Cells

15 pages, 2223 KiB

Open AccessArticle

High Level of CD8⁺PD-1⁺ Cells in Patients with Chronic Myeloid Leukemia Who Experienced Loss of MMR after Imatinib Discontinuation

by Paulina Kwaśnik, Joanna Zaleska, Dorota Link-Lenczowska, Magdalena Zawada, Hubert Wysogląd, Bogdan Ochrem, Grażyna Bober, Ewa Wasilewska, Iwona Hus, Monika Szarejko, Witold Prejzner, Olga Grzybowska-Izydorczyk, Agnieszka Klonowska-Szymczyk, Ewa Mędraś, Michał Kiełbus, Tomasz Sacha and Krzysztof Giannopoulos

Cells 2024, 13(8), 723; https://doi.org/10.3390/cells13080723 - 22 Apr 2024

Viewed by 1568

Abstract

Treatment-free remission (TFR) is achieved in approximately half of chronic myeloid leukemia (CML) patients treated with tyrosine kinase inhibitors. The mechanisms responsible for TFR maintenance remain elusive. This study aimed to identify immune markers responsible for the control of residual CML cells early [...] Read more.

Treatment-free remission (TFR) is achieved in approximately half of chronic myeloid leukemia (CML) patients treated with tyrosine kinase inhibitors. The mechanisms responsible for TFR maintenance remain elusive. This study aimed to identify immune markers responsible for the control of residual CML cells early in the TFR (at 3 months), which may be the key to achieving long-term TFR and relapse-free survival (RFS) after discontinuation of imatinib. Our study included 63 CML patients after imatinib discontinuation, in whom comprehensive analysis of changes in the immune system was performed by flow cytometry, and changes in the BCR::ABL1 transcript levels were assessed by RQ-PCR and ddPCR. We demonstrated a significant increase in the percentage of CD8⁺PD-1⁺ cells in patients losing TFR. The level of CD8⁺PD-1⁺ cells is inversely related to the duration of treatment and incidence of deep molecular response (DMR) before discontinuation. Analysis of the ROC curve showed that the percentage of CD8⁺PD-1⁺ cells may be a significant factor in early molecular recurrence. Interestingly, at 3 months of TFR, patients with the e13a2 transcript had a significantly higher proportion of the PD-1-expressing immune cells compared to patients with the e14a2. Our results suggest the important involvement of CD8⁺PD-1⁺ cells in the success of TFR and may help in identifying a group of patients who could successfully discontinue imatinib. Full article

(This article belongs to the Collection Trends and Advances in Tumor Immunology)

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Figure 1

Figure 1
Immunological characteristics of all patients enrolled in the study. Differences in the percentages of immune populations at the moment of stopping imatinib and at 3 months after discontinuation in analyzed patients (Wilcoxon signed-rank test). (A) DC subpopulations; mDC, median: 0.20 vs. 0.28%; pDC, median: 0.12 vs. 0.15%; mDC PD-1+, median: 35.81 vs. 32.23%. (B) NKT-like and NK cells; NKT-like cells, median: 14.45 vs. 12.80%; NKT-like PD-1+; median: 21.02 vs. 21.28%; CD56brightCD16-PD-1+, median: 2.31 vs. 2.08%; CD56dimCD16+PD-1+, median: 3.71 vs. 3.49%. (C) CD4+ T cells and regulatory T cells; Treg CD4+CD25+CD127dimFOXP3+, median: 3.00 vs. 2.89%; CD4+PD-1+, median: 21.59 vs. 19.34%. Red color indicates statistical significance p < 0.05, blue color indicates tendency p < 0.1. Full article ">Figure 2
Changes in immune populations in patients with stable MMR or lost MMR at 3 months after withdrawal. Differences in the percentages of immune populations between patient groups were analyzed with the Mann–Whitney U test. (A) CD8+PD-1+ cells, median: 17.70 vs. 27.13%. (B) mDC PD-1+, median: 31.55 vs. 42.88%. (C) pDC PD-1+, median: 33.42 vs. 46.76%. Red color indicates statistical significance p < 0.05, blue color indicates tendency p < 0.1. Full article ">Figure 3
Comparison of ROC curves showing an analysis of potential immunological biomarkers by age, duration of DMR, length of TKI treatment before TFR, and percentages of CD8+PD-1+, mDC PD-1+, and pDC PD-1+. Among the clinical data evaluated, ROC analysis indicates CD8+PD-1+ percentage as the strongest factor in early molecular reoccurrence (lost MMR) (p < 0.01). The statistically significant marker of lost MMR is the duration of DMR before stopping treatment (p < 0.05) (ROC curves). Full article ">Figure 4
Correlation between percentage of CD8+PD-1+ in patients at 3 months after withdrawal, and duration of treatment and DMR before TFR trial. The percentage of CD8+PD-1+ is inversely related to the treatment of imatinib (R = −0.3227, 95% CI: −0.5618 to −0.03378) and DMR duration (R = −0.3118, 95% CI: −0.5535 to −0.02176) (Spearman r). Red color indicates statistical significance p < 0.05, green color indicates the correlation coefficient. Full article ">Figure 5
Analysis of changes in the immune system of patients depending on the transcript type of BCR::ABL1. Higher percentage of the population expressing PD-1 in patients with e13a2 compared to patients with e14a2 (Mann–Whitney U test). Differences between patients with e13a2 vs. patients with e14a2: CD56dimCD16+PD-1+, median: 4.89 vs. 3.12%; CD19+PD-1+, median: 16.20 vs. 10.48%; CD8+PD-1+, median: 23.15 vs. 14.91%. Red color indicates statistical significance p < 0.05, blue color indicates tendency p < 0.1. Full article ">

5 pages, 1415 KiB

Open AccessCorrection

Correction: Dastghaib et al. Simvastatin Induces Unfolded Protein Response and Enhances Temozolomide-Induced Cell Death in Glioblastoma Cells. Cells 2020, 9, 2339

by Sanaz Dastghaib, Shahla Shojaei, Zohreh Mostafavi-Pour, Pawan Sharma, John B. Patterson, Afshin Samali, Pooneh Mokarram and Saeid Ghavami

Cells 2024, 13(8), 722; https://doi.org/10.3390/cells13080722 - 22 Apr 2024

Cited by 1 | Viewed by 909

Abstract

In the original publication [...] Full article

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Figure 4
Simva–TMZ modulates the autophagy machinery via the IRE-1 pathway. (A) After pretreatment with MKC8866 (30 µM, 4 h), U87 and U251 cells were co-treated with TMZ, Simva, or Simva–TMZ for 72 h. The protein levels of Beclin-1, p62, LC3β-II, and LCβ-I were determined by immunoblotting. Simva–TMZ induced an inhibition of autophagy flux (accumulation of p62 and LC3β-II) in GBM cells. In Simva–TMZ-treated cells, MKC8866 increased p62 and Beclin-1 degradation, while it differentially affected the LC3β-II/LC3β-I ratio; GAPDH was used as loading control. Densitometric analysis of the Western blot bands confirmed that Simva–TMZ significantly induced Beclin-1 and p62 accumulation in both U87 and U251 cells (p < 0.0001), which was markedly prevented in the presence of MKC8866 (B,C,E,F). In addition, MKC8866 increased the LC3β-II/LC3β-I ratio in Simva–TMZ-treated U251 cells (p < 0.0001) (G), whereas it did not change LC3β-II/LC3β-I in U87 cells (p < 0.0001) (D). The data are shown as the mean ± SD from three independent experiments (* p < 0.05; ** p < 0.01, *** p < 0.001; **** p < 0.0001). Full article ">Figure 6
PERK inhibition does not change the p-eIF2α/eIF2α ratio in Simva–TMZ-treated cells. (A) U87 and U251 were pretreated with PERKi (5 µM, 30 min) and then co-treated with Simva–TMZ for 72 h. The protein levels of eIF2α and p-eIF2α were determined using immunoblotting; GAPDH was used as a loading control. (B,C) Densitometric analysis of the immunoblots showed that Simva–TMZ by itself significantly reduced the p-eIF2α/eIF2α ratio, which was not further decreased by the PERKi in either cell line. Of note, control levels of p-eIF2α were significantly decreased by the PERKi as well. The data are expressed as the means ± SD of three independent experiments ** p < 0.01; **** p < 0.0001). Full article ">Figure 7
PERK inhibition differentially affects autophagy flux in U87 and U251 cells treated with Simva–TMZ. (A) U87 and U251 cells were pretreated GSK PERK inhibitor (5 µM, 30 min) and then co-treated with Simva–TMZ as described for 72 h. The protein levels of p62, LC3β-II, and LCβ-I were determined by immunoblotting. Simva–TMZ induced an inhibition of autophagy flux (accumulation of p62 and LC3β-II) in GBM cells. The PERKi decreased p62 degradation (autophagosome degradation) in both U87 and U251 cells, while it increased the LC3β-II/LC3β-I ratio in U251 cells and decreased it in U87 cells. GAPDH was used as a loading control. (B–E) Densitometric analysis of the Western blot bands to quantify p62 and LC3β-II/LC3β-I protein amount. Data are expressed as the mean ± SD of three independent experiments (** p < 0.01; **** p < 0.0001). Full article ">Figure 9
p-eIF2α phosphatase inhibition increases the p-eIF2α/eIF2α ratio in Simva–TMZ treated in GBM cells. (A) U87 and U251 cells were pretreated with salubrinal (15 µM, 30 min) followed by co-treatment with Simva–TMZ for 72 h. Cell lysates were collected, and the p-eIF2α/eIF2α protein amount ratios were determined using immunoblotting; GAPDH was used as a loading control. (B,C) Densitometric analysis of the Western blot bands shows that salubrinal significantly (p < 0.0001) increased the p-eIF2α/eIF2α ratio with Simva–TMZ treatment. Data are expressed as the means ± SD of three independent experiments (** p < 0.01, **** p < 0.0001). Full article ">

21 pages, 2210 KiB

Open AccessReview

Drosophila Contributions towards Understanding Neurofibromatosis 1

by Kalliopi Atsoniou, Eleni Giannopoulou, Eirini-Maria Georganta and Efthimios M. C. Skoulakis

Cells 2024, 13(8), 721; https://doi.org/10.3390/cells13080721 - 21 Apr 2024

Cited by 1 | Viewed by 1870

Abstract

Neurofibromatosis 1 (NF1) is a multisymptomatic disorder with highly variable presentations, which include short stature, susceptibility to formation of the characteristic benign tumors known as neurofibromas, intense freckling and skin discoloration, and cognitive deficits, which characterize most children with the condition. Attention deficits [...] Read more.

Neurofibromatosis 1 (NF1) is a multisymptomatic disorder with highly variable presentations, which include short stature, susceptibility to formation of the characteristic benign tumors known as neurofibromas, intense freckling and skin discoloration, and cognitive deficits, which characterize most children with the condition. Attention deficits and Autism Spectrum manifestations augment the compromised learning presented by most patients, leading to behavioral problems and school failure, while fragmented sleep contributes to chronic fatigue and poor quality of life. Neurofibromin (Nf1) is present ubiquitously during human development and postnatally in most neuronal, oligodendrocyte, and Schwann cells. Evidence largely from animal models including Drosophila suggests that the symptomatic variability may reflect distinct cell-type-specific functions of the protein, which emerge upon its loss, or mutations affecting the different functional domains of the protein. This review summarizes the contributions of Drosophila in modeling multiple NF1 manifestations, addressing hypotheses regarding the cell-type-specific functions of the protein and exploring the molecular pathways affected upon loss of the highly conserved fly homolog dNf1. Collectively, work in this model not only has efficiently and expediently modelled multiple aspects of the condition and increased understanding of its behavioral manifestations, but also has led to pharmaceutical strategies towards their amelioration. Full article

(This article belongs to the Special Issue Drosophila Models of Development and Disease)

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Full article ">Figure 1
A schematic representation of the exons of the full-length transcripts of human and Drosophila Nf1. The alternatively spliced exons are indicated in black. Exons encoding different known domains of Nf1 are indicated in different colors (same color code as in <a href="#cells-13-00721-f002" class="html-fig">Figure 2</a>)—Gray: CSRD, cysteine/serine-rich domain; Light green: TBD, tubulin-binding domain; Yellow: GRD, GTPase-activating protein (GAP)-related domain; Light blue: Sec14, bipartite lipid-binding module with a Sec14-like domain; Olive green: PH, pleckstrin homology domain; Purple: NLS, nuclear localization signal. Full article ">Figure 2
Alignment of the human and Drosophila neurofibromin proteins. The human (bottom line, blue) and Drosophila (Nf1-PB) (top line, red) neurofibromin proteins were aligned using both FlyBase (<a href="http://flybase.org/reports/FBgn0015269" target="_blank">http://flybase.org/reports/FBgn0015269</a>) and NCBI (<a href="https://blast.ncbi.nlm.nih.gov/Blast.cgi" target="_blank">https://blast.ncbi.nlm.nih.gov/Blast.cgi</a>) protein BLAST tools. The fly protein is 54% identical and 68% similar to the human protein over its entire length. CSRD, cysteine/serine-rich domain (Dm aa 582-928); TBD, tubulin-binding domain (Dm aa 1133-1241); GRD, GTPase-activating protein (GAP)-related domain (Dm aa 1242-1574); Sec14, bipartite lipid-binding module with a Sec14-like domain (Dm aa 1602-1750); PH, pleckstrin homology domain (Dm aa 1759-1868); NLS, nuclear localization signal (Hs aa 2555-2571, absent in Dm); aa, amino acids. Full article ">Figure 2 Cont.
Alignment of the human and Drosophila neurofibromin proteins. The human (bottom line, blue) and Drosophila (Nf1-PB) (top line, red) neurofibromin proteins were aligned using both FlyBase (<a href="http://flybase.org/reports/FBgn0015269" target="_blank">http://flybase.org/reports/FBgn0015269</a>) and NCBI (<a href="https://blast.ncbi.nlm.nih.gov/Blast.cgi" target="_blank">https://blast.ncbi.nlm.nih.gov/Blast.cgi</a>) protein BLAST tools. The fly protein is 54% identical and 68% similar to the human protein over its entire length. CSRD, cysteine/serine-rich domain (Dm aa 582-928); TBD, tubulin-binding domain (Dm aa 1133-1241); GRD, GTPase-activating protein (GAP)-related domain (Dm aa 1242-1574); Sec14, bipartite lipid-binding module with a Sec14-like domain (Dm aa 1602-1750); PH, pleckstrin homology domain (Dm aa 1759-1868); NLS, nuclear localization signal (Hs aa 2555-2571, absent in Dm); aa, amino acids. Full article ">

12 pages, 3126 KiB

Open AccessArticle

Expression of PDLIM5 Spliceosomes and Regulatory Functions on Myogenesis in Pigs

by Yu Fu, Shixin Li, Jingru Nie, Dawei Yan, Bo Zhang, Xin Hao and Hao Zhang

Cells 2024, 13(8), 720; https://doi.org/10.3390/cells13080720 - 21 Apr 2024

Viewed by 1281

Abstract

Meat yield, determined by muscle growth and development, is an important economic trait for the swine industry and a focus of research in animal genetics and breeding. PDZ and LIM domain 5 (PDLIM5) are cytoskeleton-related proteins that play key roles in various tissues [...] Read more.

Meat yield, determined by muscle growth and development, is an important economic trait for the swine industry and a focus of research in animal genetics and breeding. PDZ and LIM domain 5 (PDLIM5) are cytoskeleton-related proteins that play key roles in various tissues and cells. These proteins have multiple isoforms, primarily categorized as short (PDLIM5-short) and long (PDLIM5-long) types, distinguished by the absence and presence of an LIM domain, respectively. However, the expression patterns of swine PDLIM5 isoforms and their regulation during porcine skeletal muscle development remain largely unexplored. We observed that PDLIM5-long was expressed at very low levels in pig muscles and that PDLIM5-short and total PDLIM5 were highly expressed in the muscles of slow-growing pigs, suggesting that PDLIM5-short, the dominant transcript in pigs, is associated with a slow rate of muscle growth. PDLIM5-short suppressed myoblast proliferation and myogenic differentiation in vitro. We also identified two single nucleotide polymorphisms (−258 A > T and −191 T > G) in the 5′ flanking region of PDLIM5, which influenced the activity of the promoter and were associated with muscle growth rate in pigs. In summary, we demonstrated that PDLIM5-short negatively regulates myoblast proliferation and differentiation, providing a theoretical basis for improving pig breeding programs. Full article

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Characterization of PDLIM5 expression in pigs. (A) Determination of PDLIM5 expression in different tissues of TP pigs at the embryonic stage using sqRT-PCR. Expression of total PDLIM5 (B) and PDLIM5-short (C) at the transcript level in the LD of three pig breeds. Total PDLIM5 contains all splice variants; PDLIM5-short, short isoform of PDLIM5 without the LIM domain, and PDLIM5-long, long isoform PDLIM5 with the LIM domain. LD for longissimus dorsi; BF for back fat. TP for tibetan pig (n = 6), WJ for wujin pig (n = 6), LW for large white (n = 6). Each bar represents the means ± SD. Different letters indicate significant differences between groups. Full article ">Figure 2
PDLIM5 inhibits myoblast proliferation. (A) Efficiency of the detection of PDLIM5-short overexpression plasmid. (B) CCK8 assay of proliferating myoblasts transfected with overexpression constructs. (C) Representative images of EdU staining for proliferated cells after pcDNA3.1-PDLIM5 transfection. Blue indicates nuclei stained with DAPI, red indicates EdU-positive proliferating cells, scale bar = 130 µm. (D–G) The mRNA expression levels of proliferative genes. GAPDH is used as a reference gene. The data represent the mean ± SD of three independent experiments, ** p < 0.01, *** p < 0.001, N.S., not significant. Full article ">Figure 3
PDLIM5 suppresses myogenic differentiation. (A–C) Expression of myogenic genes (MyoG, MyoD, and MyHC) at the transcript level. Porcine myoblasts were transfected with pcDNA3.1 or PDLIM5-short overexpression plasmid, and then induced to differentiate for 0, 2, and 4 d (D0, D2, and D4). (D,E) Representative images of MyHC staining for myoblasts after pcDNA3.1-PDLIM5 transfection. Transfected cells cultured with differentiation medium for 3 and 6 d. Blue indicates nuclei stained with DAPI; red indicates MyHC-positive myotubes; scale bar = 130 µm. The data represent the mean ± SD of three independent experiments. GAPDH has been used as a reference gene. * p < 0.05, ** p < 0.01. Full article ">Figure 4
SNP sites and promoter activity analysis. (A) Comparison of the activities of double luciferase vectors expressed after transfection of C2C12 cells with different fragment lengths. (B) Sequencing results of −521 bp ± 86 bp double luciferase active vectors constructed with four different haplotypes (TG, AG, TT, and AT). Arrows indicate the sites of two SNPs, −258 A > T (red) and −191 T > G (green). (C) Dual-luciferase analysis for promoter activity of four haplotype double luciferase vectors in −521 bp ± 86 bp. Each bar represents the mean ± SD of six independent experiments. Different capital letters represent significant differences, p < 0.01. Full article ">

17 pages, 655 KiB

Open AccessReview

Epigenetic Changes in Alzheimer’s Disease: DNA Methylation and Histone Modification

by Laura Maria De Plano, Alessandra Saitta, Salvatore Oddo and Antonella Caccamo

Cells 2024, 13(8), 719; https://doi.org/10.3390/cells13080719 - 21 Apr 2024

Cited by 5 | Viewed by 3519

Abstract

Alzheimer’s disease (AD) is a devastating neurodegenerative disorder characterized by progressive cognitive decline and memory loss, imposing a significant burden on affected individuals and their families. Despite the recent promising progress in therapeutic approaches, more needs to be done to understand the intricate [...] Read more.

Alzheimer’s disease (AD) is a devastating neurodegenerative disorder characterized by progressive cognitive decline and memory loss, imposing a significant burden on affected individuals and their families. Despite the recent promising progress in therapeutic approaches, more needs to be done to understand the intricate molecular mechanisms underlying the development and progression of AD. Growing evidence points to epigenetic changes as playing a pivotal role in the pathogenesis of the disease. The dynamic interplay between genetic and environmental factors influences the epigenetic landscape in AD, altering gene expression patterns associated with key pathological events associated with disease pathogenesis. To this end, epigenetic alterations not only impact the expression of genes implicated in AD pathogenesis but also contribute to the dysregulation of crucial cellular processes, including synaptic plasticity, neuroinflammation, and oxidative stress. Understanding the complex epigenetic mechanisms in AD provides new avenues for therapeutic interventions. This review comprehensively examines the role of DNA methylation and histone modifications in the context of AD. It aims to contribute to a deeper understanding of AD pathogenesis and facilitate the development of targeted therapeutic strategies. Full article

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21 pages, 4072 KiB

Open AccessArticle

AAV-Mediated Restoration of Dystrophin-Dp71 in the Brain of Dp71-Null Mice: Molecular, Cellular and Behavioral Outcomes

by Ophélie Vacca, Faouzi Zarrouki, Charlotte Izabelle, Mehdi Belmaati Cherkaoui, Alvaro Rendon, Deniz Dalkara and Cyrille Vaillend

Cells 2024, 13(8), 718; https://doi.org/10.3390/cells13080718 - 20 Apr 2024

Viewed by 2427

Abstract

A deficiency in the shortest dystrophin-gene product, Dp71, is a pivotal aggravating factor for intellectual disabilities in Duchenne muscular dystrophy (DMD). Recent advances in preclinical research have achieved some success in compensating both muscle and brain dysfunctions associated with DMD, notably using exon [...] Read more.

A deficiency in the shortest dystrophin-gene product, Dp71, is a pivotal aggravating factor for intellectual disabilities in Duchenne muscular dystrophy (DMD). Recent advances in preclinical research have achieved some success in compensating both muscle and brain dysfunctions associated with DMD, notably using exon skipping strategies. However, this has not been studied for distal mutations in the DMD gene leading to Dp71 loss. In this study, we aimed to restore brain Dp71 expression in the Dp71-null transgenic mouse using an adeno-associated virus (AAV) administrated either by intracardiac injections at P4 (ICP4) or by bilateral intracerebroventricular (ICV) injections in adults. ICP4 delivery of the AAV9-Dp71 vector enabled the expression of 2 to 14% of brain Dp71, while ICV delivery enabled the overexpression of Dp71 in the hippocampus and cortex of adult mice, with anecdotal expression in the cerebellum. The restoration of Dp71 was mostly located in the glial endfeet that surround capillaries, and it was associated with partial localization of Dp71-associated proteins, α1-syntrophin and AQP4 water channels, suggesting proper restoration of a scaffold of proteins involved in blood–brain barrier function and water homeostasis. However, this did not result in significant improvements in behavioral disturbances displayed by Dp71-null mice. The potential and limitations of this AAV-mediated strategy are discussed. This proof-of-concept study identifies key molecular markers to estimate the efficiencies of Dp71 rescue strategies and opens new avenues for enhancing gene therapy targeting cognitive disorders associated with a subgroup of severely affected DMD patients. Full article

(This article belongs to the Topic Animal Models of Human Disease 2.0)

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Figure 1
Transduction territories of the AAV9-CAG-GFP vector following intracardiac administration: (A) GFP expression (green) in whole-brain sections of wild-type (left) and Dp71-null (right) mice after intracardiac injection at postnatal day 4 (ICP4) of AAV9-GFP vector (scale bar: 500 µm); (B,C) colocalization of GFP expression (green) and the neuronal marker NeuN (red) or astrocyte marker GFAP (red) in the hippocampus (B) and cerebellum (C). The nuclear marker, DAPI, is shown in blue (scale bar: 100 µm). Note that AAV9 intracardially injected at P4 widely transduced non-neuronal, mostly glial, cells in both wild-type and Dp71-null mice. SLM: stratum lacunosum moleculare; MCL: molecular cell layer. Full article ">Figure 2
Dp71 re-expression following intracardiac injections at postnatal day 4 (ICP4). Mice were injected with the AAV9-CAG-GFP control vector (WT-C, Dp71-C) and AAV9-CBA-GFP-2A-Dp71 vector (Dp71-T). (A) Dp71 mRNA levels quantified by qPCR in the three groups of mice in the hippocampus, cortex and cerebellum, as indicated. (B) Dp71 protein levels quantified using Western blots in the three groups of mice in the hippocampus (HIP), cortex CX) and cerebellum (CBL). The image on the left shows an example of a Western blot with 4 mice from each group and the detection using the H4 antibody of dystrophins Dp427, Dp140 and Dp71 (green). Vinculin (red) was used as control protein for normalization. Importantly, note that all (n = 7) treated mice showed Dp71 protein rescue. (C) Dp71 localization by immunofluorescence staining using the pan-specific H4 antibody (red) on 12 µm cryosections. Images were taken at ×10 and ×0.5 magnifications (inserts: ×20 and ×1 magnifications) (scale bar: 100 µm). * p < 0.05, ** p< 0.01, ns for non-significant, Mann–Whitney test. Full article ">Figure 3
Expressions of AQP4 and α1-syntrophin along the walls of blood vessels after intracardiac administration (ICP4) of the AAV vectors. (A,B) For both antibodies, the immunofluorescent (IF) staining is shown in tissue sections of the hippocampus and cerebellum, as indicated, in Dp71-null mice injected with the AAV9-CBA-GFP-2A-Dp71 vector (Dp71-T) and with the control vector (Dp71-C, WT, C). (A) Immunostaining of AQP4 (red) on 12 µm cryosections. Images taken at ×10 and ×0.5 magnifications (inserts: ×20 and ×1 magnifications). The white arrows indicate labeled vessels (scale bar: 100 µm). (B) Immunostaining of α1-syntrophin (red) on 12 µm cryosections. Images were taken at ×10 and ×0.5 magnifications (inserts: ×20 and ×1 magnifications). The white arrows indicate labeled vessels (scale bar: 100 µm). Full article ">Figure 4
Dp71 re-expression following intracerebroventricular injections (ICVs). Mice were injected at 7 weeks with the AAV9-CAG-GFP control vector (WT-C, Dp71-C) and with the AAV9-CBA-GFP-2A-Dp71 vector (Dp71-T). (A) Transduction territories of the AAV9-CAG-GFP vector in the WT and Dp71-null mouse brain sections, as revealed by GFP immunofluorescent staining (green) (scale bar: 100 µm). (B) Dp71 protein levels in the hippocampus (HIP), cortex (CX) and cerebellum (CBL) quantified by Western blots. The image on the left shows the Western blot for the 6 treated mice (DP-T) and one WT control mice (WT-C). Dp71 was detected using the H4 antibody. Vinculin (Vinc) was used as the control protein for normalization. Importantly, note that all (n = 6) treated mice showed Dp71 protein rescue. (C) Dp71 expression revealed by immunofluorescent staining with the pan-specific H4 antibody (red) on 12 µm cryosections of hippocampus and cerebellum. Images were taken at ×10 and ×0.5 magnifications (inserts: ×20 and ×1 magnifications) (scale bars: 100 µm). SO: stratum oriens; SP: stratum pyramidale; SR: stratum radiatum; MCL: molecular cell layer. Full article ">Figure 5
Expressions of AQP4 and α1-syntrophin along the walls of blood vessels after intracerebroventricular administration (ICV) of the AAV vectors. (A,B) For both antibodies the immunofluorescent (IF) staining is shown in tissue sections of the hippocampus and cerebellum, as indicated, in the Dp71-null mice injected with the AAV9-CBA-GFP-2A-Dp71 vector (Dp71-T) and with the control vector (Dp71-C, WT, C). (A) Immunostaining of AQP4 (red) on 12 µm cryosections. The white arrows indicate labeled vessels. Images were taken at ×10 and ×0.5 magnifications (inserts: ×20 and ×1 magnifications) (scale bar: 100 µm). (B) Immunostaining of α-1-syntrophin (red) on 12 µm cryosections. The white arrows indicate labeled vessels. Images were taken at ×20 and ×1 magnifications (scale bar: 50 µm). Full article ">Figure 6
Behavioral study following ICP4 and ICV administration of the AAV vectors. (A–C) The plots show the data recorded following intracardiac injections at P4 (ICP4) in the three groups of mice (Dp71-T, n = 7; WT-C, n = 9; Dp71-C, n = 7). (A) Latency to the first entry in the lit box (s), number of entries and time spent in the lit box (s) in the light–dark choice test (LD). (B) Total number of arms visited, time spent (%) and number of entries (%) in the open arms in the elevated plus maze (EPM). (C) Distance traveled (m), average speed (m/s) and percent distance traveled in center in the 30 min open field exploration test (OF). (D–F) The plots show the data recorded following stereotaxic intracerebroventricular (ICV) injections at 6–8 weeks in the three groups of mice (Dp71-T, n = 6; WT-C, n = 6; Dp71-C, n = 6). (D) Latency to the first entry in the lit box (s), number of entries and time spent in the lit box (s) in the light–dark choice test (LD). (E) Total number of arms visited, time spent (%) and number of entries (%) in the open arms in the elevated plus maze (EPM). (F) Distance traveled (m), average speed (m/s) and percent distance traveled in center in the 30 min open field exploration test (OF). The results are the means ± SEM, * p < 0.05, ns for non-significant, Mann–Whitney test. Full article ">

35 pages, 7957 KiB

Open AccessReview

Fusobacterium nucleatum: An Overview of Evidence, Demi-Decadal Trends, and Its Role in Adverse Pregnancy Outcomes and Various Gynecological Diseases, including Cancers

by Arunita Ghosh, Ken Jaaback, Angela Boulton, Michelle Wong-Brown, Steve Raymond, Partha Dutta, Nikola A. Bowden and Arnab Ghosh

Cells 2024, 13(8), 717; https://doi.org/10.3390/cells13080717 - 20 Apr 2024

Viewed by 3710

Abstract

Gynecological and obstetric infectious diseases are crucial to women’s health. There is growing evidence that links the presence of Fusobacterium nucleatum (F. nucleatum), an anaerobic oral commensal and potential periodontal pathogen, to the development and progression of various human diseases, including [...] Read more.

Gynecological and obstetric infectious diseases are crucial to women’s health. There is growing evidence that links the presence of Fusobacterium nucleatum (F. nucleatum), an anaerobic oral commensal and potential periodontal pathogen, to the development and progression of various human diseases, including cancers. While the role of this opportunistic oral pathogen has been extensively studied in colorectal cancer in recent years, research on its epidemiological evidence and mechanistic link to gynecological diseases (GDs) is still ongoing. Thus, the present review, which is the first of its kind, aims to undertake a comprehensive and critical reappraisal of F. nucleatum, including the genetics and mechanistic role in promoting adverse pregnancy outcomes (APOs) and various GDs, including cancers. Additionally, this review discusses new conceptual advances that link the immunomodulatory role of F. nucleatum to the development and progression of breast, ovarian, endometrial, and cervical carcinomas through the activation of various direct and indirect signaling pathways. However, further studies are needed to explore and elucidate the highly dynamic process of host–F. nucleatum interactions and discover new pathways, which will pave the way for the development of better preventive and therapeutic strategies against this pathobiont. Full article

(This article belongs to the Section Cellular Pathology)

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A schematic representation depicting the role of F. nucleatum in adverse pregnancy outcomes (APOs), gynecological diseases (GDs), and gynecological cancers (GCs). Full article ">Figure 2
Role of Fusobacterium nucleatum (F. nucleatum) in adverse pregnancy outcomes (APO). (A) Interaction between Fusobacterium adhesion A (FadA), with vascular endothelial cadherin (VE-Cadherin) to internalize F. nucleatum in endothelial cells for bacterial dissemination, leading to increased inflammatory cytokines causing chorioamnionitis and preterm birth. (B) Fusobacterium apoptosis-inducing protein 2 (Fap2) binds with D-galactose-β (1–3)-N-acetyl-D-galactosamine (Gal-GalNAc) on endothelial cells to localize into placenta by suppressing TIGIT mediated activation of T cells and natural killer (NK) cells. (C) Lipopolysaccharide (LPS) interacts with TLR 4 on endothelial cells to activate the NF-κB pathway, leading to an inflammatory cytokine storm causing placental inflammation. Full article ">Figure 3
Role of Fusobacterium nucleatum (F. nucleatum) in gynecological diseases (GD). (A) F. nucleatum increases TAGLN expression in endometrial fibroblasts to convert them into endometriosis lesion-forming myofibroblast cells. (B) Schematic representation displaying the interdependent beneficial relationship between F. nucleatum and vaginal bacteria, ultimately leading to bacterial vaginosis. Full article ">Figure 4
Role of Fusobacterium nucleatum (F. nucleatum) in gynecological cancers (GC). (A) Fusobacterium apoptosis-inducing protein 2 (Fap2) binds with D-galactose-β (1–3)-N-acetyl-D-galactosamine (Gal-GalNAc) on cancer cells to induce metastasis from primary tumor sites to other organs. (B) Lipopolysaccharide (LPS) on F. nucleatum activated TLR4/MyD88 pathway to induce chemoresistance in cancer cells. (C) Interaction between Fusobacterium adhesion A (FadA), with epithelial cadherin (E Cadherin) on cancer cells to increase b-catenin expression and induce cancer cell proliferation. (D) Reactive oxygen species (ROS) and extracellular vesicles secreted from F. nucleatum induce DNA damage in cancer cells to acquire further mutation and genomic instability. Full article ">

14 pages, 2583 KiB

Open AccessArticle

The Expression and Secretion Profile of TRAP5 Isoforms in Gaucher Disease

by Margarita M. Ivanova, Julia Dao, Neala Loynab, Sohailla Noor, Neil Kasaci, Andrew Friedman and Ozlem Goker-Alpan

Cells 2024, 13(8), 716; https://doi.org/10.3390/cells13080716 - 20 Apr 2024

Cited by 1 | Viewed by 1515

Abstract

Background: Gaucher disease (GD) is caused by glucocerebrosidase (GCase) enzyme deficiency, leading to glycosylceramide (Gb-1) and glucosylsphingosine (Lyso-Gb-1) accumulation. The pathological hallmark for GD is an accumulation of large macrophages called Gaucher cells (GCs) in the liver, spleen, and bone marrow, which are [...] Read more.

Background: Gaucher disease (GD) is caused by glucocerebrosidase (GCase) enzyme deficiency, leading to glycosylceramide (Gb-1) and glucosylsphingosine (Lyso-Gb-1) accumulation. The pathological hallmark for GD is an accumulation of large macrophages called Gaucher cells (GCs) in the liver, spleen, and bone marrow, which are associated with chronic organ enlargement, bone manifestations, and inflammation. Tartrate-resistant acid phosphatase type 5 (TRAP5 protein, ACP5 gene) has long been a nonspecific biomarker of macrophage/GCs activation; however, the discovery of two isoforms of TRAP5 has expanded its significance. The discovery of TRAP5′s two isoforms revealed that it is more than just a biomarker of macrophage activity. While TRAP5a is highly expressed in macrophages, TRAP5b is secreted by osteoclasts. Recently, we have shown that the elevation of TRAP5b in plasma is associated with osteoporosis in GD. However, the role of TRAP isoforms in GD and how the accumulation of Gb-1 and Lyso-Gb-1 affects TRAP expression is unknown. Methods: 39 patients with GD were categorized into cohorts based on bone mineral density (BMD). TRAP5a and TRAP5b plasma levels were quantified by ELISA. ACP5 mRNA was estimated using RT-PCR. Results: An increase in TRAP5b was associated with reduced BMD and correlated with Lyso-Gb-1 and immune activator chemokine ligand 18 (CCL18). In contrast, the elevation of TRAP5a correlated with chitotriosidase activity in GD. Lyso-Gb-1 and plasma seemed to influence the expression of ACP5 in macrophages. Conclusions: As an early indicator of BMD alteration, measurement of circulating TRAP5b is a valuable tool for assessing osteopenia–osteoporosis in GD, while TRAP5a serves as a biomarker of macrophage activation in GD. Understanding the distinct expression pattern of TRAP5 isoforms offers valuable insight into both bone disease and the broader implications for immune system activation in GD. Full article

(This article belongs to the Topic Osteoimmunology and Bone Biology)

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Figure 1
Plasma TRAP5a and TRAP5b concentrations. (A) TRAP5a level, Control vs. GD. F-Test, two tail p < 0.0001, unpaired t-test one tail p = 0.0323, two tail p = 0.0646, Control n = 35, GD n = 39. (B) TRAP5a concentrations in control subjects and GD with no bone complication (NB), osteopenia (OSN), and osteoporosis (OSR). There is no significant difference between NB, OSN, and OSR. Control n = 35, GD-NB n = 11, GD-OSN n = 14, GD-OSR n = 14. (C) Relationship between the TRAP5a plasma level and BMD in patients with GD on different therapies: no treatments—NT, NAÏVE, enzyme replacement therapy—ERT, and substrate reduction therapy—SRT. The analysis shows that there is only a significant difference between the control group and patients with normal BMD who are on SRT therapy. The unpaired t-test one tail p < 0.001. (D) TRAP5b level, Control vs. GD. p < 0.05 t-test. Control n = 14, GD patients: n = 39. (E) TRAP5b level in control subjects and patients with GD with no bone complication (N), osteopenia (OSN), and osteoporosis (OSR). ** p < 0.05; Kruskal–Wallis’s test, one-way ANOVA. (F) Relationship between the level of TRAP5b and BMD in patients with GD who are on different therapies. The Kruskal–Wallis’s test indicates significant differences between the groups (p < 0.0001). Dunn’s multiple comparison test shows significant differences between the control group and OSN/ERT, controls and OSR/ERT, and controls and OSR/SRT cohorts. Two-group comparisons using the unpaired t-test show significant differences between Control and NB cohorts (SRT and ERT), Control and OSN (SRT and ERT), and Control and OSR (SRT and ERT). Due to the limited number of samples, the “No treatment” OSN and OSR were excluded from the analysis. (G) Scatterplot analysis of TRAP5a and TRAP5b levels in patients with GD. Pearson and Spearman correlation analysis determined the absence of correlation between TRAP5a and TRAP5b. Pearson correlation r = 0.06, p = 0.35, Spearman correlation r = 0.27, p = 0.08. The asterisk (*) p ≤ 0.05; (**) p ≤ 0.01. Full article ">Figure 2
Longitudinal dynamics of TRAP5a and TRAP5b. Visit 1 (V1) is the initial visit, and visit 5 (V5) is the follow-up visit, which is an average of 24 months later. (A–C) Plasma level of TRAP5a level within 24 months of monitoring. GD patients with normal BMD (A), osteopenia (B), and osteoporosis (C). (D–F) Plasma level of TRAP5b within 24 months of monitoring. GD patients with normal BMD (D), with osteopenia (E), and osteoporosis (F). Blue color indicates the normal range of TRAP5a or TRAP5b. Full article ">Figure 3
Correlation between TRAP5a and GD clinical biomarkers Chito, Lyso-Gb1, and CCL18. (A) Scatterplot analysis of TRAP5a and Chito. The correlation between TRAP5a and Chito was determined by Spearman correlation analysis. p < 0.05 was considered statistically significant. (B,C) Scatterplot analysis of TRAP5a, Lyso-Gb1 (B), and CCL18 (C) showed no correlation between biomarkers. (D–F) Correlation matrix and hierarchical clustering. Correlation coefficients for measurements of biomarkers and clinical parameters are visualized by tile-color intensities (blue color, strong; light red color, weak, deep red color, negative correlation). Correlation coefficient = 0.8, strong positive relationships; correlation coefficient = between 0.5 and 0.7, a moderate positive relationship; correlation coefficient between 0.3 and 0.5 indicates variables with a low correlation. Pearson’s correlation (E) and Spearman correlation (F) p-values are labeled inside the titles. The red color indicates significant differences, p < 0.05. Full article ">Figure 4
Comparison of age group, BMD score, and TRAP5 in GD cohort. (A,B) Scatterplot analysis of age and Z- or T-score. (C,D) Scatterplot analysis of age and TRAP5b (B) and TRAP5a (C) showed no correlation between age and biomarkers. (E,F) The correlation between TRAP5b and Z-score (E) and TRAP5b and T-score (F). TRAP5b and Z-score were determined by linear Pearson correlation analysis. r = −0.4, p < 0.05. was considered statistically significant, with medium correlation. (G,H) A scatterplot analysis of TRAP5a and Z-score (G) or T-score (H) showed no correlation between biomarkers. Full article ">Figure 5
Expression of ACP5, Chit1, and MCP-1 mRNA in macrophages. (A) Basal levels of ACP5, MCP1, and Chit1 in control (n = 9) vs. GD macrophages (n = 9) were measured by q-RT-PCR. Values are averages +/− SEM. t-test p < 0.005. (B) Macrophages derived from healthy control PBMCs were treated with healthy control plasma (n = 5), and plasma collected from GD patients with normal bone mineral density (NB, n = 3), osteopenia (OSN, n = 4), and osteoporosis (OSR, n = 2). ACP5 was measured by q-RT-PCR. Values are averages +/− SEM. (C) Macrophages derived from GD PBMC were treated with plasma collected from GD patients with normal bone mineral density (NB), osteopenia (OSN), and osteoporosis (OSR). ACP5 was measured by q-RT-PCR. Values are averages +/− SEM. (D,E) Macrophages derived from healthy control and GD PBMCs were treated with plasma collected from healthy controls (n = 4) and GD patients (n = 3). q-RT-PCR measured Chit1 (D) and MCP-1 (E). Values are averages +/− SEM. (F) Macrophages derived from GD PBMCs were treated with increasing concentrations of Lyso-Gb-1 for 1 and 24 h. ACP5 was measured by q-RT-PCR. Values are averages +/− SEM. (G) THP-1 cells were treated with the indicated concentrations of Lyso-Gb-1, or vehicle control, for 1, 2, 3, and 4 h, and q-RT-PCR of ACP5 was performed. * Statistically significant differences. Full article ">

15 pages, 1214 KiB

Open AccessArticle

5-Hydroxymethylcytosine in Cell-Free DNA Predicts Immunotherapy Response in Lung Cancer

by Jianming Shao, Yitian Xu, Randall J. Olsen, Saro Kasparian, Kai Sun, Sunil Mathur, Jun Zhang, Chuan He, Shu-Hsia Chen, Eric H. Bernicker and Zejuan Li

Cells 2024, 13(8), 715; https://doi.org/10.3390/cells13080715 - 19 Apr 2024

Cited by 1 | Viewed by 1983

Abstract

Immune checkpoint inhibitors (ICIs) drastically improve therapeutic outcomes for lung cancer, but accurately predicting individual patient responses to ICIs remains a challenge. We performed the genome-wide profiling of 5-hydroxymethylcytosine (5hmC) in 85 plasma cell-free DNA (cfDNA) samples from lung cancer patients and developed [...] Read more.

Immune checkpoint inhibitors (ICIs) drastically improve therapeutic outcomes for lung cancer, but accurately predicting individual patient responses to ICIs remains a challenge. We performed the genome-wide profiling of 5-hydroxymethylcytosine (5hmC) in 85 plasma cell-free DNA (cfDNA) samples from lung cancer patients and developed a 5hmC signature that was significantly associated with progression-free survival (PFS). We built a 5hmC predictive model to quantify the 5hmC level and validated the model in the validation, test, and control sets. Low weighted predictive scores (wp-scores) were significantly associated with a longer PFS compared to high wp-scores in the validation [median 7.6 versus 1.8 months; p = 0.0012; hazard ratio (HR) 0.12; 95% confidence interval (CI), 0.03–0.54] and test (median 14.9 versus 3.3 months; p = 0.00074; HR 0.10; 95% CI, 0.02–0.50) sets. Objective response rates in patients with a low or high wp-score were 75.0% (95% CI, 42.8–94.5%) versus 0.0% (95% CI, 0.0–60.2%) in the validation set (p = 0.019) and 80.0% (95% CI, 44.4–97.5%) versus 0.0% (95% CI, 0.0–36.9%) in the test set (p = 0.0011). The wp-scores were also significantly associated with PFS in patients receiving single-agent ICI treatment (p < 0.05). In addition, the 5hmC predictive signature demonstrated superior predictive capability to tumor programmed death-ligand 1 and specificity to ICI treatment response prediction. Moreover, we identified novel 5hmC-associated genes and signaling pathways integral to ICI treatment response in lung cancer. This study provides proof-of-concept evidence that the cfDNA 5hmC signature is a robust biomarker for predicting ICI treatment response in lung cancer. Full article

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Prediction of progression-free survival by a 5hmC predictive signature in lung cancer patients receiving immune checkpoint inhibitor treatment. (A–C) Kaplan–Meier analysis of progression-free survival (PFS) based on weighted predictive (wp)-scores in the training set (A), the validation set (B), and the test set (C). 6−mo: estimated PFS in 6 months. Dots on the survival curve indicate that a patient was censored. HR, hazard ratio. CI, confidence interval. Cox proportional-hazards regression model was used to calculate hazard ratio. Log-rank test was used to evaluate the survival difference between groups. Full article ">Figure 2
Weighted predictive scores in lung cancer patients receiving immune checkpoint inhibitor treatment. (A) Receiver operating characteristics (ROC) analysis of weighted predictive (wp)-scores. AUC, area under the curve. CI, confidence interval. (B) Distribution of wp-scores in patients with or without an objective response to immune checkpoint inhibitors in lung cancer patients. Wilcoxon rank sum tests were used to compare the wp-score difference between groups. Full article ">Figure 3
Prediction of survival by a 5hmC predictive signature in lung cancer patients receiving immune checkpoint inhibitor monotherapy. (A) Kaplan–Meier analysis of progression-free survival (PFS) based on weighted predictive (wp)-scores. (B) Kaplan–Meier analysis of overall survival (OS) based on weighted predictive (wp)-scores. 6−mo: estimated PFS in 6 months. 12−mo: estimated OS in 12 months. Dots on the survival curve indicate that a patient was censored. HR: hazard ratio. CI: confidence interval. Cox proportional-hazards regression model was used to calculate hazard ratio. Log-rank test was used to evaluate the survival difference between groups. Full article ">Figure 4
Genes and pathways associated with immune checkpoint inhibitor treatment response in lung cancer. (A) Canonical signaling pathways enriched with genes significantly associated with immune check-point inhibitor (ICI) treatment response. Ingenuity pathway analysis (IPA) was used to conduct pathway analysis. Ratio denotes the proportion of genes related to progression-free survival within each pathway to the total number of genes constituting that pathway. (B) Hazard ratios for progression-free survival (PFS) in genes significantly enriched in canonical pathways presented by Forest plot. Genes involved in significant canonical pathways are displayed. Univariate Cox proportional-hazards regression model was used to calculate hazard ratio, p value < 0.05 is considered as significant. Full article ">

1 pages, 146 KiB

Open AccessCorrection

Correction: Won et al. Ex Vivo Perfusion Using a Mathematical Modeled, Controlled Gas Exchange Self-Contained Bioreactor Can Maintain a Mouse Kidney for Seven Days. Cells 2022, 11, 1822

by Natalie Won, Jorge Castillo-Prado, Xinzhu Tan, John Ford, David Heath, Laura Ioana Mazilescu, Markus Selzner and Ian M. Rogers

Cells 2024, 13(8), 714; https://doi.org/10.3390/cells13080714 - 19 Apr 2024

Viewed by 821

Abstract

In the original publication [...] Full article

14 pages, 1702 KiB

Open AccessFeature PaperReview

Nuclear Phospholipids and Signaling: An Update of the Story

by Irene Casalin, Eleonora Ceneri, Stefano Ratti, Lucia Manzoli, Lucio Cocco and Matilde Y. Follo

Cells 2024, 13(8), 713; https://doi.org/10.3390/cells13080713 - 19 Apr 2024

Cited by 4 | Viewed by 1324

Abstract

In the last three decades, the presence of phospholipids in the nucleus has been shown and thoroughly investigated. A considerable amount of interest has been raised about nuclear inositol lipids, mainly because of their role in signaling acting. Here, we review the main [...] Read more.

In the last three decades, the presence of phospholipids in the nucleus has been shown and thoroughly investigated. A considerable amount of interest has been raised about nuclear inositol lipids, mainly because of their role in signaling acting. Here, we review the main issues of nuclear phospholipid localization and the role of nuclear inositol lipids and their related enzymes in cellular signaling, both in physiological and pathological conditions. Full article

(This article belongs to the Special Issue Nuclear Organization, Dynamics and Phase Separation in Health and Disease)

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Figure 1
Role of nuclear PI-PLCβ1 in Myelodysplastic Neoplasms (MDS). (A) Correlation between increased risk of AML progression in MDS patients with the mono-allelic deletion of the PI-PLCB1 gene (del20p). (B) Increased expression of nuclear PI-PLCβ1, induced by Azacytidine sensitivity due to hypermethylation of the PI-PLCB1 promoter, promotes normal myeloid differentiation in MDS cells. MDS: Myelodysplastic Neoplasms; AML: Acute Myeloid Leukemia; PI-PLCB1: phosphoinositide-specific phospholipase C β1. [Created by <a href="http://Biorender.com" target="_blank">Biorender.com</a>]. Full article ">Figure 2
Role of nuclear PI-PLCβ1 in physiological myogenic differentiation and in myotonic dystrophies (DM). In physiological myogenic differentiation, PI-PLCβ1 metabolizes PIP2 leading to IP3 formation, that once phosphorylated by IPMK activates the Wnt/β catenin pathway. β catenin activates c-jun which in turn activates the cyclin D3 promoter. Cyclin D3-Cdk4/6 regulates the phosphorylation of CUGBP1 enabling its interaction with eIF2 activating translational activity. The downregulation of PI-PLCβ1 and consequent decrease in cyclin D3 expression leads to decreased CUGBP1-eIF2 interaction culminating in dysregulated myogenic differentiation. PIP2: phosphatidylinositol 4,5-bisphosphate; PI-PLCB1: phosphoinositide-specific phospholipase C β1; DAG: diacylglycerol; IP3: inositol 1,4,5-trisphosphate; IP5: inositol pentakisphosphate; IPMK: inositol polyphosphate multikinase; CUGBP1: CUG-binding protein 1; eIF2: eukaryotic initiation factor 2. [Created by <a href="http://Biorender.com" target="_blank">Biorender.com</a>]. Full article ">Figure 3
Role of nuclear PI-PLCβ1 in Glioblastoma (GBM). The downregulation of PI-PLCβ1 dictates various significant physio-pathological alterations, culminating in enhanced cellular migratory, invasive capacities, proliferation, and survival, which lead to a more aggressive phenotype. GBM: Glioblastoma Multiforme; PI-PLCB1: phosphoinositide-specific phospholipase C β1; MMP: matrix metalloproteinase; STAT3: Signal Transducer and Activator of Transcription 3 Signal Transducer and Activator of Transcription 3; ERK: Extracellular Signal-Regulated Kinase [Created by <a href="http://Biorender.com" target="_blank">Biorender.com</a>]. Full article ">Figure 4
Schematic representation of the role of nuclear PI-PLCβ1 and PI-PLCδ in different diseases. PI-PLCβ1: phosphoinositide-specific phospholipase C β1; PI-PLCδ: phosphoinositide-specific phospholipase C δ; IP3: inositol triphosphate; DAG: diacylglycerol. [Created by <a href="http://Biorender.com" target="_blank">Biorender.com</a>]. Full article ">

22 pages, 1151 KiB

Open AccessReview

Hematopoietic Stem Cells as an Integrative Hub Linking Lifestyle to Cardiovascular Health

by Xinliang Chen, Chaonan Liu, Junping Wang and Changhong Du

Cells 2024, 13(8), 712; https://doi.org/10.3390/cells13080712 - 19 Apr 2024

Viewed by 2575

Abstract

Despite breakthroughs in modern medical care, the incidence of cardiovascular disease (CVD) is even more prevalent globally. Increasing epidemiologic evidence indicates that emerging cardiovascular risk factors arising from the modern lifestyle, including psychosocial stress, sleep problems, unhealthy diet patterns, physical inactivity/sedentary behavior, alcohol [...] Read more.

Despite breakthroughs in modern medical care, the incidence of cardiovascular disease (CVD) is even more prevalent globally. Increasing epidemiologic evidence indicates that emerging cardiovascular risk factors arising from the modern lifestyle, including psychosocial stress, sleep problems, unhealthy diet patterns, physical inactivity/sedentary behavior, alcohol consumption, and tobacco smoking, contribute significantly to this worldwide epidemic, while its underpinning mechanisms are enigmatic. Hematological and immune systems were recently demonstrated to play integrative roles in linking lifestyle to cardiovascular health. In particular, alterations in hematopoietic stem cell (HSC) homeostasis, which is usually characterized by proliferation, expansion, mobilization, megakaryocyte/myeloid-biased differentiation, and/or the pro-inflammatory priming of HSCs, have been shown to be involved in the persistent overproduction of pro-inflammatory myeloid leukocytes and platelets, the cellular protagonists of cardiovascular inflammation and thrombosis, respectively. Furthermore, certain lifestyle factors, such as a healthy diet pattern and physical exercise, have been documented to exert cardiovascular protective effects through promoting quiescence, bone marrow retention, balanced differentiation, and/or the anti-inflammatory priming of HSCs. Here, we review the current understanding of and progression in research on the mechanistic interrelationships among lifestyle, HSC homeostasis, and cardiovascular health. Given that adhering to a healthy lifestyle has become a mainstream primary preventative approach to lowering the cardiovascular burden, unmasking the causal links between lifestyle and cardiovascular health from the perspective of hematopoiesis would open new opportunities to prevent and treat CVD in the present age. Full article

(This article belongs to the Special Issue Stem Cell, Differentiation, Regeneration and Diseases)

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17 pages, 14628 KiB

Open AccessArticle

Involvement of Mast Cells in the Pathology of COVID-19: Clinical and Laboratory Parallels

by Andrey V. Budnevsky, Sergey N. Avdeev, Djuro Kosanovic, Evgeniy S. Ovsyannikov, Inessa A. Savushkina, Nadezhda G. Alekseeva, Sofia N. Feigelman, Viktoria V. Shishkina, Andrey A. Filin, Dmitry I. Esaulenko and Inna M. Perveeva

Cells 2024, 13(8), 711; https://doi.org/10.3390/cells13080711 - 19 Apr 2024

Cited by 1 | Viewed by 1502

Abstract

Recent studies suggested the potential role of mast cells (MCs) in the pathology of coronavirus disease 2019 (COVID-19). However, the precise description of the MCs’ activation and the engagement of their proteases is still missing. The objective of this study was to further [...] Read more.

Recent studies suggested the potential role of mast cells (MCs) in the pathology of coronavirus disease 2019 (COVID-19). However, the precise description of the MCs’ activation and the engagement of their proteases is still missing. The objective of this study was to further reveal the importance of MCs and their proteases (chymase, tryptase, and carboxypeptidase A3 (CPA3)) in the development of lung damage in patients with COVID-19. This study included 55 patients who died from COVID-19 and 30 controls who died from external causes. A histological analysis of the lung parenchyma was carried out to assess the protease profiles and degranulation activity of MCs. In addition, we have analyzed the general blood test, coagulogram, and C-reactive protein. The content of tryptase-positive MCs (Try-MCs) in the lungs of patients with COVID-19 was higher than in controls, but their degranulation activity was lower. The indicators of chymase-positive MCs (Chy-MCs) were significantly lower than in the controls, while the content of CPA3-positive MCs (CPA3-MCs) and their degranulation activity were higher in patients with COVID-19. In addition, we have demonstrated the existence of correlations (positive/negative) between the content of Try-MCs, Chy-MCs, and CPA3-MCs at different states of their degranulation and presence (co-adjacent/single) and the levels of various immune cells (neutrophils, eosinophils, basophils, and monocytes) and other important markers (blood hemoglobin, activated partial thromboplastin time (aPTT), international normalized ratio (INR), and fibrinogen). Thus, the identified patterns suggest the numerous and diverse mechanisms of the participation of MCs and their proteases in the pathogenesis of COVID-19, and their impact on the inflammatory process and coagulation status. At the same time, the issue requires further study in larger cohorts of patients, which will open up the possibility of using drugs acting on this link of pathogenesis to treat lung damage in patients with COVID-19. Full article

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25 pages, 3128 KiB

Open AccessArticle

Genomic Engineering of Oral Keratinocytes to Establish In Vitro Oral Potentially Malignant Disease Models as a Platform for Treatment Investigation

by Leon J. Wils, Marijke Buijze, Marijke Stigter-van Walsum, Arjen Brink, Britt E. van Kempen, Laura Peferoen, Elisabeth R. Brouns, Jan G. A. M. de Visscher, Erik H. van der Meij, Elisabeth Bloemena, Jos B. Poell and Ruud H. Brakenhoff

Cells 2024, 13(8), 710; https://doi.org/10.3390/cells13080710 - 19 Apr 2024

Viewed by 1540

Abstract

Precancerous cells in the oral cavity may appear as oral potentially malignant disorders, but they may also present as dysplasia without visual manifestation in tumor-adjacent tissue. As it is currently not possible to prevent the malignant transformation of these oral precancers, new treatments [...] Read more.

Precancerous cells in the oral cavity may appear as oral potentially malignant disorders, but they may also present as dysplasia without visual manifestation in tumor-adjacent tissue. As it is currently not possible to prevent the malignant transformation of these oral precancers, new treatments are urgently awaited. Here, we generated precancer culture models using a previously established method for the generation of oral keratinocyte cultures and incorporated CRISPR/Cas9 editing. The generated cell lines were used to investigate the efficacy of a set of small molecule inhibitors. Tumor-adjacent mucosa and oral leukoplakia biopsies were cultured and genetically characterized. Mutations were introduced in CDKN2A and TP53 using CRISPR/Cas9 and combined with the ectopic activation of telomerase to generate cell lines with prolonged proliferation. The method was tested in normal oral keratinocytes and tumor-adjacent biopsies and subsequently applied to a large set of oral leukoplakia biopsies. Finally, a subset of the immortalized cell lines was used to assess the efficacy of a set of small molecule inhibitors. Culturing and genomic engineering was highly efficient for normal and tumor-adjacent oral keratinocytes, but success rates in oral leukoplakia were remarkably low. Knock-out of CDKN2A in combination with either the activation of telomerase or knock-out of TP53 seemed a prerequisite for immortalization. Prolonged culturing was accompanied by additional genetic aberrations in these cultures. The generated cell lines were more sensitive than normal keratinocytes to small molecule inhibitors of previously identified targets. In conclusion, while very effective for normal keratinocytes and tumor-adjacent biopsies, the success rate of oral leukoplakia cell culturing methods was very low. Genomic engineering enabled the prolonged culturing of OL-derived keratinocytes but was associated with acquired genetic changes. Further studies are required to assess to what extent the immortalized cultures faithfully represent characteristics of the cells in vivo. Full article

(This article belongs to the Special Issue Oral Diseases: Biological and Molecular Pathogenesis)

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16 pages, 6770 KiB

Open AccessArticle

The Role of β3-Adrenergic Receptors in Cold-Induced Beige Adipocyte Production in Pigs

by Shuo Yang, Hong Ma, Liang Wang, Fang Wang, Jiqiao Xia, Dongyu Liu, Linlin Mu, Xiuqin Yang and Di Liu

Cells 2024, 13(8), 709; https://doi.org/10.3390/cells13080709 - 19 Apr 2024

Cited by 1 | Viewed by 1506

Abstract

After exposure to cold stress, animals enhance the production of beige adipocytes and expedite thermogenesis, leading to improved metabolic health. Although brown adipose tissue in rodents is primarily induced by β3-adrenergic receptor (ADRB3) stimulation, the activation of major β-adrenergic [...] Read more.

After exposure to cold stress, animals enhance the production of beige adipocytes and expedite thermogenesis, leading to improved metabolic health. Although brown adipose tissue in rodents is primarily induced by β3-adrenergic receptor (ADRB3) stimulation, the activation of major β-adrenergic receptors (ADRBs) in pigs has been a topic of debate. To address this, we developed overexpression vectors for ADRB1, ADRB2, and ADRB3 and silenced the expression of these receptors to observe their effects on the adipogenic differentiation stages of porcine preadipocytes. Our investigation revealed that cold stress triggers the transformation of subcutaneous white adipose tissue to beige adipose tissue in pigs by modulating adrenergic receptor levels. Meanwhile, we found that ADRB3 promotes the transformation of white adipocytes into beige adipocytes. Notably, ADRB3 enhances the expression of beige adipose tissue marker genes, consequently influencing cellular respiration and metabolism by regulating lipolysis and mitochondrial expression. Therefore, ADRB3 may serve as a pivotal gene in animal husbandry and contribute to the improvement of cold intolerance in piglets. Full article

(This article belongs to the Special Issue Cellular Biology Research in Adipose Progenitor Cells, Adipocytes and Adipose Tissue)

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21 pages, 7404 KiB

Open AccessArticle

GW501516-Mediated Targeting of Tetraspanin 15 Regulates ADAM10-Dependent N-Cadherin Cleavage in Invasive Bladder Cancer Cells

by Alexandre Barbaud, Isabelle Lascombe, Adeline Péchery, Sergen Arslan, François Kleinclauss and Sylvie Fauconnet

Cells 2024, 13(8), 708; https://doi.org/10.3390/cells13080708 - 19 Apr 2024

Viewed by 1564

Abstract

Bladder cancer aggressiveness is correlated with abnormal N-cadherin transmembrane glycoprotein expression. This protein is cleaved by the metalloprotease ADAM10 and the γ-secretase complex releasing a pro-angiogenic N-terminal fragment (NTF) and a proliferation-activating soluble C-terminal fragment (CTF2). Tetraspanin 15 (Tspan15) is identified as an [...] Read more.

Bladder cancer aggressiveness is correlated with abnormal N-cadherin transmembrane glycoprotein expression. This protein is cleaved by the metalloprotease ADAM10 and the γ-secretase complex releasing a pro-angiogenic N-terminal fragment (NTF) and a proliferation-activating soluble C-terminal fragment (CTF2). Tetraspanin 15 (Tspan15) is identified as an ADAM10-interacting protein to induce selective N-cadherin cleavage. We first demonstrated, in invasive T24 bladder cancer cells, that N-cadherin was cleaved by ADAM10 generating NTF in the extracellular environment and leaving a membrane-anchored CTF1 fragment and that Tspan15 is required for ADAM10 to induce the selective N-cadherin cleavage. Targeting N-cadherin function in cancer is relevant to preventing tumor progression and metastases. For antitumor molecules to inhibit N-cadherin function, they should be complete and not cleaved. We first showed that the GW501516, an agonist of the nuclear receptor PPARβ/δ, decreased Tspan15 and prevented N-cadherin cleavage thus decreasing NTF. Interestingly, the drug did not modify ADAM10 expression, which was important because it could limit side effects since ADAM10 cleaves numerous substrates. By targeting Tspan15 to block ADAM10 activity on N-cadherin, GW501516 could prevent NTF pro-tumoral effects and be a promising molecule to treat bladder cancer. More interestingly, it could optimize the effects of the N-cadherin antagonists those such as ADH-1 that target the N-cadherin ectodomain. Full article

(This article belongs to the Special Issue Cancer-Related Signaling Cascades: Current Knowledge and Potential Therapeutic Targets)

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21 pages, 1772 KiB

Open AccessReview

Lineage Reprogramming: Genetic, Chemical, and Physical Cues for Cell Fate Conversion with a Focus on Neuronal Direct Reprogramming and Pluripotency Reprogramming

by Taichi Umeyama, Taito Matsuda and Kinichi Nakashima

Cells 2024, 13(8), 707; https://doi.org/10.3390/cells13080707 - 19 Apr 2024

Cited by 1 | Viewed by 2254

Abstract

Although lineage reprogramming from one cell type to another is becoming a breakthrough technology for cell-based therapy, several limitations remain to be overcome, including the low conversion efficiency and subtype specificity. To address these, many studies have been conducted using genetics, chemistry, physics, [...] Read more.

Although lineage reprogramming from one cell type to another is becoming a breakthrough technology for cell-based therapy, several limitations remain to be overcome, including the low conversion efficiency and subtype specificity. To address these, many studies have been conducted using genetics, chemistry, physics, and cell biology to control transcriptional networks, signaling cascades, and epigenetic modifications during reprogramming. Here, we summarize recent advances in cellular reprogramming and discuss future directions. Full article

(This article belongs to the Collection Signaling Pathways in Cell Generation and Reprogramming)

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10 pages, 3996 KiB

Open AccessArticle

Flow Cytometry-Based Assay to Detect Alpha Galactosidase Enzymatic Activity at the Cellular Level

by Nóra Fekete, Luca Kamilla Li, Gergely Tibor Kozma, György Fekete, Éva Pállinger and Árpád Ferenc Kovács

Cells 2024, 13(8), 706; https://doi.org/10.3390/cells13080706 - 19 Apr 2024

Viewed by 1950

Abstract

Background: Fabry disease is a progressive, X chromosome-linked lysosomal storage disorder with multiple organ dysfunction. Due to the absence or reduced activity of alpha-galactosidase A (AGAL), glycosphingolipids, primarily globotriaosyl-ceramide (Gb3), concentrate in cells. In heterozygous women, symptomatology is heterogenous and currently routinely used [...] Read more.

Background: Fabry disease is a progressive, X chromosome-linked lysosomal storage disorder with multiple organ dysfunction. Due to the absence or reduced activity of alpha-galactosidase A (AGAL), glycosphingolipids, primarily globotriaosyl-ceramide (Gb3), concentrate in cells. In heterozygous women, symptomatology is heterogenous and currently routinely used fluorometry-based assays measuring mean activity mostly fail to uncover AGAL dysfunction. The aim was the development of a flow cytometry assay to measure AGAL activity in individual cells. Methods: Conventional and multispectral imaging flow cytometry was used to detect AGAL activity. Specificity was validated using the GLA knockout (KO) Jurkat cell line and AGAL inhibitor 1-deoxygalactonojirimycin. The GLA KO cell line was generated via CRISPR-Cas9-based transfection, validated with exome sequencing, gene expression and substrate accumulation. Results: Flow cytometric detection of specific AGAL activity is feasible with fluorescently labelled Gb3. In the case of Jurkat cells, a substrate concentration of 2.83 nmol/mL and 6 h of incubation are required. Quenching of the aspecific exofacial binding of Gb3 with 20% trypan blue solution is necessary for the specific detection of lysosomal substrate accumulation. Conclusion: A flow cytometry-based assay was developed for the quantitative detection of AGAL activity at the single-cell level, which may contribute to the diagnosis of Fabry patients. Full article

(This article belongs to the Section Cellular Metabolism)

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Graphical abstract

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Full article ">Figure 1
Detection of AGAL activity with flow cytometry. (A) Quenching of the 2.83 nmol/mL exofacial Fl-Gb3 allows the detection of intracellular Fl-Gb3 detection via flow cytometry. (B) Representative images of brightfield and masked cells (exofacial signal quenched via 0.2% trypan blue) showing the effect of quenching using imaging cytometry upon addition of 2.83 nmol/mL Fl-Gb3. (C) The validation quenching of exofacial Fl-Gb3, as the bright detail intensity decreases upon trypan blue quenching, as detected by imaging cytometry—green line unquenched cells, gray line quenched cells (D) Representative histogram of 2.83 nmol/mL exogenous Fl-Gb3 substrate accumulation—this resulted from measuring the fluorescent intensity of uptaken and hydrolysed Fl-Gb3 compared to cells treated with DMSO. (E) Concentration-dependent Fl-Gb3 metabolism change compared to baseline after 3 h of incubation with 0.56–11.32 nmol/mL Fl-Gb3, as shown. (F) Time-dependent curve showing a peak of 2.83 nmol/mL Fl-Gb3 uptake at 5 h incubation. Data are represented as mean ± SD; * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001 by one-way ANOVA followed by Tukey’s multiple comparisons test (A,F) or Dunnett’s multiple comparisons test (E). AGAL—alpha galactosidase A, FC—flow cytometry, Fl-Gb3—fluorescently labelled globotriaosyl-ceramide, DMSO—dimethyl sulphoxide. Full article ">Figure 2
Generation of alpha galactosidase deficient Jurkat cells. (A) Guide RNA (sgRNA) design targeting the 1st exon of the GLA gene. (B) GLA gene editing analyzed at the DNA level with next-generation whole exome sequencing of transfected and wild-type Jurkat cells. (C) Analysis of GLA gene expression in transfected and wild-type Jurkat cells. (D) Detection of 2.83 nmol/mL Fl-Gb3 substrate accumulation after 3 h incubation, as detected by imaging cytometry showing masked and corresponding brightfield included GLA KO and wild-type Jurkat cells. Data are represented as mean ± SD; **** p < 0.0001 by Student’s t test (C). Fl-Gb3—fluorescently labelled globotriaosyl-ceramide; KO—knockout. Full article ">Figure 3
Validation of specific AGAL activity detection. (A) Fl-Gb3 substrate accumulation can be detected upon 2.83 nmol/mL Fl-Gb3 addition to Jurkat cells (blue histogram), treatment of wild-type Jurkat cells with 2.83 nmol/mL Fl-Gb3 and DGJ (rose histogram) yields the same accumulation as GLA KO Jurkat cells treated with 2.83 nmol/mL Fl-Gb3 (purple histrogram). (B) Upon treatment with 2.83 nmol/mL Fl-Gb3 a time-dependent substrate accumulation can be detected in AGAL deficient Jurkat cells, similarly to wild-type Jurkat cells treated with AGAL inhibitor (bullets show mean of 50,000 cells/measurement). (C) Fl-Gb3 substrate accumulation is significantly higher in GLA KO Jurkat cells. (D) Radar plot showing the quantification of significantly higher Fl-Gb3 accumulation in GLA KO Jurkat cells of spot intensity count, spot count, and bright detail intensity, respectively. (E) Fl-Gb3 treated Jurkat GLA KO cells show no difference upon addition of DGJ, as shown in masked brightfield images, as well in bar plot, summarizing the bright detail intensity detected by imaging cytometry. Data are represented as mean ± SD; * p < 0.05, *** p < 0.001, **** p < 0.0001 by two-way ANOVA followed by Tukey’s multiple comparisons test (B) or Student’s t test (C). FC—flow cytometry; AGAL—alpha galactosidase A; Fl-Gb3—fluorescently labelled globotriaosyl-ceramide; DGJ—1-deoxygalactonojirimycin; KO—knockout; ns—not significant. Full article ">

19 pages, 2941 KiB

Open AccessArticle

Chemogenetic Manipulation of Amygdala Kappa Opioid Receptor Neurons Modulates Amygdala Neuronal Activity and Neuropathic Pain Behaviors

by Guangchen Ji, Peyton Presto, Takaki Kiritoshi, Yong Chen, Edita Navratilova, Frank Porreca and Volker Neugebauer

Cells 2024, 13(8), 705; https://doi.org/10.3390/cells13080705 - 19 Apr 2024

Viewed by 1981

Abstract

Neuroplasticity in the central nucleus of the amygdala (CeA) plays a key role in the modulation of pain and its aversive component. The dynorphin/kappa opioid receptor (KOR) system in the amygdala is critical for averse-affective behaviors in pain conditions, but its mechanisms are [...] Read more.

Neuroplasticity in the central nucleus of the amygdala (CeA) plays a key role in the modulation of pain and its aversive component. The dynorphin/kappa opioid receptor (KOR) system in the amygdala is critical for averse-affective behaviors in pain conditions, but its mechanisms are not well understood. Here, we used chemogenetic manipulations of amygdala KOR-expressing neurons to analyze the behavioral consequences in a chronic neuropathic pain model. For the chemogenetic inhibition or activation of KOR neurons in the CeA, a Cre-inducible viral vector encoding Gi-DREADD (hM4Di) or Gq-DREADD (hM3Dq) was injected stereotaxically into the right CeA of transgenic KOR-Cre mice. The chemogenetic inhibition of KOR neurons expressing hM4Di with a selective DREADD actuator (deschloroclozapine, DCZ) in sham control mice significantly decreased inhibitory transmission, resulting in a shift of inhibition/excitation balance to promote excitation and induced pain behaviors. The chemogenetic activation of KOR neurons expressing hM3Dq with DCZ in neuropathic mice significantly increased inhibitory transmission, decreased excitability, and decreased neuropathic pain behaviors. These data suggest that amygdala KOR neurons modulate pain behaviors by exerting an inhibitory tone on downstream CeA neurons. Therefore, activation of these interneurons or blockade of inhibitory KOR signaling in these neurons could restore control of amygdala output and mitigate pain. Full article

(This article belongs to the Special Issue Molecular and Cellular Mechanisms of Chronic Pain)

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Figure 1

Figure 1
Nocifensive, emotional, and anxiety-like pain behaviors in neuropathic (SNL) KOR-Cre mice. (A) Experimental design. (B) Mechanical withdrawal thresholds significantly decreased in SNL mice (n = 19, *** p < 0.001, unpaired t-tests) compared to sham controls (n = 10). (C) Duration of ultrasonic vocalizations significantly increased in SNL mice (n = 13, ** p < 0.01, unpaired t-tests) compared to sham controls (n = 15). In the light/dark box test, SNL mice showed decreased frequency of entries (D, n = 19, ** p < 0.01, unpaired t-tests) and decreased time (E, n = 19, *** p < 0.001, unpaired t-tests) in the light box compared to sham controls (n = 10). (F) Representative traces of the light/dark box explorations by a sham and an SNL mouse. Bar histograms show the mean ± SEM. Figure created with BioRender.com. Full article ">Figure 2
Chemogenetic inhibition of CeA-KOR neurons induces pain-like behaviors. (A) Experimental design. (B) Diagram of a coronal brain slice (2.30 mm caudal to bregma) shows stereotaxic injection of a Cre-inducible viral vector encoding Gi-DREADD (hM4Di) or control vector (Dio-mCherry) into the right CeA of KOR-Cre mice. (C) Confocal image (20× objective, scale bar 200 µm) of KOR neurons expressing hM4Di (mCherry fluorescence) in the CeA. (D–G) In sham control mice (n = 10), systemic DCZ (100 μg/kg, i.p.; see 2.3 “Chemogenetic manipulations”) significantly decreased mechanical withdrawal thresholds (D, n = 10, *** p < 0.001, paired t-test) and decreased light box entries (F, n = 10, * p < 0.05, paired t-test), but had no significant effect on vocalizations (E, n = 5) or light box duration (G, n = 10) compared to pre-drug baseline. Systemic DCZ did not have any significant effects in sham mice treated with the control vector (Dio-mCherry, D–G, n = 5). In SNL mice, systemic DCZ had no significant effects on pain behaviors (D–G, n = 9). DCZ significantly decreased mechanical thresholds and light box frequency in sham mice, suggesting that chemogenetic inhibition of CeA-KOR neurons induces pain-like behaviors. Bar histograms show the mean ± SEM. Figure created with BioRender.com. Full article ">Figure 3
Chemogenetic activation of CeA-KOR neurons reduces neuropathic pain behaviors. (A) Experimental design. (B) Diagram of a coronal brain slice (2.30 mm caudal to bregma) shows stereotaxic injection of a Cre-inducible viral vector encoding Gq-DREADD (hM3Dq) into the right CeA of SNL KOR-Cre mice. (C) Confocal image (20× objective, bar 200 µm) of KOR neurons expressing hM3Dq (mCherry fluorescence) in the CeA. (D–G). Systemic DCZ (100 μg/kg, i.p.; see 2.3 “Chemogenetic manipulations”) significantly increased mechanical withdrawal thresholds ((D), *** p < 0.001, n = 13), decreased ultrasonic vocalizations (E, n = 8, *** p < 0.001, paired t-test), and increased light box frequency (F, n = 13, ** p < 0.01, paired t-test) and light box time (G, n = 13, ** p < 0.01, paired t-test). Systemic saline had no effects on mechanical withdrawal thresholds (D), ultrasonic vocalizations (E), and light box test (F,G) compared to pre-drug baseline (n = 5). DCZ significantly increased mechanical withdrawal thresholds, decreased ultrasonic vocalizations, and increased light box frequency and time, suggesting that chemogenetic activation of CeA-KOR neurons decreased pain-like behaviors in SNL mice. Bar histograms show the mean ± SEM. Figure created with BioRender.com. Full article ">Figure 4
Validation of chemogenetic activation or inhibition of CeA-KOR neurons with electrophysiology. (A) Experimental design. (B) Whole-cell patch recording from mCherry-expressing KOR neurons following chemogenetic activation (hM3Dq, left) or inhibition (hM4Di, right) (DCZ). (C) Chemogenetic activation of KOR neurons in the CeA (CeM and CeL). (C1) Coronal brain slice shows stereotaxic injection of a Cre-inducible viral vector encoding Gq-DREADD (hM3Dq) into the right CeA of transgenic KOR-Cre mice. (C2) Patch–clamp recording of a CeA-KOR neuron expressing hM3Dq (mCherry). (C3) Representative trace of DCZ-induced membrane depolarization and action potential firing in an hM3Dq-expressing CeA-KOR neuron. (C4) Averaged number of action potentials in 5 min before, during, and after DCZ (0.5 µM, 15 min, n = 6 neurons, p > 0.05, one-way ANOVA). (C5) Averaged resting membrane potentials during ACSF pre-drug control and DCZ (0.5 µM, 15 min) (n = 6 neurons, *** p < 0.001, paired t-test). (C6) Percentage of CeA-KOR neurons expressing hM3Dq (mCherry) that responded to DCZ (n = 6 neurons, * p < 0.05, Chi-square test). (D) Chemogenetic inhibition of KOR neurons in the CeA. (D1) Coronal brain slice shows stereotaxic injection of a Cre-inducible viral vector encoding Gi-DREADD (hM4Di) into the right CeA of transgenic KOR-Cre mice. (D2) Patch–clamp recording of a CeA-KOR neuron expressing hM4Di (mCherry). (D3) Individual trace of DCZ-induced membrane hyperpolarization in an hM4Di-expressing CeA-KOR neuron. (D4) Averaged resting membrane potentials during ACSF pre-drug control and DCZ (n = 7 neurons, ** p < 0.01, paired t-test). (D5) Individual traces of the effect of DCZ on the excitability of an hM4Di-expressing CeA-KOR neuron measured with depolarizing current injections from a holding potential of −60 mV. (D6) Summary data for action potential firing (n = 7 neurons, ** p < 0.01, paired t-test). Bar histograms show the mean ± SEM. Figure created with BioRender.com. Full article ">Figure 5
Effects of chemogenetic activation of CeA-KOR neurons on non-KOR neurons in the CeL in neuropathic KOR-Cre mice. (A) Diagram of hypothesis and experimental strategy. Whole-cell patch recording from non-KOR CeL neurons with chemogenetic activation (DCZ) of hM3Dq-expressing CeA-KOR neurons. (B) Coronal brain slice (2.30 mm caudal to bregma) shows recording sites of non-KOR neurons (n = 9) in the CeL in brain slices from neuropathic KOR-Cre mice (4 weeks post SNL induction). (C) Voltage-clamp recordings of evoked excitatory postsynaptic currents (EPSCs) in non-KOR CeL neurons. DCZ (0.5 µM, 15 min) had no significant effect (left: summary data, n = 9, two-way ANOVA with Bonferroni post hoc tests; right: individual traces). (D) Voltage-clamp recordings of evoked inhibitory postsynaptic currents (IPSCs). DCZ (0.5 µM, 15 min) increased IPSCs of non-KOR CeL neurons significantly (left: summary data, n = 8, * p < 0.05, *** p < 0.001, two-way ANOVA with Bonferroni post hoc tests; right: individual traces). (E) DCZ (0.5 µM, 15 min) decreased the frequency–current function of non-KOR CeL neurons significantly. Current–clamp recordings of action potentials generated by direct intracellular current injections (500 ms; 0 pA to 200 pA) from a holding potential of −60 mV before (ACSF) and during DCZ (0.5 µM, 15 min) application (left: summary data, n = 8, ** p < 0.01, two-way ANOVA with Bonferroni post hoc tests; right: individual traces). Full article ">Figure 6
Effects of chemogenetic inhibition of CeA-KOR neurons on non-KOR neurons in the CeL in sham control KOR-Cre mice. (A) Diagram of hypothesis and experimental strategy. Whole-cell patch recording from non-KOR CeL neurons with chemogenetic inhibition (DCZ) of hM4Di-expressing CeA-KOR neurons in SNL KOR-Cre mice. (B) Coronal brain slice (2.30 mm caudal to bregma) shows recording sites of non-KOR neurons (n = 8) in the CeL in brain slices from sham KOR-Cre mice (4 weeks post-surgery). (C) Voltage–clamp recordings of evoked EPSCs. DCZ (0.5 µM) had no significant effects on EPSCs of non-KOR CeL neurons (left: summary data, n = 8, two-way ANOVA with Bonferroni post hoc tests; right: individual traces). (D) Voltage–clamp recordings of evoked IPSCs. DCZ (0.5 µM) decreased IPSCs in CeL neurons significantly (left: summary data, n = 8, * p < 0.05, ** p < 0.01, *** p < 0.001, two-way ANOVA with Bonferroni post hoc tests; right: individual traces). (E) DCZ (0.5 µM) had no significant effects on the frequency–current function of non-KOR CeL neurons. Current–clamp recordings of action potentials generated by direct intracellular current injections (500 ms; 0 pA to 200 pA) from a holding potential of −60 mV before (ACSF) and during DCZ (0.5 µM) application (left: summary data, n = 7, two-way ANOVA with Bonferroni post hoc tests; right: individual traces). Full article ">

19 pages, 2125 KiB

Open AccessReview

From Hematopoietic Stem Cells to Platelets: Unifying Differentiation Pathways Identified by Lineage Tracing Mouse Models

by Bryce A. Manso, Alessandra Rodriguez y Baena and E. Camilla Forsberg

Cells 2024, 13(8), 704; https://doi.org/10.3390/cells13080704 - 19 Apr 2024

Cited by 1 | Viewed by 2770

Abstract

Platelets are the terminal progeny of megakaryocytes, primarily produced in the bone marrow, and play critical roles in blood homeostasis, clotting, and wound healing. Traditionally, megakaryocytes and platelets are thought to arise from multipotent hematopoietic stem cells (HSCs) via multiple discrete progenitor populations [...] Read more.

Platelets are the terminal progeny of megakaryocytes, primarily produced in the bone marrow, and play critical roles in blood homeostasis, clotting, and wound healing. Traditionally, megakaryocytes and platelets are thought to arise from multipotent hematopoietic stem cells (HSCs) via multiple discrete progenitor populations with successive, lineage-restricting differentiation steps. However, this view has recently been challenged by studies suggesting that (1) some HSC clones are biased and/or restricted to the platelet lineage, (2) not all platelet generation follows the “canonical” megakaryocytic differentiation path of hematopoiesis, and (3) platelet output is the default program of steady-state hematopoiesis. Here, we specifically investigate the evidence that in vivo lineage tracing studies provide for the route(s) of platelet generation and investigate the involvement of various intermediate progenitor cell populations. We further identify the challenges that need to be overcome that are required to determine the presence, role, and kinetics of these possible alternate pathways. Full article

(This article belongs to the Section Stem Cells)

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Graphical abstract

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Full article ">Figure 1
Classical hematopoietic tree. Self-renewing, multipotent HSCs reside at the apex of the hematopoietic hierarchy. The differentiation to MPPs results in the loss of self-renewal yet maintains multipotency. Successive differentiation then occurs, with downstream progenitor pools becoming progressively more lineage-restricted. Classically, platelets arise by the differentiation of MPPs into CMPs, MEPs, and MkPs, which mature into megakaryocytes that ultimately generate platelets. Full article ">Figure 2
Routes of platelet generation revealed by lineage tracing. Two major lineage tracing methods have been primarily employed to interrogate the route(s) of platelet specification. (A) Single and bulk cell transplantation and (B) in situ labeling have suggested the possibility of multiple alternative paths of megakaryopoiesis involving the differential use of progenitor cell states. Solid lines indicate “classical” paths, whereas dashed lines represent new and/or expanded differentiation steps elucidated by the studies discussed here. Other cell lineages are omitted for visual clarity. Full article ">Figure 3
Different experimental strategies require unique interpretations. The experimental approach utilized in lineage tracing studies (transplantation or in situ labeling) necessitates specific interpretation of results and understanding of potential caveats. Single HSC transplants allow an assessment of cellular output from an individual HSC clone, yet readout may be underestimated due to the potential for relatively low-donor-derived chimerism that could be below the method of detection employed. Conversely, bulk HSC transplants significantly improve the detection of donor-derived cells, yet the output of individual HSCs is not possible to assess but is rather the average response of all HSCs transplanted. In situ label induction that uniquely labels each HSC clone allows for the simultaneous assessment of each clone yet may suffer from the same limitations as single-cell HSC transplants (i.e., underestimation of individual HSC contribution due to limits of detection). Similar to bulk HSC transplants, genetic labeling strategies label only a subset of heterogenic HSCs whose measured output is the average of all labeled cells. Both transplantation and in situ labeling also have the potential to skew resulting data and interpretation due to the cell surface phenotype or type of label induction employed. For example, fluorescent genetic reporters may be detectable in platelets, but genetic barcoding approaches are undetectable due to lack of genetic material. If only some heterogeneous HSC clones are assessed, then results can only be understood based on the phenotypic or transcriptomic profile used experimentally [<a href="#B20-cells-13-00704" class="html-bibr">20</a>,<a href="#B68-cells-13-00704" class="html-bibr">68</a>,<a href="#B70-cells-13-00704" class="html-bibr">70</a>,<a href="#B80-cells-13-00704" class="html-bibr">80</a>]. Full article ">Figure 4
Proposed unification of adult steady-state platelet generation from HSCs, as determined by lineage tracing. Combining the available lineage tracing data, we propose an expanded and unified view of megakaryopoiesis. The phenotypic HSC pool comprises heterogeneous populations likely to be ordered into various sub-hierarchies and may also possess varying degrees of lineage priming, bias, and/or restriction. HSCs then transition to MPPs, including MPP2, which may be a primary subset involved in platelet formation. Importantly, the transition out of the LT-HSC cell state must be accompanied by gene expression of Flk2, which is incompatible with a direct HSC-to-platelet path. The “classical” CMP > MEP > MkP differentiation progression may then occur, or specific myeloid progenitor cell states may be bypassed. All possible pathways converge upon the obligate MkP cell state, the maturation of which into megakaryocytes results in eventual platelet production. Full article ">Figure 5
The biological significance of seemingly redundant platelet specification pathways. The collective findings of the studies reviewed herein reveal continual and consistent megakaryocyte lineage generation and platelet production by the hematopoietic system (see also <a href="#cells-13-00704-f004" class="html-fig">Figure 4</a>). We posit that platelet and erythrocyte production are the default fates of hematopoiesis, with the many shared intermediate progenitor cell states acquiring and/or shifting their differentiation potential to other specific lineages as physiological demand requires. The biological significance of such parallel and redundant paths is to ensure hemostasis and temper the effects of perturbation with respect to platelet output. Full article ">

15 pages, 73643 KiB

Open AccessArticle

Establishment and Characterization of SV40 T-Antigen Immortalized Porcine Muscle Satellite Cell

by Mengru Ni, Jingqing He, Tao Li, Gan Zhao, Zhengyu Ji, Fada Ren, Jianxin Leng, Mengyan Wu, Ruihua Huang, Pinghua Li and Liming Hou

Cells 2024, 13(8), 703; https://doi.org/10.3390/cells13080703 - 18 Apr 2024

Viewed by 1909

Abstract

Muscle satellite cells (MuSCs) are crucial for muscle development and regeneration. The primary pig MuSCs (pMuSCs) is an ideal in vitro cell model for studying the pig’s muscle development and differentiation. However, the long-term in vitro culture of pMuSCs results in the gradual [...] Read more.

Muscle satellite cells (MuSCs) are crucial for muscle development and regeneration. The primary pig MuSCs (pMuSCs) is an ideal in vitro cell model for studying the pig’s muscle development and differentiation. However, the long-term in vitro culture of pMuSCs results in the gradual loss of their stemness, thereby limiting their application. To address this conundrum and maintain the normal function of pMuSCs during in vitro passaging, we generated an immortalized pMuSCs (SV40 T-pMuSCs) by stably expressing SV40 T-antigen (SV40 T) using a lentiviral-based vector system. The SV40 T-pMuSCs can be stably sub-cultured for over 40 generations in vitro. An evaluation of SV40 T-pMuSCs was conducted through immunofluorescence staining, quantitative real-time PCR, EdU assay, and SA-β-gal activity. Their proliferation capacity was similar to that of primary pMuSCs at passage 1, and while their differentiation potential was slightly decreased. SiRNA-mediated interference of SV40 T-antigen expression restored the differentiation capability of SV40 T-pMuSCs. Taken together, our results provide a valuable tool for studying pig skeletal muscle development and differentiation. Full article

(This article belongs to the Special Issue Stem Cell, Differentiation, Regeneration and Diseases)

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22 pages, 6410 KiB

Open AccessArticle

Lipidomic Analysis of Plasma Extracellular Vesicles Derived from Alzheimer’s Disease Patients

by Marios G. Krokidis, Krishna A. Pucha, Maja Mustapic, Themis P. Exarchos, Panagiotis Vlamos and Dimitrios Kapogiannis

Cells 2024, 13(8), 702; https://doi.org/10.3390/cells13080702 - 18 Apr 2024

Cited by 1 | Viewed by 2214

Abstract

Analysis of blood-based indicators of brain health could provide an understanding of early disease mechanisms and pinpoint possible intervention strategies. By examining lipid profiles in extracellular vesicles (EVs), secreted particles from all cells, including astrocytes and neurons, and circulating in clinical samples, important [...] Read more.

Analysis of blood-based indicators of brain health could provide an understanding of early disease mechanisms and pinpoint possible intervention strategies. By examining lipid profiles in extracellular vesicles (EVs), secreted particles from all cells, including astrocytes and neurons, and circulating in clinical samples, important insights regarding the brain’s composition can be gained. Herein, a targeted lipidomic analysis was carried out in EVs derived from plasma samples after removal of lipoproteins from individuals with Alzheimer’s disease (AD) and healthy controls. Differences were observed for selected lipid species of glycerolipids (GLs), glycerophospholipids (GPLs), lysophospholipids (LPLs) and sphingolipids (SLs) across three distinct EV subpopulations (all-cell origin, derived by immunocapture of CD9, CD81 and CD63; neuronal origin, derived by immunocapture of L1CAM; and astrocytic origin, derived by immunocapture of GLAST). The findings provide new insights into the lipid composition of EVs isolated from plasma samples regarding specific lipid families (MG, DG, Cer, PA, PC, PE, PI, LPI, LPE, LPC), as well as differences between AD and control individuals. This study emphasizes the crucial role of plasma EV lipidomics analysis as a comprehensive approach for identifying biomarkers and biological targets in AD and related disorders, facilitating early diagnosis and potentially informing novel interventions. Full article

(This article belongs to the Section Cells of the Nervous System)

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19 pages, 2653 KiB

Open AccessReview

miRNA-Mediated Fine Regulation of TLR-Induced M1 Polarization

by Noah Rumpel, Georg Riechert and Julia Schumann

Cells 2024, 13(8), 701; https://doi.org/10.3390/cells13080701 - 18 Apr 2024

Cited by 3 | Viewed by 1577

Abstract

Macrophage polarization to the M1 spectrum is induced by bacterial cell wall components through stimulation of Toll-like family (TLR) receptors. By orchestrating the expression of relevant mediators of the TLR cascade, as well as associated pathways and feedback loops, macrophage polarization is coordinated [...] Read more.

Macrophage polarization to the M1 spectrum is induced by bacterial cell wall components through stimulation of Toll-like family (TLR) receptors. By orchestrating the expression of relevant mediators of the TLR cascade, as well as associated pathways and feedback loops, macrophage polarization is coordinated to ensure an appropriate immune response. This is central to the successful control of pathogens and the maintenance of health. Macrophage polarization is known to be modulated at both the transcriptional and post-transcriptional levels. In recent years, the miRNA-based post-transcriptional regulation of M1 polarization has received increasing attention from the scientific community. Comparative studies have shown that TLR stimulation alters the miRNA profile of macrophages and that macrophages from the M1 or the M2 spectrum differ in terms of miRNAs expressed. Simultaneously, miRNAs are considered critical post-transcriptional regulators of macrophage polarization. In particular, miRNAs are thought to play a regulatory role in the switch between the early proinflammatory response and the resolution phase. In this review, we will discuss the current state of knowledge on the complex interaction of transcriptional and post-transcriptional regulatory mechanisms that ultimately determine the functionality of macrophages. Full article

(This article belongs to the Special Issue Role and Regulation of Toll-Like Receptors and Signalings in Development and Disease)

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Figure 1
Signaling cascades of TLR4 and TLR2 receptors. Bacteria express molecular structures on their cell surface that are specifically recognized by receptors of the Toll-like receptor (TLR) family. Gram-negative bacteria are characterized by the expression of lipopolysaccharide (LPS), which induces the TLR4 signaling cascade. In contrast, the TLR2 signaling cascade is typically induced by Gram-positive bacteria through the recognition of cell wall components such as lipoteichoic acid (LTA). In the case of Gram-negative stimulation of TLR4, signaling occurs via the adapter proteins MyD88 (MyD88-dependent cascade) and TRIF (MyD88-independent cascade). When Gram-positive bacteria stimulate TLR2, the Rac1-PI3K-Akt signaling pathway is activated in addition to the MyD88-dependent signaling cascade. AP-1 = activating protein-1, Akt1 = AKT serine-threonine protein kinase 1/protein kinase B, ERK = extracellular signal-regulated kinases, FOS = Fos proto-oncogene, IFN-β1 = interferon beta 1, IκB = NFκB inhibitor, IKK = IκB kinase, IL = interleukin, IRAK = interleukin 1 receptor associated kinase, IRF = interferon regulatory factor, JNK = c-Jun N-terminal kinase 1, JUN = Jun proto-oncogene, LY96 = lymphocyte antigen 96, MyD88 = myeloid differentiation primary response 88, NFκB = nuclear factor of kappa light polypeptide gene enhancer in B-cells, NOD = nucleotide binding oligomerization domain, p38 = mitogen-activated protein kinase 14, p50 = NFκB p50 subunit, p65 = NFκB p65 subunit, PI3K = phosphatidylinositol-4,5-bisphosphate 3-kinases, Rac1 = Rac family small GTPase 1, RIPK2 = receptor interacting serine/threonine kinase 2, SOCS1 = suppressor of cytokine signaling 1, TAB = TGF-beta activated kinase 1 binding protein, TAK1 = TGF-beta activated kinase 1, TLR = toll-like receptor, TNF-α = tumor necrosis factor-alpha, TRAF6 = TNF receptor associated factor 6, TRAM = TIR domain containing adaptor molecule 2, and TRIF = TIR domain containing adaptor molecule 1. Full article ">Figure 2
Negative feedback loops within the TLR4 and the TLR2 signaling cascade. Activation of TLR4 by Gram-negative bacteria and of TLR2 by Gram-positive bacteria induces the upregulation of regulatory proteins such as STAT3, STAT6, IRAKM, and SOCS1, as well as transcription factors such as C/EBPbeta, KLF4, and members of the NFAT family. These mediators are known to inhibit central mediators of the TLR signaling cascade and also induce transcriptional expression of M2 spectrum markers. The net effect is an attenuation of macrophage M1 polarization. AP-1 = activating protein-1, Akt1 = AKT serine-threonine protein kinase 1/Protein Kinase B, C/EBPβ = CCAAT enhancer binding protein beta, CREB = cAMP responsive element binding protein, ERK = extracellular signal-regulated kinases, FOS = Fos proto-oncogene, IFN-β1 = interferon beta 1, IκB = NFκB inhibitor, IKK = IκB kinase, IL = interleukin, IRAK = interleukin 1 receptor associated kinase, IRF = interferon regulatory factor, JAK = Janus kinase, JNK = c-Jun N-terminal kinase 1, JUN = Jun proto-oncogene, KLF4 = KLF transcription factor 4, LY96 = lymphocyte antigen 96, MyD88 = myeloid differentiation primary response 88, NFAT = nuclear factor of activated T cells, NFκB = nuclear factor of kappa light polypeptide gene enhancer in B-cells, NOD = nucleotide binding oligomerization domain, p38 = mitogen-activated protein kinase 14, p50 = NFκB p50 subunit, p65 = NFκB p65 subunit, PI3K = phosphatidylinositol-4,5-bisphosphate 3-kinases, Rac1 = Rac family small GTPase 1, RIPK2 = receptor interacting serine/threonine kinase 2, SOCS1 = suppressor of cytokine signaling 1, STAT = signal transducer and activator of transcription, TAB = TGF-beta activated kinase 1 binding protein, TAK1 = TGF-beta activated kinase 1, TLR = toll-like receptor, TNF-α = tumor necrosis factor-alpha, TRAF6 = TNF receptor associated factor 6, TRAM = TIR domain containing adaptor molecule 2, TRIF = TIR domain containing adaptor molecule 1, and TYK2 = tyrosine kinase 2. Full article ">Figure 3
miRNA targets within the TLR4 and the TLR2 signaling cascade. Activation of TLR4 by Gram-negative bacteria and of TLR2 by Gram-positive bacteria leads to changes in the miRNA expression profile of macrophages. Various mediators of the TLR signaling cascade are target genes of differentially expressed miRNAs, forming a feedback mechanism. To what extent the stimulating agent (Gram-negative versus Gram-positive) and the activated TLR family member (TLR4 versus TLR2) influence the type and/or direction of expression of altered miRNAs is unclear from the current literature. However, it is well established that miR-155-5p plays a distinct role in the post-transcriptional fine-tuning of macrophage polarization and is upregulated after both TLR4 and TLR2 stimulation. AP-1 = activating protein-1, Akt1 = AKT serine-threonine protein kinase 1/protein kinase B, C/EBPβ = CCAAT enhancer binding protein beta, CREB = cAMP responsive element binding protein, ERK = extracellular signal-regulated kinases, FOS = Fos proto-oncogene, IFN-β1 = interferon beta 1, IκB = NFκB inhibitor, IKK = IκB kinase, IL = interleukin, IRAK = interleukin 1 receptor associated kinase, IRF = interferon regulatory factor, JAK = Janus kinase, JNK = c-Jun N-terminal kinase 1, JUN = Jun proto-oncogene, KLF4 = KLF transcription factor 4, LY96 = lymphocyte antigen 96, MyD88 = myeloid differentiation primary response 88, NFAT = nuclear factor of activated T cells, NFκB = nuclear factor of kappa light polypeptide gene enhancer in B-cells, NOD = nucleotide binding oligomerization domain, p38 = mitogen-activated protein kinase 14, p50 = NFκB p50 subunit, p65 = NFκB p65 subunit, PI3K = phosphatidylinositol-4,5-bisphosphate 3-kinases, PTEN = phosphatase and tensin homolog, Rac1 = Rac family small GTPase 1, RIPK2 = receptor interacting serine/threonine kinase 2, SOCS1 = suppressor of cytokine signaling 1, STAT = signal transducer and activator of transcription, TAB = TGF-beta activated kinase 1 binding protein, TAK1 = TGF-beta activated kinase 1, TLR = toll-like receptor, TNF-α = tumor necrosis factor-alpha, TRAF6 = TNF receptor associated factor 6, TRAM = TIR domain containing adaptor molecule 2, TRIF = TIR domain containing adaptor molecule 1, and TYK2 = tyrosine kinase 2. Full article ">

19 pages, 8656 KiB

Open AccessArticle

Probing the Effects of Retinoblastoma Binding Protein 6 (RBBP6) Knockdown on the Sensitivity of Cisplatin in Cervical Cancer Cells

by Harshini Mehta, Melvin Anyasi Ambele, Ntlotlang Mokgautsi and Pontsho Moela

Cells 2024, 13(8), 700; https://doi.org/10.3390/cells13080700 - 18 Apr 2024

Viewed by 1866

Abstract

Cervical cancer is a major cause of death in women despite the advancement of current treatment modalities. The conventional therapeutic agent, cisplatin (CCDP), is the standard treatment for CC; however, resistance often develops due to the cancer’s heterogeneity. Therefore, a detailed elucidation of [...] Read more.

Cervical cancer is a major cause of death in women despite the advancement of current treatment modalities. The conventional therapeutic agent, cisplatin (CCDP), is the standard treatment for CC; however, resistance often develops due to the cancer’s heterogeneity. Therefore, a detailed elucidation of the specific molecular mechanisms driving CC is crucial for the development of targeted therapeutic strategies. Retinoblastoma binding protein 6 (RBBP6) is a potential biomarker associated with cell proliferation and is upregulated in cervical cancer sites, exhibiting apoptosis and dysregulated p53 expression. Furthermore, RBBP6 has been demonstrated to sensitize cancer cells to radiation and certain chemotherapeutic agents by regulating the Bcl-2 gene, thus suggesting a crosstalk among RBBP6/p53/BCL-2 oncogenic signatures. The present study, therefore, investigated the relationship between cisplatin and RBBP6 expression in CC cells. Herein, we first explored bioinformatics simulations and identified that the RBBP6/p53/BCL-2 signaling pathway is overexpressed and correlated with CC. For further analysis, we explored the Genomics of Drug Sensitivity in Cancer (GDSC) and found that most of the CC cell lines are sensitive to CCDP. To validate these findings, RBBP6 was silenced in HeLa and Vero cells using RNAi technology, followed by measurement of wild-type p53 and Bcl-2 at the mRNA level using qPCR. Cells co-treated with cisplatin and siRBBP6 were subsequently analyzed for apoptosis induction and real-time growth monitoring using flow cytometry and the xCELLigence system, respectively. Cancer cells in the co-treatment group showed a reduction in apoptosis compared to the cisplatin-treated group. Moreover, the real-time growth monitoring revealed a reduced growth rate in RBBP6 knockdown cells treated with cisplatin. Although wild-type p53 remained unchanged in the co-treatment group of cancer cells, Bcl-2 was completely repressed, suggesting that RBBP6 is necessary for sensitizing cervical cancer cells to cisplatin treatment by downregulating Bcl-2. The Vero cell population, which served as a non-cancerous control cell line in this study, remained viable following treatment with both siRBBP6 and cisplatin. Findings from this study suggest that RBBP6 expression promotes cisplatin sensitivity in HeLa cells through Bcl-2 downregulation. Knockdown of RBBP6 limits apoptosis induction and delays cell growth inhibition in response to cisplatin. The knowledge obtained here has the potential to help improve cisplatin efficacy through personalized administration based on the expression profile of RBBP6 among individual patients. Full article

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Figure 1

Figure 1
mRNA expression analysis in HeLa and Vero cells after transfection with 100 pmol siRNA targeting RBBP6. Experiments were performed in duplicates. (*) p < 0.05, (**) p < 0.01, (ns) p > 0.05. (A) protein–protein interaction of RBBP6/P53/BCL-2 oncogenic signatures showing co-expression and co-occurrence within the same clustering network. (B) Affected biological process. (C) Enriched biological pathways when RBBP6/P53/BCL-2 oncogenes are dysregulated in cervical cancer. Effect of RBBP6 silencing on (D) RBBP6, (E) BCL-2, and (F) p53 gene expression in HeLa cells. Effect of RBBP6 silencing on (G) RBBP6, (H) BCL-2, and (I) p53 gene expression in Vero cells, with a p-value < 0.05 considered statistically significant. Full article ">Figure 2
(A) Drug response of RBBP6/P53/BCL-2 oncogenes to cisplatin (CDDP) in CESC cell lines. (B) The table shows the IC50 of CDDP on the treated cell lines. Full article ">Figure 3
RBBP6, Bcl-2, and p53 gene expression in response to CDDP treatment. (A) RBBP6, TP53, and BCL-2 oncogenes are expressed in different CC cell lines, including HeLa cells. (B) Cell viability analysis using an MTT assay in HeLa cells treated with CDDP at 50, 25, 12.5, 6.25, and 3.125 µg/mL. Experiments were performed in triplicates. (***) p < 0.001, (ns) p > 0.05. mRNA expression analysis in HeLa CC cells after treatment with 25 µg/mL CDDP for 24 and 48 h exposure periods. Experiments were performed in duplicates. (*) p < 0.05, (**) p < 0.01, (ns) p > 0.05. Effect of CDDP treatment on (C) RBBP6, (D) BCL-2, and (E) p53 gene expression in HeLa cells, as well as the effects of treatment in Vero kidney cells, as shown in (F) RBBP6 and (G) BCL-2 gene expression. For the Vero cell lines, the experiments were performed in duplicates. (*) p < 0.05, (**) p < 0.01. Full article ">Figure 4
RBBP6 knockdown and CDDP treatment synergistically reduced the expression of RBBP6/P53/BCL-2 signatures in the CC (A–C) dysregulation of RBBP6/P53/BCL-2 oncogenes in CC tissues compared to adjacent normal tissues acquired from the Human Protein Atlas (HPA). RBBP6/P53/BCL-2 oncogenes positively correlate with each other in CC, which was demonstrated through positive Pearson correlation coefficients and statistically significant p-values below the threshold of 0.05. (D–F) mRNA expression analysis in HeLa CC cells after transfection with 100 pmol siRNA targeting RBBP6 and co-treatment with 25 µg/mL CDDP for 24 and 48 h exposure periods. Experiments were performed in duplicates. (*) p < 0.05, (**) p < 0.01, (***) p < 0.001 (ns) p > 0.05. Effect of CDDP treatment post-transfection on (G) RBBP6, (H) BCL-2, and (I) p53 gene expression in HeLa cells. mRNA expression analysis in Vero kidney cells after transfection with 100 pmol siRNA targeting RBBP6 and co-treatment with 25 µg/mL CDDP for 24 and 48 hour exposure periods. Experiments were performed in duplicates. (J,K) The effect of CDDP treatment post-transfection on RBBP6 and BCL-2 gene expression in Vero cells. Western blot analysis showed significant synergistic effects of siRBBP6 with CDDP on RBBP6, BCL-2, and P53 expression compared to CDDP alone. GAPDH was used as an internal control (L). Full article ">Figure 5
Flow cytometry analysis of apoptosis in HeLa cervical cells using Annexin V-FITC and PI following co-treatment with siRBBP6 and cisplatin for 24 and 48 h. Viable cells (green), early and late apoptotic cells (blue), and necrotic cells (red) were detected in (A) untreated cells and cells treated with (B) siRBBP6, (C) CDDP for 24 h, (D) CDDP for 48 h, (E) siRBBP6 and CDDP for 24 h, and (F) siRBBP6 and CDDP for 48 h. <a href="#cells-13-00700-t004" class="html-table">Table 4</a> shows the flow cytometry analysis of apoptosis in HeLa cells using Annexin V-FITC. Full article ">Figure 6
Flow cytometry analysis of apoptosis in Vero kidney cells using Annexin V-FITC and PI following co-treatment with siRBBP6 and cisplatin for 24 and 48 h. Viable cells (green), early and late apoptotic cells (blue), and necrotic cells (red) were detected in (A) untreated cells and cells treated with (B) siRBBP6, (C) CDDP for 24 h, (D) CDDP for 48 h, (E) siRBBP6 and CDDP for 24 h, and (F) siRBBP6 and CDDP for 48 h. <a href="#cells-13-00700-t005" class="html-table">Table 5</a> shows the flow cytometry analysis of apoptosis in Vero cells using Annexin V-FITC. Full article ">Figure 7
Cell growth analysis of HeLa cells using the xCELLigence RTCA system following RBBP6 knockdown and co-treatment with cisplatin over a period of 72 h. The proliferation of untreated cells (red), cells treated with siRBBP6 (green), 12.5 µg/mL CDDP (turquoise blue), 25 µg/mL CDDP (blue), and cells co-treated with siRBBP6 + 12.5 µg/mL CDDP (dark green) and siRBBP6 + 25 µg/mL CDDP (pink) was monitored in real time over a period of 72 h. Experiments were performed in duplicates. Full article ">Figure 8
Cell growth analysis of Vero cells using the xCELLigence RTCA system following RBBP6 knockdown and co-treatment with cisplatin for 24 and 48 h. The proliferation of untreated cells (red), cells treated with siRBBP6 (green), 12.5 µg/mL CDDP (turquoise blue), 25 µg/mL CDDP (blue) only, and cells co-treated with siRBBP6 + 12.5 µg/mL CDDP (dark green) and siRBBP6 + 25 µg/mL CDDP (pink) was monitored in real time over a period of 72 h. Experiments were performed in duplicates. Full article ">

17 pages, 1099 KiB

Open AccessReview

Breaking Barriers: Modulation of Tumor Microenvironment to Enhance Bacillus Calmette–Guérin Immunotherapy of Bladder Cancer

by Omar M. Ibrahim and Pawel Kalinski

Cells 2024, 13(8), 699; https://doi.org/10.3390/cells13080699 - 18 Apr 2024

Cited by 3 | Viewed by 2238

Abstract

The clinical management of bladder cancer continues to present significant challenges. Bacillus Calmette–Guérin (BCG) immunotherapy remains the gold standard of treatment for non-muscle invasive bladder cancer (NMIBC), but many patients develop recurrence and progression to muscle-invasive disease (MIBC), which is resistant to BCG. [...] Read more.

The clinical management of bladder cancer continues to present significant challenges. Bacillus Calmette–Guérin (BCG) immunotherapy remains the gold standard of treatment for non-muscle invasive bladder cancer (NMIBC), but many patients develop recurrence and progression to muscle-invasive disease (MIBC), which is resistant to BCG. This review focuses on the immune mechanisms mobilized by BCG in bladder cancer tumor microenvironments (TME), mechanisms of BCG resistance, the dual role of the BCG-triggered NFkB/TNFα/PGE2 axis in the regulation of anti-tumor and tumor-promoting aspects of inflammation, and emerging strategies to modulate their balance. A better understanding of BCG resistance will help develop new treatments and predictive biomarkers, paving the way for improved clinical outcomes in bladder cancer patients. Full article

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13 pages, 2656 KiB

Open AccessArticle

Further Characterization of the Antiviral Transmembrane Protein MARCH8

by Takuya Tada, Yanzhao Zhang, Dechuan Kong, Michiko Tanaka, Weitong Yao, Masanori Kameoka, Takamasa Ueno, Hideaki Fujita and Kenzo Tokunaga

Cells 2024, 13(8), 698; https://doi.org/10.3390/cells13080698 - 17 Apr 2024

Viewed by 2622

Abstract

The cellular transmembrane protein MARCH8 impedes the incorporation of various viral envelope glycoproteins, such as the HIV-1 envelope glycoprotein (Env) and vesicular stomatitis virus G-glycoprotein (VSV-G), into virions by downregulating them from the surface of virus-producing cells. This downregulation significantly reduces the efficiency [...] Read more.

The cellular transmembrane protein MARCH8 impedes the incorporation of various viral envelope glycoproteins, such as the HIV-1 envelope glycoprotein (Env) and vesicular stomatitis virus G-glycoprotein (VSV-G), into virions by downregulating them from the surface of virus-producing cells. This downregulation significantly reduces the efficiency of virus infection. In this study, we aimed to further characterize this host protein by investigating its species specificity and the domains responsible for its antiviral activity, as well as its ability to inhibit cell-to-cell HIV-1 infection. We found that the antiviral function of MARCH8 is well conserved in the rhesus macaque, mouse, and bovine versions. The RING-CH domains of these versions are functionally important for inhibiting HIV-1 Env and VSV-G-pseudovirus infection, whereas tyrosine motifs are crucial for the former only, consistent with findings in human MARCH8. Through analysis of chimeric proteins between MARCH8 and non-antiviral MARCH3, we determined that both the N-terminal and C-terminal cytoplasmic tails, as well as presumably the N-terminal transmembrane domain, of MARCH8 are critical for its antiviral activity. Notably, we found that MARCH8 is unable to block cell-to-cell HIV-1 infection, likely due to its insufficient downregulation of Env. These findings offer further insights into understanding the biology of this antiviral transmembrane protein. Full article

(This article belongs to the Special Issue Untangling the Cross-Talk between Immune Responses and Infection)

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Graphical abstract

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Full article ">Figure 1
MARCH8′s antiviral function is conserved among mammals. (A) An unrooted phylogenetic tree based on MARCH family protein sequences, including mammalian MARCH8 proteins, was generated by the neighbor-joining method. Percent bootstrap values in 1000 replicates are shown on the branches. (B) Western blot analysis was performed using lysates from 293T cells transfected with human, rhesus, mouse, or bovine versions of HA-tagged MARCH8 plasmids (wild type (WT), RING-CH domain mutant (W114A, W110A, W112A), or tyrosine motif mutant (AxxL)). Antibodies specific for HA were used to detect MARCH proteins, and β-actin served as an internal control. (C,D) Viruses were prepared from 293T cells cotransfected with Env-defective HIV-1 luciferase (luc) reporter proviral DNA, either a control or increasing amounts (0, 60, or 120 ng; light grey, dark grey, or black bars, respectively) of human, rhesus, mouse, or bovine MARCH8 plasmids (WT and two mutants), together with VSV-G or HIV-1 Env expression plasmids. Infectivity was determined by infecting MAGIC5 cells with VSV-G-pseudotyped (C) or HIV-1 Env-pseudotyped (D) luc-reporter viruses and performing luciferase assays. Representative data from three independent experiments are shown as a percentage of the infectivity of control viruses (mean ± S.D., n = 3 technical replicates). Full article ">Figure 2
Mapping the domains of the human MARCH8 protein responsible for its antiviral activity. (A) The domains of MARCH8 (red) were replaced with those of MARCH3 (blue) as follows: M8/3-nCT: MARCH8 with the N-terminal CT (nCT) of MARCH3. M8/3-nTM: MARCH8 with the N-terminal TM (nTM) of MARCH3. M8/3-EC: MARCH8 with the EC of MARCH3. M8/3-cTM: MARCH8 with the C-terminal TM (cTM) of MARCH3. M8/3-cCT: MARCH8 with the C-terminal CT (cCT) of MARCH3. (B) Western blot analysis was performed using lysates from 293T cells transfected with the aforementioned HA-tagged MARCH8/MARCH3 chimera expression plasmids. Antibodies specific for HA were used to detect MARCH proteins, and β-actin was used as an internal control. (C) Immunofluorescence microscopy was conducted to analyze the subcellular localization of MARCH8, MARCH3, and their chimeric proteins, using HeLa cells transfected with HA-tagged WT or chimera MARCH expression plasmids. The subcellular localization of chimera MARCH proteins was detected by immunofluorescence microscopy. An anti-HA monoclonal antibody and Alexa 488-conjugated anti-mouse IgG were used as the primary and secondary antibodies, respectively. Arrows indicate plasma membrane localization. Bar, 10 μm. (D,E) Infectivity assays were performed as described in <a href="#cells-13-00698-f001" class="html-fig">Figure 1</a>C,D, except that VSV-G-pseudotyped (D) or HIV-1 Env-pseudotyped (E) viruses were prepared from cells transfected with fixed amounts (100 ng) of MARCH8, MARCH3, and their chimeric plasmids. Representative data from three independent experiments are shown as a percentage of the infectivity of control viruses (mean ± S.D., n = 3 technical replicates). Dagger indicates the presumed loss of antiviral activity despite its Western-blot based lower expression level. Full article ">Figure 3
MARCH8 cannot impede cell-to-cell HIV-1 infection from MDMs to CD4-positive T cells. (A) Schematic representation of the cell-free infectivity assays. Lentiviral CRISPR-mediated knockout of MARCH8 expression was performed in monocyte-derived macrophages (MDMs) obtained from two donors. Control and MARCH8-depleted MDMs were infected with HIV-1 Env-intact firefly luciferase (fLuc)-reporter viruses, washed, and cultured in fresh media. Infection of MDMs was performed using VSV-G-pseudotyped luc-reporter viruses that carry intact CXCR4-tropic HIV-1 Env, enabling the collection of viruses produced during single-round replication from MDMs without reinfection. Progeny viruses from control and MARCH8-depleted MDMs were normalized for p24 antigen and used to infect MAGIC cells, which were subjected to luc assays. (B) Cell-free infectivity of virions produced from control (CRISPR-Ctrl) and MARCH8-depleted (CRISPR-MARCH8) MDMs obtained from two donors (Donor #1 and Donor #2). Data are shown as the fold increase in viral infectivity relative to that of viruses produced from CRISPR-Ctrl MDMs (mean ± S.D. from three independent experiments). * p < 0.005, ** p < 0.001 compared with the CRISPR-Ctrl using two-tailed unpaired t-tests. ns, not significant. (C) Schematic representation of the cell-to-cell infectivity assays. Transduction with lentiviral CRISPR and HIV-1 infection were similarly conducted as in (A). After infection, MDMs were washed, incubated, and cocultured with MT4 cells that were transduced with renilla luciferase (rLuc)-expressing lentiviruses. MT4 cells were washed, cultured in the presence of nelfinavir (NFV) to block multiple replications, and subjected to dual luc assays. (D) Cell-to-cell infectivity in MT4 cells cocultured with CRISPR-Ctrl and CRISPR-MARCH8 MDMs obtained from Donor #1 and Donor #2. Data are shown as the ratio of fLuc/rLuc activity (mean ± S.D. from three independent experiments). The p value was calculated using a two-tailed unpaired Student’s t-test. ns, not significant. Full article ">

19 pages, 4088 KiB

Open AccessArticle

Quantitative Phase Imaging as Sensitive Screening Method for Nanoparticle-Induced Cytotoxicity Assessment

by Anne Marzi, Kai Moritz Eder, Álvaro Barroso, Björn Kemper and Jürgen Schnekenburger

Cells 2024, 13(8), 697; https://doi.org/10.3390/cells13080697 - 17 Apr 2024

Viewed by 1326

Abstract

The assessment of nanoparticle cytotoxicity is challenging due to the lack of customized and standardized guidelines for nanoparticle testing. Nanoparticles, with their unique properties, can interfere with biochemical test methods, so multiple tests are required to fully assess their cellular effects. For a [...] Read more.

The assessment of nanoparticle cytotoxicity is challenging due to the lack of customized and standardized guidelines for nanoparticle testing. Nanoparticles, with their unique properties, can interfere with biochemical test methods, so multiple tests are required to fully assess their cellular effects. For a more reliable and comprehensive assessment, it is therefore imperative to include methods in nanoparticle testing routines that are not affected by particles and allow for the efficient integration of additional molecular techniques into the workflow. Digital holographic microscopy (DHM), an interferometric variant of quantitative phase imaging (QPI), has been demonstrated as a promising method for the label-free assessment of the cytotoxic potential of nanoparticles. Due to minimal interactions with the sample, DHM allows for further downstream analyses. In this study, we investigated the capabilities of DHM in a multimodal approach to assess cytotoxicity by directly comparing DHM-detected effects on the same cell population with two downstream biochemical assays. Therefore, the dry mass increase in RAW 264.7 macrophages and NIH-3T3 fibroblast populations measured by quantitative DHM phase contrast after incubation with poly(alkyl cyanoacrylate) nanoparticles for 24 h was compared to the cytotoxic control digitonin, and cell culture medium control. Viability was then determined using a metabolic activity assay (WST-8). Moreover, to determine cell death, supernatants were analyzed for the release of the enzyme lactate dehydrogenase (LDH assay). In a comparative analysis, in which the average half-maximal effective concentration (EC₅₀) of the nanocarriers on the cells was determined, DHM was more sensitive to the effect of the nanoparticles on the used cell lines compared to the biochemical assays. Full article

(This article belongs to the Special Issue Research Advances in Cell Methods)

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Graphical abstract

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Full article ">Figure 1
Experimental design and workflow for comparison of PACA nanoparticle in vitro cytotoxicity assessment by DHM with downstream WST-8 and LDH assays. (A) Seeding of NIH-3T3 and RAW 264.7 cells into 96-well plates. (B) Incubation of cells with PACA, cbz-loaded PACA nanoparticles and controls. (C) Label-free DHM QPI proliferation assay. (D) WST-8 cell viability assay. (E) LDH cell death assay. (F) Determination of EC50 values. Full article ">Figure 2
DHM QPI images of RAW 264.7 macrophages and NIH-3T3 fibroblasts incubated with unloaded PACA nanoparticles in five representatively selected concentrations (0.2, 2, 8, 32 and 256 µg/mL) vs. cell culture medium controls (0 µg/mL) at time points t = 0 and t = 24 h. For both cell lines, viable proliferated cells were observed after incubation with cell culture medium control and 0.2 and 2 µg/mL of unloaded PACA nanoparticles. RAW 264.7 cells with 8 µg/mL showed cell debris at t = 0, and after 24 h; NIH-3T3 cells showed cell detachment at t = 0 and proliferated cells after 24 h. For 32 and 256 µg/mL of unloaded PACA nanoparticles, cell debris was observed for RAW 264.7 macrophages after 24 h, and proliferated cells, detached cells and cell debris were observed for NIH-3T3 with 32 µg/mL. Corresponding bright-field images (<a href="#app1-cells-13-00697" class="html-app">Figure S1</a>) and enlarged areas of DHM QPI and bright-field images (<a href="#app1-cells-13-00697" class="html-app">Figure S2</a>), which allow for a more detailed investigation of the cellular morphology alterations, are provided in the <a href="#app1-cells-13-00697" class="html-app">Supplementary Materials</a>. Full article ">Figure 3
DHM QPI images of RAW 264.7 macrophages and NIH-3T3 fibroblasts after incubation with cbz-loaded PACA nanoparticles in five representatively selected concentrations (0.002, 0.2, 8, 32 and 256 µg/mL) vs. cell culture medium controls (0 µg/mL) at time points t = 0 and t = 24 h. For both cell lines, after incubation with cell culture medium control and 0.002 µg/mL of cbz-loaded PACA nanoparticles, viable cells were detected after 24 h. For 0.2 µg/mL, cell debris could be observed for RAW 264.7, and detached and swollen cells could be observed for NIH-3T3. Macrophages incubated with 8 µg/mL of cbz-loaded PACA showed a swollen but viable cell morphology after 24 h, and for NIH-3T3, detached cells and cell debris were visible at t = 0 24 h, but after 24 h, proliferated cells were visible. Cell debris was observed in both cell lines with 32 and 256 µg/mL of cbz-loaded nanoparticles after 24 h. Corresponding bright-field images (<a href="#app1-cells-13-00697" class="html-app">Figure S3</a>) and enlarged areas of DHM QPI and bright-field images (<a href="#app1-cells-13-00697" class="html-app">Figure S4</a>), which allow for a more detailed investigation of the cellular morphology alterations, are provided in the <a href="#app1-cells-13-00697" class="html-app">Supplementary Materials</a>. Full article ">Figure 4
Dose–response relationship for unloaded PACA and cbz-loaded PACA nanoparticles on cell proliferation (DHM, green, (A) unloaded (D) cbz-loaded PACA), viability (WST-8, gray, (B) unloaded (E) cbz loaded PACA) and death (LDH, red, (C) unloaded (F) cbz loaded PACA) of RAW 264.7 macrophages and NIH-3T3 fibroblasts. Mouse RAW 264.7 macrophages and NIH-3T3 fibroblasts were seeded in 96-well plates incubated with unloaded and cbz-loaded PACA, and dry mass increments of cell populations were analyzed with DHM. Subsequently, the viability of the same cell populations was determined with a WST-8 metabolic activity assay, and the supernatants were analyzed in parallel for the release of LDH to detect cell death. The mean values ± SD from three independent experiments are shown (n = 3). Significance levels were given as p < 0.001 (***), p < 0.01 (**) and p < 0.05 (*). Full article ">

14 pages, 2664 KiB

Open AccessArticle

A Novel Interaction of Slug (SNAI2) and Nuclear Actin

by Ling Zhuo, Jan B. Stöckl, Thomas Fröhlich, Simone Moser, Angelika M. Vollmar and Stefan Zahler

Cells 2024, 13(8), 696; https://doi.org/10.3390/cells13080696 - 17 Apr 2024

Viewed by 1279

Abstract

Actin is a protein of central importance to many cellular functions. Its localization and activity are regulated by interactions with a high number of actin-binding proteins. In a yeast two-hybrid (Y2H) screening system, snail family transcriptional repressor 2 (SNAI2 or slug) was identified [...] Read more.

Actin is a protein of central importance to many cellular functions. Its localization and activity are regulated by interactions with a high number of actin-binding proteins. In a yeast two-hybrid (Y2H) screening system, snail family transcriptional repressor 2 (SNAI2 or slug) was identified as a yet unknown potential actin-binding protein. We validated this interaction using immunoprecipitation and analyzed the functional relation between slug and actin. Since both proteins have been reported to be involved in DNA double-strand break (DSB) repair, we focused on their interaction during this process after treatment with doxorubicin or UV irradiation. Confocal microscopy elicits that the overexpression of actin fused to an NLS stabilizes complexes of slug and γH2AX, an early marker of DNA damage repair. Full article

(This article belongs to the Special Issue Cytoskeletal Remodeling in Health and Disease)

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Figure 1
Co-immunoprecipitation of slug and actin in both directions in lysates of HeLa cells confirms their interaction. (a) Detection for actin, (b) detection for slug. Lane 1: IP for actin, lane 2: IP for slug, lane 3: negative control (beads), lanes 4–6: the respective flow-throughs. Full article ">Figure 2
Slug and actin mutually influence each other. (a) Upper panel: Slug is successfully silenced to 20% of the initial level 24 h after treatment with 5 µL of transfection solution. Lower-left panel: After silencing of slug, actin aggregates emerge; red: F-actin, blue: nuclei, scale bar: 25 µm. Lower-right panel: Quantitative analysis of the actin aggregates. Nt: non-targeting siRNA. The aggregation of F-actin was quantified by counting the number of particles in 40 single cells (from duplicate wells of three independent experiments); n = 3, mean ± SEM. (b) Left panel: Representative Western blot showing the slug level after the addition of the indicated concentrations of latrunculin B (Lat B) and jasplakinolide (jasp) for 24 h. The leftmost lane depicts the size marker. Right panel: Quantitative densitometric analysis of the Western blots showing a decrease in slug levels after treatment with 100 nM of the actin-polymerizing compound jasp. Protein levels were normalized to solvent control. (n = 3, mean ± SEM, half-tailed unpaired equal-variance t-test * p < 0.05). (c) Nuclear–cytoplasmic ratio of slug after the treatment panels analogous to (b). The nuclear fluorescence intensity of slug as determined using confocal microscopy was reduced after 24 h treatment. The N/C ratios were estimated using Fiji software 2.9.0 and normalized to DMSO control. (n = 3, mean ± SEM, half-tailed unpaired equal-variance t-test * p < 0.05, ns: not significant). Full article ">Figure 3
Actin-manipulating compounds and DNA-damaging interventions have a synergistic effect on apoptosis induction in HeLa cells. (a) Left panel: Effect of the co-treatment of cells with increasing concentrations of Lat B and doxorubicin; right panel: the calculated Bliss values show actin-binding compounds and doxo dose-dependently increased apoptosis in HeLa. (b) Co-treatment of the cells with jasp, panels analogous to (a). (c) Treatment of the cells with UVA irradiation, panels analogous to (a). n = 3, mean ± SEM. The Bliss independence value is often used to analyze synergistic effects of drug combinations. Values between 0 and 1 represent antagonism; values higher than 1 represent synergism. Full article ">Figure 4
Slug and actin fused with NLS colocalize during the DNA damage repair process. (a) The cells were overexpressed with actin fused with mCherry and NLS. Slug was stained using indirect immunofluorescence (r = 0.35 ± 0.03). (b) The cells were overexpressed with nuclear Actin-Chromobody (TagGFP2) (r = 0.30 ± 0.02). n = 3, mean ± SEM, scale bar: 10 μm, single cell number for each group: 20, number of square regions of each nucleus for evaluation: 3. (c) Both methods for increasing nuclear actin elicited actin fibers in the nucleus, scale bar: 10 μm. Full article ">Figure 5
The colocalization between slug and γH2AX, as well as between slug and RPA2, is stabilized by nuclear actin. (a) Colocalization between slug and γH2AX during DNA repair with (red symbols) and without (blue symbols) expression of nuclear actin; (b) colocalization between slug and RPA2 during DNA repair with (red symbols) and without (blue symbols) expression of nuclear actin. n = 3, mean ± SEM, single cell number for each group: 20, number of square regions of each nucleus for evaluation: 3. * p < 0.05, ** p < 0.01, **** p < 0.0001, ns: not significant. Full article ">Figure 6
(a) The spatial correlation between slug and γH2AX increases after induction of DNA damage with UV irradiation. Latrunculin B does not influence this effect. (b) The spatial correlation between slug, RPA2, and γH2AX is not changed after induction of DNA damage with UV irradiation. n = 3, mean ± SEM, single cell number for each group: 20, number of square regions of each nucleus for evaluation: 3. ns: not significant, * p < 0.05, ** p < 0.01, *** p < 0.001. Full article ">

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Open AccessReview

Three-Dimensional Cultivation a Valuable Tool for Modelling Canine Mammary Gland Tumour Behaviour In Vitro

by Mykhailo Huniadi, Natália Nosálová, Viera Almášiová, Ľubica Horňáková, Alexandra Valenčáková, Nikola Hudáková and Dasa Cizkova

Cells 2024, 13(8), 695; https://doi.org/10.3390/cells13080695 - 17 Apr 2024

Cited by 1 | Viewed by 1608

Abstract

Cell cultivation has been one of the most popular methods in research for decades. Currently, scientists routinely use two-dimensional (2D) and three-dimensional (3D) cell cultures of commercially available cell lines and primary cultures to study cellular behaviour, responses to stimuli, and interactions with [...] Read more.

Cell cultivation has been one of the most popular methods in research for decades. Currently, scientists routinely use two-dimensional (2D) and three-dimensional (3D) cell cultures of commercially available cell lines and primary cultures to study cellular behaviour, responses to stimuli, and interactions with their environment in a controlled laboratory setting. In recent years, 3D cultivation has gained more attention in modern biomedical research, mainly due to its numerous advantages compared to 2D cultures. One of the main goals where 3D culture models are used is the investigation of tumour diseases, in both animals and humans. The ability to simulate the tumour microenvironment and design 3D masses allows us to monitor all the processes that take place in tumour tissue created not only from cell lines but directly from the patient’s tumour cells. One of the tumour types for which 3D culture methods are often used in research is the canine mammary gland tumour (CMT). The clinically similar profile of the CMT and breast tumours in humans makes the CMT a suitable model for studying the issue not only in animals but also in women. Full article

(This article belongs to the Section Cell Methods)

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12 pages, 3261 KiB

Open AccessArticle

Unraveling the Pathogenetic Mechanisms Underlying the Association between Specific Mitochondrial DNA Haplogroups and Parkinson’s Disease

by Min-Yu Lan, Tsu-Kung Lin, Baiba Lace, Algirdas Utkus, Birute Burnyte, Kristina Grigalioniene, Yu-Han Lin, Inna Inashkina and Chia-Wei Liou

Cells 2024, 13(8), 694; https://doi.org/10.3390/cells13080694 - 17 Apr 2024

Viewed by 1434

Abstract

Variants of mitochondrial DNA (mtDNA) have been identified as risk factors for the development of Parkinson’s disease (PD). However, the underlying pathogenetic mechanisms remain unclear. Cybrid models carrying various genotypes of mtDNA variants were tested for resistance to PD-simulating MPP⁺ treatment. The [...] Read more.

Variants of mitochondrial DNA (mtDNA) have been identified as risk factors for the development of Parkinson’s disease (PD). However, the underlying pathogenetic mechanisms remain unclear. Cybrid models carrying various genotypes of mtDNA variants were tested for resistance to PD-simulating MPP⁺ treatment. The most resistant line was selected for transcriptome profiling, revealing specific genes potentially influencing the resistant characteristic. We then conducted protein validation and molecular biological studies to validate the related pathways as the influential factor. Cybrids carrying the W3 mtDNA haplogroup demonstrated the most resistance to the MPP⁺ treatment. In the transcriptome study, PPP1R15A was identified, while further study noted elevated expressions of the coding protein GADD34 across all cybrids. In the study of GADD34-related mitochondrial unfolding protein response (mtUPR), we found that canonical mtUPR, launched by the phosphate eIF2a, is involved in the resistant characteristic of specific mtDNA to MPP⁺ treatment. Our study suggests that a lower expression of GADD34 in the late phase of mtUPR may prolong the mtUPR process, thereby benefitting protein homeostasis and facilitating cellular resistance to PD development. We herein demonstrate that GADD34 plays an important role in PD development and should be further investigated as a target for the development of therapies for PD. Full article

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