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. 2022 Mar 11;11(3):426.
doi: 10.3390/biology11030426.

Long Noncoding RNA GAS5 Contained in Exosomes Derived from Human Adipose Stem Cells Promotes Repair and Modulates Inflammation in a Chronic Dermal Wound Healing Model

Rekha S Patel  1 , Sabrina Impreso  1 , Ashley Lui  2 , Gitanjali Vidyarthi  1 , Paul Albear  1 , Niketa A Patel  1   2
Affiliations
Free PMC article

Long Noncoding RNA GAS5 Contained in Exosomes Derived from Human Adipose Stem Cells Promotes Repair and Modulates Inflammation in a Chronic Dermal Wound Healing Model

Rekha S Patel et al. Biology (Basel). .
Free PMC article

Abstract

Chronic recalcitrant wounds result from delayed or slowed healing processes. Underlying inflammation is a substantial risk factor for impaired dermal wound healing and often leads to chronic wound-related sequelae. Human adipose stem cells (hASCs) have shown tremendous potential in regenerative medicine. The goal of this project was to improve the outcome of chronic wounds by harvesting the exosomes from hASCs for therapeutic intervention. The results demonstrate that long noncoding RNA GAS5 is highly enriched in hASC exosomes and, further, that GAS5 is central to promoting wound repair in vitro. To evaluate the outcome of wound healing in a chronic low-grade inflammatory environment, lipopolysaccharide-treated HDF cells were evaluated for their response to hASC exosome treatment. Ingenuity pathway analysis identified inflammation pathways and genes affected by exosomes in a GAS5-dependent manner. Using siRNA to deplete GAS5 in HDF, the results demonstrated that Toll-like receptor 7 (TLR7) expression levels were regulated by GAS5. Importantly, the results demonstrate that GAS5 regulates inflammatory pathway genes in a chronic inflammation environment. The results presented here demonstrate that hASC exosomes are a viable therapeutic that accelerate the healing of chronic recalcitrant wounds.

Keywords: GAS5; chronic wounds; exosomes; human adipose stem cells; human dermal fibroblast (HDF); inflammation; lipopolysaccharide (LPS); long noncoding RNA (lncRNA); wound healing.

Conflict of interest statement

The authors declare no conflict of interest with regard to this manuscript.

Figures

Figure 1
Figure 1
Exosomes isolated from hASCs were verified by (a) western blot for hASC exosomal tetraspanin markers using antibodies against CD9, CD63, and CD81. The bands are representative of results obtained from experiments repeated five times. The graph represents ±SEM densitometric units. (b) The size and purity od hASC exosomes were evaluated using NanoSight v3.2.01 and (c) levels of long noncoding RNAs GAS5 and MALAT1 by absolute quantification by qPCR per 1 µg of exosomes across batches. (d) 1µg of mCherry or GFP overexpression plasmids were transfected into hASCs and exosomes were isolated from conditioned media. HDF cells were treated with 1 µg of exosomes and imaged using the Keyence microscope after 24 h showing uptake of hASC exosomes carrying mCherry or GFP (scale bar 20 µm, n = 3). (e) HDF cells were grown in a 35mm plate with Ibidi μ-inserts to generate consistent gaps. Inserts were removed and HDF cells were treated with exosomes (Exo) or exosomes depleted of GAS5 (Exo-G5) or depleted of MALAT1 (Exo-M1). Gap was imaged at time 0 and re-imaged after 18 hours. Wound gap was measured using Image J and area was calculated in µm2 (n = 3). Statistical analysis was performed by one-way ANOVA and significant p-values (<0.05) are indicated on graph.
Figure 2
Figure 2
HDF cells were seeded in a Seahorse XFp miniplate and treated with 100 μM H2O2 for 1 h, followed by medium change and treatment with hASC exosomes (Exo) or exosomes depleted of GAS5 (Exo-G5) for 18 h. A Mito Stress Test Assay was performed according to the manufacturer’s instructions and repeated three times. The readings were normalized to the protein content of each well. Seahorse Wave software was used for analysis of oxygen consumption rate (OCR), basal respiration, percent spare respiratory capacity and coupling efficiency (n = 3). Statistical analysis was performed by one-way ANOVA and significant p-values (<0.05) are indicated on the graph.
Figure 3
Figure 3
HDF cells were treated with 5 ng/mL LPS for 6 h and the medium was changed, followed by treatment with 1 μg hASC exosomes (Exo) or exosomes depleted of GAS5 (Exo-G5) for 18 h. (a) Acridine orange (AO) and propidium iodide (PI) dual staining was used to determine the viability of HDF cells (n = 3). Statistical analysis was performed by one-way ANOVA and significant p-values (<0.05) are indicated on the graphs. (b) Immunocytochemistry was performed using Ki67 staining as a marker for cellular proliferation in HDF cells. Cells were also stained with nuclear marker DAPI and imaged with a Keyence BZx-810 microscope (scale bar = 200 µm). Colocalization of Ki67 was determined using Keyence software (n = 3). Statistical analysis was performed by one-way ANOVA and significant p-values (<0.05) are indicated on the graph. (c) HDF cells were grown in a 35 mm plate with Ibidi μ-inserts to generate consistent gaps. Inserts were removed and HDF cells were treated with 5 ng/mL LPS for 6 h followed by treatment with Exo or Exo-G5 for 18 h. Gaps were imaged at time 0 and reimaged after 18 h and 24 h. Wound gap was measured using Image J and area was calculated in µm2 (n = 3). Statistical analysis was performed by one-way ANOVA and significant p-values (<0.05) are indicated on the graph. (d) RNA was isolated from HDF cells and SYBR Green real-time qPCR was performed using primers for IL1β and IL6; relative quantification was calculated, normalizing to GAPDH (n = 3). Statistical analysis was performed by one-way ANOVA and significant p-values (<0.05) are indicated on the graph.
Figure 4
Figure 4
HDF cells were treated with 5 ng/mL LPS for 6 h followed by hASC exosomes or exosomes depleted of GAS5 for 18 h. LPS was maintained in the media and cells were harvested after 4 days. RNA was isolated and PCR was run using the Human Inflammation Array (Qiagen, cat #PAHS-077Z). (a) Using GeneGlobe online data analysis software (Qiagen), a heatmap was generated from array data showing differentially expressed genes. (b) Genes identified from the heatmap showing patterns correlating to LPS, Exo, and Exo-G5 treatments were verified further by real-time qPCR. Relative quantification (RQ) was determined using a control sample as reference (n = 3). Statistical analysis was performed by one-way ANOVA and significant p-values (<0.05) are indicated on the graph. (c) ingenuity pathway analysis was performed on array data identifying canonical pathways influenced by GAS5 presence in exosomes. Changes in (d) the TLR pathway and (e) wound healing pathway were significantly altered in response to exosome and GAS5-depleted exosome treatment.
Figure 4
Figure 4
HDF cells were treated with 5 ng/mL LPS for 6 h followed by hASC exosomes or exosomes depleted of GAS5 for 18 h. LPS was maintained in the media and cells were harvested after 4 days. RNA was isolated and PCR was run using the Human Inflammation Array (Qiagen, cat #PAHS-077Z). (a) Using GeneGlobe online data analysis software (Qiagen), a heatmap was generated from array data showing differentially expressed genes. (b) Genes identified from the heatmap showing patterns correlating to LPS, Exo, and Exo-G5 treatments were verified further by real-time qPCR. Relative quantification (RQ) was determined using a control sample as reference (n = 3). Statistical analysis was performed by one-way ANOVA and significant p-values (<0.05) are indicated on the graph. (c) ingenuity pathway analysis was performed on array data identifying canonical pathways influenced by GAS5 presence in exosomes. Changes in (d) the TLR pathway and (e) wound healing pathway were significantly altered in response to exosome and GAS5-depleted exosome treatment.
Figure 5
Figure 5
(a) HDF cells were treated with 5 ng/mL LPS for 4 days. SYBR Green real-time qPCR was performed using GAS5 primers. Relative quantification (RQ) was determined using a control sample as reference (n = 3). Statistical analysis was performed by t-test and significant p-values (<0.05) are indicated on the graph. (b) GAS5 was depleted in HDF cells by transfecting 25 nM GAS5 siRNA or negative control siRNA (siRNA Con) for 48 h. RNA was isolated and real-time qPCR was performed using primers specific for GAS5, TLR7, IFNα, IL1β, or TNFα. Relative quantification (RQ) was determined using a control sample as reference (n = 3). Statistical analysis was performed by t-test and significant p-values (<0.05) are indicated on the graph.
Figure 6
Figure 6
HDF cells were grown on a collagen scaffold to mimic 3D wound healing. Chronic inflammation was induced for 4 days using 5 ng/mL LPS for 6 h followed by treatment with hASC exosomes (Exo) or exosomes depleted of GAS5 (Exo-G5) for 18 h. LPS was maintained in the media along with the treatment. The 3D wound model was maintained at 37 °C and wound closure was imaged every 24 h using a Keyence BX810 microscope (n = 3). Wound closure was calculated each day using a Keyence’s Cell migration assay with Hybrid cell count software to calculate wound gap area. Statistical analysis was performed by one-way ANOVA and significant p-values (<0.05) are indicated on the graph.
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