Proteomic Discovery and Array-Based Validation of Biomarkers from Urinary Exosome by Supramolecular Probe

Exosomes are nanoscale, membrane-enclosed vesicles with contents similar to their parent cells, which are rich in potential biomarkers. Urine, as a noninvasive sampling body fluid, has the advantages of being simple to collect, stable in protein, diverse and not regulated by homeostatic mechanisms of the body, making it a favorable target for studying tumor biomarkers. In this report, the urinary exosomal proteome was analyzed and high-throughput downstream validation was performed using a supramolecular probe-based capture and in situ detection. The technology demonstrated the efficient enrichment of exosomes with a high concentration (5.5 × 1010 particles/mL) and a high purity (2.607 × 1010 particles/mg) of exosomes from urine samples. Proteomic analysis of urine samples from patients with hepatocellular carcinoma and healthy individuals combined with proteomic screening techniques revealed that 68 proteins were up-regulated in patients with hepatocellular carcinoma. As a proof-of-principle study, three of these differentially expressed proteins, including OLFM4, HDGF and GDF15, were validated using the supramolecular probe-based array (48 samples per batch). These findings demonstrate the great potential of this approach toward a liquid biopsy for the discovery and validation of biomarkers from urinary exosomes, and it can be extended to various biological samples with lower content of exosomes

Supramolecular Exosome Array for Efficient Capture and In Situ Detection of Protein Biomarkers

Exosomes are an emerging source for disease biomarker discovery due to the high stability of proteins protected by phospholipid bilayers. However, liquid biopsy with exosomes remains challenging due to the extreme complexity of biological samples. Herein, we introduced an amphiphile-dendrimer supramolecular probe (ADSP) for the efficient capture and high-throughput analysis of exosomes, enabling the array-based assay for marker proteins. Amphiphilic amphotericin B was functionalized onto highly branched globular dendrimers, which can then insert into the exosome membrane efficiently, forming a supramolecular complex through multivalent interactions between the probe and the bilayer of exosomes. The ADSP can be easily coated onto magnetic beads or the nitrocellulose membrane, facilitating the capture of exosomes from a minimum amount of clinical samples. The captured exosomes can be detected with target protein antibodies via Western blotting or in a high-throughput array-based dot blotting format. This new strategy exhibited excellent extraction capability from trace body fluids with superior sensitivity (less than 1 μL plasma), good quantitation ability (R2 > 0.99), and high throughput (96 samples in one batch) using clinical plasma samples. The combination of proteomics and ADSP will provide a platform for the discovery and validation of protein biomarkers for cancer diagnosis and prognosis

Proteomic Discovery and Array-Based Validation of Biomarkers from Urinary Exosome by Supramolecular Probe

Exosomes are nanoscale, membrane-enclosed vesicles with contents similar to their parent cells, which are rich in potential biomarkers. Urine, as a noninvasive sampling body fluid, has the advantages of being simple to collect, stable in protein, diverse and not regulated by homeostatic mechanisms of the body, making it a favorable target for studying tumor biomarkers. In this report, the urinary exosomal proteome was analyzed and high-throughput downstream validation was performed using a supramolecular probe-based capture and in situ detection. The technology demonstrated the efficient enrichment of exosomes with a high concentration (5.5 × 1010 particles/mL) and a high purity (2.607 × 1010 particles/mg) of exosomes from urine samples. Proteomic analysis of urine samples from patients with hepatocellular carcinoma and healthy individuals combined with proteomic screening techniques revealed that 68 proteins were up-regulated in patients with hepatocellular carcinoma. As a proof-of-principle study, three of these differentially expressed proteins, including OLFM4, HDGF and GDF15, were validated using the supramolecular probe-based array (48 samples per batch). These findings demonstrate the great potential of this approach toward a liquid biopsy for the discovery and validation of biomarkers from urinary exosomes, and it can be extended to various biological samples with lower content of exosomes

Additional file 3 of Post-translational modification of CDK1–STAT3 signaling by fisetin suppresses pancreatic cancer stem cell properties

Additional file 3: Table S2. Protein kinase like domain associated genes

Additional file 1 of Post-translational modification of CDK1–STAT3 signaling by fisetin suppresses pancreatic cancer stem cell properties

Additional file 1: Figure S1. a Representative flow cytometry plots for CD44 and CD24 expression in human pancreatic cancer HPC-Y5 cells with DMSO or fisetin treatment. Cells were treated with fisetin (100 µM) for 48 h. b Statistical plot of ratio of CD44 + /CD24 + positive and CD44-/CD24- negative cells in control or fisetin treatment HPC-Y5 cells. Data are presented as mean ± SD (n = 3); *P  1.5). d Heat map of Biological Process in GO enrichment analysis of differentially expressed proteins in each Q subset according to P value of Fisher's exact test. Figure S2. Heat map of Cellular Component in GO enrichment analysis of differentially expressed proteins in each Q subset according to P value of Fisher's exact test. Figure S3. Heat map of Molecular Function in GO enrichment analysis of differentially expressed proteins in each Q subset according to P value of Fisher's exact test. Figure S4. a Heat map of KEGG pathway enrichment analysis of differentially expressed proteins in each Q subset according to P value of Fisher's exact test. Enrichment pathways of Q1 and Q2 indicated proteins in important pathways including PI3K–Akt signaling, pathways in cancer, metabolism pathways and ECM-receptor interaction were declined in PANC-1 cells with fisetin treatment. b Heat map of protein domain enrichment analysis of differentially expressed proteins in each Q subset. Enrichment protein domain of Q1 and Q2 indicated proteins with EGF-like domain and Laminin EGF domain were reduced by fisetin treatment. c Protein domain enrichment analysis of whole differentially expressed proteins quantified by proteomics analysis. Figure S5. a Summary of acetylated sites and proteins quantified by acetyl-proteomics analysis. b Summary of differentially expressed acetylated sites and proteins quantified by acetyl-proteomics analysis. 368 sites were changed over 1.2-folds (P < 0.05) including 307 up-regulated and 61 down-regulated in 264 proteins. c Go enrichment analysis of differentially expressed acetylated proteins. d Immunoprecipitation and western blot determined that EP300 was acetyl-transferase of CDK1. Figure S6. Protein motif analysis was performed by statistical analysis of the patterns of amino acid sequences before and after all acetylated sites in samples. 19 types of conserved motifs were identified by motif analysis. Figure S7. a Western blot analysis was used to determine expression of CDK1, STAT3, CD44 and Sox2 in adherent PANC-1 cells or spheres generated from PANC-1 cells. Adhe, adherent cells. b Inhibition of CD44 and Sox2 by CDK1 silencing can be rescued by over-expressing STAT3. Expression of CD44, Sox2, CDK1, STAT3, p-CDK1 and p-STAT3 were examined by western blot analysis. c Inhibition of CDK1-STAT3 signaling by fisetin in purified pancreatic cancer stem cell spheres. Expression of CD44, Sox2, CDK1, STAT3, p-CDK1 and p-STAT3 were performed by western blot analysis. d-e Direct suppression of purified pancreatic oncospheres by fisetin. Second generation of PANC-1 and HPC-Y5 cells from oncospheres were subjected to the tumor sphere-formation assay in ultra-low cluster plates. After the cultivation process to initial point, these tumor spheres were treated with or without fisetin (100 μM) for 48 h. Scale bars, 100 μm. Data are presented as mean ± SD (n = 3),*P < 0.05; ns, no significance. Figure S8. a HDAC3 silencing reduced levels of p-CDK1, p-STAT3, CD44 and Sox2. Western blot analysis was used to determine expression of CDK1, STAT3, CD44 and Sox2 in HDAC3 silencing PANC-1 cells. b-c Lack of HDAC3 weakened tumor sphere formatting capacity in PDAC cells. Scale bars, 100 μm. Data are presented as mean ± SD (n = 4); *P < 0.05. d HDAC3 over-expression increased levels of p-CDK1, p-STAT3, CD44 and Sox2. Western blot analysis was used to determine expression of CDK1, STAT3, CD44 and Sox2 in HDAC3 over-expression PANC-1 cells. e–f Over-expressing HDAC3 enhanced the sphere formatting capacity both in PANC-1 and HPC-Y5 cells. Scale bars, 100 μm. Data are presented as mean ± SD (n = 4); *P < 0.05, **P < 0.01. g Fisetin reduced expression of HDAC3 both in PANC-1 and HPC-Y5 cells. Figure S9. a Fraction-affected (Fa) and CI are explored after 48-h incubation with fisetin and gemcitabine combination, CI < 1 represents synergy. b Representative section of magnetic resonance imaging (MRI) for spontaneous pancreatic ductal adenocarcinoma in KPC mice. Figure S10. a Western blot analysis was used to determine expression of CDK1 in stable CDK1 knockout PANC-1 cells. CDK1-KO: CDK1-knockout. b Quantification of relative phosphorylation of CDK1 was performed by analyzing western blot results with image J software. The relative phosphorylation of CDK1 was significant reduced in PANC-1 and HPC-Y5 cells with fisetin (100 μM) treatment. Fis, fisetin; *P < 0.05; ns, no significance. c qRT-PCR showed that mRNA expression of CDK1 was not influenced by fisetin treatment in pancreatic cancer cells. Data are presented as mean ± SD (n = 3). ns, no significance. d Proteasome inhibitor MG132 restore the expression of CDK1 in PDAC cells with fisetin treatment. PANC-1 and HPC-Y5 ells were cultured with or without fisetin (100 μM) treatment for 48 h. Before the collection of cells, MG132 (10 μM) were added to culture medium for 0, 6 and 12 h. h, hours. e Immunoprecipitation and western blot determined that fisetin induced prominent ubiquitination of CDK1 in pancreatic cancer cells. IP, immunoprecipitation. Ub, ubiquitin. Figure S11. a Western blot analysis was used to determine phosphorylation of CDK1 at Thr14 and Thr161 residues in pancreatic cancer PANC-1 and HPC-Y5 cells. p-CDK1(T161): phosphorylation of CDK1 at Thr161; p-CDK1(T14): phosphorylation of CDK1 at Thr14

Image_1_One-Week Effects of Antibiotic Treatment on Gut Microbiota of Late Neonates With Pneumonia or Meningitis.tif

Background: The neonatal period is a critical period for the establishment of the intestinal microbial community. Antibiotics can change the composition of gut microbiota.Methods: Fecal samples were collected from 14 patients with pneumonia and 14 patients with meningitis before and after antibiotic treatment, and fecal samples from five healthy neonates at the 14th and 21st days after birth were collected as well. DNA of fecal samples was extracted, and PCR amplification was performed targeting the V3–V4 variable region of 16S rDNA. After detection by high-throughput sequencing, OTU (operational taxonomic unit) clustering, species annotation, and α diversity analysis were calculated and analyzed statistically.Results: In the healthy control group, the abundance of Bifidobacterium increased significantly from 16.75 to 40.42%, becoming the most dominant bacteria. The results of α diversity analysis suggested that the Sobs indexes of the gut microbiota in the pneumonia and meningitis groups were significantly lower than that in the healthy control group (p 2 = 0.565), and there was no significant change in the diversity of gut microbiota before and after the use of antibiotics.Conclusions: The gut microbiota of neonates with infectious diseases were mainly related to the disease conditions. The initial state of neonatal gut microbiome determines its state after 1-week antibiotic treatment. Antibiotic application with 7 days had little effect on the community richness and some effect on the composition of gut microbiota of neonates with pneumonia or meningitis.</p

Additional file 4 of Post-translational modification of CDK1–STAT3 signaling by fisetin suppresses pancreatic cancer stem cell properties

Additional file 4: Table S3. Levels of transcriptome and protein phosphorylation of genes in HIF-1 signaling

Image_3_One-Week Effects of Antibiotic Treatment on Gut Microbiota of Late Neonates With Pneumonia or Meningitis.tif

Background: The neonatal period is a critical period for the establishment of the intestinal microbial community. Antibiotics can change the composition of gut microbiota.Methods: Fecal samples were collected from 14 patients with pneumonia and 14 patients with meningitis before and after antibiotic treatment, and fecal samples from five healthy neonates at the 14th and 21st days after birth were collected as well. DNA of fecal samples was extracted, and PCR amplification was performed targeting the V3–V4 variable region of 16S rDNA. After detection by high-throughput sequencing, OTU (operational taxonomic unit) clustering, species annotation, and α diversity analysis were calculated and analyzed statistically.Results: In the healthy control group, the abundance of Bifidobacterium increased significantly from 16.75 to 40.42%, becoming the most dominant bacteria. The results of α diversity analysis suggested that the Sobs indexes of the gut microbiota in the pneumonia and meningitis groups were significantly lower than that in the healthy control group (p 2 = 0.565), and there was no significant change in the diversity of gut microbiota before and after the use of antibiotics.Conclusions: The gut microbiota of neonates with infectious diseases were mainly related to the disease conditions. The initial state of neonatal gut microbiome determines its state after 1-week antibiotic treatment. Antibiotic application with 7 days had little effect on the community richness and some effect on the composition of gut microbiota of neonates with pneumonia or meningitis.</p

Additional file 2 of Post-translational modification of CDK1–STAT3 signaling by fisetin suppresses pancreatic cancer stem cell properties

Additional file 2: Table S1. Proteins identified by proteomic

Image_4_One-Week Effects of Antibiotic Treatment on Gut Microbiota of Late Neonates With Pneumonia or Meningitis.tif

Background: The neonatal period is a critical period for the establishment of the intestinal microbial community. Antibiotics can change the composition of gut microbiota.Methods: Fecal samples were collected from 14 patients with pneumonia and 14 patients with meningitis before and after antibiotic treatment, and fecal samples from five healthy neonates at the 14th and 21st days after birth were collected as well. DNA of fecal samples was extracted, and PCR amplification was performed targeting the V3–V4 variable region of 16S rDNA. After detection by high-throughput sequencing, OTU (operational taxonomic unit) clustering, species annotation, and α diversity analysis were calculated and analyzed statistically.Results: In the healthy control group, the abundance of Bifidobacterium increased significantly from 16.75 to 40.42%, becoming the most dominant bacteria. The results of α diversity analysis suggested that the Sobs indexes of the gut microbiota in the pneumonia and meningitis groups were significantly lower than that in the healthy control group (p 2 = 0.565), and there was no significant change in the diversity of gut microbiota before and after the use of antibiotics.Conclusions: The gut microbiota of neonates with infectious diseases were mainly related to the disease conditions. The initial state of neonatal gut microbiome determines its state after 1-week antibiotic treatment. Antibiotic application with 7 days had little effect on the community richness and some effect on the composition of gut microbiota of neonates with pneumonia or meningitis.</p