Go to Top Go to Bottom
Anim Biosci > Volume 33(9); 2020 > Article
Shin, Lee, Oh, Jung, and Oh: Effects of gamma-aminobutyric acid and piperine on gene regulation in pig kidney epithelial cell lines



Gamma-aminobutyric acid (GABA) and piperine (PIP) are both nutritional supplements with potential use in animal diets. The purpose of this study is to investigate the effect of GABA and/or PIP treatment on the gene expression pattern of a pig kidney epithelial cell line.


LLCPK1 cells were treated with GABA, PIP, or both, and then the gene expression pattern was analyzed using microarray. Gene ontology analysis was done using GeneOntology (Geneontology.org), and validation was performed using quantitative real-time polymerase chain reaction.


Gene ontology enrichment analysis was used to identify key pathway(s) of genes whose expression levels were regulated by these treatments. Microarray results showed that GABA had a positive effect on the transcription of genes related to regulation of erythrocyte differentiation and that GABA and PIP in combination had a synergistic effect on genes related to immune systems and processes. Furthermore, we found that effects of GABA and/or PIP on these selected genes were controlled by JNK/p38 MAPK pathway.


These results can improve our understanding of mechanisms involved in the effect of GABA and/or PIP treatment on pig kidney epithelial cells. They can also help us evaluate their potential as a clinical diagnosis and treatment.


Gamma-aminobutyric acid (GABA) is one of inhibitory neurotransmitters known to be synthesized in the brain from glutamic acid via glutamic acid decarboxylase [1]. Its dysregulation can potentially result in seizure. Therefore, it is a common target to treat epilepsy [2]. GABA is known to act through its ionotropic type-A and -C receptors (GABAA and GABAC receptors) [3] and its metabotropic type-B receptor (GABAB receptor) [4]. GABAergic system, which involve the interaction of the neurotransmitter GABA and its receptors, was first discovered in the neuron of the brain tissue [5], but was shown to be present in several organs including kidney [6].
Piperine (PIP) is a major alkaloid present in seeds of black pepper ( Piper nigrum), long pepper (P. longum), and other pepper species (Piperaceae). It is responsible for pepper seeds’ characteristic biting taste [7]. Beside its dietary function, PIP is long known to have various physiological benefits including anti-inflammatory, anti-cancer, anti-oxidant, and bioavailability-enhancing activities [8]. Moreover, PIP has been proposed as an alternative to antibiotic growth promoter in animal feedings [9]. PIP can modulate GABAA receptors [10]. We have recently demonstrated that PIP and GABA have synergistic effect in pig kidney cell line LLC-PK1, resulting in increased erythropoietin (EPO) and EPO receptor (R) expression possibly via the activation of MAPK signaling cascade through GABAA receptor mediated signaling [11].
EPO is a pleiotropic cytokine that can affect infection and inflammation in kidney [12]. Thus, we hypothesized that GABA and PIP might be useful for treating or preventing possible kidney related diseases and infection. However, beside EPO and EPO-R upregulation, little is known about differential expression profiles of the genes following GABA and PIP treatment in kidney epithelial cells.
Thus, the objective of this research was to perform micro array analysis to determine effects of GABA and PIP on gene expression of pig kidney epithelial cells. Expression levels of genes in key pathways were validated. Results revealed that genes affected by GABA and PIP in expression level were associated with MAPK pathway. These results provide new insight into effects of GABA and PIP. They could be used to evaluate their impact on kidney epithelial cells.


Cell lines culture and treatment

LLC-PK1 (ATCC CL101) was obtained from the American Type Culture Collection (Manassas, VA, USA). Cells were cultured at 37°C with 5% CO2 in Dulbecco’s modified Eagle’s medium (Hyclone, Logan, UT, USA) with 8% Fetal Bovine Serum, 100 U/mL penicillin, and 100 μg/mL streptomycin (Welgene, Daegu, Korea). Treatments with GABA and PIP (Sigma Aldrich, St. Louis, MO, USA), MAPK inhibitors SB 202190 and SP600125 (Calbiochem, San Diego, CA, USA) was performed when cells reached 80% to 90% confluence. Cells were incubated at 37°C with 5% CO2 in DMEM without fetal bovine serum for 1 hour before treatments with 0.1 mM GABA and/or 5 μM PIP in final concentration.

RNA isolation

Prepared cells were harvested and RNAs were isolated using TRIzol reagent (Ambion, Carlsbad, CA, USA) or RNeasy min kit (Qiagen, Germantown, MD, USA). The purity and integrity of total RNA were checked using NanoDrop One (Thermo Scientific, Waltham, MA, USA).

Microarray analysis

cRNA was prepared from 1 to 5 μg total RNA using Agilent’s Quick Amp labeling kit (Agilent, Santa Clara, CA, USA). Labeling of probes, in vitro transcription, hybridization, and dyeing of chips were performed by Macrogen Gene Company Limited (Seoul, Korea). Then 1.65 μg of cRNA was hybridized to Agilent Porcine Gene Expression microarray (43,803 probes). Arrays were scanned for data export and processing using Agilent Feature Extraction v11.0.1.1 software on R 2.15.1. Shortly after, signal intensity was extracted. Quality check and filtering were performed by flag. Probe signal intensity was converted to log (base 2) value. Normalization for untreated, GABA, PIP, or both was performed using quantile normalization. Fold changes (FC) compared to untreated sample were calculated. Probes that yielded >1.5 or <−1.5 folds change with a p-value <0.05 in either treatment relative to untreated LLC-PK1 were retained, totaling 2,393 probes.

Differential gene expression analysis

Heatmapper [13] was used to generate heatmap plot representing genes using average linkage clustering method with Pearson measurement method. To evaluate biological functions of differentially expressed gene, gene ontology analysis was performed using statistical analysis tool PANTHER Overrepresentation Test [14] (Released 20190308) with GeneOntology database released 2019-01-01 and Sus scrofa (all genes) as reference. Fischer’s exact test with Bonferroni correction for multiple testing (p<0.05) was performed with the set of validated genes from microarray data. Functional groups were ordered by their overall gene numbers and overall enrichment score [15].

Quantitative real-time reverse-transcription polymerase chain reaction and statistical analysis

To validate selected differentially expressed genes, real-time reverse-transcription polymerase chain reaction (RT-PCR) was performed using CFX96 Real-Time System (BIO-RAD, Hercules, CA, USA). Briefly, 1 μg of RNA was treated with DNA-free Kit (Thermo Scientific, USA) following the manufacturer’s protocol. Subsequently, first-strand DNA synthesis was conducted with oligo [13] and AccuPower CycleScript RT PreMix kit (BIONEER, Daejeon, Korea). Amplification was done using IQ SYBR Green Supermix (BIO-RAD, USA). Primers used are listed in Table 1. The results were reported as FC compared to control expression normalized to glyceraldehyde 3-phosphate dehydrogenase by the Pfaffl method [16]. Pairwise comparisons between means of different treatments were performed using a two tailed Student t-test, the null hypothesis being that the means are equal.


Differentially expressed genes in kidney cell after treatment with GABA, PIP, or both

Differential expressed genes heatmap has been plotted in Figure 1A. For validation purpose, FCs of genes of interest were retrieved as differential signals from multiple probes might reflect differential isotype expression upon treatment [17]. Probes were located and mRNA isotypes of the genes of interest were analyzed using UCSC genome Browser (http://genome.ucsc.edu/) based on Sus Scrofa genome (Sscrofa11. 1/susScr11) (Figure 1B). High mobility group protein B2 (HMGB2) was represented by five probes. However, validation showed that only four probes corresponded to HMGB2. Three of these probes were located in the 3′ UTR and one probe was located in the third exon of identified HMGB2 isotypes. Of these four probes, A_72_P675158 was upregulated by GABA and A_72_P077771 was synergistically upregulated by GABA and PIP at significant levels while the remaining two showed synergistic upregulation at lower magnitude (FC<1.5). LIM domain-binding protein 1 (LDB1) was represented by two probes. A_72_P540123 located in the seventh exon of AB242619 or the second exon of AK344041 showed upregulation upon GABA treatment. On the other hand, A_72_P185256 located in the 5′ UTR of AB242619 showed no significant change upon GABA and/or PIP treatment. Only one probe for Wilms tumor protein homolog (WT1) was available. A_72_P077696 located in the 3′ UTR of the longest isotype showed upregulation by GABA alone and in combination with PIP. To validate these results, we designed quantitative RT-PCR (RT-qPCR) primers in the 3′UTR of reference sequences of HMGB2, LDB1, and WT1 according to NCBI RNA reference sequences collection (RefSeq). After GABA and/or PIP treatment at the same condition as for microarray analysis, mRNAs were extracted and RT-qPCR was performed to evaluate expression levels of HMGB2, LDB1, and WT1 after GABA and/or PIP treatment compared to untreated cells (Figure 1C). HMGB2 and LDB1 showed increase by GABA treatment as A_72_P675158 and A_72_P540123 probes. WT1 showed expression pattern that concurred with its microarray probe.

Gene ontology analysis of genes regulated by GABA and/or PIP treatment

From microarray data, we identified 302 genes upregulated by GABA alone and 26 genes upregulated by PIP alone (FC >1.5). There were 202 downregulated genes by GABA alone and 43 downregulated genes by PIP alone. Synergistically upregulated genes were defined by two criteria. First, we filtered for genes with FCs greater than 1.5 upon GABA and PIP co-treatment. Second, among these genes, we selected 227 genes that has higher FC after co-treatment compared to treatment by GABA alone or PIP alone. Twenty genes were defined as synergistically downregulated as FCs after co-treatment were <−1.5 while FCs after GABA or PIP treatment were between 1.0 and 1.1. GO analysis was performed for genes upregulated by GABA, GABA/PIP, and downregulated by GABA alone. We were unable to perform GO analysis for lists of genes affected by PIP treatment and genes downregulated by GABA/PIP in combination due to low number of genes in these lists (Figure 2). GABA-upregulated genes were related to metabolic process (31.5%), biological regulation (26.2%), cellular process (15.6%), localization (12.3%), and cellular component organization or biogenesis (11.3%). GABA- and PIP- upregulated genes were related to metabolic process (30.4%), biological regulation (23.2%), cellular component organization or biogenesis (11.9%), and cellular process (9.3%). Genes downregulated by GABA alone were related to metabolic process (31.5%), biological regulation (24.9%), response to stimulus (13.0%), and cellular process (11.4%).

Fold enrichment analysis of differentially expressed genes

Fold enrichment analysis can evaluate the number of genes that represent a specific pathway versus the number expected at random case [14]. At a p-value cut-off of 0.05, 15 biological processes were enriched at >1.89- fold for GABA upregulated genes, 76 biological processes were enriched at >2.00-fold for GABA downregulated genes, and 15 genes were enriched at >1.80-fold for synergistically upregulated genes (Figure 3A). The most upregulated biological pathway by GABA alone treatment was erythrocyte differentiation, while the majority of downregulated biological pathways were involved in responses to various stimulus. The most upregulated biological pathway in synergistically upregulated was related to reproductive development. In contrast to fold enrichment higher than one, fold enrichments that were lower than one represented biological processes that were underrepresented and therefore putatively downregulated in the gene list of interest (Figure 3B). At p-value cut-off of 0.05, nine biological processes were enriched at <0.18-fold for GABA upregulated genes and seven biological pathways were enriched at <0.10-fold for GABA/PIP upregulated gene. Both lists showed underrepresentation of biological processes related to stimulus.

Validation and analysis of genes related to biological pathways upon treatment with GABA or GABA/PIP in combination

Based on microarray data and enrichment analysis, we identified seven genes that were upregulated by GABA and related to biological process controlling positive regulation of erythrocyte differentiation. We also identified 31 genes that were synergistically upregulated and related to immune systems and processes. FCs of these genes of interests were retrieved from microarray data (Table 2). Validation was performed for inhibin subunit beta A (INHBA), signal transducer and activator of transcription 1 (STAT1), hypoxia-inducible factor 1-alpha (HIF-1alpha), and SPF36 ring finger protein like 1 (ZPF36L1) among GABA upregulated genes. Our previous study has shown that EPO and EPO-R upregulation by GABA/PIP in combination can be downregulated by inhibitor of JNK (SP600126) and inhibitor of p38 (SB203580) MAPK [11]. Therefore, we investigated if MAPK inhibition could affect GABA upregulated genes (Figure 4A). INHBA, STAT1, and HIF1A were validated to be upregulated by GABA. Inhibition of JNK activation significantly downregulated expression of these genes. However, inhibition of p38 activation affected expression of these genes at lesser extent. Validation was performed for tripartite motif containing 8 (TRIM8), GATA binding protein 3 (GATA3), BPI fold containing family A member 1 (BPIFA1), and C-C motif chemokine ligand 4 (CCL4) among synergistically upregulated genes involved in biological process related to immune system process. Expression analysis upon addition of inhibitors was also performed for those genes (Figure 4B). Results showed that TRIM8, GATA3, BPIFA1, and CCL4 were synergistically upregulated by GABA and PIP in combination, while the addition of MAPK inhibitors downregulated their expression.


Neurotransmitter GABA has been widely studied in human patients as treatment for neuronal diseases including Alzheimer’s disease [18]. In addition, several studies have shown that GABA plays an important role in non-neuronal tissues and that it can be used to treat diseases including liver injury [19]. In kidney, GABA is shown to have anti-inflammatory properties and promote fibroblast proliferation [20]. It can be used to treat renal dysfunction by controlling blood pressure and lipid profile [21], demonstrating its pharmacological potential. In dairy cows, dietary supplementation of GABA has been shown to improve the food intake, lactation performance, and health of early lactating calves [22]. In Hanwoo steers, GABA supplementation improved in vitro rumen fermentation and lowered blood endotoxin levels [23]. Similarly, GABA improved growth performance of weaned pigs [24].
It has been previously shown that plant derived alkaloid PIP can affect GABAA receptor, thus affecting GABA induced signals [11]. Moreover, PIP has been proposed as an alternative growth promoter to antibiotics in animal diets [9,25]. However, while its beneficiary effects in poultry has been investigated [2528], its impact on porcine health remains relatively elusive. In previous study, we have previously demonstrated that expression of EPO and EPO-R is upregulated by GABA and PIP in combination in epithelial kidney cell lines through MAPK pathway [11].
In this study, we analyzed microarray data of differential gene expression upon treatment with GABA and/or PIP to improve our understanding of affected processes. We observed that the main process affected by treatment with GABA or GABA/PIP was biological regulation. Interestingly, the percentage of genes related to response to stimulus among genes downregulated by GABA was higher than other treatment. Moreover, fold enrichment analysis showed that response to stimulus was one of the most underrepresented pathways in genes upregulated by GABA. This suggests that GABA affects stimulus response in kidney. Therefore, the anti-stress effect after GABA treatment might not be limited to neural cells.
Fold enrichment analysis revealed a group of genes that represented putative key pathway affected by GABA and/or PIP treatments. GABA treatment greatly affected seven genes related to erythrocyte differentiation. Of these seven genes, three were validated in our study. INHBA, also known as erythroid differentiation protein, was shown to be involved in several pathways such as neoplastic activity beside erythroid differentiation [29]. STAT1 has been shown to be able to rescue GATA1 knock out phenotype (failure of differentiation of hematopoietic progenitors into erythrocytes and megakaryocytes) in mice [30]. HIF1A is a transcription factor activated in response to hypoxia. It can induce EPO expression [31]. Our findings showed that GABA could induce expression of those genes in kidney cells, suggesting that GABA treatment might be effective as a treatment or supplement to treat diseases, such as well-known anemia occurring in growing piglet [32].
Surprisingly, only a few genes were significantly upregulated or downregulated (26 and 43, respectively) by PIP treatment alone. No specific biological process was enriched at significant level by PIP treatment alone. This suggests that PIP might have less effect on kidney cells than GABA. Another possibility was that we treated cells with a relatively low PIP concentration in this study. Effects of PIP treatment might not have been assayed at its full potential. Indeed, to investigate GABA/PIP synergistic effect, when we treated LLC-PK1 cells with 5 μM PIP. It has been reported that PIP has no toxicity at concentration up to 50 μM [11]. Therefore, to investigate the full potential effect of PIP treatment on the kidney, further analysis with higher concentration might be needed.
As our previous results indicated that GABA and PIP in combination increased expression levels of EPO and EPOR, we investigated biological processes of additional genes upregulated by GABA and PIP in combination. According to fold enrichment analysis, GABA and PIP in combination increased expression level of genes related to reproductive tissue development. Although co-treatment might have major role in reproductive development, some genes that were designated to gonad development (GO:0008406) and reproductive structure development (GO: GO:0048608) such as GATA3 and WT1 were also related to erythrocyte or EPO expression [33]. We have previously shown that GABA and PIP in combination have a synergistic effect in increasing EPO and EPO-R expression and that kidney is one of the main organs responsible for EPO synthesis [34]. Thus, GABA and PIP in combination might have a synergistic role in increasing red blood cell production. Beside process related to reproductive development, GABA and PIP in combination synergistically upregulated genes related to immune system process. TRIM8 is a TRIM protein known to positively regulate nuclear factor-κB activation [35]. GATA3 is a key transcription factor in immune regulation [36]. BPIFA1 is a secreted protein that has a protective role during infection [37]. CCL4 is a chemokine related to pro-inflammatory response [38]. We validated these genes’ upregulation in the present study. Moreover, we showed that these synergistically upregulated genes were controlled by MAPK pathway, like EPO, EPO-R, and GABA upregulated genes.
In conclusion, we identified genes upregulated by GABA, PIP, or both in kidney cells. GABA affected several biological pathways, including the expected erythrocyte differentiation pathway. GABA lowered expression levels of genes related to stimulus, showing that GABA treatment might have anti-stress effect on kidney cells. While PIP treatment was previously shown to affect GABAA receptor, its effect was not as extensive as GABA. However, co-treatment increased expression levels of genes related to reproductive systems, blood cell developments, and immune system. This suggests that GABA and PIP in combination might increase response of aforementioned processes through MAPK pathway.



We certify that there is no conflict of interest with any financial organization regarding the material discussed in the manuscript.


This work was supported by the Korea Institute of Planning and Evaluation for Technology in Food, Agriculture and Forestry (IPET) through the Agri-Bio Industry Technology Development Program funded by the Ministry of Agriculture, Food and Rural Affairs (MAFRA, 116084-03-3-HD020), Republic of Korea.

Figure 1
Hierarchical clustering of dataset of expressional changes upon treatment with GABA, PIP, or both in LLCPK1 kidney cells based on 2,393 probes. Heatmap rows were clustered by average linkage and Euclidean cluster (A). Table of probes in Agilent Porcine Gene Expression microarray represent genes of interest with FC, location of probes, and primer designed in genes according to UCSC gene browser (B). RT-qPCR validation of genes of interest upon treatment with GABA, PIP, or both (C). GABA, gamma-aminobutyric acid; PIP, piperine; FC, fold changes; UCSC, University of California Santa Cruz; RT-qPCR, quantitative reverse transcription polymerase chain reaction.
Figure 2
Functional annotation chart showing distribution of genes regulated by GABA or GABA/PIP co-treatment in LLC-PK1 cells based on PANTHER. GABA, gamma-aminobutyric acid; PIP, piperine.
Figure 3
Fold enrichment plot showing biological processes positively enriched in GABA- upregulated, GA A-downregulated, and GABA/PIP co-treatment synergistically upregulated gene lists (A). Fold enrichment plot showing underrepresented biological processes in GABA and GABA/PIP co-treatment upregulated gene lists (B). Biological terms were identified by genes with respect to biological process through AmiGO. GABA, gamma-aminobutyric acid; PIP, piperine.
Figure 4
RT-qPCR analysis of genes upregulated by GABA alone that are involved in erythrocyte differentiation (GO:0045648) (A) and genes synergistically upregulated by GABA and PIP co-treatment that are involved in regulation of immune system process (GO:0002682) (B). Cells [39] were treated with GABA (G), PIP (P), or both (G+P) as described previously. 5 μM MAPK inhibitor SB203580 (SB5) and 10 μM of MAPK inhibitor SP600125 (SP10) were added at 1 hour prior to treatment with GABA, PIP, or both. Relative expression to control was normalized to GAPDH expression. RT-qPCR were performed three times and representative experiments were presented. RT-qPCR, quantitative reverse transcription polymerase chain reaction; GABA, gamma-aminobutyric acid; PIP, piperine; GAPDH, glyceraldehyde-3-phosphate dehydrogenase. Two tailed student t-test was performed, * p<0.01, ** p<0.001.
Table 1
List of primers used in this study
Primer Primer sequence (5′ to 3′)
Pig_BPIFA1_96F cccccactgggatgactgctccaga
Pig_BPIFA1_96R gggagtgctggcaccaccgctgta
Pig_CCL14_88F ccagcagccagtgccccaagcct
Pig_CCL14_88R acccagtcatccctggggttggcac
Pig_GAPDH_qPCR_F_144 gcgagaactgcctttctgag
Pig_GAPDH_qPCR_R_144 aaggttgcctcgtttgtctg
Pig_GATA3_qPCF_106F tcggcagcgcgaagggcaggt
Pig_GATA3_qPCF_106R gcccacaggcattgcagacggggt
Pig_HIF1A_qPCR_F_99 atggaacggagcaaaagaca
Pig_HIF1A_qPCR_R_99 tggtcagctgtggtaatcca
Pig_HMGB2_qPCR_F_123 agtgcaggttgcagcttttt
Pig_HMGB2_qPCR_R_123 cgagtttgctgttaccatacaca
Pig_INHBA_qPCR_F_104 aaaggtgtgggacagaggtg
Pig_INHBA_qPCR_R_104 ttgcaatacacgggactgaa
Pig_LDB1_qPCR_F_99 ggcctctgagaaatgtcctg
Pig_LDB1_qPCR_R_99 cttgaaggggatggagtcag
Pig_STAT1_qPCR_F_104 ttcttcctgaacccaccttg
Pig_STAT1_qPCR_R_104 ttcagctggtccacattgag
Pig_TRIM8_80F tggccaagaaggagaagcagctgcgga
Pig_TRIM8_80R ggggacgctctgcaggaagggca
Pig_WT1_qPCR_F_106 cgctctcaaagaaggaaacg
Pig_WT1_qPCR_F_106 cgctctcaaagaaggaaacg
Pig_WT1_qPCR_R_106 agcagaggaccaactcctca
Pig_WT1_qPCR_R_106 agcagaggaccaactcctca
Pig_ZFP36L1_qPCR_F_109 acggcaccggcaccttccct
Pig_ZFP36L1_qPCR_R_109 tggcgacacctctcccaaagggg
Table 2
List of genes upregulated by GABA related to positive regulation of erythrocyte differentiation and synergistically upregulated by GABA and PIP related to immune system process
Items Gene GABA Piperine G+P
Positive regulation of erythrocyte differentiation ZFP36L1 1.66 1.01 1.20
STAT1 1.54 1.04 1.02
HIF1A 1.62 1.03 1.08
STAT1 1.54 1.04 1.02
HMGB2 1.56 −1.04 1.41
LDB1 1.90 1.17 1.19
INHBA 1.78 1.12 −1.42
Immune system process DEFB1 1.26 1.14 1.51
TRIM8 −1.03 1.44 2.31
ADAM15 2.05 1.05 2.17
TEC 1.16 1.19 1.53
CAV1 1.35 1.17 1.52
PLCL2 1.12 −1.05 1.53
CD3E 1.96 −1.04 2.07
HMGB2 −1.04 −1.04 1.61
GATA3 −1.39 −1.25 1.63
CCNB2 1.09 −1.10 1.50
ARID4A 1.02 1.04 1.59
C4A 1.16 1.27 1.59
TMEM173 1.56 1.41 1.94
BPIFA1 1.38 −1.11 2.47
TMEM173 1.56 1.41 1.94
TREM2 1.25 1.03 1.53
ENPP2 −1.28 1.14 1.50
ITM2A −1.05 1.10 1.86
RAB29 1.12 1.02 1.78
CD3E 1.96 −1.04 2.07
OAS2 1.02 1.06 1.66
IRAK1 1.19 −1.10 1.51
THRA 1.29 1.14 1.52
HMGB2 −1.04 −1.04 1.61
TOP2A 1.22 −1.05 1.59
SLA-DOA 1.43 1.03 1.51
KMT2E 1.14 −1.06 1.71
REST −1.03 −1.00 1.61
BPIFA1 1.38 −1.11 2.47
GCNT1 −1.08 1.26 1.56
CCL14 −1.59 −1.56 2.70

Genes’ fold changes (FCs) compared to control are listed for GABA, PIP, and GABA/PIP (G+P) co-treatment.

GABA, gamma-aminobutyric acid; PIP, piperine; ZFP36L1, SPF36 ring finger protein like 1; STAT1, signal transducer and activator of transcription 1; HIF1A, hypoxia-inducible factor 1-alpha; HMGB2, high mobility group protein B2; LDB1, LIM domain-binding protein 1; INHBA, inhibin subunit beta A; DEFB1, defensin beta 1; TRIM8, tripartite motif containing 8; ADAM15, ADAM metallopeptidase domain 15; TEC, Tec protein ty-rosine kinase; CAV1, caveolin 1; PLCL2, phospholipase C like 2; CD3E, CD3e molecule; GATA3, GATA binding protein 3; CCNB2, cyclin B2; ARID4A, AT-rich interaction domain 4A; C4A, complement C4A (Rodgers Blood Group); TMEM173, transmembrane protein 173; BPIFA1, BPI fold containing family A member 1; TREM2, triggering receptor expressed on myeloid cells 2; ENPP2, ectonucleotide pyrophosphatase/phosphodiesterase 2; ITM2A, integral membrane protein 2A; RAB29, ras-related protein Rab-7L; OAS2, 2′-5′-oligoadenylate synthetase 2; IRAK1, interleukin-1 receptor-associated kinase 1; THRA, thyroid hormone receptor alpha; TOP2A, DNA topoisomerase II alpha; SLA-DOA, major histocompatibility complex, classII Do alpha; KMT2E, myeloid/lymphoid or mixed-lineage leukemia 5; REST, RE1-silencing transcription factor; GCNT1, glucosami-nyl (N-acetyl) transferase 1; CCL14, C-C motif chemokine ligand 14.


1. Bowery NG, Smart TG. GABA and glycine as neurotransmitters: a brief history. Br J Pharmacol 2006; 147:Suppl 1S109–19. https://doi.org/10.1038/sj.bjp.0706443
crossref pmid pmc
2. Wong CGT, Bottiglieri T, Snead OC. GABA, gamma-hydroxybutyric acid, and neurological disease. Ann Neurol 2003; 54:Suppl 6S3–12. https://doi.org/10.1002/ana.10696
3. Hashimoto T. GABA receptor chloride ion channel. Nihon Rinsho 1998; 56:1824–9.
4. Bettler B, Kaupmann K, Bowery N. GABAB receptors: drugs meet clones. Curr Opin Neurobiol 1998; 8:345–50. https://doi.org/10.1016/S0959-4388(98)80059-7
crossref pmid
5. Roberts E, Frankel S, Harman PJ. Amino acids of nervous tissue. Proc Soc Exp Biol Med 1950; 74:383–7. https://doi.org/10.3181/00379727-74-17916
crossref pmid
6. Takano K, Yatabe MS, Abe A, et al. Characteristic expressions of GABA receptors and GABA producing/transporting molecules in rat kidney. PLoS One 2014; 9:e105835 https://doi.org/10.1371/journal.pone.0105835
crossref pmid pmc
7. Govindarajan VS. Pepper - chemistry, technology, and quality evaluation. CRC Crit Rev Food Sci Nutr 1977; 9:115–225. https://doi.org/10.1080/10408397709527233
crossref pmid
8. Meghwal M, Goswami TK. Piper nigrum and piperine: an update. Phytother Res 2013; 27:1121–30. https://doi.org/10.1002/ptr.4972
crossref pmid
9. Abou-Elkhair R, Ahmed HA, Selim S. Effects of black pepper (Piper nigrum), turmeric powder (Curcuma longa) and coriander seeds (Coriandrum sativum) and their combinations as feed additives on growth performance, carcass traits, some blood parameters and humoral immune response of broiler chickens. Asian-Australas J Anim Sci 2014; 27:847–54. https://doi.org/10.5713/ajas.2013.13644
crossref pmid pmc pdf
10. Khom S, Strommer B, Schoffmann A, et al. GABAA receptor modulation by piperine and a non-TRPV1 activating derivative. Biochem Pharmacol 2013; 85:1827–36. https://doi.org/10.1016/j.bcp.2013.04.017
crossref pmid pmc
11. Lee YM, Choi JH, Min WK, Han JK, Oh JW. Induction of functional erythropoietin and erythropoietin receptor gene expression by gamma-aminobutyric acid and piperine in kidney epithelial cells. Life Sci 2018; 215:207–15. https://doi.org/10.1016/j.lfs.2018.11.024
crossref pmid
12. Nairz M, Sonnweber T, Schroll A, Theurl I, Weiss G. The pleiotropic effects of erythropoietin in infection and inflammation. Microbes Infect 2012; 14:238–46. https://doi.org/10.1016/j.micinf.2011.10.005
crossref pmid pmc
13. Babicki S, Arndt D, Marcu A, et al. Heatmapper: web-enabled heat mapping for all. Nucleic Acids Res 2016; 44:W147–53. https://doi.org/10.1093/nar/gkw419
crossref pmid pmc pdf
14. Mi H, Muruganujan A, Ebert D, Huang X, Thomas PD. PANTHER version 14: more genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools. Nucleic Acids Res 2019; 47:D419–26. https://doi.org/10.1093/nar/gky1038
crossref pmid pdf
15. Thomas PD, Campbell MJ, Kejariwal A, et al. PANTHER: a library of protein families and subfamilies indexed by function. Genome Res 2003; 13:2129–41. https://doi.org/10.1101/gr.772403
crossref pmid pmc
16. Pfaffl MW. A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res 2001; 29:e45 https://doi.org/10.1093/nar/29.9.e45
crossref pmid pmc pdf
17. Stalteri MA, Harrison AP. Interpretation of multiple probe sets mapping to the same gene in Affymetrix GeneChips. BMC Bioinformatics 2007; 8:13 https://doi.org/10.1186/1471-2105-8-13
crossref pmid pmc pdf
18. Solas M, Puerta E, Ramirez MJ. Treatment options in alzheimer’s disease: the GABA story. Curr Pharm Des 2015; 21:4960–71.
crossref pmid
19. Wang S, Zhang L, Liu C, Lu WY. Protective roles of hepatic GABA signaling in liver injury. Int J Physiol Pathophysiol Pharmacol 2017; 9:153
pmid pmc
20. Han D, Kim HY, Lee HJ, Shim I, Hahm DH. Wound healing activity of gamma-aminobutyric Acid (GABA) in rats. J Microbiol Biotechnol 2007; 17:1661–9.
21. Sasaki S, Yokozawa T, Cho EJ, Oowada S, Kim M. Protective role of gamma-aminobutyric acid against chronic renal failure in rats. J Pharm Pharmacol 2006; 58:1515–25. https://doi.org/10.1211/jpp.58.11.0013
crossref pmid
22. Wang DM, Wang C, Liu HY, Liu JX, Ferguson JD. Effects of rumen-protected gamma-aminobutyric acid on feed intake, lactation performance, and antioxidative status in early lactating dairy cows. J Dairy Sci 2013; 96:3222–7. https://doi.org/10.3168/jds.2012-6285
crossref pmid
23. Mamuad LL, Kim SH, Ku MJ, Lee SS. Effect of gamma-aminobutyric acid producing bacteria on in vitro rumen fermentation, growth performance, and meat quality of Hanwoo steers. Asian-Australas J Anim Sci 2020; 33:1087–95. https://doi.org/10.5713/ajas.19.0785
crossref pmid pmc pdf
24. Li X, Hao J, Liu X, et al. Effect of the treatment by slightly acidic electrolyzed water on the accumulation of gamma-aminobutyric acid in germinated brown millet. Food Chem 2015; 186:249–55. https://doi.org/10.1016/j.foodchem.2015.03.004
crossref pmid
25. Windisch W, Schedle K, Plitzner C, Kroismayr A. Use of phytogenic products as feed additives for swine and poultry. J Anim Sci 2008; 86:Issue suppl_14E140–8. https://doi.org/10.2527/jas.2007-0459
crossref pmid pdf
26. Giannenas I, Papaneophytou CP, Tsalie E, et al. Dietary supplementation of benzoic acid and essential oil compounds affects buffering capacity of the feeds, performance of Turkey Poults and their antioxidant status, pH in the digestive tract, intestinal microbiota and morphology. Asian-Australas J Anim Sci 2014; 27:225–36. https://doi.org/10.5713/ajas.2013.13376
crossref pmid pmc pdf
27. da Silva Cardoso V, Vermelho AB, Ribeiro de Lima CA, et al. Antigenotoxic effect of piperine in broiler chickens intoxicated with Aflatoxin B1. Toxins (Basel) 2016; 8:316 https://doi.org/10.3390/toxins8110316
crossref pmid pmc
28. Cardoso VD, de Lima CAR, de Lima MEF, Dorneles LEG, Danelli MDM. Piperine as a phytogenic additive in broiler diets. Pesquisa Agropecuaria Brasileira 2012; 47:489–96.
crossref pdf
29. Seder CW, Hartojo W, Lin L, et al. Upregulated INHBA expression may promote cell proliferation and is associated with poor survival in lung adenocarcinoma. Neoplasia 2009; 11:388–96. https://doi.org/10.1593/neo.81582
crossref pmid pmc
30. Huang Z, Richmond TD, Muntean AG, Barber DL, Weiss MJ, Crispino JD. STAT1 promotes megakaryopoiesis downstream of GATA-1 in mice. J Clin Invest 2007; 117:3890–9. https://doi.org/10.1172/JCI33010
crossref pmid pmc
31. Choi SM, Choi KO, Park YK, Cho H, Yang EG, Park H. Clioquinol, a Cu(II)/Zn(II) chelator, inhibits both ubiquitination and asparagine hydroxylation of hypoxia-inducible factor-1alpha, leading to expression of vascular endothelial growth factor and erythropoietin in normoxic cells. J Biol Chem 2006; 281:34056–63. https://doi.org/10.1074/jbc.M603913200
crossref pmid
32. Dale DG, Macdonald MA, Moxley JE. Hemoglobin levels of piglets at birth and at 21 days and their relation to weight at 154 days of age. Can J Comp Med Vet Sci 1961; 25:193–7.
pmid pmc
33. Dame C, Kirschner KM, Bartz KV, Wallach T, Hussels CS, Scholz H. Wilms tumor suppressor, Wt1, is a transcriptional activator of the erythropoietin gene. Blood 2006; 107:4282–90. https://doi.org/10.1182/blood-2005-07-2889
crossref pmid pdf
34. Haase VH. Regulation of erythropoiesis by hypoxia-inducible factors. Blood Rev 2013; 27:41–53. https://doi.org/10.1016/j.blre.2012.12.003
crossref pmid pmc
35. Li Q, Yan J, Mao AP, et al. Tripartite motif 8 (TRIM8) modulates TNFalpha- and IL-1beta-triggered NF-kappaB activation by targeting TAK1 for K63-linked polyubiquitination. Proc Natl Acad Sci USA 2011; 108:19341–6. https://doi.org/10.1073/pnas.1110946108
crossref pmid pmc
36. Wan YY. GATA3: a master of many trades in immune regulation. Trends Immunol 2014; 35:233–42. https://doi.org/10.1016/j.it.2014.04.002
crossref pmid pmc
37. Akram KM, Moyo NA, Leeming GH, et al. An innate defense peptide BPIFA1/SPLUNC1 restricts influenza A virus infection. Mucosal Immunol 2018; 11:71–81. https://doi.org/10.1038/mi.2017.45
crossref pmid pdf
38. Sokol CL, Luster AD. The chemokine system in innate immunity. Cold Spring Harb Perspect Biol 2015; 7:a016303 https://doi.org/10.1101/cshperspect.a016303
crossref pmid pmc
39. Zorova LD, Popkov VA, Plotnikov EY, et al. Mitochondrial membrane potential. Anal Biochem 2018; 552:50–9. https://doi.org/10.1016/j.ab.2017.07.009
crossref pmid

Editorial Office
Asian-Australasian Association of Animal Production Societies(AAAP)
Room 708 Sammo Sporex, 23, Sillim-ro 59-gil, Gwanak-gu, Seoul 08776, Korea   
TEL : +82-2-888-6558    FAX : +82-2-888-6559   
E-mail : editor@animbiosci.org               

Copyright © 2024 by Asian-Australasian Association of Animal Production Societies.

Developed in M2PI

Close layer
prev next