scholarly journals PhenoChip: A single-cell phenomic platform for high-throughput photophysiological analyses of microalgae

2020 ◽  
Vol 6 (36) ◽  
pp. eabb2754
Author(s):  
Lars Behrendt ◽  
M. Mehdi Salek ◽  
Erik L. Trampe ◽  
Vicente I. Fernandez ◽  
Kang Soo Lee ◽  
...  
Keyword(s):  
Single Cell ◽  
Aquatic Ecosystems ◽  
Single Cells ◽  
Thermal Sensitivity ◽  
Photosynthetic Performance ◽  
Cell Level ◽  
Chemical Treatments ◽  
Photosynthetic Microorganisms ◽  
Systematic Selection ◽  
Selection Of

Photosynthetic microorganisms are key players in aquatic ecosystems with strong potential for bioenergy production, yet their systematic selection at the single-cell level for improved productivity or stress resilience (“phenotyping”) has remained largely inaccessible. To facilitate the phenotyping of microalgae and cyanobacteria, we developed “PhenoChip,” a platform for the multiparametric photophysiological characterization and selection of unicellular phenotypes under user-controlled physicochemical conditions. We used PhenoChip to expose single cells of the coral symbiont Symbiodinium to thermal and chemical treatments and monitor single-cell photophysiology via chlorophyll fluorometry. This revealed strain-specific thermal sensitivity thresholds and distinct pH optima for photosynthetic performance, and permitted the identification of single cells with elevated resilience toward rising temperature. Optical expulsion technology was used to collect single cells from PhenoChip, and their propagation revealed indications of transgenerational preservation of photosynthetic phenotypes. PhenoChip represents a versatile platform for the phenotyping of photosynthetic unicells relevant to biotechnology, ecotoxicology, and assisted evolution.

scholarly journals BRIE2: computational identification of splicing phenotypes from single-cell transcriptomic experiments

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yuanhua Huang ◽  
Guido Sanguinetti
Keyword(s):  
Alternative Splicing ◽  
Single Cell ◽  
Rna Splicing ◽  
Single Cells ◽  
Computational Method ◽  
Cell Level ◽  
Transcriptomic Data ◽  
Alternative Transcripts ◽  
Computational Identification ◽  
Selection Of

AbstractRNA splicing is an important driver of heterogeneity in single cells through the expression of alternative transcripts and as a determinant of transcriptional kinetics. However, the intrinsic coverage limitations of scRNA-seq technologies make it challenging to associate specific splicing events to cell-level phenotypes. BRIE2 is a scalable computational method that resolves these issues by regressing single-cell transcriptomic data against cell-level features. We show that BRIE2 effectively identifies differential disease-associated alternative splicing events and allows a principled selection of genes that capture heterogeneity in transcriptional kinetics and improve RNA velocity analyses, enabling the identification of splicing phenotypes associated with biological changes.

scholarly journals SUGAR-seq enables simultaneous detection of glycans, epitopes, and the transcriptome in single cells

2021 ◽  
Vol 7 (8) ◽  
pp. eabe3610
Author(s):  
Conor J. Kearney ◽  
Stephin J. Vervoort ◽  
Kelly M. Ramsbottom ◽  
Izabela Todorovski ◽  
Emily J. Lelliott ◽  
...  
Keyword(s):  
Single Cell ◽  
Posttranslational Modification ◽  
Cellular Differentiation ◽  
Single Cells ◽  
Simultaneous Detection ◽  
Surface Protein ◽  
Rna Seq ◽  
Cell Level ◽  
Simultaneous Integration ◽  
Unique Surface

Multimodal single-cell RNA sequencing enables the precise mapping of transcriptional and phenotypic features of cellular differentiation states but does not allow for simultaneous integration of critical posttranslational modification data. Here, we describe SUrface-protein Glycan And RNA-seq (SUGAR-seq), a method that enables detection and analysis of N-linked glycosylation, extracellular epitopes, and the transcriptome at the single-cell level. Integrated SUGAR-seq and glycoproteome analysis identified tumor-infiltrating T cells with unique surface glycan properties that report their epigenetic and functional state.

scholarly journals Single-Cell and Bulk Fluorescence Excitation Signatures of Seven Phytoplankton Species During Nitrogen Depletion and Resupply

2018 ◽  
Vol 73 (3) ◽  
pp. 304-312 ◽  
Author(s):  
Stefan T. Faulkner ◽  
Cameron M. Rekully ◽  
Eric M. Lachenmyer ◽  
Ergun Kara ◽  
Tammi L. Richardson ◽  
...  
Keyword(s):  
Single Cell ◽  
Aquatic Ecosystems ◽  
Single Cells ◽  
Vital Role ◽  
Phytoplankton Species ◽  
Nitrogen Depletion ◽  
Excitation Spectra ◽  
Fluorescence Excitation ◽  
Fluorescence Excitation Spectra ◽  
Taxonomic Groups

Phytoplankton play a vital role as primary producers in aquatic ecosystems. One common approach to classifying phytoplankton is fluorescence excitation spectroscopy, which leverages the variation in types and concentrations of pigments among different phytoplankton taxonomic groups. Here, we used a fluorescence imaging photometer to measure excitation ratios (“signatures”) of single cells and bulk cultures of seven differently pigmented phytoplankton species as they progressed from nitrogen N-replete to N-depleted conditions. Our objective was to determine whether N depletion alters the fluorescence excitation signature of each species and, if so, how quickly they recover when N (as nitrate) was resupplied, because these factors affect our ability to classify the species correctly. Of the seven species studied, only Proteomonas sulcata, a marine cryptophyte, showed measurable changes in single-cell fluorescence excitation ratios and bulk fluorescence excitation spectra. These changes were likely due to decreases in the cellular concentration of phycoerythrin, a N-rich pigment, as N became scarce. Within 3 h of resupply of N, fluorescence signatures began returning to pre-depletion values and were indistinguishable from N-replete cells by 80 h after resupply. These data suggest that our classification approach is robust for non-PE containing phytoplankton. PE-containing phytoplankton might exhibit systematic changes in their signatures depending on their level of N depletion, but this could be detected and the phytoplankton re-classified following a few hours of incubation in N replete conditions.

scholarly journals High Throughput Immunophenotyping and Expression Profiling at Single Cell Level Reveal BCR-ABL1 Dependent Surface Markers of Chronic Myeloid Leukemia Stem Cells

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 2920-2920
Author(s):  
Marianna Romzova ◽  
Dagmar Smitalova ◽  
Peter Taus ◽  
Jiri Mayer ◽  
Martin Culen
Keyword(s):  
Stem Cells ◽  
Single Cell ◽  
Expression Profiling ◽  
Myeloid Leukemia ◽  
Single Cells ◽  
Transcript Level ◽  
Surface Expression ◽  
Surface Markers ◽  
Cell Level ◽  
Tki Treatment

BACKGROUND: Bcr-abl1 oncogene targeted treatment with tyrosine kinase inhibitors (TKI) showed an impressive efficacy against proliferating chronic myeloid leukemia (CML) cells. However, rapid relapses in more than half of CML patients after discontinuation of the treatment suggest a presence of quiescent leukemic stem cells inherently resistant to BCR-ABL1 inhibition. Understanding the heterogeneity of CML stem cell compartment is crucial for preventing the treatment failure. Specificity of already established leukemic stem cell (LSC) markers has been tested mainly in bulk CD34+CD38- populations at diagnosis. Phenotypes and molecular signatures of therapy resistant BCR ABL1 positive stem cells is however yet to be established. AIMS: Identification of BCR-ABL1 dependent LSC markers at single cell level by direct comparison their surface and transcript expression with the levels and the presence of BCR-ABL1 transcript at diagnosis and after administration of TKI treatment. METHODS: Total number of 375 cells were obtained from bone marrow and peripheral blood of 4 chronic phase CML patients. Cells were collected prior any treatment and three months after TKI treatment initiation. Normal bone marrow cells and BCR-ABL1 positive K562 cell line were used as controls. Indexed immuno-phenotyping and sorting of CD34+CD38- single cells was performed using a panel of 11 specific surface markers. Collected single cells were lysed and cDNA was enriched for 11 targets using 22 cycle pre-amplification. Expression profiling was carried on SmartChip real-time PCR system (Takara Bio) detecting following genes: BCR-ABL1, CD26, CD25, IL1-Rap, CD56, CD90, CD93, CD69, KI67, and control genes GUS and HPRT. Unsupervised clustering was performed using principal component analysis (PCA). Correlations were measured by Spearman rank method. RESULTS: At diagnosis, majority of BCR-ABL1+ C34+CD38- stem cells co-express IL1-Rap, CD26, and CD69 on their surface (88%, 82%, 78% overlap). Only 56% of BCR-ABL1+ cells positive for aforementioned markers co-express CD25, 28% CD93 and 16% CD56. The expression of these markers could also be detected in 4-11% of BCR-ABL1- cell, although this could be technical inaccuracy caused by the single cell profiling. CD90 marker did not show any correlation with BCR-ABL1 expression. At transcript level the expression of IL-1Rap, CD26, CD25 and CD56 was observed in 62%, 52% 45% and 16% BCR-ABL1+ cells, and up to 7% of BCR-ABL1- cells. CD69 expression was observed in 90% of BCR-ABL+ cells at transcript level, but also in 71% BCR-ABL- cells. BCR-ABL1 independent expression was observed for cKIT. (60% vs. 76 % in positive vs negative). Finally proliferation marker KI67 was expressed only in 6% of the BCR-ABL1+ cells. PCA analysis divided cells into several distinct clusters with BCR-ABL1 as the main contributor, and cKIT, CD69 and CD26, IL-1RAP as other significant factors. Interestingly BCR-ABL1+ cells collected during TKI treatment showed persistent surface expression of IL-1Rap and CD26, while CD56, CD69 and CD93 were only on part of the BCR-ABL1+ cells. CD25 was significantly deregulated during TKI treatment. CONCLUSION: At diagnosis up to 80% of LSC co-express 3 specific surface markers - IL-1RAP, CD26 and CD69. Variable portion of LSC co-express additional markers such are CD25, CD56 and CD93. During TKI treatment the surface expression of majority of markers is decreased, where the best correlated LSC marker is IL-1Rap, followed by CD26 and CD69. CD56 marker seems to persist in the same proportion of cells while CD25 disappears. cKIT is highly expressed in normal BM and HSC from CML patients, but also in some LSC. CD34+CD38- cells show non-proliferating phenotype. Disclosures Mayer: AOP Orphan Pharmaceuticals AG: Research Funding.

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 Integration of marker-free selection of single cells at a wireless electrode array with parallel fluidic isolation and electrical lysis

2019 ◽  
Vol 10 (5) ◽  
pp. 1506-1513 ◽  
Author(s):  
Min Li ◽  
Robbyn K. Anand
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Electrode Array ◽  
Cell Capture ◽  
Bipolar Electrodes ◽  
Manual Intervention ◽  
Electrical Lysis ◽  
Marker Free ◽  
Selection Of

We present integration of selective single-cell capture at an array of wireless electrodes (bipolar electrodes, BPEs) with transfer into chambers, reagent exchange, fluidic isolation and rapid electrical lysis in a single platform, thus minimizing sample loss and manual intervention steps.

scholarly journals Response of Listeria monocytogenes to Disinfection Stress at the Single-Cell and Population Levels as Monitored by Intracellular pH Measurements and Viable-Cell Counts

2009 ◽  
Vol 75 (13) ◽  
pp. 4550-4556 ◽  
Author(s):  
Vicky G. Kastbjerg ◽  
Dennis S. Nielsen ◽  
Nils Arneborg ◽  
Lone Gram
Keyword(s):  
Listeria Monocytogenes ◽  
Single Cell ◽  
Intracellular Ph ◽  
Bacterial Population ◽  
Single Cells ◽  
Viable Cell ◽  
Population Subdivision ◽  
Single Cell Level ◽  
Cell Level ◽  
Cell Counts

ABSTRACT Listeria monocytogenes has a remarkable ability to survive and persist in food production environments. The purpose of the present study was to determine if cells in a population of L. monocytogenes differ in sensitivity to disinfection agents as this could be a factor explaining persistence of the bacterium. In situ analyses of Listeria monocytogenes single cells were performed during exposure to different concentrations of the disinfectant Incimaxx DES to study a possible population subdivision. Bacterial survival was quantified with plate counting and disinfection stress at the single-cell level by measuring intracellular pH (pHi) over time by fluorescence ratio imaging microscopy. pHi values were initially 7 to 7.5 and decreased in both attached and planktonic L. monocytogenes cells during exposure to sublethal and lethal concentrations of Incimaxx DES. The response of the bacterial population was homogenous; hence, subpopulations were not detected. However, pregrowth with NaCl protected the planktonic bacterial cells during disinfection with Incimaxx (0.0015%) since pHi was higher (6 to 6.5) for the bacterial population pregrown with NaCl than for cells grown without NaCl (pHi 5 to 5.5) (P < 0.05). The protective effect of NaCl was reflected by viable-cell counts at a higher concentration of Incimaxx (0.0031%), where the salt-grown population survived better than the population grown without NaCl (P < 0.05). NaCl protected attached cells through drying but not during disinfection. This study indicates that a population of L. monocytogenes cells, whether planktonic or attached, is homogenous with respect to sensitivity to an acidic disinfectant studied on the single-cell level. Hence a major subpopulation more tolerant to disinfectants, and hence more persistent, does not appear to be present.

scholarly journals Combined Molecular Genetic and Cytogenetic Analysis from Single Cells after Isothermal Whole-Genome Amplification

2011 ◽  
Vol 57 (7) ◽  
pp. 1032-1041 ◽  
Author(s):  
Thomas Kroneis ◽  
Jochen B Geigl ◽  
Amin El-Heliebi ◽  
Martina Auer ◽  
Peter Ulz ◽  
...  
Keyword(s):  
Single Cell ◽  
Tumor Cells ◽  
Whole Genome Amplification ◽  
Single Cells ◽  
Molecular Genetic ◽  
Target Cells ◽  
Whole Genome ◽  
Single Cell Level ◽  
Cell Level ◽  
Genome Amplification

BACKGROUND Analysis of chromosomal aberrations or single-gene disorders from rare fetal cells circulating in the blood of pregnant women requires verification of the cells' genomic identity. We have developed a method enabling multiple analyses at the single-cell level that combines verification of the genomic identity of microchimeric cells with molecular genetic and cytogenetic diagnosis. METHODS We used a model system of peripheral blood mononuclear cells spiked with a colon adenocarcinoma cell line and immunofluorescence staining for cytokeratin in combination with DNA staining with the nuclear dye TO-PRO-3 in a preliminary study to define candidate microchimeric (tumor) cells in Cytospin preparations. After laser microdissection, we performed low-volume on-chip isothermal whole-genome amplification (iWGA) of single and pooled cells. RESULTS DNA fingerprint analysis of iWGA aliquots permitted successful identification of all analyzed candidate microchimeric cell preparations (6 samples of pooled cells, 7 samples of single cells). Sequencing of 3 single-nucleotide polymorphisms was successful at the single-cell level for 20 of 32 allelic loci. Metaphase comparative genomic hybridization (mCGH) with iWGA products of single cells showed the gains and losses known to be present in the genomic DNA of the target cells. CONCLUSIONS This method may be instrumental in cell-based noninvasive prenatal diagnosis. Furthermore, the possibility to perform mCGH with amplified DNA from single cells offers a perspective for the analysis of nonmicrochimeric rare cells exhibiting genomic alterations, such as circulating tumor cells.

scholarly journals Bayesian inference of the gene expression states of single cells from scRNA-seq data

2019 ◽  
Author(s):  
Jérémie Breda ◽  
Mihaela Zavolan ◽  
Erik van Nimwegen
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Single Cells ◽  
Downstream Processing ◽  
Noise Removal ◽  
Rna Seq ◽  
Expression Of Genes ◽  
Normalization Methods ◽  
Quantify Gene Expression ◽  
Selection Of

AbstractIn spite of a large investment in the development of methodologies for analysis of single-cell RNA-seq data, there is still little agreement on how to best normalize such data, i.e. how to quantify gene expression states of single cells from such data. Starting from a few basic requirements such as that inferred expression states should correct for both intrinsic biological fluctuations and measurement noise, and that changes in expression state should be measured in terms of fold-changes rather than changes in absolute levels, we here derive a unique Bayesian procedure for normalizing single-cell RNA-seq data from first principles. Our implementation of this normalization procedure, called Sanity (SAmpling Noise corrected Inference of Transcription activitY), estimates log expression values and associated errors bars directly from raw UMI counts without any tunable parameters.Comparison of Sanity with other recent normalization methods on a selection of scRNA-seq datasets shows that Sanity outperforms other methods on basic downstream processing tasks such as clustering cells into subtypes and identification of differentially expressed genes. More importantly, we show that all other normalization methods present severely distorted pictures of the data. By failing to account for biological and technical Poisson noise, many methods systematically predict the lowest expressed genes to be most variable in expression, whereas in reality these genes provide least evidence of true biological variability. In addition, by confounding noise removal with lower-dimensional representation of the data, many methods introduce strong spurious correlations of expression levels with the total UMI count of each cell as well as spurious co-expression of genes.

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.

Sign in / Sign up

Export Citation Format

Share Document