Quantitative Single Cell Research Articles

The spinal muscular atrophy gene product regulates actin dynamics.

Spinal Muscular Atrophy (SMA) is a neuromuscular disease caused by low levels of the Survival of Motoneuron (SMN) protein. SMN interacts with and regulates the actin-binding protein profilin2a, thereby influencing actin dynamics. Dysfunctional actin dynamics caused by SMN loss disrupts neurite outgrowth, axonal pathfinding, and formation of functional synapses in neurons. Whether the SMN protein directly interacts with and regulates filamentous (F-) and monomeric globular (G-) actin is still elusive. In a quantitative single cell approach, we show that SMN loss leads to dysregulated F-/G-actin fractions. Furthermore, quantitative assessment of cell morphology suggests an F-actin organizational defect. Interestingly, this is mediated by an interaction of SMN with G- and F-actin. In co-immunoprecipitation, in-vitro pulldown and co-localization assays, we elucidated that this interaction is independent of the SMN-profilin2a interaction. Therefore, we suggest two populations being relevant for functional actin dynamics in healthy neurons: SMN-profilin2a-actin and SMN-actin. Additionally, those two populations may influence each other and therefore regulate binding of SMN to actin. In SMA, we showed a dysregulated co-localization pattern of SMN-actin which could only partially rescued by SMN restoration. However, dysregulation of F-/G-actin fractions was reduced by SMN restoration. Taken together, our results suggest a novel molecular function of SMN in binding to actin independent from SMN-profilin2a interaction.

Cell scientist to watch – Alexis Barr

ABSTRACT Alexis Barr is a Cancer Research UK (CRUK) Career Development Fellow at the Institute of Clinical Sciences (ICS), Imperial College London and Medical Research Council (MRC) Investigator at the MRC Laboratory of Medical Sciences (LMS). Alexis graduated in Natural Sciences from the University of Cambridge, UK, and then undertook a PhD at the CRUK Cambridge Institute, where she studied the role of centrosomes in mitotic spindle assembly under the supervision of Fanni Gergely. For her postdoctoral studies, Alexis moved to the Institute of Cancer Research in London, where she joined the team of Chris Bakal and was awarded a Pathway to Independence Fellowship. There, she investigated the mechanisms that control cell cycle entry using quantitative single-cell imaging. In 2018, Alexis was awarded a CRUK Career Development Fellowship to start her own research group at the ICS, to research the control of cell cycle entry and exit and how these pathways can be manipulated to treat cancer. She was awarded the 2024 Women in Cell Biology Early Career Medal by the British Society for Cell Biology (BSCB). We spoke with Alexis over Zoom to find out more about her career, her advice on collaborative research and her approaches to scientific mentorship.

Targeting valine catabolism to inhibit metabolic reprogramming in prostate cancer

Metabolic reprogramming and energetic rewiring are hallmarks of cancer that fuel disease progression and facilitate therapy evasion. The remodelling of oxidative phosphorylation and enhanced lipogenesis have previously been characterised as key metabolic features of prostate cancer (PCa). Recently, succinate-dependent mitochondrial reprogramming was identified in high-grade prostate tumours, as well as upregulation of the enzymes associated with branched-chain amino acid (BCAA) catabolism. In this study, we hypothesised that the degradation of the BCAAs, particularly valine, may play a critical role in anapleurotic refuelling of the mitochondrial succinate pool, as well as the maintenance of intracellular lipid metabolism. Through the suppression of BCAA availability, we report significantly reduced lipid content, strongly indicating that BCAAs are important lipogenic fuels in PCa. This work also uncovered a novel compensatory mechanism, whereby fatty acid uptake is increased in response to extracellular valine deprivation. Inhibition of valine degradation via suppression of 3-hydroxyisobutyryl-CoA hydrolase (HIBCH) resulted in a selective reduction of malignant prostate cell proliferation, decreased intracellular succinate and impaired cellular respiration. In combination with a comprehensive multi-omic investigation that incorporates next-generation sequencing, metabolomics, and high-content quantitative single-cell imaging, our work highlights a novel therapeutic target for selective inhibition of metabolic reprogramming in PCa.

Multiplex profiling of developmental cis-regulatory elements with quantitative single-cell expression reporters.

The inability to scalably and precisely measure the activity of developmental cis-regulatory elements (CREs) in multicellular systems is a bottleneck in genomics. Here we develop a dual RNA cassette that decouples the detection and quantification tasks inherent to multiplex single-cell reporter assays. The resulting measurement of reporter expression is accurate over multiple orders of magnitude, with a precision approaching the limit set by Poisson counting noise. Together with RNA barcode stabilization via circularization, these scalable single-cell quantitative expression reporters provide high-contrast readouts, analogous to classic in situ assays but entirely from sequencing. Screening >200 regions of accessible chromatin in a multicellular in vitro model of early mammalian development, we identify 13 (8 previously uncharacterized) autonomous and cell-type-specific developmental CREs. We further demonstrate that chimeric CRE pairs generate cognate two-cell-type activity profiles and assess gain- and loss-of-function multicellular expression phenotypes from CRE variants with perturbed transcription factor binding sites. Single-cell quantitative expression reporters can be applied in developmental and multicellular systems to quantitatively characterize native, perturbed and synthetic CREs at scale, with high sensitivity and at single-cell resolution.

Transcriptional repression of the oncofetal LIN28B gene by the transcription factor SOX6

The identification of regulatory networks contributing to fetal/adult gene expression switches is a major challenge in developmental biology and key to understand the aberrant proliferation of cancer cells, which often reactivate fetal oncogenes. One key example is represented by the developmental gene LIN28B, whose aberrant reactivation in adult tissues promotes tumor initiation and progression. Despite the prominent role of LIN28B in development and cancer, the mechanisms of its transcriptional regulation are largely unknown. Here, by using quantitative RT-PCR and single cell RNA sequencing data, we show that in erythropoiesis the expression of the transcription factor SOX6 matched a sharp decline of LIN28B mRNA during human embryo/fetal to adult globin switching. SOX6 overexpression repressed LIN28B not only in a panel of fetal-like erythroid cells (K562, HEL and HUDEP1; ≈92% p < 0.0001, 54% p = 0.0009 and ≈60% p < 0.0001 reduction, respectively), but also in hepatoblastoma HepG2 and neuroblastoma SH-SY5H cells (≈99% p < 0.0001 and ≈59% p < 0.0001 reduction, respectively). SOX6-mediated repression caused downregulation of the LIN28B/Let-7 targets, including MYC and IGF2BP1, and rapidly blocks cell proliferation. Mechanistically, Lin28B repression is accompanied by SOX6 physical binding within its locus, suggesting a direct mechanism of LIN28B downregulation that might contribute to the fetal/adult erythropoietic transition and restrict cancer proliferation.

Brain tissue- and cell type-specific eQTL Mendelian randomization reveals efficacy of FADS1 and FADS2 on cognitive function

Epidemiological studies suggested an association between omega-3 fatty acids and cognitive function. However, the causal role of the fatty acid desaturase (FADS) gene, which play a key role in regulating omega-3 fatty acids biosynthesis, on cognitive function is unclear. Hence, we used two-sample Mendelian randomization (MR) to estimate the gene-specific causal effect of omega-3 fatty acids (N = 114,999) on cognitive function (N = 300,486). Tissue- and cell type-specific effects of FADS1/FADS2 expression on cognitive function were estimated using brain tissue cis-expression quantitative trait loci (cis-eQTL) datasets (GTEx, N ≤ 209; MetaBrain, N ≤ 8,613) and single cell cis-eQTL data (N = 373), respectively. These causal effects were further evaluated in whole blood cis-eQTL data (N ≤ 31,684). A series of sensitivity analyses were conducted to validate MR assumptions. Leave-one-out MR showed a FADS gene-specific effect of omega-3 fatty acids on cognitive function [β = −1.3 × 10−2, 95% confidence interval (CI) (−2.2 × 10−2, −5 × 10−3), P = 2 × 10−3]. Tissue-specific MR showed an effect of increased FADS1 expression in cerebellar hemisphere and FADS2 expression in nucleus accumbens basal ganglia on maintaining cognitive function, while decreased FADS1 expression in nine brain tissues on maintaining cognitive function [colocalization probability (PP.H4) ranged from 71.7% to 100.0%]. Cell type-specific MR showed decreased FADS1/FADS2 expression in oligodendrocyte was associated with maintaining cognitive function (PP.H4 = 82.3%, respectively). Increased FADS1/FADS2 expression in whole blood showed an effect on cognitive function maintenance (PP.H4 = 86.6% and 88.4%, respectively). This study revealed putative causal effect of FADS1/FADS2 expression in brain tissues and blood on cognitive function. These findings provided evidence to prioritize FADS gene as potential target gene for maintenance of cognitive function.

Abstract A089: Quantitative MRI metrics and single cell transcriptome reveal effects of stroma-directed drug and chemotherapy in a GEM model of pancreatic cancer

Abstract Hypothesis: The dense stroma present in pancreatic ductal adenocarcinoma (PDA) harbors a unique tumor microenvironment (TME) that is immune suppressive and underlies the chemo-resistance of PDA. We have evaluated synthetic vitamin D combined with chemoimmunotherapy in a pilot clinical study (NCT03519308). To elucidate the underlying mechanisms of this treatment, we designed a matched study in a genetically engineered mouse model of PDA (KPC mice) to test the hypothesis that synthetic vitamin D enhances the effect of chemotherapy with or without immune checkpoint inhibition. To detect changes in TME, we have integrated diffusion weighted (DW) and dynamic contrast enhanced (DCE) MRI with immunohistochemistry (IHC) and single cell RNA sequencing (scRNAseq). Methods: KPC mice were randomly assigned to one of four groups: 1) Control (untreated); 2) Nab-paclitaxel + gemcitabine + cisplatin (Chemo); 3) Chemo + synthetic vitamin D (calcipotriol, Cal); 4) Chemo + Cal + PD-L1. The treatment lasted for 14 days followed by euthanasia and tumor collection for IHC and scRNAseq. Respiratory motion-robust DW- and DCE-MRI were performed on treatment days 0, 7 and 14. Results: Compared to consistent tumor growth (measured by MRI) in the Control group, both progression and regression were observed in groups 2) - 4), suggesting that the KPC model captured the varied treatment responses observed in the clinic. Capillary perfusion/permeability of the tumor measured by Ktrans (a DCE-MRI metric) was reduced at day 7 in the Chemo group (P&amp;lt;0.05), whereas Chemo+Cal reversed the reduction of Ktrans. Chemo-induced Ktrans reduction was corroborated with a significant reduction of microvascular density by IHC of CD31 compared to the Control. Addition of PD-L1 did not appear to enhance the tumor growth delay by Chemo+Cal. scRNAseq analysis revealed that while Chemo significantly delayed the tumor growth compared to the Control, it increased the portion of mesenchymal cells in the tumor and upregulated epithelial-to-mesenchymal transition (EMT) genes known to resist chemotherapy. In contrast, Chemo+Cal increased the fraction of epithelial cells and downregulated EMT genes compared to Chemo. Trasncriptome analysis of the tumor cells demonstrated that Chemo treatment increased the expression of Fibronectin 1 (FN1), a gene associated with tumor invasiveness, EMT, and metastasis, while lowering the expression of Trefoil Factor Family1 (Tff1), which is related to tumor-suppression and chemosensitivity. Chemo+Cal treatment reversed the expression of both FN1 and Tff1 gene compared to Chemo treatment. Conclusion: Single cell transcriptome analysis provided valuable insights into treatment-induced molecular subtype changes, which may predict future resistance and invasiveness. Our study revealed important mechanisms of calcipotriol that enhance the efficacy of chemotherapy by improving microvascular perfusion and permeability and by reducing chemo-resistance by enriching epithelial cells in PDA tumors. Citation Format: Hoon Choi, Mamta Gupta, Thomas Karasic, Miguel Joaquim, Emma Furth, Stephen Pickup, Cynthia Clendenin, Hee Kwon Song, Yong Fan, Jeffrey Duda, James Gee, Mark Rosen, Peter O’Dwyer, Rong Zhou. Quantitative MRI metrics and single cell transcriptome reveal effects of stroma-directed drug and chemotherapy in a GEM model of pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr A089.

Prediction of mechanistic subtypes of Parkinson’s using patient-derived stem cell models

Parkinson’s disease is a common, incurable neurodegenerative disorder that is clinically heterogeneous: it is likely that different cellular mechanisms drive the pathology in different individuals. So far it has not been possible to define the cellular mechanism underlying the neurodegenerative disease in life. We generated a machine learning-based model that can simultaneously predict the presence of disease and its primary mechanistic subtype in human neurons. We used stem cell technology to derive control or patient-derived neurons, and generated different disease subtypes through chemical induction or the presence of mutation. Multidimensional fluorescent labelling of organelles was performed in healthy control neurons and in four different disease subtypes, and both the quantitative single-cell fluorescence features and the images were used to independently train a series of classifiers to build deep neural networks. Quantitative cellular profile-based classifiers achieve an accuracy of 82%, whereas image-based deep neural networks predict control and four distinct disease subtypes with an accuracy of 95%. The machine learning-trained classifiers achieve their accuracy across all subtypes, using the organellar features of the mitochondria with the additional contribution of the lysosomes, confirming the biological importance of these pathways in Parkinson’s. Altogether, we show that machine learning approaches applied to patient-derived cells are highly accurate at predicting disease subtypes, providing proof of concept that this approach may enable mechanistic stratification and precision medicine approaches in the future.

Toward Normalization of Quantitative Single Cell ICP-MS Experiments

Single-cell ICP-MS was used to study the uptake and apoptotic status of nanoplatinum (IV) treated cells, specifically selenized yeast, and the question of using commercialized reference material to validate single cell ICP-MS analysis is addressed.

Surveying the global landscape of post-transcriptional regulators

Numerous proteins regulate gene expression by modulating mRNA translation and decay. To uncover the full scope of these post-transcriptional regulators, we conducted an unbiased survey that quantifies regulatory activity across the budding yeast proteome and delineates the protein domains responsible for these effects. Our approach couples a tethered function assay with quantitative single-cell fluorescence measurements to analyze ~50,000 protein fragments and determine their effects on a tethered mRNA. We characterize hundreds of strong regulators, which are enriched for canonical and unconventional mRNA-binding proteins. Regulatory activity typically maps outside the RNA-binding domains themselves, highlighting a modular architecture that separates mRNA targeting from post-transcriptional regulation. Activity often aligns with intrinsically disordered regions that can interact with other proteins, even in core mRNA translation and degradation factors. Our results thus reveal networks of interacting proteins that control mRNA fate and illuminate the molecular basis for post-transcriptional gene regulation.

Reliable quantification of citrate isomers and isobars with direct-infusion tandem mass spectrometry

Direct-infusion tandem mass spectrometry (DI-MS/MS) is an excellent tool for large cohort high-throughput quantitative metabolomics, MS imaging and single cell studies but incapable of discriminating isomers/isobars with similar MS spectral features. With experimental and density-functional theory (DFT) approaches, here, we comprehensively investigated the fragmentation pathways and characteristics of differential ion-mobility spectrometry (DMS) for three citrate isomers (citrate, isocitrate, glucaro-1,4-lactone) and an isobar (quinate) co-existing in biological sample such as urine. Results showed that all these compounds gave better MS spectra in negative-ion mode than positive-ion one and had numerous fragment ions under collision-induced dissociation (CID) with sequential losses of H2O and CO2. All observed fragment ions were assignable by combining experimental with DFT calculation results. A DI-DMS-MS/MS method was then developed to simultaneously quantify these four isomers/isobars with m/z 191–87 (CoV, −5.5 V), 191–73 (CoV, −3.5 V), 191–85 (CoV, −29.5 V) and m/z 191–93 (CoV, −41.5 V) for citrate, isocitrate, glucaro-1,4-lactone and quinate, respectively. The low limit-of-quantification was below 5.5 nM whilst accuracy was above 94% for all above compounds. The urinary concentrations of them in human and C57BL/6 mouse samples were further quantified showing clear inter-individual and inter-species level differences with significantly higher levels of isocitrate, glucaro-1,4-lactone and quinate in human urine samples than mouse ones. This provides an approach to understand the detailed fragmentation pathways for organic isomers/isobars and a high-throughput MS strategy to quantify them in complex mixtures for metabolomics, lipidomics, foodomics and exposomics especially when chromatographic separations are not useable.

Cell morphology as a biological fingerprint of chondrocyte phenotype in control and inflammatory conditions.

Little is known how inflammatory processes quantitatively affect chondrocyte morphology and how single cell morphometric data could be used as a biological fingerprint of phenotype. We investigated whether trainable high-throughput quantitative single cell morphology profiling combined with population-based gene expression analysis can be used to identify biological fingerprints that are discriminatory of control vs. inflammatory phenotypes. The shape of a large number of chondrocytes isolated from bovine healthy and human osteoarthritic (OA) cartilages was quantified under control and inflammatory (IL-1β) conditions using a trainable image analysis technique measuring a panel of cell shape descriptors (area, length, width, circularity, aspect ratio, roundness, solidity). The expression profiles of phenotypically relevant markers were quantified by ddPCR. Statistical analysis, multivariate data exploration, and projection-based modelling were used for identifying specific morphological fingerprints indicative of phenotype. Cell morphology was sensitive to both cell density and IL-1β. In both cell types, all shape descriptors correlated with expression of extracellular matrix (ECM)- and inflammatory-regulating genes. A hierarchical clustered image map revealed that individual samples sometimes responded differently in control or IL-1β conditions than the overall population. Despite these variances, discriminative projection-based modeling revealed distinct morphological fingerprints that discriminated between control and inflammatory chondrocyte phenotypes: the most essential morphological characteristics attributable to non-treated control cells was a higher cell aspect ratio in healthy bovine chondrocytes and roundness in OA human chondrocytes. In contrast, a higher circularity and width in healthy bovine chondrocytes and length and area in OA human chondrocytes indicated an inflammatory (IL-1β) phenotype. When comparing the two species/health conditions, bovine healthy and human OA chondrocytes exhibited comparable IL-1β-induced morphologies in roundness, a widely recognized marker of chondrocyte phenotype, and aspect ratio. Overall, cell morphology can be used as a biological fingerprint for describing chondrocyte phenotype. Quantitative single cell morphometry in conjunction with advanced methods for multivariate data analysis allows identifying morphological fingerprints that can discriminate between control and inflammatory chondrocyte phenotypes. This approach could be used to assess how culture conditions, inflammatory mediators, and therapeutic modulators regulate cell phenotype and function.

A MATQ-seq-Based Protocol for Single-Cell RNA-seq in Bacteria.

Microbes exhibit an extraordinary capacity to adapt their physiology to different environments using phenotypic heterogeneity. However, the majority of gene regulation studies are conducted in bulk reflecting only averaged gene expression levels across millions of cells. Bacterial single-cell RNA-seq (scRNA-seq) can overcome this by enabling whole transcriptome and unbiased analysis of microbes at the single-cell level. Here, we describe a detailed workflow of single-cell RNA-seq based on the multiple annealing and dC-tailing-based quantitative single-cell RNA-seq (MATQ-seq) protocol. Following adjustments to the original eukaryotic protocol, the workflow was applied to two major human pathogens Salmonella enterica serovar Typhimurium (henceforthSalmonella) and Pseudomonas aeruginosa (henceforthPseudomonas). The development of bacterial scRNA-seq protocols offers promising avenues to explore the molecular programs underlying phenotypic heterogeneity on the transcriptome level in different settings such as infection, persistence, ecology, and biofilms.

Abstract IA019: Ectopic levels of low-complexity domain interactions repress endogenous oncogenic transcription

Abstract Mammalian transcription factors (TFs) ubiquitously contain intrinsically disordered low-complexity domains (LCDs) that perform transactivation functions. Recent studies have shown that dynamic, multivalent, and selective interactions between TF LCDs play an essential role in transactivation, but how such interactions mediate gene transcription remains unclear. It has been proposed that liquid-liquid phase separation (LLPS) of TFs driven by extensive LCD-LCD interactions is the mechanism underlying transactivation. Here, we investigate how tuning the level and localization of LCD-LCD interactions in vivo affects transcription of endogenous human genes. By quantitative single-cell imaging, we reveal that efficient gene activation by the oncogenic TF EWS/FLI1 requires narrow optimum of LCD-LCD interactions at its target genes associated with GGAA microsatellites. Increasing LCD-LCD interactions toward putative LLPS represses transcription of these genes in Ewing sarcoma cells. Likewise, ectopically creating LCD-LCD interactions to sequester EWS/FLI1 into a well-documented LLPS compartment, the nucleolus, represses EWS/FLI1 -driven transcription and inhibits malignant transformation of Ewing sarcoma. In addition, using live-cell single-molecule imaging, we show that a TF diffuses significantly more slowly in the nucleolus than in the nucleoplasm, demonstrating an important impact of LLPS on TF dynamic behaviors and single-molecule diffusion measurement as an effective approach to diagnose LLPS in vivo. Our findings show how altering the balance of LCD-LCD interactions can influence transcriptional regulation and suggest a potential therapeutic strategy for targeting disease-causing TFs. Citation Format: Shasha Chong. Ectopic levels of low-complexity domain interactions repress endogenous oncogenic transcription. [abstract]. In: Proceedings of the AACR Special Conference: Cancer Epigenomics; 2022 Oct 6-8; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2022;82(23 Suppl_2):Abstract nr IA019.

Trans-cellular tunnels induced by the fungal pathogen Candida albicans facilitate invasion through successive epithelial cells without host damage

The opportunistic fungal pathogen Candida albicans is normally commensal, residing in the mucosa of most healthy individuals. In susceptible hosts, its filamentous hyphal form can invade epithelial layers leading to superficial or severe systemic infection. Although invasion is mainly intracellular, it causes no apparent damage to host cells at early stages of infection. Here, we investigate C. albicans invasion in vitro using live-cell imaging and the damage-sensitive reporter galectin-3. Quantitative single cell analysis shows that invasion can result in host membrane breaching at different stages and host cell death, or in traversal of host cells without membrane breaching. Membrane labelling and three-dimensional ‘volume’ electron microscopy reveal that hyphae can traverse several host cells within trans-cellular tunnels that are progressively remodelled and may undergo ‘inflations’ linked to host glycogen stores. Thus, C. albicans early invasion of epithelial tissues can lead to either host membrane breaching or trans-cellular tunnelling.

Tuning levels of low-complexity domain interactions to modulate endogenous oncogenic transcription

Gene activation by mammalian transcription factors (TFs) requires multivalent interactions of their low-complexity domains (LCDs), but how such interactions regulate transcription remains unclear. It has been proposed that extensive LCD-LCD interactions culminating in liquid-liquid phase separation (LLPS) of TFs is the dominant mechanism underlying transactivation. Here, we investigated how tuning the amount and localization of LCD-LCD interactions invivo affects transcription of endogenous human genes. Quantitative single-cell and single-molecule imaging reveals that the oncogenic TF EWS::FLI1 requires a narrow optimum of LCD-LCD interactions to activate its target genes associated with GGAA microsatellites. Increasing LCD-LCD interactions toward putative LLPS represses transcription of these genes in patient-derived cells. Likewise, ectopically creating LCD-LCD interactions to sequester EWS::FLI1 into a well-documented LLPS compartment, the nucleolus, inhibits EWS::FLI1-driven transcription and oncogenic transformation. Our findings show how altering the balance of LCD-LCD interactions can influence transcriptional regulation and suggest a potential therapeutic strategy for targeting disease-causing TFs.

Single cell imaging-based chromatin biomarkers for tumor progression

Tumour progression within the tissue microenvironment is accompanied by complex biomechanical alterations of the extracellular environment. While histopathology images provide robust biochemical markers for tumor progression in clinical settings, a quantitative single cell score using nuclear morphology and chromatin organization integrated with the long range mechanical coupling within the tumor microenvironment is missing. We propose that the spatial chromatin organization in individual nuclei characterises the cell state and their alterations during tumor progression. In this paper, we first built an image analysis pipeline and implemented it to classify nuclei from patient derived breast tissue biopsies of various cancer stages based on their nuclear and chromatin features. Replacing H&E with DNA binding dyes such as Hoescht stained tissue biopsies, we improved the classification accuracy. Using the nuclear morphology and chromatin organization features, we constructed a pseudo-time model to identify the chromatin state changes that occur during tumour progression. This enabled us to build a single-cell mechano-genomic score that characterises the cell state during tumor progression from a normal to a metastatic state. To gain further insights into the alterations in the local tissue microenvironments, we also used the nuclear orientations to identify spatial neighbourhoods that have been posited to drive tumor progression. Collectively, we demonstrate that image-based single cell chromatin and nuclear features are important single cell biomarkers for phenotypic mapping of tumor progression.

Asymmetric organelle inheritance predicts human blood stem cell fate

AbstractUnderstanding human hematopoietic stem cell fate control is important for its improved therapeutic manipulation. Asymmetric cell division, the asymmetric inheritance of factors during division instructing future daughter cell fates, was recently described in mouse blood stem cells. In human blood stem cells, the possible existence of asymmetric cell division remained unclear because of technical challenges in its direct observation. Here, we use long-term quantitative single-cell imaging to show that lysosomes and active mitochondria are asymmetrically inherited in human blood stem cells and that their inheritance is a coordinated, nonrandom process. Furthermore, multiple additional organelles, including autophagosomes, mitophagosomes, autolysosomes, and recycling endosomes, show preferential asymmetric cosegregation with lysosomes. Importantly, asymmetric lysosomal inheritance predicts future asymmetric daughter cell-cycle length, differentiation, and stem cell marker expression, whereas asymmetric inheritance of active mitochondria correlates with daughter metabolic activity. Hence, human hematopoietic stem cell fates are regulated by asymmetric cell division, with both mechanistic evolutionary conservation and differences to the mouse system.

Volume 99A, Number 6, June 2021 Cover Image

AbstractReconstructing the threedimensional interrelation of nerve cells in the brain from two dimensional images improves our understanding of their ways of communication. This is just one example of Quantitative Singlecell Optical Technologies aiding cellular analysis compiled in this months' special issue. (read more … cite here the guest editorial)

Mechanism and ultrasensitivity in Hedgehog signaling revealed by Patched1 disease mutations

Hedgehog signaling is fundamental in animal embryogenesis, and its dysregulation causes cancer and birth defects. The pathway is triggered when the Hedgehog ligand inhibits the Patched1 membrane receptor, relieving repression that Patched1 exerts on the GPCR-like protein Smoothened. While it is clear how loss-of-function Patched1 mutations cause hyperactive Hedgehog signaling and cancer, how other Patched1 mutations inhibit signaling remains unknown. Here, we develop quantitative single-cell functional assays for Patched1, which, together with mathematical modeling, indicate that Patched1 inhibits Smoothened enzymatically, operating in an ultrasensitive regime. Based on this analysis, we propose that Patched1 functions in cilia, catalyzing Smoothened deactivation by removing cholesterol bound to its extracellular, cysteine-rich domain. Patched1 mutants associated with holoprosencephaly dampen signaling by three mechanisms: reduced affinity for Hedgehog ligand, elevated catalytic activity, or elevated affinity for the Smoothened substrate. Our results clarify the enigmatic mechanism of Patched1 and explain how Patched1 mutations lead to birth defects.