase like 2 (LOXL2), transglutaminase 2 (TGM2)) (Fig. 3). It also induced pro-inflammatory molecules including chemokines (e.g., chemokine c-x-c motif chemokine ligand 5 (CXCL5)), cytokines (e.g., interleukin 8 (IL8), interleukin 23a (IL23A), tumor necrosis factor (TNF)), transcription factors (e.g., interferon regulatory factor 1 (IRF1)), and the lipocalin neutrophil gelatinase-associated lipocalin (NGAL or LCN2) (Fig. 4D). IRF1, LCN2 (NGAL), PLAUR, LOXL2, TGFBI, and SMAD3 are among the top 20 most significantly upregulated genes in PTECs following 2% human serum treatment (Supplemental Tables 3 and 4).
Because the loss of metabolic capacity and gain of pro-inflammatory and pro-fibrotic attributes could be detrimental to PTEC function, we next looked at whether the expression of proximal marker genes changed. Serum treatment caused a downregulation of several genes selectively expressed by PTECs in vivo including the water channel aquaporin 1 (AQP1) and the sodium potassium-transporting ATPase subunits alpha and beta (ATP1B1 and ATP1A1) (Fig. 4E). Concomitantly, there was downregulation of three key transcriptional regulators: peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PPARGC1A), estrogen related receptor alpha (ESRRA), and SREBF2, while forkhead box M1 (FOXM1) was induced (Fig. 4E). ATP1B1 and PPARGC1A were among the top 20 downregulated genes in the flight condition (Supplemental Table 4). Advaita upstream regulator analysis identified both TNF (ground: p = 9.0x10− 3 and flight: p = 2.4x10− 2) and FOXM1 (ground: p = 2.71x10− 9 and flight: p = 1.31x10− 8) as transcription factors likely to have been activated by serum treatment based on the number of consistently observed DE genes and gene interactions (Table 2). Conversely, SREBF2 (ground: p = 5.86x10− 9 and flight: p = 8.31x10− 9) and PPARGC1A (ground: p = 1.2x10− 1 and flight: p = 1.75x10− 2) were predicted to have been inhibited by serum treatment (Table 2). The target genes of PPARGC1A include genes involved in mitochondrial oxidative phosphorylation (e.g., CPT1A and EHHADHA) as well as genes with regulatory roles (e.g., ESRRA and SIRT3), while those of FOXM1 tend to be related to cell proliferation (e.g., CCNA1 and CCNB1) and DNA damage response (e.g., RAD51 and RAD54).
Table 2
Upstream regulators of the transcriptional response of PTECs to 2% human serum. Proteins predicted to have been inhibited or activated by 2% human serum treatment in PTECs in ground and flight conditions based on Advaita upstream regulator analysis. Upstream regulators with non-significant p-values are noted by red text.
|
|
Ground serum vs. Ground media
|
Flight serum vs. Flight media
|
Upstream regulator
|
Directional change
|
DE targets (+/-)/ DE targets
|
p-value
|
FDR p-value
|
DE targets (+/-)/ DE targets
|
p-value
|
FDR p-value
|
TNF
|
activated
|
32/45
|
6.15E-04
|
9.00E-03
|
31/42
|
1.00E-03
|
2.40E-02
|
FOXM1
|
activated
|
18/18
|
1.27E-10
|
2.71E-09
|
18/19
|
5.45E-10
|
1.31E-08
|
SREBF2
|
inhibited
|
15/15
|
2.99E-12
|
5.86E-09
|
15/15
|
3.76E-12
|
8.31E-09
|
PPARGC1A
|
inhibited
|
7/8
|
1.00E-03
|
1.20E-01
|
8/9
|
1.75E-04
|
1.40E-02
|
PPARA
|
inhibited
|
12/16
|
8.00E-03
|
4.94E-01
|
16/20
|
6.50E-05
|
8.00E-03
|
RXRA
|
inhibited
|
10/12
|
5.00E-03
|
3.57E-01
|
16/20
|
5.26E-06
|
1.00E-03
|
*For each upstream regulator, the predicted directional change in activity (activation or inhibition) with 2% human serum treatment is shown. The DE targets (+/-) / DE targets column depicts the number of target genes with a directional change in expression consistent with the predicted change in upstream regulator activity over the total number of differentially expressed target genes for that upstream regulator. The unadjusted p-value and FDR adjusted p-value is presented for each upstream regulator.
|
PT-MPS biomarker responses to 2% human serum in flight and ground conditions
To validate the observations that 2% human serum appeared to promote transcription of cellular proliferation and induce proinflammatory genes, we quantified KIM-1 and IL-6 from device effluents. The magnitude of 2% human serum-induced secretion of KIM-1 and IL-6 varied by donor but was consistently increased relative to media control (Fig. 4A and 4B). Serum treatment significantly increased KIM-1 secretion relative to media control for both ground (20.9-fold, p < 0.0001) and flight conditions (14.5-fold, p < 0.0001) (Fig. 4C). There was no difference in serum-induced secretion of KIM-1 between ground and flight. IL-6 secretion was significantly increased by serum treatment relative to media control in both ground (3.3-fold, p = 0.0004) and flight conditions (5.2-fold, p < 0.0001) (Fig. 4D). The difference in IL-6 change from media control to serum between the flight and ground condition was not statistically different (p = 0.073, linear mixed effects model) suggesting that there was no interaction between microgravity and serum exposure on IL-6 secretion.
Transcriptional response of PTECs to vitamin D in ground and flight conditions: To characterize the changes induced by vitamin D exposure and identify condition-dependent responses, RNA from multiple replicates of control- or 25(OH)D3-treated PT-MPS was isolated and transcriptomic profiles were measured by RNA-seq. Comparing the differentially expressed (DE) genes revealed 598 DE and 147 DE in the ground and flight groups, respectively (Fig. 5A). In each condition roughly half the genes were upregulated, and half were downregulated. Gene ontology enrichment analysis revealed over-representation of the set of DE genes in cellular component terms such as mitochondrion (GO:0005739) and mitochondrial respiratory chain (GO:0005746) (Fig. 5B). The number of DE genes within each term varied by condition, with the ground condition having a greater number DE in each term. Advaita iPathwayGuide analysis showed the pathways most affected by vitamin D treatment were metabolic pathways, oxidative phosphorylation, and cytokine-cytokine receptor interaction (Fig. 5C). Oxidative phosphorylation was more affected by vitamin D treatment on ground (p = 1.43x10− 19, 42 DE genes) than in flight (p = 1.22x10− 8, 19 DE genes). Consistent with this observation, more genes within the electron transport chain were downregulated in ground than in flight (Fig. 5D). Vitamin D treatment induced several members of the c-x-c motif ligand family in both conditions including CXCL1, CXCL2, CXCL3 and CXCL6, while the cytokine interleukin 6 (IL6) was only induced with 25(OH)D3 treatment for the ground condition (Fig. 6E). The proliferation associated genes FOXM1 and marker of proliferation Ki67 (Ki67) were only significantly upregulated in the ground condition (Fig. 5E).
Impact of microgravity on PTEC metabolism of vitamin D
25(OH)D3 undergoes multiple metabolic reactions within PTECs including bioactivation to 1α,25(OH)2D3 via CYP27B1 as well as inactivation through CYP24A1 mediated conversion to 24R,25(OH)2D3 and CYP3A5 mediated conversion to 4β,25(OH)2D3 (Fig. 6A) To evaluate the impact of microgravity on PTEC metabolism of 25(OH)D3, we quantified 25(OH)D3 and its primary metabolites 1α,25-dihydroxy vitamin D3, 4β,25-dihydroxy vitamin D3, and 24R,25-dihydroxy vitamin D3 in the device effluents. Expression of CYP3A5, CYP24A1, and CYP27B1 was detected in all samples (Fig. 6B). Formation of 1α,25(OH)2D3 and 4β,25(OH)2D3 was consistent across donors, whereas formation of 24R,25(OH)2D3 varied by donor (Fig. 6C). Formation of 1α,25(OH)2D3 (p = 0.1036), 4β,25(OH)2D3 (p = 0.4451), and 24R,25(OH)2D3 (p = 0.2228) did not differ between ground and flight (Fig. 6D). Consistent with formation of 1α,25(OH)2D3 and agonism of the VDR, the expression of CYP24A1 but not CYP3A5 or CYP27B1 was significantly higher in vitamin D treated samples than media controls for both ground and flight conditions (Fig. 6E). The expression of CYP24A1 was correlated with formation of 24R,25(OH)2D3 in ground samples (r = 0.77, p = 0.008) but not flight samples (r = 0.17, p = 0.715) (Fig. 6F).
PT-MPS biomarker responses to vitamin D in flight and ground conditions
To assess whether treatment with vitamin D resulted in effluent biomarkers, similarly to PT-MPS, we measured KIM-1 and IL-6 in flight and ground samples. Comparison of samples for both biomarkers demonstrated consistent increases for all four donors for flight and ground, although interpretation is limited by sample availability (Figs. 7A and 7B). Vitamin D treatment significantly increased KIM-1 secretion relative to media control for both ground (9.2-fold, p < 0.0001) and flight conditions (5.2-fold, p < 0.0001) (Fig. 7C). IL-6 secretion was significantly increased by Vitamin D treatment in ground (p < 0.0001) and flight (p = 0.0018) (Fig. 7D). In addition, when comparing levels of IL-6 in vitamin D-treated PT-MPS between ground and flight, the levels in flight were significantly lower in comparison to ground (p-value = 0.001).