healthy hff 1 line human fibroblasts (ATCC)


Structured Review

Healthy Hff 1 Line Human Fibroblasts, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/healthy hff 1 line human fibroblasts/product/ATCC
Average 86 stars, based on 1 article reviews
Price from $9.99 to $1999.99
Images
1) Product Images from "Tarin-Loaded Nanoliposomes Activate Apoptosis and Autophagy and Inhibit the Migration of Human Mammary Adenocarcinoma Cells"
Article Title: Tarin-Loaded Nanoliposomes Activate Apoptosis and Autophagy and Inhibit the Migration of Human Mammary Adenocarcinoma Cells
Journal: International Journal of Nanomedicine
doi: 10.2147/IJN.S434626

Figure Legend Snippet: Viability of healthy human cells (HFF-1) exposed to nanoliposome-encapsulated tarin (upper panels) and free tarin (bottom panels) for 24 h and 48 h. The viability of HFF-1 cells in cultures was determined employing resazurin as an indicator. The x-axis in the upper panel refers to the encapsulated tarin concentration, while empty liposomes refer to the corresponding volume of liposomal solution used to reach that concentration. *p< 0.05 compared to the control. ns – non-significant relative to the control.
Techniques Used: Concentration Assay, Liposomes
human foreskin fibroblasts hff 1 cell line (ATCC)


Structured Review

Human Foreskin Fibroblasts Hff 1 Cell Line, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/human foreskin fibroblasts hff 1 cell line/product/ATCC
Average 86 stars, based on 1 article reviews
Price from $9.99 to $1999.99
Images
1) Product Images from "The study of tryptophol containing emulgel on fungal reduction and skin irritation"
Article Title: The study of tryptophol containing emulgel on fungal reduction and skin irritation
Journal: Scientific Reports
doi: 10.1038/s41598-023-46121-z

Figure Legend Snippet: Cell viability ( a ) and cytotoxicity ( b ) of TOH-treated human foreskin fibroblasts (HFF- 1) cells at 37 °C as determined by MTT, Mitogreen, LDH, and dual AO/EB staining assays. Percentages of cell viability and cytotoxicity were shown as mean ± SD. *P < 0.05 and ****P < 0.0001 indicate significant differences compared with the control group (concentration 0). TOH Tryptophol, VOZ voriconazole.
Techniques Used: Staining, Concentration Assay
human fibroblasts hff 1 cell lines (ATCC)


Structured Review
Human Fibroblasts Hff 1 Cell Lines, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/human fibroblasts hff 1 cell lines/product/ATCC
Average 86 stars, based on 1 article reviews
Price from $9.99 to $1999.99
Images
hff 1 cells (ATCC)


Structured Review
Hff 1 Cells, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/hff 1 cells/product/ATCC
Average 86 stars, based on 1 article reviews
Price from $9.99 to $1999.99
Images
hff 1 (ATCC)


Structured Review

Hff 1, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/hff 1/product/ATCC
Average 86 stars, based on 1 article reviews
Price from $9.99 to $1999.99
Images
1) Product Images from "Human cytomegalovirus mediates APOBEC3B relocalization early during infection through a ribonucleotide reductase-independent mechanism"
Article Title: Human cytomegalovirus mediates APOBEC3B relocalization early during infection through a ribonucleotide reductase-independent mechanism
Journal: Journal of Virology
doi: 10.1128/jvi.00781-23

Figure Legend Snippet: A3B relocalization occurs early during HCMV infection. ( A and C ) Representative IF microscopy images of HFF-1 cells stably expressing A3B-HA incubated with medium alone (mock) or infected with the indicated HCMV strains for the indicated timepoints (10 µm scale). ( B and D ) Quantification of A3B-HA subcellular localization phenotypes shown in panels A and C. Each histogram bar reports the percentage of cells with whole cell, cytoplasmic, and nuclear A3B-HA ( n > 100 cells per condition; mean ± SD with P values from unpaired Student’s t -tests).
Techniques Used: Infection, Microscopy, Stable Transfection, Expressing, Incubation

Figure Legend Snippet: A3B relocalization requires de novo translation of HCMV proteins but not viral DNA synthesis. ( A ) Schematic representation of experimental workflows of CHX and PAA treatment of infected cells. Image created with BioRender. ( B ) Representative IF microscopy images of HFF-1 cells stably expressing A3B-HA incubated with medium alone (mock) or infected with AD169-GFP and treated with DMSO or CHX for 24 h (10 µm scale). ( C ) Representative IF microscopy images of U373 cells stably expressing A3B-HA incubated with medium alone (mock) or infected with AD169-GFP or AD169-GFP ΔIE1 for 72 h (10 µm scale). ( D ) Representative IF microscopy images of HFF-1 cells stably expressing A3B-HA incubated with medium alone (mock) or infected with AD169-GFP and treated with DMSO or PAA for 48 h (10 µm scale). ( E ) Quantification of A3B-HA subcellular localization phenotypes shown in panels B and D. Each histogram bar reports the percentage of cells with cytoplasmic A3B-HA ( n > 80 cells per condition; mean ± SD with P values from unpaired Student’s t -tests).
Techniques Used: DNA Synthesis, Infection, Microscopy, Stable Transfection, Expressing, Incubation
hff 1 (ATCC)


Structured Review
![A) Workflow of skin aging and senescence analyses. In step one, replication stress was induced by passage culturing using human foreskin fibroblasts, <t>HFF-1,</t> to prepare each PDL (see STAR Methods), and generate RNA-seq, ChIP-seq with H3K27Ac antibody, and ATAC-seq data. In the second step, two independent public RNA-seq datasets were analyzed, one in vitro and another in vivo . Finally, in the third step, we constructed a mathematical model based on the multi-omics analysis and in vitro experimental results. B) Growth curve of HFF-1 (blue line) and BJ cells (green line). N = 3, mean (SD). C) Western blot of p53 and p21 in replication-stress-induced HFF-1 cells. (Left panel) Representative image. (Middle panel) Quantification of p53 expression. N = 3, * p < 0.05 (Dunnett’s test). (Right panel) Quantification of p21 expression. N = 3, * p < 0.05, ** p < 0.01 (Dunnett’s test). D) (Left panel) SA-β-gal staining of replication-stress-induced HFF-1 cells. SA-β-gal-positive cells are indicated by an arrowhead (black). (Right panel) Quantification of SA-β-gal: SA-β-gal-positive rate (%) = number of SA-β-gal positive cells / total number of cells × 100, N = 3 (4 points/well), *** p < 0.001 (Dunnett’s test). E) Transcription factor (TF) enrichment analysis of RNA-seq data derived from replication-stress-induced HFF-1 cells. The heatmap shows the normalized TF enrichment scores calculated using the DoRothEA. F) Enriched motifs in the gained ATAC-seq peaks with increase of PDL. log(adj-p value) and proportion of target sequences with motif was calculated using the “findMotifsGenome.pl” function of HOMER. G) (Upper panel) Venn diagram showing RNA-seq differentially expressed genes (DEGs; |fold change (FC)| > 1.2, adj-p < 0.05, blue shade), genes annotated from ATAC differential peaks (|log 2 FC| > 0, adj-p < 0.05, purple shade), and genes annotated from H3K27Ac differential peaks (|log 2 FC| > 0, adj-p value < 0.05, red shade) between PDL 24, PDL 36, and PD47. The number of genes in each condition is shown in the Venn diagram. (Lower panel) The top five upstream regulators using Ingenuity Pathway Analysis (IPA) are shown with epigenetic-linked DEGs (93 genes). A right-tailed Fisher’s exact test was used to calculate –log(adj-p) of overlap. H) (Upper panel) Venn diagram showing the public in vitro DEGs (blue shade) and in vivo DEGs (red shade). (Lower panel) Heat map showing top five pathways annotated in the pathway enrichment analysis (Kyoto Encyclopedia of Genes and Genomes [KEGG]). The adj-p value was calculated using “compareCluster” of clusterProfiler. I) Upstream regulators using common genes between the public in vitro and in vivo datasets. The top four upstream regulators of 592 downregulated and 502 upregulated genes are shown with either a red or blue bar. A right-tailed Fisher’s exact test was used to calculate the adj-p value of overlap. J) Correlation analysis between the public in vitro (PDL), the public in vivo (age), and gene expression data. Spearman correlations were calculated using the “cor” function of R software; THBS1 (red) and FMOD (blue). R was calculated using the “ggpmisc::stat_poly_eq” function.](https://bio-rxiv-images-cdn.bioz.com/dois_ending_with_70/10__1101_slash_2023__07__18__546970/10__1101_slash_2023__07__18__546970___F2.large.jpg)
Hff 1, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/hff 1/product/ATCC
Average 86 stars, based on 1 article reviews
Price from $9.99 to $1999.99
Images
1) Product Images from "Positive and negative feedback regulation of the TGF-β1–SMAD4 axis explains two equilibrium states in human skin aging"
Article Title: Positive and negative feedback regulation of the TGF-β1–SMAD4 axis explains two equilibrium states in human skin aging
Journal: bioRxiv
doi: 10.1101/2023.07.18.546970
![... induced by passage culturing using human foreskin fibroblasts, HFF-1, to prepare each PDL (see STAR Methods), and ... A) Workflow of skin aging and senescence analyses. In step one, replication stress was induced by passage culturing using human foreskin fibroblasts, HFF-1, to prepare each PDL (see STAR Methods), and generate RNA-seq, ChIP-seq with H3K27Ac antibody, and ATAC-seq data. In the second step, two independent public RNA-seq datasets were analyzed, one in vitro and another in vivo . Finally, in the third step, we constructed a mathematical model based on the multi-omics analysis and in vitro experimental results. B) Growth curve of HFF-1 (blue line) and BJ cells (green line). N = 3, mean (SD). C) Western blot of p53 and p21 in replication-stress-induced HFF-1 cells. (Left panel) Representative image. (Middle panel) Quantification of p53 expression. N = 3, * p < 0.05 (Dunnett’s test). (Right panel) Quantification of p21 expression. N = 3, * p < 0.05, ** p < 0.01 (Dunnett’s test). D) (Left panel) SA-β-gal staining of replication-stress-induced HFF-1 cells. SA-β-gal-positive cells are indicated by an arrowhead (black). (Right panel) Quantification of SA-β-gal: SA-β-gal-positive rate (%) = number of SA-β-gal positive cells / total number of cells × 100, N = 3 (4 points/well), *** p < 0.001 (Dunnett’s test). E) Transcription factor (TF) enrichment analysis of RNA-seq data derived from replication-stress-induced HFF-1 cells. The heatmap shows the normalized TF enrichment scores calculated using the DoRothEA. F) Enriched motifs in the gained ATAC-seq peaks with increase of PDL. log(adj-p value) and proportion of target sequences with motif was calculated using the “findMotifsGenome.pl” function of HOMER. G) (Upper panel) Venn diagram showing RNA-seq differentially expressed genes (DEGs; |fold change (FC)| > 1.2, adj-p < 0.05, blue shade), genes annotated from ATAC differential peaks (|log 2 FC| > 0, adj-p < 0.05, purple shade), and genes annotated from H3K27Ac differential peaks (|log 2 FC| > 0, adj-p value < 0.05, red shade) between PDL 24, PDL 36, and PD47. The number of genes in each condition is shown in the Venn diagram. (Lower panel) The top five upstream regulators using Ingenuity Pathway Analysis (IPA) are shown with epigenetic-linked DEGs (93 genes). A right-tailed Fisher’s exact test was used to calculate –log(adj-p) of overlap. H) (Upper panel) Venn diagram showing the public in vitro DEGs (blue shade) and in vivo DEGs (red shade). (Lower panel) Heat map showing top five pathways annotated in the pathway enrichment analysis (Kyoto Encyclopedia of Genes and Genomes [KEGG]). The adj-p value was calculated using “compareCluster” of clusterProfiler. I) Upstream regulators using common genes between the public in vitro and in vivo datasets. The top four upstream regulators of 592 downregulated and 502 upregulated genes are shown with either a red or blue bar. A right-tailed Fisher’s exact test was used to calculate the adj-p value of overlap. J) Correlation analysis between the public in vitro (PDL), the public in vivo (age), and gene expression data. Spearman correlations were calculated using the “cor” function of R software; THBS1 (red) and FMOD (blue). R was calculated using the “ggpmisc::stat_poly_eq” function.](https://bio-rxiv-images-cdn.bioz.com/dois_ending_with_70/10__1101_slash_2023__07__18__546970/10__1101_slash_2023__07__18__546970___F2.large.jpg)
Figure Legend Snippet: A) Workflow of skin aging and senescence analyses. In step one, replication stress was induced by passage culturing using human foreskin fibroblasts, HFF-1, to prepare each PDL (see STAR Methods), and generate RNA-seq, ChIP-seq with H3K27Ac antibody, and ATAC-seq data. In the second step, two independent public RNA-seq datasets were analyzed, one in vitro and another in vivo . Finally, in the third step, we constructed a mathematical model based on the multi-omics analysis and in vitro experimental results. B) Growth curve of HFF-1 (blue line) and BJ cells (green line). N = 3, mean (SD). C) Western blot of p53 and p21 in replication-stress-induced HFF-1 cells. (Left panel) Representative image. (Middle panel) Quantification of p53 expression. N = 3, * p < 0.05 (Dunnett’s test). (Right panel) Quantification of p21 expression. N = 3, * p < 0.05, ** p < 0.01 (Dunnett’s test). D) (Left panel) SA-β-gal staining of replication-stress-induced HFF-1 cells. SA-β-gal-positive cells are indicated by an arrowhead (black). (Right panel) Quantification of SA-β-gal: SA-β-gal-positive rate (%) = number of SA-β-gal positive cells / total number of cells × 100, N = 3 (4 points/well), *** p < 0.001 (Dunnett’s test). E) Transcription factor (TF) enrichment analysis of RNA-seq data derived from replication-stress-induced HFF-1 cells. The heatmap shows the normalized TF enrichment scores calculated using the DoRothEA. F) Enriched motifs in the gained ATAC-seq peaks with increase of PDL. log(adj-p value) and proportion of target sequences with motif was calculated using the “findMotifsGenome.pl” function of HOMER. G) (Upper panel) Venn diagram showing RNA-seq differentially expressed genes (DEGs; |fold change (FC)| > 1.2, adj-p < 0.05, blue shade), genes annotated from ATAC differential peaks (|log 2 FC| > 0, adj-p < 0.05, purple shade), and genes annotated from H3K27Ac differential peaks (|log 2 FC| > 0, adj-p value < 0.05, red shade) between PDL 24, PDL 36, and PD47. The number of genes in each condition is shown in the Venn diagram. (Lower panel) The top five upstream regulators using Ingenuity Pathway Analysis (IPA) are shown with epigenetic-linked DEGs (93 genes). A right-tailed Fisher’s exact test was used to calculate –log(adj-p) of overlap. H) (Upper panel) Venn diagram showing the public in vitro DEGs (blue shade) and in vivo DEGs (red shade). (Lower panel) Heat map showing top five pathways annotated in the pathway enrichment analysis (Kyoto Encyclopedia of Genes and Genomes [KEGG]). The adj-p value was calculated using “compareCluster” of clusterProfiler. I) Upstream regulators using common genes between the public in vitro and in vivo datasets. The top four upstream regulators of 592 downregulated and 502 upregulated genes are shown with either a red or blue bar. A right-tailed Fisher’s exact test was used to calculate the adj-p value of overlap. J) Correlation analysis between the public in vitro (PDL), the public in vivo (age), and gene expression data. Spearman correlations were calculated using the “cor” function of R software; THBS1 (red) and FMOD (blue). R was calculated using the “ggpmisc::stat_poly_eq” function.
Techniques Used: RNA Sequencing Assay, ChIP-sequencing, In Vitro, In Vivo, Construct, Western Blot, Expressing, Staining, Derivative Assay, Software

Figure Legend Snippet: A) TGF-β1 ELISA in replication-stress-induced HFF-1 cell supernatant. N = 3, *** p < 0.001 (Dunnett’s test). B) Western blot analysis of THBS1 and FMOD in replication-stress-induced HFF-1 cells. (Left panel) Representative image. (Middle panel) Quantification of THBS1 expression. N = 3, * p < 0.05 (Dunnett’s test). (Right panel) Quantification of FMOD expression. N = 3, * p < 0.05 (Dunnett’s test). C) Western blot analysis of THBS1 and p21 in human dermal and epidermal tissues (N = 6). The data were normalized to the maximum (1) value. R was calculated using the “stat_poly_eq” function of R. (Upper panel) The age of each donor is displayed in the bottom of the image (see donor list in Table S2). (Lower left panel) Quantification of THBS1 expression in dermis. (Lower right panel) Quantification of p21 expression in dermis. D) Time-course cell proliferation analysis of control (blue-circled dots) or 4 ng/mL TGF-β1-treated (red triangular dots) cells stained with trypan blue. N = 3, mean (SD). E) BrdU incorporation assay. Control (blue), 4 ng/mL TGF-β1 (red), or 1 μg/mL THBS1 (purple). F) Western blot of Lamin-B1 and p21 in TGF-β1-stimulated HFF-1 cells. Cell lysates were collected 48 h after control (blue) or TGF-β1 (red) treatment. (Left panel) Representative image. (Middle panel) Quantification of Lamin-B1. N = 3, * p < 0.05 (vs. Control, Dunnett’s test). (Right panel) Quantification of p21. N = 3, *** p < 0.001 (Dunnett’s test). G) Western blot of p21 in THBS1-stimulated HFF-1 cells. Cell lysates were collected 48 h after control (blue) or THBS1 (purple) treatment. (Left panel) Representative image. (Right panel) Quantification of p21. N = 3, * p < 0.05 (Dunnett’s test). H) IL-6 and IL-8 ELISA in TGF-β1- or THBS1-stimulated HFF-1 cells. Cell supernatants were collected 48 h after TGF-β1 (red) or THBS1 (purple) treatment. (Upper left panel) Quantification of IL-6 ELISA with TGF-β1 treatment. N = 3, ** p < 0.01, *** p < 0.001 (Dunnett’s test). (Upper right panel) Quantification of IL-6 ELISA with THBS1 treatment. N = 3, ** p < 0.01 (Dunnett’s test). (Bottom left panel) Quantification of IL-8 ELISA with TGF-β1 treatment. N = 3, ** p < 0.01, *** p < 0.001 (Dunnett’s test). (Bottom right panel) Quantification of IL-8 ELISA with THBS1 treatment. N = 3, ** p < 0.01 (Dunnett’s test). I) Effect of TGF-β1 or THBS1 treatment and inhibition by FMOD on SA-β-gal activity. HFF-1 cells were treated with control, TGF-β1 (4 ng/mL), THBS1 (0.5 μg/mL), or FMOD (8 ng/mL). Combinations of TGF-β1 (4 ng/mL) and FMOD (8 ng/mL) as well as THBS1 (0.5 μg/mL) and FMOD (8 ng/mL) were performed alongside stand-alone treatments. (Left panel) Representative images. SA-β-gal-positive cells are shown with an arrowhead (black). Scale bars, 200 μm. (Right panel) Quantification of SA-β-gal: SA-β-gal-positive rate (%) = number of SA-β-gal-positive cells / total number of cells × 100, N = 3 (4 points/well), *** p < 0.001 (Tukey’s multiple comparisons).
Techniques Used: Enzyme-linked Immunosorbent Assay, Western Blot, Expressing, Staining, BrdU Incorporation Assay, Inhibition, Activity Assay

Figure Legend Snippet: A) Western blot of THBS1 and FMOD in TGF-β1-stimulated HFF-1 cells. Cell lysates were collected 48 h after control (blue) or TGF-β1 (red) treatment. (Left panel) Representative image. (Middle panel) Quantification of THBS1. N = 3, * p < 0.05 (vs. Control, Dunnett’s test). (Right panel) Quantification of FMOD. N = 3, * p < 0.05, ** p < 0.01 (Dunnett’s test). B) Western blot analysis of THBS1 in TGF-β1- and FMOD-stimulated HFF-1 cells. Cell lysates were collected 48 h after treatment with control (blue), 4 ng/mL TGF-β1 (red), or a combination of 4 ng/mL TGF-β1 and 8 ng/mL FMOD (purple). (Left panel) Representative image. (Right panel) Quantification of THBS1. N = 3, * p < 0.05, ** p < 0.01 (Tukey’s multiple comparisons). C) FMOD ELISA of THBS1-stimulated HFF-1 cells. Cells were treated with THBS1 (purple) for 48 h and their supernatants were analyzed. N = 3, * p < 0.01 (Dunnett’s test). D) Western blot analysis of THBS1 in THBS1-stimulated BJ cells. Cell lysates were collected 48 h after control (blue) or THBS1 (purple) treatment. (Left panel) Representative image. (Right panel) Quantification of THBS1. N = 3, ** p < 0.01 (Dunnett’s test). E) Western blot analysis of THBS1 with c-Fos/c-Jun knockdown (KD). Cell lysates were collected 48 h after control (blue) or TGF-β1 (red) treatment. (Left panel) Representative image. (Right panel) Quantification of THBS1. N = 3, ** p < 0.01 (Dunnett’s test). F) FMOD ELISA of kinase inhibitor-treated HFF-1 cells. Cells were treated with ZM306416HCl, Ki8751, GW5074, or U0126 for 48 h and their supernatants were analyzed. N = 3, ** p < 0.01, *** p < 0.001 (Dunnett’s test). G) FMOD ELISA in kinase inhibitor- and TGF-β1-treated HFF-1 cells. Cells were treated with Akt inhibitor VIII or LY294002 combined with TGF-β1 for 48 h and their supernatants were analyzed. N = 3, ** p < 0.01 (Student’s t -test), † p < 0.05, †† p < 0.01 (Dunnett’s test). H) Regulatory network of THBS1 and FMOD. In human dermal fibroblasts, TGF-β1 induced THBS1 production via TGF-βR–SMAD activation (red shade). FMOD was regulated via activation of the VEGFR–cRaf–MEK pathway (blue shade). Crosstalk between these pathways occurred with the TGF-β pathway inhibiting the VEGF pathway via the PI3K-Akt pathway (green shade).
Techniques Used: Western Blot, Enzyme-linked Immunosorbent Assay, Activation Assay

Figure Legend Snippet: A) Quantification of FMOD in LY294002-treated HFF-1 cells by ELISA. HFF-1 cells were initially treated with TGF-β1 and LY294002 was added at certain time points (0 h, purple; 8 h, green; 24 h, bright red; 32 h, orange) and supernatants were collected at 48 h. The relative expression to the Control (DMEM supplemented with 2% FBS) is shown. N = 3, *** p < 0.01 (vs. Control, Student’s t -test), † p < 0.05, †† p < 0.01 (vs. TGF-β1, Dunnett’s test). B) Experimental validation of simulated FMOD expression in HFF-1 cells treated with VEGF165 by ELISA. HFF-1 cells were treated with VEGF165 for 48 h and the supernatants were analyzed. N = 3, * p < 0.05 (Dunnett’s test). C) Validation of the sensitivity analysis by western blot analysis of THBS1 following siRNA KD of SMADs in HFF-1 cells. Lysates were collected 48 h after pretreatment with each SMAD siRNA alone or in combination for 24 h prior to stimulation with or without TGF-β1 (4 ng/mL). (Left panel) Representative image. (Right panel) Quantification of THBS1 with SMAD KD. N = 3, *** p < 0.001 (vs. Non-target Control treatment, Student’s t -test), †† p < 0.01 (vs. Non-target TGF-β1 treatment, Dunnett’s test). D) Effect of siRNA KD of SMADs on SA-β-gal activity. HFF-1 cells were pretreated with each siRNA (25 nM) and stimulated with TGF-β1 (4 ng/mL). (Left panel) Representative images. SA-β-gal-positive cells are indicated with the arrowhead (black). Scale bars, 200 μm. (Right panel) Quantification of SA-β-gal: SA-β-gal-positive rate (%) = SA-β-gal-positive cells / total number of cells × 100, N = 3 (4 points/well), *** p < 0.001 (Tukey’s multiple comparisons).
Techniques Used: Enzyme-linked Immunosorbent Assay, Expressing, Western Blot, Activity Assay
hff 1 (ATCC)


Structured Review
![A) Workflow of skin aging and senescence analyses. In step one, replication stress was induced by passage culturing using human foreskin fibroblasts, <t>HFF-1,</t> to prepare each PDL (see STAR Methods), and generate RNA-seq, ChIP-seq with H3K27Ac antibody, and ATAC-seq data. In the second step, two independent public RNA-seq datasets were analyzed, one in vitro and another in vivo . Finally, in the third step, we constructed a mathematical model based on the multi-omics analysis and in vitro experimental results. B) Growth curve of HFF-1 (blue line) and BJ cells (green line). N = 3, mean (SD). C) Western blot of p53 and p21 in replication-stress-induced HFF-1 cells. (Left panel) Representative image. (Middle panel) Quantification of p53 expression. N = 3, * p < 0.05 (Dunnett’s test). (Right panel) Quantification of p21 expression. N = 3, * p < 0.05, ** p < 0.01 (Dunnett’s test). D) (Left panel) SA-β-gal staining of replication-stress-induced HFF-1 cells. SA-β-gal-positive cells are indicated by an arrowhead (black). (Right panel) Quantification of SA-β-gal: SA-β-gal-positive rate (%) = number of SA-β-gal positive cells / total number of cells × 100, N = 3 (4 points/well), *** p < 0.001 (Dunnett’s test). E) Transcription factor (TF) enrichment analysis of RNA-seq data derived from replication-stress-induced HFF-1 cells. The heatmap shows the normalized TF enrichment scores calculated using the DoRothEA. F) Enriched motifs in the gained ATAC-seq peaks with increase of PDL. log(adj-p value) and proportion of target sequences with motif was calculated using the “findMotifsGenome.pl” function of HOMER. G) (Upper panel) Venn diagram showing RNA-seq differentially expressed genes (DEGs; |fold change (FC)| > 1.2, adj-p < 0.05, blue shade), genes annotated from ATAC differential peaks (|log 2 FC| > 0, adj-p < 0.05, purple shade), and genes annotated from H3K27Ac differential peaks (|log 2 FC| > 0, adj-p value < 0.05, red shade) between PDL 24, PDL 36, and PD47. The number of genes in each condition is shown in the Venn diagram. (Lower panel) The top five upstream regulators using Ingenuity Pathway Analysis (IPA) are shown with epigenetic-linked DEGs (93 genes). A right-tailed Fisher’s exact test was used to calculate –log(adj-p) of overlap. H) (Upper panel) Venn diagram showing the public in vitro DEGs (blue shade) and in vivo DEGs (red shade). (Lower panel) Heat map showing top five pathways annotated in the pathway enrichment analysis (Kyoto Encyclopedia of Genes and Genomes [KEGG]). The adj-p value was calculated using “compareCluster” of clusterProfiler. I) Upstream regulators using common genes between the public in vitro and in vivo datasets. The top four upstream regulators of 592 downregulated and 502 upregulated genes are shown with either a red or blue bar. A right-tailed Fisher’s exact test was used to calculate the adj-p value of overlap. J) Correlation analysis between the public in vitro (PDL), the public in vivo (age), and gene expression data. Spearman correlations were calculated using the “cor” function of R software; THBS1 (red) and FMOD (blue). R was calculated using the “ggpmisc::stat_poly_eq” function.](https://bio-rxiv-images-cdn.bioz.com/dois_ending_with_70/10__1101_slash_2023__07__18__546970/10__1101_slash_2023__07__18__546970___F2.large.jpg)
Hff 1, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/hff 1/product/ATCC
Average 86 stars, based on 1 article reviews
Price from $9.99 to $1999.99
Images
1) Product Images from "Positive and negative feedback regulation of the TGF-β1–SMAD4 axis explains two equilibrium states in human skin aging"
Article Title: Positive and negative feedback regulation of the TGF-β1–SMAD4 axis explains two equilibrium states in human skin aging
Journal: bioRxiv
doi: 10.1101/2023.07.18.546970
![... induced by passage culturing using human foreskin fibroblasts, HFF-1, to prepare each PDL (see STAR Methods), and ... A) Workflow of skin aging and senescence analyses. In step one, replication stress was induced by passage culturing using human foreskin fibroblasts, HFF-1, to prepare each PDL (see STAR Methods), and generate RNA-seq, ChIP-seq with H3K27Ac antibody, and ATAC-seq data. In the second step, two independent public RNA-seq datasets were analyzed, one in vitro and another in vivo . Finally, in the third step, we constructed a mathematical model based on the multi-omics analysis and in vitro experimental results. B) Growth curve of HFF-1 (blue line) and BJ cells (green line). N = 3, mean (SD). C) Western blot of p53 and p21 in replication-stress-induced HFF-1 cells. (Left panel) Representative image. (Middle panel) Quantification of p53 expression. N = 3, * p < 0.05 (Dunnett’s test). (Right panel) Quantification of p21 expression. N = 3, * p < 0.05, ** p < 0.01 (Dunnett’s test). D) (Left panel) SA-β-gal staining of replication-stress-induced HFF-1 cells. SA-β-gal-positive cells are indicated by an arrowhead (black). (Right panel) Quantification of SA-β-gal: SA-β-gal-positive rate (%) = number of SA-β-gal positive cells / total number of cells × 100, N = 3 (4 points/well), *** p < 0.001 (Dunnett’s test). E) Transcription factor (TF) enrichment analysis of RNA-seq data derived from replication-stress-induced HFF-1 cells. The heatmap shows the normalized TF enrichment scores calculated using the DoRothEA. F) Enriched motifs in the gained ATAC-seq peaks with increase of PDL. log(adj-p value) and proportion of target sequences with motif was calculated using the “findMotifsGenome.pl” function of HOMER. G) (Upper panel) Venn diagram showing RNA-seq differentially expressed genes (DEGs; |fold change (FC)| > 1.2, adj-p < 0.05, blue shade), genes annotated from ATAC differential peaks (|log 2 FC| > 0, adj-p < 0.05, purple shade), and genes annotated from H3K27Ac differential peaks (|log 2 FC| > 0, adj-p value < 0.05, red shade) between PDL 24, PDL 36, and PD47. The number of genes in each condition is shown in the Venn diagram. (Lower panel) The top five upstream regulators using Ingenuity Pathway Analysis (IPA) are shown with epigenetic-linked DEGs (93 genes). A right-tailed Fisher’s exact test was used to calculate –log(adj-p) of overlap. H) (Upper panel) Venn diagram showing the public in vitro DEGs (blue shade) and in vivo DEGs (red shade). (Lower panel) Heat map showing top five pathways annotated in the pathway enrichment analysis (Kyoto Encyclopedia of Genes and Genomes [KEGG]). The adj-p value was calculated using “compareCluster” of clusterProfiler. I) Upstream regulators using common genes between the public in vitro and in vivo datasets. The top four upstream regulators of 592 downregulated and 502 upregulated genes are shown with either a red or blue bar. A right-tailed Fisher’s exact test was used to calculate the adj-p value of overlap. J) Correlation analysis between the public in vitro (PDL), the public in vivo (age), and gene expression data. Spearman correlations were calculated using the “cor” function of R software; THBS1 (red) and FMOD (blue). R was calculated using the “ggpmisc::stat_poly_eq” function.](https://bio-rxiv-images-cdn.bioz.com/dois_ending_with_70/10__1101_slash_2023__07__18__546970/10__1101_slash_2023__07__18__546970___F2.large.jpg)
Figure Legend Snippet: A) Workflow of skin aging and senescence analyses. In step one, replication stress was induced by passage culturing using human foreskin fibroblasts, HFF-1, to prepare each PDL (see STAR Methods), and generate RNA-seq, ChIP-seq with H3K27Ac antibody, and ATAC-seq data. In the second step, two independent public RNA-seq datasets were analyzed, one in vitro and another in vivo . Finally, in the third step, we constructed a mathematical model based on the multi-omics analysis and in vitro experimental results. B) Growth curve of HFF-1 (blue line) and BJ cells (green line). N = 3, mean (SD). C) Western blot of p53 and p21 in replication-stress-induced HFF-1 cells. (Left panel) Representative image. (Middle panel) Quantification of p53 expression. N = 3, * p < 0.05 (Dunnett’s test). (Right panel) Quantification of p21 expression. N = 3, * p < 0.05, ** p < 0.01 (Dunnett’s test). D) (Left panel) SA-β-gal staining of replication-stress-induced HFF-1 cells. SA-β-gal-positive cells are indicated by an arrowhead (black). (Right panel) Quantification of SA-β-gal: SA-β-gal-positive rate (%) = number of SA-β-gal positive cells / total number of cells × 100, N = 3 (4 points/well), *** p < 0.001 (Dunnett’s test). E) Transcription factor (TF) enrichment analysis of RNA-seq data derived from replication-stress-induced HFF-1 cells. The heatmap shows the normalized TF enrichment scores calculated using the DoRothEA. F) Enriched motifs in the gained ATAC-seq peaks with increase of PDL. log(adj-p value) and proportion of target sequences with motif was calculated using the “findMotifsGenome.pl” function of HOMER. G) (Upper panel) Venn diagram showing RNA-seq differentially expressed genes (DEGs; |fold change (FC)| > 1.2, adj-p < 0.05, blue shade), genes annotated from ATAC differential peaks (|log 2 FC| > 0, adj-p < 0.05, purple shade), and genes annotated from H3K27Ac differential peaks (|log 2 FC| > 0, adj-p value < 0.05, red shade) between PDL 24, PDL 36, and PD47. The number of genes in each condition is shown in the Venn diagram. (Lower panel) The top five upstream regulators using Ingenuity Pathway Analysis (IPA) are shown with epigenetic-linked DEGs (93 genes). A right-tailed Fisher’s exact test was used to calculate –log(adj-p) of overlap. H) (Upper panel) Venn diagram showing the public in vitro DEGs (blue shade) and in vivo DEGs (red shade). (Lower panel) Heat map showing top five pathways annotated in the pathway enrichment analysis (Kyoto Encyclopedia of Genes and Genomes [KEGG]). The adj-p value was calculated using “compareCluster” of clusterProfiler. I) Upstream regulators using common genes between the public in vitro and in vivo datasets. The top four upstream regulators of 592 downregulated and 502 upregulated genes are shown with either a red or blue bar. A right-tailed Fisher’s exact test was used to calculate the adj-p value of overlap. J) Correlation analysis between the public in vitro (PDL), the public in vivo (age), and gene expression data. Spearman correlations were calculated using the “cor” function of R software; THBS1 (red) and FMOD (blue). R was calculated using the “ggpmisc::stat_poly_eq” function.
Techniques Used: RNA Sequencing Assay, ChIP-sequencing, In Vitro, In Vivo, Construct, Western Blot, Expressing, Staining, Derivative Assay, Software

Figure Legend Snippet: A) TGF-β1 ELISA in replication-stress-induced HFF-1 cell supernatant. N = 3, *** p < 0.001 (Dunnett’s test). B) Western blot analysis of THBS1 and FMOD in replication-stress-induced HFF-1 cells. (Left panel) Representative image. (Middle panel) Quantification of THBS1 expression. N = 3, * p < 0.05 (Dunnett’s test). (Right panel) Quantification of FMOD expression. N = 3, * p < 0.05 (Dunnett’s test). C) Western blot analysis of THBS1 and p21 in human dermal and epidermal tissues (N = 6). The data were normalized to the maximum (1) value. R was calculated using the “stat_poly_eq” function of R. (Upper panel) The age of each donor is displayed in the bottom of the image (see donor list in Table S2). (Lower left panel) Quantification of THBS1 expression in dermis. (Lower right panel) Quantification of p21 expression in dermis. D) Time-course cell proliferation analysis of control (blue-circled dots) or 4 ng/mL TGF-β1-treated (red triangular dots) cells stained with trypan blue. N = 3, mean (SD). E) BrdU incorporation assay. Control (blue), 4 ng/mL TGF-β1 (red), or 1 μg/mL THBS1 (purple). F) Western blot of Lamin-B1 and p21 in TGF-β1-stimulated HFF-1 cells. Cell lysates were collected 48 h after control (blue) or TGF-β1 (red) treatment. (Left panel) Representative image. (Middle panel) Quantification of Lamin-B1. N = 3, * p < 0.05 (vs. Control, Dunnett’s test). (Right panel) Quantification of p21. N = 3, *** p < 0.001 (Dunnett’s test). G) Western blot of p21 in THBS1-stimulated HFF-1 cells. Cell lysates were collected 48 h after control (blue) or THBS1 (purple) treatment. (Left panel) Representative image. (Right panel) Quantification of p21. N = 3, * p < 0.05 (Dunnett’s test). H) IL-6 and IL-8 ELISA in TGF-β1- or THBS1-stimulated HFF-1 cells. Cell supernatants were collected 48 h after TGF-β1 (red) or THBS1 (purple) treatment. (Upper left panel) Quantification of IL-6 ELISA with TGF-β1 treatment. N = 3, ** p < 0.01, *** p < 0.001 (Dunnett’s test). (Upper right panel) Quantification of IL-6 ELISA with THBS1 treatment. N = 3, ** p < 0.01 (Dunnett’s test). (Bottom left panel) Quantification of IL-8 ELISA with TGF-β1 treatment. N = 3, ** p < 0.01, *** p < 0.001 (Dunnett’s test). (Bottom right panel) Quantification of IL-8 ELISA with THBS1 treatment. N = 3, ** p < 0.01 (Dunnett’s test). I) Effect of TGF-β1 or THBS1 treatment and inhibition by FMOD on SA-β-gal activity. HFF-1 cells were treated with control, TGF-β1 (4 ng/mL), THBS1 (0.5 μg/mL), or FMOD (8 ng/mL). Combinations of TGF-β1 (4 ng/mL) and FMOD (8 ng/mL) as well as THBS1 (0.5 μg/mL) and FMOD (8 ng/mL) were performed alongside stand-alone treatments. (Left panel) Representative images. SA-β-gal-positive cells are shown with an arrowhead (black). Scale bars, 200 μm. (Right panel) Quantification of SA-β-gal: SA-β-gal-positive rate (%) = number of SA-β-gal-positive cells / total number of cells × 100, N = 3 (4 points/well), *** p < 0.001 (Tukey’s multiple comparisons).
Techniques Used: Enzyme-linked Immunosorbent Assay, Western Blot, Expressing, Staining, BrdU Incorporation Assay, Inhibition, Activity Assay

Figure Legend Snippet: A) Western blot of THBS1 and FMOD in TGF-β1-stimulated HFF-1 cells. Cell lysates were collected 48 h after control (blue) or TGF-β1 (red) treatment. (Left panel) Representative image. (Middle panel) Quantification of THBS1. N = 3, * p < 0.05 (vs. Control, Dunnett’s test). (Right panel) Quantification of FMOD. N = 3, * p < 0.05, ** p < 0.01 (Dunnett’s test). B) Western blot analysis of THBS1 in TGF-β1- and FMOD-stimulated HFF-1 cells. Cell lysates were collected 48 h after treatment with control (blue), 4 ng/mL TGF-β1 (red), or a combination of 4 ng/mL TGF-β1 and 8 ng/mL FMOD (purple). (Left panel) Representative image. (Right panel) Quantification of THBS1. N = 3, * p < 0.05, ** p < 0.01 (Tukey’s multiple comparisons). C) FMOD ELISA of THBS1-stimulated HFF-1 cells. Cells were treated with THBS1 (purple) for 48 h and their supernatants were analyzed. N = 3, * p < 0.01 (Dunnett’s test). D) Western blot analysis of THBS1 in THBS1-stimulated BJ cells. Cell lysates were collected 48 h after control (blue) or THBS1 (purple) treatment. (Left panel) Representative image. (Right panel) Quantification of THBS1. N = 3, ** p < 0.01 (Dunnett’s test). E) Western blot analysis of THBS1 with c-Fos/c-Jun knockdown (KD). Cell lysates were collected 48 h after control (blue) or TGF-β1 (red) treatment. (Left panel) Representative image. (Right panel) Quantification of THBS1. N = 3, ** p < 0.01 (Dunnett’s test). F) FMOD ELISA of kinase inhibitor-treated HFF-1 cells. Cells were treated with ZM306416HCl, Ki8751, GW5074, or U0126 for 48 h and their supernatants were analyzed. N = 3, ** p < 0.01, *** p < 0.001 (Dunnett’s test). G) FMOD ELISA in kinase inhibitor- and TGF-β1-treated HFF-1 cells. Cells were treated with Akt inhibitor VIII or LY294002 combined with TGF-β1 for 48 h and their supernatants were analyzed. N = 3, ** p < 0.01 (Student’s t -test), † p < 0.05, †† p < 0.01 (Dunnett’s test). H) Regulatory network of THBS1 and FMOD. In human dermal fibroblasts, TGF-β1 induced THBS1 production via TGF-βR–SMAD activation (red shade). FMOD was regulated via activation of the VEGFR–cRaf–MEK pathway (blue shade). Crosstalk between these pathways occurred with the TGF-β pathway inhibiting the VEGF pathway via the PI3K-Akt pathway (green shade).
Techniques Used: Western Blot, Enzyme-linked Immunosorbent Assay, Activation Assay

Figure Legend Snippet: A) Quantification of FMOD in LY294002-treated HFF-1 cells by ELISA. HFF-1 cells were initially treated with TGF-β1 and LY294002 was added at certain time points (0 h, purple; 8 h, green; 24 h, bright red; 32 h, orange) and supernatants were collected at 48 h. The relative expression to the Control (DMEM supplemented with 2% FBS) is shown. N = 3, *** p < 0.01 (vs. Control, Student’s t -test), † p < 0.05, †† p < 0.01 (vs. TGF-β1, Dunnett’s test). B) Experimental validation of simulated FMOD expression in HFF-1 cells treated with VEGF165 by ELISA. HFF-1 cells were treated with VEGF165 for 48 h and the supernatants were analyzed. N = 3, * p < 0.05 (Dunnett’s test). C) Validation of the sensitivity analysis by western blot analysis of THBS1 following siRNA KD of SMADs in HFF-1 cells. Lysates were collected 48 h after pretreatment with each SMAD siRNA alone or in combination for 24 h prior to stimulation with or without TGF-β1 (4 ng/mL). (Left panel) Representative image. (Right panel) Quantification of THBS1 with SMAD KD. N = 3, *** p < 0.001 (vs. Non-target Control treatment, Student’s t -test), †† p < 0.01 (vs. Non-target TGF-β1 treatment, Dunnett’s test). D) Effect of siRNA KD of SMADs on SA-β-gal activity. HFF-1 cells were pretreated with each siRNA (25 nM) and stimulated with TGF-β1 (4 ng/mL). (Left panel) Representative images. SA-β-gal-positive cells are indicated with the arrowhead (black). Scale bars, 200 μm. (Right panel) Quantification of SA-β-gal: SA-β-gal-positive rate (%) = SA-β-gal-positive cells / total number of cells × 100, N = 3 (4 points/well), *** p < 0.001 (Tukey’s multiple comparisons).
Techniques Used: Enzyme-linked Immunosorbent Assay, Expressing, Western Blot, Activity Assay
hff 1 (ATCC)


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Hff 1, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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human skin fibroblast hff 1 (ATCC)


Structured Review
Human Skin Fibroblast Hff 1, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/human skin fibroblast hff 1/product/ATCC
Average 86 stars, based on 1 article reviews
Price from $9.99 to $1999.99
Images
human foreskin fibroblast 1 hff 1 cell line (ATCC)


Structured Review
Human Foreskin Fibroblast 1 Hff 1 Cell Line, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/human foreskin fibroblast 1 hff 1 cell line/product/ATCC
Average 86 stars, based on 1 article reviews
Price from $9.99 to $1999.99