scholarly journals Novel approach for quantification of multiple immunofluorescent signals using histograms and 2D plot profiling of whole-section panoramic images

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Roko Duplancic ◽  
Darko Kero
Keyword(s):  
Histological Section ◽  
Cell Counting ◽  
Tissue Samples ◽  
Spatial Gradients ◽  
Multiple Markers ◽  
Novel Approach ◽  
Academic Settings ◽  
Panoramic Images ◽  
Multiple Regions ◽  
Staining Protocol

AbstractWe describe a novel approach for quantification and colocalization of immunofluorescence (IF) signals of multiple markers on high-resolution panoramic images of serial histological sections utilizing standard staining techniques and readily available software for image processing and analysis. Human gingiva samples stained with primary antibodies against the common leukocyte antigen CD45 and factors related to heparan sulfate glycosaminoglycans (HS GAG) were used. Expression domains and spatial gradients of IF signals were quantified by histograms and 2D plot profiles, respectively. The importance of histomorphometric profiling of tissue samples and IF signal thresholding is elaborated. This approach to quantification of IF staining utilizes pixel (px) counts and comparison of px grey value (GV) or luminance. No cell counting is applied either to determine the cellular content of a given histological section nor the number of cells positive to the primary antibody of interest. There is no selection of multiple Regions-Of-Interest (ROIs) since the entire histological section is quantified. Although the standard IF staining protocol is applied, the data output enables colocalization of multiple markers (up to 30) from a given histological sample. This can serve as an alternative for colocalization of IF staining of multiple primary antibodies based on repeating cycles of staining of the same histological section since those techniques require non standard staining protocols and sophisticated equipment that can be out of reach for small laboratories in academic settings. Combined with the data from ontological bases, this approach to quantification of IF enables creation of in silico virtual disease models.

scholarly journals Circular RNA hsa_circ_0006401 promotes proliferation and metastasis in colorectal carcinoma

2021 ◽  
Vol 12 (5) ◽  
Author(s):  
Chenjing Zhang ◽  
Xiaolu Zhou ◽  
Xiaoge Geng ◽  
Yu Zhang ◽  
Jingya Wang ◽  
...  
Keyword(s):  
Splice Junction ◽  
Circular Rna ◽  
Host Gene ◽  
Cell Counting ◽  
Tissue Samples ◽  
Proliferation And Metastasis ◽  
And Migration ◽  
Proliferation And Migration

AbstractDysregulation of circular RNA (circRNA) expression is involved in the progression of cancer. Here, we aimed to study the potential function of hsa_circ_0006401 in colorectal cancer (CRC). CircRNA hsa_circ_0006401 expression levels in CRC and adjacent nontumor tissues were analyzed by real-time quantitative PCR (qRT-PCR) and circRNA in situ hybridization (RNA-ISH). Then, CRC cell proliferation was assessed by cell counting. Wound-healing and transwell assays were utilized to detect the effect of hsa_circ_0006401 on CRC migration. A circRNA-ORF construct was created, and a specific antibody against the splice junction of hsa_circ_0006401 was prepared. Finally, the proteins directly binding to hsa_circ_0006401 peptides were identified by immunoprecipitation combined with mass spectrometry. In our study, we found hsa_circ_0006401 was closely related to CRC metastasis and exhibited upregulated expression in metastatic CRC tissue samples. Proliferation and migration were inhibited in vitro when hsa_circ_0006401 expression was silenced. Downregulation of hsa_circ_0006401 expression decreased CRC proliferation and liver metastasis in vivo. A 198-aa peptide was encoded by sequences of the splice junction absent from col6a3. Hsa_circ_0006401 promoted CRC proliferation and migration by encoding the hsa_circ_0006401 peptide. Hsa_circ_0006401 peptides decreased the mRNA and protein level of the host gene col6a3 by promoting col6a3 mRNA stabilation. In conclusion, our study revealed that circRNAs generated from col6a3 that contain an open-reading frame (ORF) encode a novel 198-aa functional peptide and hsa_circ_0006401 peptides promote stability of the host gene col6a3 mRNA to promote CRC proliferation and metastasis.

scholarly journals Cell-Tak coating may cause mis-normalization of Seahorse metabolic flux data

2021 ◽  
Author(s):  
Michal Šíma ◽  
Stanislava Martínková ◽  
Anežka Kafková ◽  
Jan Pala ◽  
Jan Trnka
Keyword(s):  
Metabolic Flux ◽  
Cell Number ◽  
Cell Counting ◽  
Fluorescent Detection ◽  
Data Normalization ◽  
Tissue Samples ◽  
Flux Data ◽  
Research Areas ◽  
Healthy State ◽  
A Cell

Metabolic flux investigations of cells and tissue samples are a rapidly advancing tool in diverse research areas. Reliable methods of data normalization are crucial for an adequate interpretation of results and to avoid a misinterpretation of experiments and incorrect conclusions. The most common methods for metabolic flux data normalization are to cell number, DNA and protein. Data normalization may be affected by a variety of factors, such as density, healthy state, adherence efficiency, or proportional seeding of cells. The mussel-derived adhesive Cell-Tak is often used to immobilize poorly adherent cells. Here we demonstrate that this coating may strongly affect the fluorescent detection of DNA leading to an incorrect and highly variable normalization of metabolic flux data. Protein assays are much less affected and cell counting can virtually completely remove the effect of the coating. Cell-Tak coating also affects cell shape in a cell line-specific manner and may change cellular metabolism. Based on these observations we recommend cell counting as a gold standard normalization method for Seahorse metabolic flux measurements with protein content as a reasonable alternative.

scholarly journals Circular RNA circCCDC66 Contributes to Malignant Phenotype of Osteosarcoma by Sponging miR-338-3p to Upregulate the Expression of PTP1B

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Deng Xiang ◽  
Yugang Li ◽  
Yanshui Lin
Keyword(s):  
Cell Proliferation ◽  
Molecular Mechanism ◽  
Cell Lines ◽  
Rapid Development ◽  
Circular Rna ◽  
Molecular Medicine ◽  
Cell Counting ◽  
Luciferase Reporter ◽  
Circular Rnas ◽  
Tissue Samples

In recent years, the mechanism of cancer research has become hotspots of life science and medicine, especially due to the rapid development of molecular medicine and bioinformatics research. Similarly, the molecular mechanism also has received increasing attention in osteosarcoma (OS) research. Also, a considerable amount of research confirmed that circular RNAs (circRNAs) could regulate cancer cell growth and metastasis. This study aimed to explore the effect of a circRNA, circCCDC66, on OS and reveal its potential molecular mechanism. High circCCDC66 expression level was found in OS patient-derived tissue samples and OS cell lines by qRT-PCR. The abilities cell proliferation and metastatic of U2OS and SW1353 cells were then assessed by Cell Counting Kit-8 and transwell assay, respectively. The interaction between circCCDC66 and its target miRNAs were verified by the dual-luciferase reporter assay. Through functional experiments, we found that circCCDC66 knockdown promoted the inhibition of cell proliferation and metastatic of OS cell lines. From mechanistic perspective, circCCDC66 upregulated PTP1B by sponging miR-338-3p. Collectively, our findings demonstrated that circCCDC66 contributed to malignant behaviors of OS cells by miR-338-3p/PTP1B pathway, which suggested circCCDC66/miR-338-3p/PTP1B axis might be a potential therapeutic target.

lncRNA KCNQ1OT1 promotes the proliferation, migration and invasion of retinoblastoma cells by upregulating HIF-1α via sponging miR-153-3p

2020 ◽  
Vol 68 (8) ◽  
pp. 1349-1356
Author(s):  
Yujin Wang ◽  
Jixiang Wang ◽  
Hongyan Hao ◽  
Xiangxia Luo
Keyword(s):  
Colony Formation ◽  
Rna Binding ◽  
Hypoxia Inducible Factor ◽  
Cell Counting ◽  
Luciferase Reporter ◽  
Migration And Invasion ◽  
Luciferase Reporter Gene ◽  
Tissue Samples ◽  
Qrt Pcr ◽  
Gene Assay

It is reported that lncRNA KCNQ1 opposite strand/antisense transcript 1 (KCNQ1OT1) is oncogenic in many cancers. This work aimed at probing into its expression and biological functions in retinoblastoma (RB) as well as its regulatory effects on miR-153-3p and hypoxia-inducible factor-1α (HIF-1α). In our study, RB samples in pair were collected, and quantitative real-time PCR (qRT-PCR) was employed for examining the expression levels of KCNQ1OT1, miR-153-3p and HIF-1α. KCNQ1OT1 short hairpin RNAs were transfected into SO-Rb50 and HXO-RB44 cell to inhibit the expression of KCNQ1OT1. The proliferative activity, colony formation ability and apoptosis were examined through cell counting kit-8 assay, colony formation assays, Transwell assay and flow cytometry, respectively. qRT-PCR and western blot analysis were used for analyzing the changes of miR-153-3p and HIF-1α induced by KCNQ1OT1. The regulatory relationships between miR-153-3p and KCNQ1OT1, miR-153-3p and HIF-1α were examined by dual luciferase reporter gene assay and RNA-binding protein immunoprecipitation assay. The results of our study showed that KCNQ1OT1 expression was markedly enhanced in RB tissue samples, and KCNQ1OT1 knockdown had an inhibitory effect on the proliferation, migration, invasion and viability of RB cells. There were two validated binding sties between KCNQ1OT1 and miR-153-3p, and KCNQ1OT1 negatively regulated the expression of miR-153-3p in RB cells. HIF-1α was a target gene of miR-153-3p, and could be positively regulated by KCNQ1OT1. In conclusion, our study indicates that KCNQ1OT1 can increase the malignancy of RB cells via regulating miR-153-3p/HIF-1α axis.

scholarly journals Automated Spatially Targeted Optical Micro Proteomics (AutoSTOMP) 2.0 identifies proteins enriched within inflammatory lesions in tissue sections and human clinical biopsies.

2021 ◽  
Author(s):  
BOCHENG YIN ◽  
Laura R Caggiano ◽  
Rung-Chi Li ◽  
Emily McGowan ◽  
Jeffery W. Holmes ◽  
...  
Keyword(s):  
Protein Expression ◽  
Cell Biology ◽  
Cell Types ◽  
Specific Cell ◽  
Fixed Tissue ◽  
Tissue Samples ◽  
Novel Approach ◽  
Esophageal Tissue ◽  
Inflammatory Proteins

Tissue microenvironment properties like blood flow, extracellular matrix or proximity to immune infiltrate are important regulators of cell biology. However, methods to study regional protein expression in context of the native tissue environment are limited. To address this need we have developed a novel approach to visualize, purify and measure proteins in situ using Automated Spatially Targeted Optical Micro Proteomics (AutoSTOMP) 2.0. We previously implemented AutoSTOMP to identify proteins localized to the vacuoles of obligate intracellular microbes at the 1-2 μm scale within infected host cells1. Here we report custom codes in SikuliX to specify regions of heterogeneity in a tissue section and then biotin tag and identify proteins belonging to specific cell types or structures within those regions. To enrich biotinylated targets from fixed tissue samples we developed a biochemical protocol compatible with LC-MS. These tools were applied to a) identify inflammatory proteins expressed by CD68+ macrophages in rat cardiac infarcts and b) characterize inflammatory proteins enriched in IgG4+ lesions in esophageal tissue. These data indicate that AutoSTOMP is a flexible approach to determine regional protein expression in situ on a range of primary tissues and clinical biopsies where current tools are limited.

scholarly journals Upregulation of SNTB1 Correlates with Poor Prognosis and Promotes Cell Growth in Colorectal Cancer

2021 ◽  
Author(s):  
Liya Liu ◽  
Youqin Chen ◽  
Xiaoying Lin ◽  
Meizhu Wu ◽  
Jiapeng Li ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cell Cycle ◽  
Colony Formation ◽  
Malignant Tumors ◽  
Cdna Array ◽  
Cell Counting ◽  
Nude Mouse Model ◽  
Tissue Samples

Abstract Background: Colorectal cancer (CRC) is one of the most highly malignant tumors and has a complicated pathogenesis. A preliminary study identified syntrophin beta 1 (SNTB1) as a potential oncogene in CRC. However, the clinical significance, biological function, and underlying mechanisms of SNTB1 in CRC are unknown. Thus, the present study aimed to investigate the function of SNTB1 in CRC.Methods: The expression profile of SNTB1 in CRC samples was evaluated by database analysis, cDNA array, tissue microarray, Quantitative real-time PCR (qPCR), and immunohistochemistry. SNTB1 expression in human CRC cells was silenced using short hairpin RNAs and its mRNA and protein levels were assessed by qPCR and western blotting, respectively. Cell proliferation, colony formation, cell cycle and apoptosis were determined by the cell counting, colony formation, and flow cytometry assays, respectively. A xenograft nude mouse model of CRC was established for validating the roles of SNTB1 in vivo. Immunohistochemistry was used to score the expression of SNTB1 in tissue samples. The isobaric tags for relative and absolute quantification (iTRAQ) was used to analyze the differentially expressed proteins after knockdown of SNTB1 in CRC cells.Results: SNTB1 expression was increased in CRC tissue compared with adjacent noncancerous tissues and the increased expression was associated with shorter overall survival of CRC patients. Silencing of SNTB1 suppressed cell viability and survival, induced cell cycle arrest and apoptosis in vitro, and inhibited the growth of CRC cells in vivo. Further elucidation of the regulation of STNB on CRC growth by iTRAQ analysis identified 210 up-regulated and 55 down-regulated proteins in CRC cells after SNTB knockdown. A PPI network analysis identified protein kinase N2 (PKN2) as a hub protein and was up-regulated in CRC cells after SNTB1 knockdown. Western-blot analysis further confirmed that SNTB1 knockdown significantly up-regulated PKN2 protein expression in CRC cells and decreased the phosphorylation of both ERK1/2 and AKT. Conclusion: These findings indicate that SNTB1 is overexpressed in CRC. Elevated SNTB1 levels are correlated with shorter patient survival. Importantly, SNTB1 promoted tumor growth and progression of CRC, possibly by reducing the expression of PKN2 and activating the ERK and AKT signaling pathway. Our study highlights the potential of SNTB1 as a new prognostic predictor and therapeutic target for CRC.

scholarly journals Automated highly multiplexed super-resolution imaging of protein nano-architecture in cells and tissues

2019 ◽  
Author(s):  
Maja Klevanski ◽  
Frank Herrmannsdoerfer ◽  
Varun Venkataramani ◽  
Steffen Sass ◽  
Mike Heilemann ◽  
...  
Keyword(s):  
Cultured Cells ◽  
Protein Localization ◽  
Super Resolution ◽  
Protein Distribution ◽  
Tissue Samples ◽  
Target Proteins ◽  
Presynaptic Nerve Terminal ◽  
Solution Exchange ◽  
Staining Protocol ◽  
Cellular Compartments

ABSTRACTUnderstanding the nano-architecture of protein machines in diverse sub-cellular compartments remains a challenge despite rapid progress in super-resolution microscopy. While singlemolecule localization microscopy techniques allow the visualization and identification of cellular structures with near-molecular resolution, multiplex-labeling of tens of target proteins within the same sample has not yet been achieved routinely. However, single sample multiplexing is essential to detect patterns that threaten to get lost in multi-sample averaging. Here, we report maS3TORM (multiplexed automated serial staining stochastic optical reconstruction microscopy), a microscopy approach capable of fully automated 3D dSTORM imaging and solution exchange employing a re-staining protocol to achieve highly multiplexed protein localization within individual biological samples. We demonstrate 3D super-resolution images of 15 target proteins in single cultured cells and 16 targets in individual neuronal tissue samples with <10 nm localization precision. This allowed us to define novel nano-architectural features of protein distribution within the presynaptic nerve terminal.

scholarly journals Object detection for automatic cancer cell counting in zebrafish xenografts

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0260609
Author(s):  
Carina Albuquerque ◽  
Leonardo Vanneschi ◽  
Roberto Henriques ◽  
Mauro Castelli ◽  
Vanda Póvoa ◽  
...  
Keyword(s):  
Human Error ◽  
Tumor Biology ◽  
Cell Counting ◽  
Cell Detection ◽  
Cancer Model ◽  
Data Set ◽  
Novel Approach ◽  
Median Error ◽  
Different Shapes ◽  
Crowded Scenes

Cell counting is a frequent task in medical research studies. However, it is often performed manually; thus, it is time-consuming and prone to human error. Even so, cell counting automation can be challenging to achieve, especially when dealing with crowded scenes and overlapping cells, assuming different shapes and sizes. In this paper, we introduce a deep learning-based cell detection and quantification methodology to automate the cell counting process in the zebrafish xenograft cancer model, an innovative technique for studying tumor biology and for personalizing medicine. First, we implemented a fine-tuned architecture based on the Faster R-CNN using the Inception ResNet V2 feature extractor. Second, we performed several adjustments to optimize the process, paying attention to constraints such as the presence of overlapped cells, the high number of objects to detect, the heterogeneity of the cells’ size and shape, and the small size of the data set. This method resulted in a median error of approximately 1% of the total number of cell units. These results demonstrate the potential of our novel approach for quantifying cells in poorly labeled images. Compared to traditional Faster R-CNN, our method improved the average precision from 71% to 85% on the studied data set.

scholarly journals Long noncoding RNA SNHG4 promotes renal cell carcinoma tumorigenesis and invasion by acting as ceRNA to sponge miR-204-5p and upregulate RUNX2

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Jie Wu ◽  
Tingting Liu ◽  
Lulu Sun ◽  
Shaojin Zhang ◽  
Gang Dong
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Proliferation ◽  
Tumor Growth ◽  
Cell Carcinoma ◽  
Mouse Models ◽  
Cell Lines ◽  
Renal Cell ◽  
Cell Counting ◽  
Tissue Samples ◽  
Qrt Pcr

Abstract Background Long noncoding RNAs (lncRNAs) are involved in the tumorigenesis and progression of human cancers, including renal cell carcinoma (RCC). Small nucleolar RNA host gene 4 (SNHG4) is reported to play an essential role in tumor growth and progression. However, the molecular mechanisms and function of SNHG4 in RCC remain undocumented. Methods Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to examine expression levels of SNHG4 in RCC tissue samples and cell lines. Cell counting kit-8, western blotting, activities of caspase-3, -8, and -9, wound-healing, and transwell invasion assays were performed to explore cell proliferation, apoptosis, migration, and invasion. The interaction among SNHG4, miR-204-5p, and RUNX2 was verified by bioinformatic analysis, a luciferase gene report, qRT-PCR, western blot analysis, and RNA immunoprecipitation assays. Xenograft mouse models were carried out to examine the role of SNHG4 in RCC in vivo. Results SNHG4 was highly expressed in RCC tissue samples and cell lines, and its upregulation was significantly involved in node involvement, distant metastasis, and reduced overall and relapse-free survival of patients with RCC. SNHG4 acted as an oncogenic lncRNA with promoted RCC cell proliferation, migration, invasion, and inhibited apoptosis. SNHG4 boosted tumor growth in xenograft mouse models. Mechanistically, SNHG4 functioned as a competing endogenous RNA (ceRNA) for sponging miR-204-5p, leading to the upregulation of its target RUNX2 to promote RCC cell proliferation and invasion. Conclusion SNHG4 and miR-204-5p might be indicated in RCC progression via RUNX2, suggesting the potential use of SNHG4/miR-204-5p/RUNX2 axis in RCC treatment.

Long non-coding RNA LINC00115 contributes to the progression of colorectal cancer by targeting miR-489-3p via PI3K/AKT/mTOR pathway

2020 ◽  
Author(s):  
Weiyu Feng ◽  
Baodong Li ◽  
Jinbang Wang ◽  
Huiliang Zhang ◽  
Yonggang Liu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Molecular Mechanisms ◽  
Biological Effects ◽  
Inverse Correlation ◽  
Mtor Signaling ◽  
Cell Counting ◽  
Luciferase Reporter ◽  
Migration And Invasion ◽  
Regulatory Relationship ◽  
Tissue Samples

Abstract Background Long noncoding RNAs (lncRNAs) are tumor-related regulators and have been found to be involved in the underlying molecular mechanisms of colorectal cancer (CRC). However, the role of lncRNA LINC00115 during CRC progression is not entirely elucidated. Methods The expression of LINC00115 was analyzed in paired CRC tissue samples and its clinical significance was evaluated. The biological effects on CRC cells proliferation, apoptosis, migration, invasion and PI3K/AKT/mTOR signaling were assessed by Cell Counting Kit-8 assay, Transwell assay, flow cytometry analysis and Western blot, respectively. The regulatory relationship between LINC00115 and miR-489-3p was determined by dual-luciferase reporter assays. Results LINC00115 was significantly overexpressed in CRC and its overexpression predicted poor outcome of the patients. Downregulation of LINC00115 markedly inhibited CRC cell proliferation, increased cell apoptosis, and suppressed cell migration and invasion. Moreover, downregulation of LINC00115 led to the inactivation of PI3K/AKT/mTOR signaling. Bioinformatics analysis identified miR-489-3p as a candidate target of LINC00115. Furthermore, we revealed an inverse correlation between LINC00115 and miR-489-3p in CRC tissues. miR-489-3p might directly target LINC00115 and downregulation of miR-489-3p could rescue the biological effects induced by the absence of LINC0015. Conclusion LINC00115 serves as an excellent oncogene of CRC metastasis, the deeper understanding of LINC00115/miR-489-3p axis might provide potential therapeutic targets for CRC metastasis.

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