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Droplet microfluidics technology offers refined control over the flows of multiple fluids in micro/nano-scale, enabling fabrication of micro/nano-droplets with precisely adjustable structures and compositions in a high-throughput manner. With the combination of proper hydrogel materials and preparation methods, single or multiple cells can be efficiently encapsulated into hydrogels to produce cell-loaded hydrogel microspheres. The cell-loaded hydrogel microspheres can provide a three-dimensional, relatively independent and controllable microenvironment for cell proliferation and differentiation, which is of great value for three-dimensional cell culture, tissue engineering and regenerative medicine, stem cell research, single cell study and many other biological science fields. In this review, the preparation methods of cell-loaded hydrogel microspheres based on droplet microfluidics and its applications in biomedical field are summarized and future prospects are proposed.
Subject(s)
Hydrogels/chemistry , Microfluidics/methods , Microspheres , Regenerative Medicine , Tissue Engineering/methodsABSTRACT
Objective:This study aims to reveal the special immune infiltrating environment and possible immune escape mechanism of giant cell tumor of bone through single-cell sequencing data.Methods:The fresh samples obtained from 4 patients with primary giant cell tumor of bone from January 2018 to December 2021 were collected, and single-cell transcriptome sequencing was performed on the 10X platform to explore the characteristics and immune environment of giant cell tumor of bone by using t-distributed stochastic neighbor embedding ( t-SNE). The main cell types and signal pathways of immune cell regulation and function in giant cell tumor of bone were observed by cell communication analysis. Results:Cell clustering, the definition of basic cell types, the classification of immune cells, and the mutual regulatory relationship between cell types were analyzed for 35 643 single-cell data from 4 giant cell tumor samples of bone. It was found that giant cell tumor of bone was composed of 9 basic cell types, in which the immune cells were mainly CD8 + T cells (51%) and the non-immune cells were mainly fibroblast like spindle stromal cells (74%). The immune infiltration of giant cell tumor of bone is dominated by cytotoxic CD8 + T cells and lacks exhausted CD8 + T cells. CD4 + T cells are characterized by high expression of immune checkpoint genes CTLA4 and TIGIT. In giant cell tumor of bone, immune cells mainly act on multinucleated osteoclast like giant cells through PARs and CCL signaling pathways, but not stromal cells. Conclusion:This study defined the main cell types of giant cell tumor of bone through single cell sequencing data, and further revealed the composition characteristics of its immune infiltration, and found that the target of its immune cells was mainly multinuclear osteoclast like giant cells, which provided effective information for further understanding the occurrence and development of giant cell tumor of bone.
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Atherosclerosis is a major cause of coronary artery disease and stroke. A massive and new type of data has finally arrived in the field of atherosclerosis: single cell RNA sequencing (scRNAseq). Recently, scRNAseq has been successfully applied to the study of atherosclerosis to identify previously uncharacterized cell populations. scRNAseq is an effective approach to evaluate heterogeneous cell populations by measuring the transcriptomic profiles at the single cell level. Besides the studies of atherosclerosis, scRNAseq is being employed in various areas of biology, including cancer research and organ development. In order to analyze these new massive datasets, various analytic approaches have been developed. This review aims to enhance the understanding of this new technology by exploring how the single cell transcriptome has been applied to the study of atherosclerosis and further discuss potential analysis of using scRNAseq.
Subject(s)
Atherosclerosis , Biology , Coronary Artery Disease , Dataset , Sequence Analysis, RNA , Single-Cell Analysis , Stroke , TranscriptomeABSTRACT
Alzheimer's disease (AD) related genes have been elucidated by advanced genetic techniques. Familial autosomal dominant AD genes founded by linkage analyses are APP, PSEN1, PSEN2, ABCA7, and SORL1. Genome-wide association studies have found risk genes such as ABCA7, BIN1, CASS4, CD33, CD2AP, CELF1, CLU, CR1, DSG2, EPHA1, FERMT2, HLA-DRB5-HLA-DRB1, INPP5D, MEF2C, MS4A6A/MS4A4E, NME8, PICALM, PTK2B, SLC24A4, SORL1, and ZCWPW1. ABCA7, SORL1, TREM2, and APOE are proved to have high odds ratio (>2) in risk of AD using next generation sequencing studies. Thanks to the promising genetic techniques such as CRISPR-CAS9 and single-cell RNA sequencing opened a new era in genetics. CRISPR-CAS9 can directly link genetic knowledge to future treatment. Single-cell RNA sequencing are providing useful information on cell biology and pathogenesis of diverse diseases.
Subject(s)
Alzheimer Disease , Apolipoproteins E , CRISPR-Cas Systems , Genetic Techniques , Genetics , Genome-Wide Association Study , Odds Ratio , Sequence Analysis, RNA , Single-Cell AnalysisABSTRACT
The chemical components analysis of single cell is important for understanding of physiological processes such as cell growth, signal transduction and apoptosis.Time-of-flight secondary ion mass spectrometry ( ToF-SIMS) is a sensitive surface analysis technique with high spatial resolution and can be used for single cell and micro-area analysis.However, relatively low ioniZation yield of biomolecules limited its wide application in single cell analysis.Herein, we used metal substrate and matrix material to enhance the ioniZation yield of lipids.The signal intensity of the phosphatidylcholine PC (40:0) casted on the matrix/gold coated silicon substrate was 65 times higher than that on the silicon wafer.Signal enhancement of phosphatidylcholine PC (34:1) on the single cell surface cultured on matrix/gold coated silicon substrate was observed as well.Due to the influence of irregular topography and complex chemical environment of cell, the increase of lipids signal was smaller.Delayed extraction mode of ToF-SIMS overcame the effects of cell topography, leading to further enhancement of the signal intensity of lipids.Meanwhile, simultaneous high spatial resolution of chemical imaging and high mass resolution of the mass spectra of single cells were obtained.Our strategies provided new insights into the study of cell metabolism and cell-environment interactions.
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In recent years, the single-cell sequencing sparked enormous explosion in medical research. At the 201759th American Society of Hematology (ASH) Annual Meeting, many studies with single-cell sequencing were reported from the topics of hematopoietic stem cells (HSC), acute leukemia, mature lymphoma, myeloid proliferative neoplasm etc. The article reviews the progress of single-cell sequencing in hematological diseases according to some reports from 59th ASH Annual Meeting.
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Objective:To explore the prognostic value for circulating monocyte subsets combining left ventricular ejection fraction (LVEF) in patients with acute ST-segment elevation myocardial infarction (STEMI).Methods:STEMI patients admitted within 24 h of onset received PCI in Pingjin hospital heart center were enrolled.Flow cytometry (FCM) was used to examine 3 subsets of monocyte in peripheral blood as classical CD14++CD16-monocyte,intermediate CD14++CD16+ monocyte and non-classical CD14+CD16++ monocyte.The patients were followedup in 3 years for major adverse cardiac events (MACE) occurrence.The relationship between monocyte subsets,LVEF and MACE occurrence was studied by COX model analysis and MACE prediction model was established by ROC combining multivariate Logistic regression analysis.Results:There were 50/221 patients suffered from MACE during 3-year follow-up period.Compared with Non-MACE patients,MACE patients had the elder age (63.82±11.88) years vs (58.84±11.40) years,P=0.009;more diabetes mellitus (28.0％ vs 18.7％),P＜0.001;higher blood levels of LDL-C (2.77 mmol/L) vs (2.41 mmol/L),P=0.003 and CD14++CD16+ monocyte (47.17 cells/μl) vs (21.47 cells/μl),P＜0.001;lower LVEF (52％ vs 46％),P＜0.001.Multivariate Cox analysis indicated that CD14++CD16+ (HR=2.211,95％ CI 1.211-3.635,P=0.016) and LVEF (HR=2.014,95％ CI 1.038-2.933,P=0.022) were the independent risk factors for MACE occurrence in STEMI patients.ROC combining multivariate Logistic regression analysis presented that MACE predictive value of CD14++CD16+ monocyte combining LVEF (AUC=0.744,95％ CI 0.664-0.823,P＜0.001) was higher than the single value of CD14++CD16+ monocyte (AUC=0.683,95％ CI 0.598-0.768,P＜0.001) and LVEF(AUC=0.640,95％ CI 0.552-0.7291,P=0.003) respectively.Conclusion:Circulating level of CD14++CD16+ monocyte combining LVEF may predict MACE occurrence within 3 years in STEMI patients;it had potential value in clinical practice.
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Objective:To explore the prognostic value for circulating monocyte subsets combining left ventricular ejection fraction (LVEF) in patients with acute ST-segment elevation myocardial infarction (STEMI).Methods:STEMI patients admitted within 24 h of onset received PCI in Pingjin hospital heart center were enrolled.Flow cytometry (FCM) was used to examine 3 subsets of monocyte in peripheral blood as classical CD14++CD16-monocyte,intermediate CD14++CD16+ monocyte and non-classical CD14+CD16++ monocyte.The patients were followedup in 3 years for major adverse cardiac events (MACE) occurrence.The relationship between monocyte subsets,LVEF and MACE occurrence was studied by COX model analysis and MACE prediction model was established by ROC combining multivariate Logistic regression analysis.Results:There were 50/221 patients suffered from MACE during 3-year follow-up period.Compared with Non-MACE patients,MACE patients had the elder age (63.82±11.88) years vs (58.84±11.40) years,P=0.009;more diabetes mellitus (28.0％ vs 18.7％),P＜0.001;higher blood levels of LDL-C (2.77 mmol/L) vs (2.41 mmol/L),P=0.003 and CD14++CD16+ monocyte (47.17 cells/μl) vs (21.47 cells/μl),P＜0.001;lower LVEF (52％ vs 46％),P＜0.001.Multivariate Cox analysis indicated that CD14++CD16+ (HR=2.211,95％ CI 1.211-3.635,P=0.016) and LVEF (HR=2.014,95％ CI 1.038-2.933,P=0.022) were the independent risk factors for MACE occurrence in STEMI patients.ROC combining multivariate Logistic regression analysis presented that MACE predictive value of CD14++CD16+ monocyte combining LVEF (AUC=0.744,95％ CI 0.664-0.823,P＜0.001) was higher than the single value of CD14++CD16+ monocyte (AUC=0.683,95％ CI 0.598-0.768,P＜0.001) and LVEF(AUC=0.640,95％ CI 0.552-0.7291,P=0.003) respectively.Conclusion:Circulating level of CD14++CD16+ monocyte combining LVEF may predict MACE occurrence within 3 years in STEMI patients;it had potential value in clinical practice.
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Laser tweezers Raman spectroscopy ( LTRS ) was used to study the inhibitory effect of indol on staphyloxanthin biosynthesis in Staphylococcus aureus cells and the dynamic changes of this pigment content inside bacterial cells during batch cultivation. The Raman spectra of Staphylococcus aureus cells cultivated for different time and exposed to various doses of indol were acquired. The intensity of 1523 cm-1 band was used for the quantification of staphyloxanthin, in the meantime, the pigment was measured by UV spectrometry. The experimental result showed that an excellent linear relationship existed between the intensities of Raman peak at 1523 cm-1 of bacterial cells and the pigment contents estimated by UV spectrometry, with a correlation coefficient of 0 . 9772 . The spectral data at population level as well as single cell level revealed that indol could inhibit the production of pigment in dose-dependent manner, and the pigment content in bacterial cells incubated with indol decreased by 70%. Under the batch growth condition, the pigment amount in Staphylococcus aureus cells reached the maximum value during the middle exponential growth phase ( 12 h ) and the heterogeneity of pigment content in bacterial cells within certain populations at various time points was relatively small, with RSDs of 39. 2% to 61. 1%. This investigation indicates that LTRS can be served as a reliable method for the analysis of staphyloxanthin content at single cell level.
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Whole-genome sequencing of bacteria has recently emerged as a cost-effective and convenient approach for resolving many microbiological questions.Here, the current status of whole-genome sequencing in clinical microbiology and the main problems that exist were reviewed, focusing on six essential tasks: identifying and culturing the species of an isolate, rapid identification of pathogen properties, monitoring the emergence and spread of an epidemic outbreak, developing vaccine and monitoring its variation,metagenomics and single-cell sequencing.The authors predicted that the application of whole-genome sequencing will soon be sufficiently fast, accurate and cheap to be used in routine etiological detection, even though there is still a long way to go.
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Studies of cancer heterogeneity have received considerable attention recently, because the presence or absence of resistant sub-clones may determine whether or not certain therapeutic treatments are effective. Previously, we have reported G64, a co-regulated gene module composed of 64 different genes, can differentiate tumor intra- or inter-subpopulations in lung adenocarcinomas (LADCs). Here, we investigated whether the G64 module genes were also expressed distinctively in different subpopulations of other cancers. RNA sequencing-based transcriptome data derived from 22 cancers, except LADC, were downloaded from The Cancer Genome Atlas (TCGA). Interestingly, the 22 cancers also expressed the G64 genes in a correlated manner, as observed previously in an LADC study. Considering that gene expression levels were continuous among different tumor samples, tumor subpopulations were investigated using extreme expressional ranges of G64-i.e., tumor subpopulation with the lowest 15% of G64 expression, tumor subpopulation with the highest 15% of G64 expression, and tumor subpopulation with intermediate expression. In each of the 22 cancers, we examined whether patient survival was different among the three different subgroups and found that G64 could differentiate tumor subpopulations in six other cancers, including sarcoma, kidney, brain, liver, and esophageal cancers.
Subject(s)
Humans , Adenocarcinoma , Brain , Esophageal Neoplasms , Gene Expression , Gene Regulatory Networks , Genome , Kidney , Liver , Lung , Population Characteristics , RNA , Sarcoma , Single-Cell Analysis , Survival Analysis , TranscriptomeABSTRACT
Nitrogen is an essential nutrient for yeast cells on ethanol fermentation. In order to reveal the promoting mechanisms of organic nitrogen sources on the ethanol fermentation by yeast, Saccharomyces cerevisiae, laser tweezers Raman spectroscopy and single-cell analysis techniques were used to monitored the kinetic of intracellular bio-macromolecules of individual cells during fermentation with urea, yeast extract, ammonium nitrate or ammonium sulfate as the sole nitrogen source. Major results from this work were as follows. (1) Organic nitrogen sources had a promoting effect on the ethanol fermentation, the fermentation with urea and yeast extract reached the maximum concentration of ethanol in 14-18 h. ( 2 ) There were no apparent lag phases for the RNA synthesis of yeast cells cultured with urea and yeast extract. The averaged Raman intensity of yeast cells at peak of 782 cm-1 in the early stage of fermentation was stronger than that of cultured with ammonium nitrate and ammonium sulfate. The maximum was about 1. 9-2. 1 times of the initial intensity for urea or yeast extract, but 1. 2-1. 4 times for ammonium nitrate and ammonium sulfate. (3) The secondary structure of proteins of partial cells cultured with yeast extract was dominated byβ-sheet, while cells cultured with other nitrogen sources were dominated by α-helix absolutely. These results bring us the conclusion that the improving effect of organic nitrogen sources such as urea and yeast extract on ethanol fermentation by Saccharomyces cerevisiae may be due to that the organic nitrogen sources can shorten the lag phase of yeast cells, promote the RNA synthesis, and promote the transcription and expression of related genes.
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Objective:A method that is based on microfluidic cell chip technology was developed for the first time to analyze CD14+monocyte myeloperoxidase (MPO) expression in myelomonocytic leukemia (M4) patients. CD14+monocyte MPO expression in M4 patients was preliminarily discussed. Methods:a. The chip was prepared by using polydimethylsiloxane as the host material and by secondary foam molding. b. A total of 48 clinically diagnosed M4 patients and 52 patients with normal myelogram were included as the test and control groups, respectively. c. A method based on the microfluidic cell chip approach was established to detect CD14+mono-cytes and to determine the positive rate and degree of MPO expression in the cells. d. The microfluidic cell chip technique was used to compare CD14+monocyte MPO expression in M4 patients with that in the control. Results:a. The designed microfluidic single cell analysis chip allowed the entry of granulocytes into the corresponding microfluidic channels. Thus, blood cells were separated. Numer-ous ghost corpuscles surrounded the separated white blood cells (WBCs). WBC morphology did not show obvious changes. b. The posi-tive rate of MPO expression and the activity of CD14+monocytes in the bone marrow of M4 patients were significantly higher than those in the bone marrow of the control (P<0.05). Conclusion:A method based on microfluidic single cell technology was developed for the first time to analyze the MPO expression in CD14+monocytes. CD14+monocyte MPO activity in M4 patients was significantly higher than in the control. CD14+monocyte MPO activity can be used as an auxiliary examination marker for clinical diagnosis.
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Over the past 40 years, flow cytometry has emerged as a leading, application-rich technology that supports high-resolution characterization of individual cells which function in complex cellular networks such as the immune system. This brief overview highlights advances in multiparameter flow cytometric technologies and reagent applications for characterization and functional analysis of cells modulating the immune network. These advances significantly support high-throughput and high-content analyses and enable an integrated understanding of the cellular and molecular interactions that underlie complex biological systems.