Disorders of gut microbiota in children with Tetralogy of Fallot

Introduction

In recent years, the gut microbiota has attracted much attention due to its important role in human health and disease via interacting with the host (1,2). Gut microbiota is related to cardiovascular health and diseases, such as atherosclerosis, heart failure, and arterial stiffness (3,4). Furthermore, research suggests that there exists a close relationship between the gut microbiota and congenital heart disease (CHD). A recent case-control study suggested that disorders of maternal gut microbiota and plasma metabolites were associated with a higher risk of CHD in the offspring (5). Additionally, intestinal microbiota may be a contributing factor in necrotizing enterocolitis among term infants with cyanotic CHD (6).

Tetralogy of Fallot (TOF) is the most common form of cyanotic CHD (around 8–9.7%) and is characterized by systemic chronic hypoxia and sustained pressure overload of the right ventricle (RV) (7,8). Studies have shown that hypoxia and pressure overload can affect the gut microbiota (9-11). Thus, it is reasonable to speculate that the gut microbiota in TOF patients may be dysregulated. However, to the best of our knowledge, to date, there have been no studies exploring the changes of the gut microbiota in children with unrepaired TOF compared to healthy subjects.

Herein, a cross-sectional study was conducted to explore the changes in the gut microbiota in pediatric patients diagnosed with TOF who have not undergoing any intervention. It was hypothesized that the combined heart defects can influence the composition and function of the gut microbiota, which may be involved in the disease progression and outcome.

We present the following article in accordance with the MDAR reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-22-33/rc).

Methods

Experimental design and study cohort

This cross-sectional study was designed to investigate the changes in gut microbiota in children with TOF. Twelve pediatric patients diagnosed with TOF by echocardiography in the clinic of Guangdong Provincial People’s Hospital were enrolled in this study. Since age and gender can impact the gut microbiota (12,13), nine healthy age- and gender-matched children were enrolled as the control group. Comprehensive medical histories were obtained and physical examinations were performed to exclude conditions that were unsuitable for the trial, such as having a cold, diarrhea, constipation, jaundice, or use of any antibiotics within the past month. This study was approved by the Ethics Committee of the Guangdong Provincial People’s Hospital (No. KY-Q-2021-091-01) and all procedures were conducted in accordance with the Declaration of Helsinki (as revised in 2013). Informed consents were obtained from the parents or guardians of the participants.

Fecal sample collection and 16S rDNA gene sequencing

Fecal samples were collected from all participants and frozen at −80 ℃ for subsequent analysis. DNA was extracted using a DNA isolation kit (Findrop Biosafety Technology, Guangzhou, China) according to the manufacturer’s protocol, and quantified and qualified by using a NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). Polymerase chain reaction (PCR) amplification of the bacterial 16S rDNA genes V4 region was performed using Premix Taq Version 2.0 (TaKaRa, Dalian, China) with forward primer 515F (5'-GTGCCAGCMGCCGCGGTAA-3') and reverse primer 806R (5'-GGACTACHVGGGTWTCTAAT-3'). The PCR amplicons were then purified with AMPure XP Beads (Beckman Coulter, Indianapolis, IN, USA) and quantified using the PicoGreen dsDNA Assay Kit (Invitrogen, Carlsbad, CA, USA). Finally, sequencing was performed using the Illumina NovoSeq 6000 platform.

Bioinformatics analysis

The sequencing data were processed using the Quantitative Insights Into Microbial Ecology (QIIME2, v2020.6) pipeline as previously described (14). Venn diagrams were generated to visualize the shared and unique genera between groups using VennDiagram. Indicator species analysis was performed using the indval function in labdsv (v2.0.1), and genera with a P value <0.05 were considered significant indicators. Alpha diversity (Chao1 and Shannon) was calculated in QIIME2. Beta diversity was visualized via nonmetric multidimensional scaling (NMDS) (15) and further examined using analysis of similarities (ANOSIM). Microbial functions were predicted by PICRUSt2 and Tax4Fun (16,17).

Statistical analyses

Statistical analysis was conducted using the SPSS 20.0 software (SPSS Inc., Chicago, IL, USA), and the graphs were plotted with GraphPad Prism (Version 7.0, San Diego, USA). Categorical variables were described as whole numbers and percentages, and comparisons between groups were performed with Fisher’s exact test. Continuous variables with normal distribution were presented as mean ± standard error of the mean (SEM) or mean (95% confidence interval), and comparisons between groups were performed with t-tests. Continuous variables with non-normal distribution were presented as median and interquartile range (IQR), and comparisons between groups were performed with Wilcoxon rank-sum test. A P value <0.05 was considered statistically significant.

Results

Subjects and clinical characteristics

Twelve pediatric patients with TOF were enrolled in the study and nine healthy children matched for age and gender were enlisted as the control group. Baseline characteristics are shown in Table 1. The gender, age, and weight were not significantly different between the two groups. Specifically, there were six and nine males in the healthy group and the TOF group, respectively. The median ages were 8 and 6 months, and the median weights were 8.3 and 6.6 kg in the healthy and TOF groups, respectively. The echocardiographic indices, such as diameter of the ventricular septal defect (VSD) and pressure gradient across the right ventricular outflow tract (RVOT), were recorded.

Alterations of bacterial taxa and indicative bacterial genera

Venn diagrams were used to illustrate the similarities and differences in the genera observed in the TOF patients and the healthy controls. There were 59 overlapping genera, and 36 and 53 genera were found exclusively in the healthy group and the TOF group, respectively (Figure 1A). The taxonomic compositions and abundances of the gut microbiota between the two groups are presented at the phylum level (Figure 1B,1C). In the healthy group, the most abundant phyla were Proteobacteria, Firmicutes, and Actinobacteria, with an average abundance of 36.05%, 34.67%, and 14.30%, respectively. In the TOF group, the most abundant phyla were Firmicutes, Proteobacteria, and Bacteroidetes, with an average abundance of 47.33%, 24.44%, and 17.90%, respectively. At the genus level, 14 indicative bacterial genera (median relative abundance >0.1% and P<0.05) were identified as biomarkers that may distinguish between healthy children and TOF patients (Figure 1D). In the healthy group, Terrisporobacter, Chryseobacterium, and Prevotella were the top three genera with indicator values of 0.66, 0.51, and 0.43, respectively. In the TOF group, Faecalibacterium, Megamonas, and Subdoligranulum were the top three genera with indicator values of 1.00, 1.00, and 0.91, respectively.

Figure 1 The alterations in bacterial taxa and the indicative bacterial genera in the TOF population and the healthy population. (A) There were 59 overlapping genera between the TOF and healthy population. A total of 36 and 53 genera were found exclusively in the healthy group and the TOF group, respectively; (B,C) the taxonomic compositions and abundances of the gut microbiota between the two groups are presented at the phylum level; (D) fourteen indicative bacterial genera were identified as potential biomarkers for the differentiation between healthy and TOF children. TOF, Tetralogy of Fallot.

Altered beta diversity in the gut bacterial community

The alpha diversity of the gut microbiota was compared using Chao1 and Shannon, and the results showed that TOF patients and healthy children had similar gut microbial alpha diversity (Figure 2A,2B). The similarities and differences in the community composition between the two groups were also examined. Notably, the NMDS plot of beta diversity based on Bray-Curtis distance matrix revealed that the differences in the community composition between the two groups was greater than that within the groups (Figure 2C,2D), indicating that TOF has a significant impact on gut bacterial community composition.

Figure 2 The alpha and beta diversity in the gut bacterial community. The TOF and healthy populations exhibited a similar microbial alpha diversity as estimated by (A) Chao1 and (B) Shannon. (C) The NMDS plot of beta diversity based on Bray-Curtis distance matrix is shown. (D) ANOSIM revealed a significant difference in the community composition between the two groups. TOF, Tetralogy of Fallot; NMDS, nonmetric multidimensional scaling; ANOSIM, analysis of similarities.

Altered abundance in Enzyme Commission (EC) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthologs (KO)

The functional properties of the intestinal microbiota were predicted using PICRUSt2. Interestingly, the gut microbiota of the TOF group was characterized by a significant reduction in the abundance of enzyme EC (Enzyme Commission), including transketolase, enoyl-CoA hydratase, and lysophospholipase. The top 20 enzyme ECs in relative abundance (P<0.05) are displayed in Figure 3A. Furthermore, the TOF group showed a lower abundance of KOs (KEGG Orthologs), such as LacI family transcriptional regulator, ribose transport system permease protein, and DNA-damage-inducible protein J. The top 20 KOs in relative abundance (P<0.05) are displayed in Figure 3B.

Figure 3 The altered abundance in enzyme EC and KOs. The gut microbiota of the TOF group was characterized by a significant reduction in the abundance of (A) enzyme EC and (B) KOs. EC, Enzyme Commission; KOs, KEGG Orthologs.

Altered abundance in KEGG pathway annotations

KEGG pathway annotations at level 2, as determined by PICRUSt2, showed significant differences between the TOF group and the healthy controls. In contrast to the healthy children, the functional profile in TOF patients exhibited a greater abundance of pathways related to immune diseases (Figure 4A) and a lower abundance of pathways related to environmental adaptation (Figure 4B), membrane transport (Figure 4C), and xenobiotics biodegradation and metabolism (Figure 4D). Furthermore, KEGG pathway annotations at level 3, as determined by Tax4Fun, also presented significant differences between the two groups. In particular, the functional profile in TOF patients showed significant association with the nuclear factor (NF)-kappa(κ)B signaling pathway (Figure 5A), oxidative phosphorylation (Figure 5B), cytokine-cytokine receptor interaction (Figure 5C), and the vascular endothelial growth factor (VEGF) signaling pathway (Figure 5D), while there was a lower association with pathways involved in ribosome biogenesis in eukaryotes (Figure 5E) and glutathione metabolism (Figure 5F).

Figure 4 The impaired KEGG pathway annotations at level 2, as determined by PICRUSt2. The functional profile in TOF patients showed (A) a greater abundance of pathways involved in immune diseases and a fewer abundance of pathways involved in (B) environmental adaptation, (C) membrane transport, and (D) xenobiotics biodegradation and metabolism. *, P<0.05. KEGG, Kyoto Encyclopedia of Genes and Genomes; PICRUSt, Phylogenetic Investigation of Communities by Reconstruction of Unobserved States; TOF, Tetralogy of Fallot.

Figure 5 The impaired KEGG pathway annotations at level 3, as determined by Tax4Fun. The functional profile in TOF patients showed a greater abundance of pathways involved in (A) NF-κB signaling pathway, (B) oxidative phosphorylation, (C) cytokine-cytokine receptor interaction, and (D) VEGF signaling pathway. TOF patients showed a fewer abundance of pathways involved in (E) ribosome biogenesis in eukaryotes and (F) glutathione metabolism. *, P<0.05; **, P<0.01. KEGG, Kyoto Encyclopedia of Genes and Genomes; TOF, Tetralogy of Fallot; NF-κB, nuclear factor-kappa B; VEGF, vascular endothelial growth factor.

Discussion

The current study provided evidence that the gut microbiota in pediatric patients with unrepaired TOF differs from that in healthy children in terms of taxonomic composition, beta diversity, and functional profile. These findings suggested that the interplay between the host and the gut microbiota may be dysregulated in children with TOF, and indeed, TOF may influence the composition and function of the gut microbiota.

TOF is not only a combination of four heart defects, but it is also a systemic disease to some extent since patients are born with systemic chronic hypoxia, sustained RV pressure overload (8), and arterial stiffness (18). It has been reported that, despite having a correction in infancy, children with TOF are at a higher risk of disorders in speech and language compared to patients with VSD and cardiac insufficiency (19). Study has shown that in patients with repaired TOF, serum bile acid levels are positively correlated with the indexed RV end-diastolic volume, suggesting the presence of hepatic congestion (20). In addition, transcriptomic study on children with TOF revealed that hypoxia can lead to enhanced expression of genes related to apoptosis and remodeling, and reduced expression of genes related to myocardium contractility and function (21). However, the alterations in the gut microbiota of TOF patients remain unclear. This current study lends support the concept that TOF is a systematic condition by clearly demonstrating the imbalance and dysfunction in the gut microbiota of TOF patients.

Systemic chronic hypoxia and sustained RV pressure overload are prominent pathological features in TOF, and may be important factors involved in the gut microbiota changes observed in this current study. There is plenty of evidence to suggest that hypoxia can affect intestinal microbiota. Indeed, intrauterine hypoxia can cause changes of the initial microbiota colonization in neonatal rats (22). A recent study revealed that chronic hypoxia caused gut dysbiosis and D-galactose accumulation, thereby inducing premature senescence of bone marrow mesenchymal stem cells (23). Another research suggested that intermittent hypoxia contributed to atherosclerosis by disturbing the gut microbiome and metabolome (24). In our current study, the taxonomic compositions were found to be notably affected in TOF children, and furthermore, the indicator bacterial genera including Faecalibacterium, Akkermansia, and Subdoligranulum were identified as potential biomarkers to distinguish between TOF individuals and healthy children. Faecalibacterium has been implicated in inflammation and gut barrier integrity, and its abundance is significantly modified in children with obstructive sleep apnoea syndrome (OSAS) (25,26). In addition, Akkermansia and Subdoligranulum have been shown to be related to inflammation and metabolic status (27,28). Furthermore, we observed that the intestinal flora in TOF patients was characterized by a significant reduction in the abundance of enzyme EC and KOs. The TOF profile suggested insufficiencies in defense responses to stress (including 3-mercaptopyruvate sulfurtransferase, cyclopropane-fatty-acyl-phospholipid synthase, and DNA-damage-inducible protein J) (29-33), maintenance of metabolic homeostasis (including thiosulfate sulfurtransferase and ornithine carbamoyltransferase) (34,35), synthesis of nucleotides and nucleic acids (including transketolase and transaldolase) (36,37), and ribose transport (including ribose transport system permease protein and ribose transport system ATP-binding protein) (38,39). These results indicated that the functional properties of the gut microbiota were significantly impaired in TOF. It is noteworthy that reduced lysophospholipase activity has also been observed in injured intestinal mucosa caused by ischaemia (40). Our findings are supported by a study showing that children with OSAS had reduced gut microbiota diversity, increased inflammation, and gut barrier disruptors-related strains (26).

To further elucidate the differences in the functional profile between TOF children and healthy subjects, KEGG pathway annotations were performed. It was revealed that, in TOF patients, there was an abundance of gut microbiota associated with immune diseases, while there was a lower abundance of microbiota associated with environmental adaptation, membrane transport, and xenobiotics biodegradation and metabolism. Furthermore, it is worth noting that in the TOF group, the KEGG pathways of NF-κB signaling, oxidative phosphorylation, cytokine-cytokine receptor interaction, and VEGF signaling were significantly enriched, but there were fewer pathways associated with ribosome biogenesis in eukaryotes and glutathione metabolism. There is a close relationship between hypoxia and the NF-κB signaling pathway, as well as cytokine-cytokine receptor interaction and the VEGF signaling pathway (41-44). The NF-κB signaling pathway plays a crucial role in inflammation, immunity, cell proliferation, differentiation, and survival (45), as well as in intestinal homeostasis and diseases (46). Additionally, the NF-κB signaling pathway has been implicated in hypoxic conditions, yet its role may be double-edged. Study has shown that the NF-κB signaling pathway is activated in cyanotic myocardial tissues and hypoxia-stimulated cardiomyocytes, which is inferred as a compensatory response to stress (41). However, another study revealed a pathogenic aspect, in which NF-κB signaling played an important role in chronic intermittent hypoxia-induced atherosclerosis (43). In addition, oxidative phosphorylation is crucial to the synthesis of ATP (47) and the increased enrichment of oxidative phosphorylation in TOF may serve as an adaptive mechanism for a more energy requirement. This inference can be supported by a previous study on TOF patients, where a potential adaptive mechanism was found to enhance ATP output and minimize hypoxic damage (8). However, a reduced relative abundance of ribosome biogenesis in eukaryotes was observed, which suggested that protein production may be impaired in TOF. Interestingly, the metabolism of glutathione, which serves as a major intracellular antioxidant and an indicator of oxidative stress (48,49), was significantly less enriched in TOF patients. These results further indicated that the gut microbiota in TOF patients has been perturbed, resulting in increased levels of inflammatory, oxidative, and immune responses, and decreased levels of adaptation, synthesis, and metabolism.

There were some limitations to this present study. Since the sample size was small, it was difficult to explore the relationship between altered bacterial diversity and clinical parameters such as pressure gradient across the RVOT. In addition, this was an observational study, and future causality studies are warranted to translate the human observations into preclinical validation.

Conclusions

Pediatric patients with unrepaired TOF have intestinal dysbacteriosis that is characterized by altered taxonomic compositions and impaired functional profiles. These findings suggest that the interplay between the host and the gut microbiota has been dysregulated by TOF. However, further causality studies are warranted to progress from human observations to preclinical validation.

Acknowledgments

Funding: This work was supported by the Guangdong Peak Project (No. DFJH2019); the Science and Technology Projects in Guangzhou (No. 202102021149); the Postdoctoral Scientific Research Start-up Fund Project of Guangdong Provincial People’s Hospital (No. BY012021052); and the National Nature Science Foundation of China (No. 82100451).

Footnote

Reporting Checklist: The authors have completed the MDAR reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-22-33/rc

Data Sharing Statement: Available at https://tp.amegroups.com/article/view/10.21037/tp-22-33/dss

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-22-33/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was approved by the Ethics Committee of the Guangdong Provincial People’s Hospital (No. KY-Q-2021-091-01) and all procedures were conducted in accordance with the Declaration of Helsinki (as revised in 2013). Informed consents were obtained from the parents or guardians of the participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Fan Y, Pedersen O. Gut microbiota in human metabolic health and disease. Nat Rev Microbiol 2021;19:55-71. [Crossref] [PubMed]
2. Marchesi JR, Adams DH, Fava F, et al. The gut microbiota and host health: a new clinical frontier. Gut 2016;65:330-9. [Crossref] [PubMed]
3. Dinakis E, Nakai M, Gill PA, et al. The Gut Microbiota and Their Metabolites in Human Arterial Stiffness. Heart Lung Circ 2021;30:1716-25. [Crossref] [PubMed]
4. Tang WH, Kitai T, Hazen SL. Gut Microbiota in Cardiovascular Health and Disease. Circ Res 2017;120:1183-96. [Crossref] [PubMed]
5. Wang T, Chen L, Huang P, et al. Association of maternal gut microbiota and plasma metabolism with congenital heart disease in offspring: a multi-omic analysis. Sci Rep 2021;11:5339. [Crossref] [PubMed]
6. Ellis CL, Rutledge JC, Underwood MA. Intestinal microbiota and blue baby syndrome: probiotic therapy for term neonates with cyanotic congenital heart disease. Gut Microbes 2010;1:359-66. [Crossref] [PubMed]
7. Mohamed I, Stamm R, Keenan R, et al. Assessment of Disease Progression in Patients With Repaired Tetralogy of Fallot Using Cardiac Magnetic Resonance Imaging: A Systematic Review. Heart Lung Circ 2020;29:1613-20. [Crossref] [PubMed]
8. Zhu L, Wang Q, Zhang L, et al. Hypoxia induces PGC-1α expression and mitochondrial biogenesis in the myocardium of TOF patients. Cell Res 2010;20:676-87. [Crossref] [PubMed]
9. Carrillo-Salinas FJ, Anastasiou M, Ngwenyama N, et al. Gut dysbiosis induced by cardiac pressure overload enhances adverse cardiac remodeling in a T cell-dependent manner. Gut Microbes 2020;12:1-20. [Crossref] [PubMed]
10. Pral LP, Fachi JL, Corrêa RO, et al. Hypoxia and HIF-1 as key regulators of gut microbiota and host interactions. Trends Immunol 2021;42:604-21. [Crossref] [PubMed]
11. Kumar T, Pandey R, Chauhan NS. Hypoxia inducible factor-1α: the curator of gut homeostasis. Front Cell Infect Microbiol 2020;10:227. [Crossref] [PubMed]
12. Odamaki T, Kato K, Sugahara H, et al. Age-related changes in gut microbiota composition from newborn to centenarian: a cross-sectional study. BMC Microbiol 2016;16:90. [Crossref] [PubMed]
13. Rizzetto L, Fava F, Tuohy KM, et al. Connecting the immune system, systemic chronic inflammation and the gut microbiome: The role of sex. J Autoimmun 2018;92:12-34. [Crossref] [PubMed]
14. Bolyen E, Rideout JR, Dillon MR, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol 2019;37:852-7. [Crossref] [PubMed]
15. Ramette A. Multivariate analyses in microbial ecology. FEMS Microbiol Ecol 2007;62:142-60. [Crossref] [PubMed]
16. Aßhauer KP, Wemheuer B, Daniel R, et al. Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data. Bioinformatics 2015;31:2882-4. [Crossref] [PubMed]
17. Douglas GM, Maffei VJ, Zaneveld JR, et al. PICRUSt2 for prediction of metagenome functions. Nat Biotechnol 2020;38:685-8. [Crossref] [PubMed]
18. Sandhu K, Pepe S, Smolich JJ, et al. Arterial Stiffness in Congenital Heart Disease. Heart Lung Circ 2021;30:1602-12. [Crossref] [PubMed]
19. Hövels-Gürich HH, Bauer SB, Schnitker R, et al. Long-term outcome of speech and language in children after corrective surgery for cyanotic or acyanotic cardiac defects in infancy. Eur J Paediatr Neurol 2008;12:378-86. [Crossref] [PubMed]
20. Grangl G, Zöhrer E, Köstenberger M, et al. Serum Bile Acids in Repaired Tetralogy of Fallot: A Marker for Liver and Heart? PLoS One 2015;10:e0144745. [Crossref] [PubMed]
21. Ghorbel MT, Cherif M, Jenkins E, et al. Transcriptomic analysis of patients with tetralogy of Fallot reveals the effect of chronic hypoxia on myocardial gene expression. J Thorac Cardiovasc Surg 2010;140:337-345.e26. [Crossref] [PubMed]
22. Sun Y, Li L, Song J, et al. Intrauterine Hypoxia Changed the Colonization of the Gut Microbiota in Newborn Rats. Front Pediatr 2021;9:675022. [Crossref] [PubMed]
23. Xing J, Ying Y, Mao C, et al. Hypoxia induces senescence of bone marrow mesenchymal stem cells via altered gut microbiota. Nat Commun 2018;9:2020. [Crossref] [PubMed]
24. Xue J, Allaband C, Zhou D, et al. Influence of Intermittent Hypoxia/Hypercapnia on Atherosclerosis, Gut Microbiome, and Metabolome. Front Physiol 2021;12:663950. [Crossref] [PubMed]
25. Iino C, Endo T, Mikami K, et al. Significant decrease in Faecalibacterium among gut microbiota in nonalcoholic fatty liver disease: a large BMI- and sex-matched population study. Hepatol Int 2019;13:748-56. [Crossref] [PubMed]
26. Valentini F, Evangelisti M, Arpinelli M, et al. Gut microbiota composition in children with obstructive sleep apnoea syndrome: a pilot study. Sleep Med 2020;76:140-7. [Crossref] [PubMed]
27. Dao MC, Everard A, Aron-Wisnewsky J, et al. Akkermansia muciniphila and improved metabolic health during a dietary intervention in obesity: relationship with gut microbiome richness and ecology. Gut 2016;65:426-36. [Crossref] [PubMed]
28. Van Hul M, Le Roy T, Prifti E, et al. From correlation to causality: the case of Subdoligranulum. Gut Microbes 2020;12:1-13. [Crossref] [PubMed]
29. Choi TR, Song HS, Han YH, et al. Enhanced tolerance to inhibitors of Escherichia coli by heterologous expression of cyclopropane-fatty acid-acyl-phospholipid synthase (cfa) from Halomonas socia. Bioprocess Biosyst Eng 2020;43:909-18. [Crossref] [PubMed]
30. Hu Y, Benedik MJ, Wood TK. Antitoxin DinJ influences the general stress response through transcript stabilizer CspE. Environ Microbiol 2012;14:669-79. [Crossref] [PubMed]
31. Nagahara N, Nagano M, Ito T, et al. Redox regulation of mammalian 3-mercaptopyruvate sulfurtransferase. Methods Enzymol 2015;554:229-54. [Crossref] [PubMed]
32. Nagahara N, Sawada N. The mercaptopyruvate pathway in cysteine catabolism: a physiologic role and related disease of the multifunctional 3-mercaptopyruvate sulfurtransferase. Curr Med Chem 2006;13:1219-30. [Crossref] [PubMed]
33. Ruangprasert A, Maehigashi T, Miles SJ, et al. Importance of the E. coli DinJ antitoxin carboxy terminus for toxin suppression and regulated proteolysis. Mol Microbiol 2017;104:65-77. [Crossref] [PubMed]
34. Krijt J, Sokolová J, Ješina P, et al. Activity of the liver enzyme ornithine carbamoyltransferase (OTC) in blood: LC-MS/MS assay for non-invasive diagnosis of ornithine carbamoyltransferase deficiency. Clin Chem Lab Med 2017;55:1168-77. [Crossref] [PubMed]
35. Kruithof PD, Lunev S, Aguilar Lozano SP, et al. Unraveling the role of thiosulfate sulfurtransferase in metabolic diseases. Biochim Biophys Acta Mol Basis Dis 2020;1866:165716. [Crossref] [PubMed]
36. Prejanò M, Medina FE, Fernandes PA, et al. The Catalytic Mechanism of Human Transketolase. Chemphyschem 2019;20:2881-6. [Crossref] [PubMed]
37. Samland AK, Sprenger GA. Transaldolase: from biochemistry to human disease. Int J Biochem Cell Biol 2009;41:1482-94. [Crossref] [PubMed]
38. Barroga CF, Zhang H, Wajih N, et al. The proteins encoded by the rbs operon of Escherichia coli: I. Overproduction, purification, characterization, and functional analysis of RbsA. Protein Sci 1996;5:1093-9. [Crossref] [PubMed]
39. Stewart JB, Hermodson MA. Topology of RbsC, the membrane component of the Escherichia coli ribose transporter. J Bacteriol 2003;185:5234-9. [Crossref] [PubMed]
40. Otamiri T, Franzén L, Lindmark D, et al. Increased phospholipase A2 and decreased lysophospholipase activity in the small intestinal mucosa after ischaemia and revascularisation. Gut 1987;28:1445-53. [Crossref] [PubMed]
41. Gu Q, Kong Y, Yu ZB, et al. Hypoxia-induced SOCS3 is limiting STAT3 phosphorylation and NF-κB activation in congenital heart disease. Biochimie 2011;93:909-20. [Crossref] [PubMed]
42. Ramakrishnan S, Anand V, Roy S. Vascular endothelial growth factor signaling in hypoxia and inflammation. J Neuroimmune Pharmacol 2014;9:142-60. [Crossref] [PubMed]
43. Song D, Fang G, Mao SZ, et al. Selective inhibition of endothelial NF-κB signaling attenuates chronic intermittent hypoxia-induced atherosclerosis in mice. Atherosclerosis 2018;270:68-75. [Crossref] [PubMed]
44. Tang X, Li S, Yang X, et al. Novel proteins associated with chronic intermittent hypoxia and obstructive sleep apnea: From rat model to clinical evidence. PLoS One 2021;16:e0253943. [Crossref] [PubMed]
45. Oeckinghaus A, Ghosh S. The NF-kappaB family of transcription factors and its regulation. Cold Spring Harb Perspect Biol 2009;1:a000034. [Crossref] [PubMed]
46. Karrasch T, Jobin C. NF-kappaB and the intestine: friend or foe? Inflamm Bowel Dis 2008;14:114-24. [Crossref] [PubMed]
47. Nath S, Villadsen J. Oxidative phosphorylation revisited. Biotechnol Bioeng 2015;112:429-37. [Crossref] [PubMed]
48. Sekhar RV, Patel SG, Guthikonda AP, et al. Deficient synthesis of glutathione underlies oxidative stress in aging and can be corrected by dietary cysteine and glycine supplementation. Am J Clin Nutr 2011;94:847-53. [Crossref] [PubMed]
49. Lushchak VI. Glutathione homeostasis and functions: potential targets for medical interventions. J Amino Acids 2012;2012:736837. [Crossref] [PubMed]

(English Language Editor: J. Teoh)