S2 Data -

At high altitudes, oxygen deprivation can cause pathophysiological changes. Liver tissue function is known to impact whole-body energy metabolism; however, how these functions are affected by chronic hypoxia remains unclear. We aimed to elucidate changing characteristics underlying the effect of chronic hypoxia on protein and amino acid metabolism in mouse livers. Mice were maintained in a hypobaric chamber simulating high altitude for 4 weeks. Livers were collected for metabolomic analysis via ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry. For transcriptomics analysis, we conducted RNA sequencing of hepatic tissues followed by Gene Ontology and KEGG pathway enrichment analyses. Chronic hypoxic exposure caused metabolic disorders of amino acids and their derivatives in liver tissue. We identified a number of metabolites with significantly altered profiles (including amino acids, peptides, and analogues), of which serine, phenylalanine, leucine, proline, aspartic acid, L-glutamate, creatine, 5-aminovaleric acid, L-hydroxyarginin, and g-guanidinobutyrate showed great potential as biomarkers of chronic hypoxia. A total of 2124 genes with significantly different expression levels were identified in hypoxic liver tissue, of which 1244 were upregulated and 880 were downregulated. We found pathways for protein digestion and absorption, arginine and proline metabolism, and mineral absorption related to amino acid metabolism were affected by hypoxia. Our findings surrounding the regulation of key metabolites and differentially expressed genes provide new insights into changes in protein and amino acid metabolism in the liver that result from chronic hypoxia.</div

Fully connected network of differential metabolites and genes.

The nodes in the rhombus indicate metabolites, and the nodes in the circle indicate genes. The color of the line represents the positive or negative value of the correlation between the two pathways (red represents negative correlation, black represents positive correlation), and the thickness of the line is proportional to the absolute value of the correlation coefficient.</p

Transcriptomic analysis of liver tissues in low altitude and mice treated with hypoxia exposure.

(A) Scores scatter plot of liver transcriptome in control mice and mice treated with hypoxia exposure; (B) Differential genes expression counts between low altitude group and high altitude group; (C) Correlation analysis of gene expression patterns in each group; (D) Cluster map of differential genes of two groups.</p

Pathways of liver tissue significantly influenced by chronic hypoxia exposure.

(A) KEGG enrichment pathway bubble figure. Each bubble in the bubble plot represents a metabolic pathway (the top 20 with the highest significance are selected according to the p value). The abscissa where the bubble is located and the size of the bubble indicate the influence factor size of the pathway in the topological analysis. The larger the size, the larger the influence factor. The vertical axis of the bubble and the color of the bubble represent the p value of enrichment analysis (taking the negative common logarithm, that is, -log10 p-value). The darker the color, the smaller the p value, the more significant the enrichment degree. The rich factor represents the proportion of the number of differential metabolites in the pathway to the number of metabolites annotated in the pathway. (B) Differential abundance score map of all enriched metabolic pathways. The Y-axis represents the name of the differential pathway, and the coordinates on the X-axis represent the DA score. A score of 1 indicates that all identified metabolites in this pathway tend to be upregulated, and -1 indicates that all identified metabolites in this pathway tend to be downregulated. The length of the line segment indicates the absolute value of DA score, the size of the dot at the end of the line segment indicates the number of metabolites in the pathway, and the larger the dot indicates the more metabolites. The color of the line segments and dots is proportional to the DA score value. The darker the red is, the more inclined the overall expression of the pathway is to be up-regulated, and the darker the blue is, the more inclined the overall expression of the pathway is to be down-regulated.</p

Changes in metabolic profiles of two groups mice liver.

(A) The number of metabolites identified of two groups; (B) PLS-DA score plot of liver metabolites between hypoxia 4 weeks and normoxia 4 weeks. Volcano plot for high altitude group and low altitude group in (C) positive ion mode and (D) negative ion mode. Upregulated significantly differential metabolites are represented by red circles, down-regulated significantly differential metabolites are represented by blue circles, and non-significantly differential metabolites are represented by black circles.</p

S1 File -

At high altitudes, oxygen deprivation can cause pathophysiological changes. Liver tissue function is known to impact whole-body energy metabolism; however, how these functions are affected by chronic hypoxia remains unclear. We aimed to elucidate changing characteristics underlying the effect of chronic hypoxia on protein and amino acid metabolism in mouse livers. Mice were maintained in a hypobaric chamber simulating high altitude for 4 weeks. Livers were collected for metabolomic analysis via ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry. For transcriptomics analysis, we conducted RNA sequencing of hepatic tissues followed by Gene Ontology and KEGG pathway enrichment analyses. Chronic hypoxic exposure caused metabolic disorders of amino acids and their derivatives in liver tissue. We identified a number of metabolites with significantly altered profiles (including amino acids, peptides, and analogues), of which serine, phenylalanine, leucine, proline, aspartic acid, L-glutamate, creatine, 5-aminovaleric acid, L-hydroxyarginin, and g-guanidinobutyrate showed great potential as biomarkers of chronic hypoxia. A total of 2124 genes with significantly different expression levels were identified in hypoxic liver tissue, of which 1244 were upregulated and 880 were downregulated. We found pathways for protein digestion and absorption, arginine and proline metabolism, and mineral absorption related to amino acid metabolism were affected by hypoxia. Our findings surrounding the regulation of key metabolites and differentially expressed genes provide new insights into changes in protein and amino acid metabolism in the liver that result from chronic hypoxia.</div

Transcriptomics profiling of the liver tissue in response to chronic hypoxia.

(A) Volcanic plot of differential genes expression distribution. (B) The GO terms with the top 10 biological process (BP), cellular component (CC), and molecular function (MF). (C) List of GO terms with the top 30 based on the 2124 DEGs. (D) List of top 20 significantly enriched KEGG pathways. (E) Levels of changes in genes associated with protein and amino acid metabolism, n = 3 per group. *P < 0.05, **P < 0.01.</p

S1 Data -

At high altitudes, oxygen deprivation can cause pathophysiological changes. Liver tissue function is known to impact whole-body energy metabolism; however, how these functions are affected by chronic hypoxia remains unclear. We aimed to elucidate changing characteristics underlying the effect of chronic hypoxia on protein and amino acid metabolism in mouse livers. Mice were maintained in a hypobaric chamber simulating high altitude for 4 weeks. Livers were collected for metabolomic analysis via ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry. For transcriptomics analysis, we conducted RNA sequencing of hepatic tissues followed by Gene Ontology and KEGG pathway enrichment analyses. Chronic hypoxic exposure caused metabolic disorders of amino acids and their derivatives in liver tissue. We identified a number of metabolites with significantly altered profiles (including amino acids, peptides, and analogues), of which serine, phenylalanine, leucine, proline, aspartic acid, L-glutamate, creatine, 5-aminovaleric acid, L-hydroxyarginin, and g-guanidinobutyrate showed great potential as biomarkers of chronic hypoxia. A total of 2124 genes with significantly different expression levels were identified in hypoxic liver tissue, of which 1244 were upregulated and 880 were downregulated. We found pathways for protein digestion and absorption, arginine and proline metabolism, and mineral absorption related to amino acid metabolism were affected by hypoxia. Our findings surrounding the regulation of key metabolites and differentially expressed genes provide new insights into changes in protein and amino acid metabolism in the liver that result from chronic hypoxia.</div

ApoB/LDL effects on PCSK9 internalization and function.

<p>(A and B) PCSK9-488 internalization in the presence of J16 (top row), LDL and J16 (middle row), or LDL+5F6+J16 (bottom row) in APLP2 siRNA treated cells. Dotted line indicates background signal, as measured by IC alone. Scale bars, 10 μM. (B) Quantification of (A) shown as average+SEM of J16 fluorescent signal per cell in APLP2 siRNA treated cells from 3 independent experiments. Dotted line indicates average IC background levels. Scale bars, 10 μM. (C) Representative western blot showing APLP2, LDLR, ApoB, Transferrin receptor (TFNR) levels in input fraction (I), IC or J16 immunoprecipitated samples (IP Ab.) under pH 7.4 or pH 6.0 conditions with increasing concentrations of ApoB, as indicated. (D) Western blot showing recombinant ApoB, LDLR-ECD, or PCSK9 in anti-LDLR immunoprecipitated samples at pH 6.0, with or without 5F6 Fab, as indicated. All experiments were performed independently at least 3 times and representative data are shown here.</p

PCSK9-488 internalization and LDLR levels <i>in vivo</i>.

<p>PCSK9-488 (green) internalization in mouse liver in the presence of mIC and hIC (top row), mIC and J16 (middle top row), hIC and 5F6 (middle bottom row), or 5F6 and J16 (bottom row). LDLR (red) and DAPI (blue) staining shown, as indicated. Scale bars, 10 μM.</p