scholarly journals Generation of genetic tools for gauging multiple gene expression at single cell level

2021 ◽  
Author(s):  
Marta Mellini ◽  
Massimiliano Lucidi ◽  
Francesco Imperi ◽  
Paolo Visca ◽  
Livia Leoni ◽  
...  
Keyword(s):  
Gene Expression ◽  
Image Processing ◽  
Single Cell ◽  
Fluorescent Protein ◽  
Single Cells ◽  
Phenotypic Heterogeneity ◽  
Single Cell Level ◽  
Cell Level ◽  
Multiple Gene ◽  
Genetic Tools

Key microbial processes in many bacterial species are heterogeneously expressed in single cells of bacterial populations. However, the paucity of adequate molecular tools for live, real-time monitoring of multiple gene expression at the single cell level has limited the understanding of phenotypic heterogeneity. In order to investigate phenotypic heterogeneity in the ubiquitous opportunistic pathogen Pseudomonas aeruginosa, a genetic tool that allows gauging multiple gene expression at the single cell level has been generated. This tool, named pRGC, consists in a promoter-probe vector for transcriptional fusions that carries three reporter genes coding for the fluorescent proteins mCherry, green fluorescent protein (GFP) and cyan fluorescent protein (CFP). The pRGC vector has been characterized and validated via single cell gene expression analysis of both constitutive and iron-regulated promoters, showing clear discrimination of the three fluorescence signals in single cells of a P. aeruginosa population, without the need of image-processing for spectral crosstalk correction. In addition, two pRGC variants have been generated for either i) integration of the reporter gene cassette into a single neutral site of P. aeruginosa chromosome, that is suitable for long-term experiments in the absence of antibiotic selection, or ii) replication in bacterial genera other than Pseudomonas. The easy-to-use genetic tools generated in this study will allow rapid and cost-effective investigation of multiple gene expression in populations of environmental and pathogenic bacteria, hopefully advancing the understanding of microbial phenotypic heterogeneity. IMPORTANCE Within a bacterial population single cells can differently express some genes, even though they are genetically identical and experience the same chemical and physical stimuli. This phenomenon, known as phenotypic heterogeneity, is mainly driven by gene expression noise and results in the emergence of bacterial sub-populations with distinct phenotypes. The analysis of gene expression at the single cell level has shown that phenotypic heterogeneity is associated with key bacterial processes, including competence, sporulation and persistence. In this study, new genetic tools have been generated that allow easy cloning of up to three promoters upstream of distinct fluorescent genes, making it possible to gauge multiple gene expression at the single cell level by fluorescent microscopy, without the need of advanced image-processing procedures. A proof of concept has been provided by investigating iron-uptake and iron-storage gene expression in response to iron availability in P. aeruginosa.

scholarly journals Gene Expression Profiling of CD93-Selected CP-CML Stem Cells Confirms Their Quiescent Character and Biomarker Potential

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 4231-4231
Author(s):  
Gillian A. Horne ◽  
Chinmay Rajiv Munje ◽  
Ross Kinstrie ◽  
Eduardo Gómez-Castañeda ◽  
Helen Wheadon ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Board Of Directors ◽  
Research Funding ◽  
Single Cells ◽  
Gene Clustering ◽  
Single Cell Level ◽  
Cell Level ◽  
Advisory Committees ◽  
Two Populations

Abstract The introduction of BCR-ABL tyrosine kinase inhibitors has revolutionized the treatment of chronic myeloid leukemia (CML). A major clinical aim remains the identification and elimination of low-level disease persistence, termed "minimal residual disease". Disease persistence suggests, that despite targeted therapeutic approaches, BCR-ABL-independent mechanisms exist which sustain the survival of a small population of cells, termed leukemic stem cells (LSC). We previously identified CD93 expression as a promising biomarker of LSC in chronic phase (CP)-CML. Our group has described the long term self-renewal potential of Lin-CD34+93+ CP-CML cells compared to their Lin-CD34+93- counterparts through LTCIC assays (n=3, p<0.0001) and NSG engraftment models (3.5-30-fold increased in engraftment with Lin-CD34+93+ cells, p<0.03). We hypothesized that CD93+-selected cells would represent a more immature functional phenotype compared to CD93- selected cells. The aim of this study was to characterize differences in the gene expression profile between CD93+ and CD93- CML LSC populations and determine heterogeneity of each population at a single cell level. To interrogate this, we initially identified CP-CML subpopulations with the greatest functional capability compared to normal. Normal and CP-CML samples were FACS-sorted into HSC/LSC, CMP, GMP, and MEP sub-populations. Results suggest a significant change in functional status between normal and CP-CML subpopulations within the HSC/LSC compartment (lin-CD34+CD38-CD45RA-CD90+), where CML LSC demonstrated significantly increased proliferation (14 fold expansion; P<0.001) compared to normal HSC (no expansion) after 5 days in vitro culture in physiological growth factors. In addition, equivalent numbers of CML LSC produce ~4-fold more colonies in colony forming cell (CFC) assays than normal HSC (329±56 versus 86±17 per 2,000 cells, respectively (p<0.05)). Furthermore, fluorescence in situ hybridization demonstrated that >90% of lin-CD34+CD38-CD45RA-CD90+ CML LSC from all patient samples were BCR-ABL positive. Subsequent experiments were confined to the LSC population. We hypothesized that lin-CD34+CD38-CD90+CD93- CML cells would have a more mature gene expression profile compared to lin-CD34+CD38-CD90+CD93+ cells. CP-CML cells were sorted into (1) lin-CD34+, (2) lin-CD34+CD38-CD90+CD93- and (3) lin-CD34+CD38-CD90+CD93+ populations. RNA was harvested at baseline from bulk populations (1) to (3) and cDNA was generated from single cells using the Fluidigm C1 autoprep system. Using Fluidigm technology, quantitative PCR of 90 lineage-specific and cell survival genes was performed within all populations of cells (1) to (3) in 'bulk' samples (n=3), and at single cell level (n=123 CD93+, n=120 CD93-single cells; n=3 samples in total). Bulk sample analysis demonstrated a significant increase in expression of lineage commitment genes within the lin-CD34+CD38-CD90+CD93- population, as shown by increased expression of GATA1 (p=0.0007), and CBX8 (p=0.0002). The lin-CD34+CD38-CD90+CD93+ population displayed a less lineage-restricted profile with increased expression of CDK6 (p=0.05), HOXA6 (ns), CDKN1C (ns) and CKIT (p=0.0014), compared to the lin-CD34+CD38-CD90+CD93- population. Furthermore, the two populations could be segregated by differential gene expression through gene clustering. At a single cell level, differences were noted in the frequency of expression between lin-CD34+CD38-CD90+CD93- and lin-CD34+CD38-CD90+CD93+ populations, particularly in GATA1, TPOR, and VWF. Although a statistically significant change was demonstrated in gene expression between the lin-CD34+CD38-CD90+CD93- and lin-CD34+CD38-CD90+CD93+ populations in a number of genes, we were not able to segregate the populations by differential expression using gene clustering. This highlights the heterogeneous nature of the cell populations and the inability to distinctly characterize between the two populations at a single cell level. Our results validate CD93 as a potential biomarker to separate the primitive CP-CML LSC population and highlight key lineage and cell survival pathways that are altered in CML LSC. The results demonstrate the heterogeneity seen within gene expression at the single cell level, which may allow for further insight into the CML LSC compartment with further analyses. Disclosures Wheadon: GlaxoSmithKline: Research Funding. Copland:Shire: Honoraria; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; ARIAD: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria.

scholarly journals Tracking single-cell gene regulation in dynamically controlled environments using an integrated microfluidic and computational setup

2016 ◽  
Author(s):  
Matthias Kaiser ◽  
Florian Jug ◽  
Olin Silander ◽  
Siddharth Deshpande ◽  
Thomas Pfohl ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Regulation ◽  
Single Cell ◽  
Environmental Conditions ◽  
Single Cells ◽  
Fine Tuning ◽  
Growth Media ◽  
Single Cell Level ◽  
Cell Level ◽  
Operon Regulation

AbstractBacteria adapt to changes in their environment by regulating gene expression, often at the level of transcription. However, since the molecular processes underlying gene regulation are subject to thermodynamic and other stochastic fluctuations, gene expression is inherently noisy, and identical cells in a homogeneous environment can display highly heterogeneous expression levels. To study how stochasticity affects gene regulation at the single-cell level, it is crucial to be able to directly follow gene expression dynamics in single cells under changing environmental conditions. Recently developed microfluidic devices, used in combination with quantitative fluorescence time-lapse microscopy, represent a highly promising experimental approach, allowing tracking of lineages of single cells over long time-scales while simultaneously measuring their growth and gene expression. However, current devices do not allow controlled dynamical changes to the environmental conditions which are needed to study gene regulation. In addition, automated analysis of the imaging data from such devices is still highly challenging and no standard software is currently available. To address these challenges, we here present an integrated experimental and computational setup featuring, on the one hand, a new dual-input microfluidic chip which allows mixing and switching between two growth media and, on the other hand, a novel image analysis software which jointly optimizes segmentation and tracking of the cells and allows interactive user-guided fine-tuning of its results. To demonstrate the power of our approach, we study the lac operon regulation in E. coli cells grown in an environment that switches between glucose and lactose, and quantify stochastic lag times and memory at the single cell level.

scholarly journals High-throughput imaging of mRNA at the single-cell level in human primary immune cells

2020 ◽  
Author(s):  
Manasi Gadkari ◽  
Jing Sun ◽  
Adrian Carcamo ◽  
Hugh Alessi ◽  
Zonghui Hu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Immune Cells ◽  
Single Cells ◽  
Transcript Abundance ◽  
Hybridization Chain Reaction ◽  
Single Cell Level ◽  
Cell Level ◽  
Experimental Conditions ◽  
General Applicability

AbstractMeasurement of gene expression at the single-cell level has led to important advances in the study of transcriptional regulation programs in healthy and disease states. In particular, single-cell gene expression approaches have shed light on the high level of transcriptional heterogeneity of individual cells, both at baseline and in response to experimental or environmental perturbations. We have developed a method for High-Content Imaging (HCI)-based quantification of transcript abundance at the single-cell level in primary human immune cells and have validated its performance under multiple experimental conditions to demonstrate its general applicability. This method, which we abbreviate as hcHCR, combines the high sensitivity of the hybridization chain reaction (HCR) for the visualization of mRNA molecules in single cells, with the speed, scalability, and technical reproducibility of HCI. We first tested eight microscopy-compatible attachment substrates for short-term culture of primary human B cells, T cells, monocytes, or neutrophils. We then miniaturized HCR in a 384-well format and documented the ability of the method to detect increased or decreased transcript abundance at the single-cell level in thousands of cells for each experimental condition by HCI. Furthermore, we demonstrated the feasibility of multiplexing gene expression measurements by simultaneously assaying the abundance of two transcripts per cell, both at baseline and in response to an experimental stimulus. Finally, we tested the robustness of the assay to technical and biological variation. We anticipate that hcHCR will be a suitable and cost-effective assay for low- to medium-throughput chemical, genetic or functional genomic screens in primary human cells, with the possibility of performing personalized screens or screens on cells obtained from patients with a specific disease.

scholarly journals Analysis of Phase-Specific Gene Expression at the Single-Cell Level in the White-Opaque Switching System ofCandida albicans

2001 ◽  
Vol 183 (12) ◽  
pp. 3761-3769 ◽  
Author(s):  
Anja Strauß ◽  
Sonja Michel ◽  
Joachim Morschhäuser
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Reporter Gene ◽  
Single Cells ◽  
Phenotypic Switching ◽  
Specific Gene ◽  
Single Cell Level ◽  
Switching System ◽  
Cell Type ◽  
Cell Level

ABSTRACT The opportunistic fungal pathogen Candida albicanscan switch spontaneously and reversibly between different cell forms, a capacity that may enhance adaptation to different host niches and evasion of host defense mechanisms. Phenotypic switching has been studied intensively for the white-opaque switching system of strain WO-1. To facilitate the molecular analysis of phenotypic switching, we have constructed homozygous ura3 mutants from strain WO-1 by targeted gene deletion. The two URA3 alleles were sequentially inactivated using theMPA R -flipping strategy, which is based on the selection of integrative transformants carrying a mycophenolic acid (MPA) resistance marker that is subsequently deleted again by site-specific, FLP-mediated recombination. To investigate a possible cell type-independent switching in the expression of individual phase-specific genes, two different reporter genes that allowed the analysis of gene expression at the single-cell level were integrated into the genome, using URA3 as a selection marker. Fluorescence microscopic analysis of cells in which aGFP reporter gene was placed under the control of phase-specific promoters demonstrated that the opaque-phase-specificSAP1 gene was detectably expressed only in opaque cells and that the white-phase-specific WH11 gene was detectably expressed only in white cells. WhenMPA R was used as a reporter gene, it conferred an MPA-resistant phenotype on opaque but not white cells in strains expressing it from the SAP1 promoter, which was monitored at the level of single cells by a significantly enlarged size of the corresponding colonies on MPA-containing indicator plates. Similarly, white but not opaque cells became MPA resistant whenMPA R was placed under the control of the WH11 promoter. The analysis of these reporter strains showed that cell type-independent phase variation in the expression of the SAP1 and WH11 genes did not occur at a detectable frequency. The expression of these phase-specific genes of C. albicans in vitro, therefore, is tightly linked to the cell type.

scholarly journals Live-Cell Imaging Tool Optimization To Study Gene Expression Levels and Dynamics in Single Cells of Bacillus cereus

2013 ◽  
Vol 79 (18) ◽  
pp. 5643-5651 ◽  
Author(s):  
Robyn T. Eijlander ◽  
Oscar P. Kuipers
Keyword(s):  
Gene Expression ◽  
Fluorescence Microscopy ◽  
Single Cell ◽  
Fluorescent Protein ◽  
Time Lapse ◽  
Single Cell Level ◽  
Cell Level ◽  
Content Type ◽  
Over Time ◽  
Gene Expression Levels

ABSTRACTSingle-cell methods are a powerful application in microbial research to study the molecular mechanism underlying phenotypic heterogeneity and cell-to-cell variability. Here, we describe the optimization and application of single-cell time-lapse fluorescence microscopy for the food spoilage bacteriumBacillus cereusspecifically. This technique is useful to study cellular development and adaptation, gene expression, protein localization, protein mobility, and cell-to-cell communication over time at the single-cell level. By adjusting existing protocols, we have enabled the visualization of growth and development of singleB. cereuscells within a microcolony over time. Additionally, several different fluorescent reporter proteins were tested in order to select the most suitable green fluorescent protein (GFP) and red fluorescent protein (RFP) candidates for visualization of growth stage- and cell compartment-specific gene expression inB. cereus. With a case study concerningcotDexpression during sporulation, we demonstrate the applicability of time-lapse fluorescence microscopy. It enables the assessment of gene expression levels, dynamics, and heterogeneity at the single-cell level. We show thatcotDis not heterogeneously expressed among cells of a subpopulation. Furthermore, we discourage using plasmid-based reporter fusions for such studies, due to an introduced heterogeneity through copy number differences. This stresses the importance of using single-copy integrated reporter fusions for single-cell studies.

scholarly journals Microfluidic Platforms Designed for Morphological and Photosynthetic Investigations of Chlamydomonas reinhardtii on a Single-Cell Level

Cells ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 285
Author(s):  
Eszter Széles ◽  
Krisztina Nagy ◽  
Ágnes Ábrahám ◽  
Sándor Kovács ◽  
Anna Podmaniczki ◽  
...  
Keyword(s):  
Chlamydomonas Reinhardtii ◽  
Single Cell ◽  
Single Cells ◽  
Fluorescence Induction ◽  
Photochemical Quenching ◽  
Support Surface ◽  
Single Cell Level ◽  
Microfluidic Platforms ◽  
Cell Level ◽  
Non Photochemical Quenching

Chlamydomonas reinhardtii is a model organism of increasing biotechnological importance, yet, the evaluation of its life cycle processes and photosynthesis on a single-cell level is largely unresolved. To facilitate the study of the relationship between morphology and photochemistry, we established microfluidics in combination with chlorophyll a fluorescence induction measurements. We developed two types of microfluidic platforms for single-cell investigations: (i) The traps of the “Tulip” device are suitable for capturing and immobilizing single cells, enabling the assessment of their photosynthesis for several hours without binding to a solid support surface. Using this “Tulip” platform, we performed high-quality non-photochemical quenching measurements and confirmed our earlier results on bulk cultures that non-photochemical quenching is higher in ascorbate-deficient mutants (Crvtc2-1) than in the wild-type. (ii) The traps of the “Pot” device were designed for capturing single cells and allowing the growth of the daughter cells within the traps. Using our most performant “Pot” device, we could demonstrate that the FV/FM parameter, an indicator of photosynthetic efficiency, varies considerably during the cell cycle. Our microfluidic devices, therefore, represent versatile platforms for the simultaneous morphological and photosynthetic investigations of C. reinhardtii on a single-cell level.

scholarly journals Heteroresistance at the Single-Cell Level: Adapting to Antibiotic Stress through a Population-Based Strategy and Growth-Controlled Interphenotypic Coordination

mBio ◽  
2014 ◽  
Vol 5 (1) ◽  
Author(s):  
Xiaorong Wang ◽  
Yu Kang ◽  
Chunxiong Luo ◽  
Tong Zhao ◽  
Lin Liu ◽  
...  
Keyword(s):  
Growth Rate ◽  
Single Cell ◽  
Task Allocation ◽  
Bacterial Population ◽  
Population Based ◽  
Phenotypic Heterogeneity ◽  
Single Cell Level ◽  
Bacterial Survival ◽  
Cell Level ◽  
Resistant Cells

ABSTRACT Heteroresistance refers to phenotypic heterogeneity of microbial clonal populations under antibiotic stress, and it has been thought to be an allocation of a subset of “resistant” cells for surviving in higher concentrations of antibiotic. The assumption fits the so-called bet-hedging strategy, where a bacterial population “hedges” its “bet” on different phenotypes to be selected by unpredicted environment stresses. To test this hypothesis, we constructed a heteroresistance model by introducing a bla CTX-M-14 gene (coding for a cephalosporin hydrolase) into a sensitive Escherichia coli strain. We confirmed heteroresistance in this clone and that a subset of the cells expressed more hydrolase and formed more colonies in the presence of ceftriaxone (exhibited stronger “resistance”). However, subsequent single-cell-level investigation by using a microfluidic device showed that a subset of cells with a distinguishable phenotype of slowed growth and intensified hydrolase expression emerged, and they were not positively selected but increased their proportion in the population with ascending antibiotic concentrations. Therefore, heteroresistance—the gradually decreased colony-forming capability in the presence of antibiotic—was a result of a decreased growth rate rather than of selection for resistant cells. Using a mock strain without the resistance gene, we further demonstrated the existence of two nested growth-centric feedback loops that control the expression of the hydrolase and maximize population growth in various antibiotic concentrations. In conclusion, phenotypic heterogeneity is a population-based strategy beneficial for bacterial survival and propagation through task allocation and interphenotypic collaboration, and the growth rate provides a critical control for the expression of stress-related genes and an essential mechanism in responding to environmental stresses. IMPORTANCE Heteroresistance is essentially phenotypic heterogeneity, where a population-based strategy is thought to be at work, being assumed to be variable cell-to-cell resistance to be selected under antibiotic stress. Exact mechanisms of heteroresistance and its roles in adaptation to antibiotic stress have yet to be fully understood at the molecular and single-cell levels. In our study, we have not been able to detect any apparent subset of “resistant” cells selected by antibiotics; on the contrary, cell populations differentiate into phenotypic subsets with variable growth statuses and hydrolase expression. The growth rate appears to be sensitive to stress intensity and plays a key role in controlling hydrolase expression at both the bulk population and single-cell levels. We have shown here, for the first time, that phenotypic heterogeneity can be beneficial to a growing bacterial population through task allocation and interphenotypic collaboration other than partitioning cells into different categories of selective advantage.

Unmasking cellular response of a bloom-forming alga to virus infection by resolving expression profiling at a single-cell level

2017 ◽  
Author(s):  
Shilo Rosenwasser ◽  
Miguel J. Frada ◽  
David Pilzer ◽  
Ron Rotkopf ◽  
Assaf Vardi
Keyword(s):  
Gene Expression ◽  
Viral Infection ◽  
Single Cell ◽  
Host Defense ◽  
Host Response ◽  
Expression Profiles ◽  
Life Cycles ◽  
Viral Gene ◽  
Single Cell Level ◽  
Cell Level

AbstractMarine viruses are major evolutionary and biogeochemical drivers of microbial life in the ocean. Host response to viral infection typically includes virus-induced rewiring of metabolic network to supply essential building blocks for viral assembly, as opposed to activation of anti-viral host defense. Nevertheless, there is a major bottleneck to accurately discern between viral hijacking strategies and host defense responses when averaging bulk population response. Here we use Emiliania huxleyi, a bloom-forming alga and its specific virus (EhV), as one of the most ecologically important host-virus model system in the ocean. Using automatic microfluidic setup to capture individual algal cells, we quantified host and virus gene expression on a single-cell resolution during the course of infection. We revealed high heterogeneity in viral gene expression among individual cells. Simultaneous measurements of expression profiles of host and virus genes at a single-cell level allowed mapping of infected cells into newly defined infection states and uncover a yet unrecognized early phase in host response that occurs prior to viral expression. Intriguingly, resistant cells emerged during viral infection, showed unique expression profiles of metabolic genes which can provide the basis for discerning between viral resistant and sensitive cells within heterogeneous populations in the marine environment. We propose that resolving host-virus arms race at a single-cell level will provide important mechanistic insights into viral life cycles and will uncover host defense strategies.

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