bims-pideca 2024-05-26 papers

bims-pideca

Biomed News

on Class IA PI3K signalling in development and cancer

Issue of 2024‒05‒26
nineteen papers selected by
Ralitsa Radostinova Madsen, MRC-PPU

Phosphatidylinositol 3,4-bisphosphate: Out of the shadows and into the spotlight.
Rescue of impaired blood-brain barrier in tuberous sclerosis complex patient derived neurovascular unit.
PI 3-Kinase and the Histone Methyl-Transferase KMT2D Collaborate to Induce Arp2/3-Dependent Migration of Mammary Epithelial Cells.
Imaging the dynamics of messenger RNA with a bright and stable green fluorescent RNA.
Cell Competition Eliminates Aneuploid Human Pluripotent Stem Cells.
Fully automated workflow for integrated sample digestion and Evotip loading enabling high-throughput clinical proteomics.
mTORC1-CTLH E3 ligase regulates the degradation of HMG-CoA synthase 1 through the Pro/N-degron pathway.
eIF4A1 enhances LARP1-mediated translational repression during mTORC1 inhibition.
Circadian regulation of macromolecular complex turnover and proteome renewal.
An MSstats workflow for detecting differentially abundant proteins in large-scale data-independent acquisition mass spectrometry experiments with FragPipe processing.
Toward new horizons in cell biology.
Establishing a conceptual framework for holistic cell states and state transitions.
Error modelled gene expression analysis (EMOGEA) provides a superior overview of time course RNA-seq measurements and low count gene expression.
Glucose Regulation of β-Cell KATP Channels: It Is Time for a New Model!
Optical sensor reveals the hidden influence of cell dissociation on adhesion measurements.
Hyperoxia impairs induced pluripotent stem cell-derived endothelial cells and drives an atherosclerosis-like transcriptional phenotype.
In-depth organic mass cytometry reveals differential contents of 3-hydroxybutanoic acid at the single-cell level.
Protecting scientific integrity in an age of generative AI.
Origins of cancer: ain't it just mature cells misbehaving?

Curr Opin Cell Biol. 2024 May 21. pii: S0955-0674(24)00051-6. [Epub ahead of print]88 102372

Phosphatidylinositol 3,4-bisphosphate: Out of the shadows and into the spotlight.

Jayatee Ray, David G Sapp, Gregory D Fairn.

  Phosphoinositide 3-kinases regulate many cellular functions, including migration, growth, proliferation, and cell survival. Early studies equated the inhibition of Class I PI3Ks with loss of; phosphatidylinositol 3,4,5-trisphosphate (PIP3), but over time, it was realised that these; treatments also depleted phosphatidylinositol 3,4-bisphosphate (PI(3,4)P2). In recent years, the; use of better tools and an improved understanding of its metabolism have allowed for the; identification of specific roles of PI(3,4)P2. This includes the production of PI(3,4)P2 and the; activation of its effector Akt2 in response to growth factor signalling. In contrast, a lysosomal pool of PI(3,4)P2 is a negative regulator of mTORC1 during growth factor deprivation. A growing body of literature also demonstrates that PI(3,4)P2 controls many dynamic plasmalemmal processes. The significance of PI(3,4)P2 in cell biology is increasingly evident.

Keywords:  AKT; PI(3,4)P(2); Phosphoinositides; Signal transduction; endocytosis; mTOR; migration

DOI:  https://doi.org/10.1016/j.ceb.2024.102372
J Neurodev Disord. 2024 May 23. 16(1): 27

Rescue of impaired blood-brain barrier in tuberous sclerosis complex patient derived neurovascular unit.

Jacquelyn A Brown, Shannon L Faley, Monika Judge, Patricia Ward, Rebecca A Ihrie, Robert Carson, Laura Armstrong, Mustafa Sahin, John P Wikswo, Kevin C Ess, M Diana Neely.

  BACKGROUND: Tuberous sclerosis complex (TSC) is a multi-system genetic disease that causes benign tumors in the brain and other vital organs. The most debilitating symptoms result from involvement of the central nervous system and lead to a multitude of severe symptoms including seizures, intellectual disability, autism, and behavioral problems. TSC is caused by heterozygous mutations of either the TSC1 or TSC2 gene and dysregulation of mTOR kinase with its multifaceted downstream signaling alterations is central to disease pathogenesis. Although the neurological sequelae of the disease are well established, little is known about how these mutations might affect cellular components and the function of the blood-brain barrier (BBB).METHODS: We generated TSC disease-specific cell models of the BBB by leveraging human induced pluripotent stem cell and microfluidic cell culture technologies.
RESULTS: Using microphysiological systems, we demonstrate that a BBB generated from TSC2 heterozygous mutant cells shows increased permeability. This can be rescued by wild type astrocytes or by treatment with rapamycin, an mTOR kinase inhibitor.
CONCLUSION: Our results demonstrate the utility of microphysiological systems to study human neurological disorders and advance our knowledge of cell lineages contributing to TSC pathogenesis and informs future therapeutics.

Keywords:  Astrocytes; BBB; Human stem cells; Microfluidics; Rapamycin; Tissue chips; mTOR

DOI:  https://doi.org/10.1186/s11689-024-09543-y
Cells. 2024 May 19. pii: 876. [Epub ahead of print]13(10):

PI 3-Kinase and the Histone Methyl-Transferase KMT2D Collaborate to Induce Arp2/3-Dependent Migration of Mammary Epithelial Cells.

Karina D Rysenkova, Julia Gaboriaud, Artem I Fokin, Raphaëlle Toubiana, Alexandre Bense, Camil Mirdass, Mélissa Jin, Minh Chau N Ho, Elizabeth Glading, Sophie Vacher, Laura Courtois, Ivan Bièche, Alexis M Gautreau.

  Breast cancer develops upon sequential acquisition of driver mutations in mammary epithelial cells; however, how these mutations collaborate to transform normal cells remains unclear in most cases. We aimed to reconstitute this process in a particular case. To this end, we combined the activated form of the PI 3-kinase harboring the H1047R mutation with the inactivation of the histone lysine methyl-transferase KMT2D in the non-tumorigenic human mammary epithelial cell line MCF10A. We found that PI 3-kinase activation promoted cell-cycle progression, especially when growth signals were limiting, as well as cell migration, both in a collective monolayer and as single cells. Furthermore, we showed that KMT2D inactivation had relatively little influence on these processes, except for single-cell migration, which KMT2D inactivation promoted in synergy with PI 3-kinase activation. The combination of these two genetic alterations induced expression of the ARPC5L gene that encodes a subunit of the Arp2/3 complex. ARPC5L depletion fully abolished the enhanced migration persistence exhibited by double-mutant cells. Our reconstitution approach in MCF10A has thus revealed both the cell function and the single-cell migration, and the underlying Arp2/3-dependent mechanism, which are synergistically regulated when KMT2D inactivation is combined with the activation of the PI 3-kinase.

Keywords:  Arp2/3; KMT2D; MLL2; MLL4; PIK3CA

DOI:  https://doi.org/10.3390/cells13100876
Nat Chem Biol. 2024 May 23.

Imaging the dynamics of messenger RNA with a bright and stable green fluorescent RNA.

Fangting Zuo, Li Jiang, Ni Su, Yaqiang Zhang, Bingkun Bao, Limei Wang, Yajie Shi, Huimin Yang, Xinyi Huang, Ruilong Li, Qingmei Zeng, Zhengda Chen, Qiuning Lin, Yingping Zhuang, Yuzheng Zhao, Xianjun Chen, Linyong Zhu, Yi Yang.

Fluorescent RNAs (FRs) provide an attractive approach to visualizing RNAs in live cells. Although the color palette of FRs has been greatly expanded recently, a green FR with high cellular brightness and photostability is still highly desired. Here we develop a fluorogenic RNA aptamer, termed Okra, that can bind and activate the fluorophore ligand ACE to emit bright green fluorescence. Okra has an order of magnitude enhanced cellular brightness than currently available green FRs, allowing the robust imaging of messenger RNA in both live bacterial and mammalian cells. We further demonstrate the usefulness of Okra for time-resolved measurements of ACTB mRNA trafficking to stress granules, as well as live-cell dual-color superresolution imaging of RNA in combination with Pepper620, revealing nonuniform and distinct distributions of different RNAs throughout the granules. The favorable properties of Okra make it a versatile tool for the study of RNA dynamics and subcellular localization.

DOI: https://doi.org/10.1038/s41589-024-01629-x
bioRxiv. 2024 May 10. pii: 2024.05.08.593217. [Epub ahead of print]

Cell Competition Eliminates Aneuploid Human Pluripotent Stem Cells.

Amanda Ya, Chenhui Deng, Kristina M Godek.

Human pluripotent stem cells (hPSCs) maintain diploid populations for generations despite a persistently high rate of mitotic errors that cause aneuploidy, or chromosome imbalances. Consequently, to maintain genome stability, aneuploidy must inhibit hPSC proliferation, but the mechanisms are unknown. Here, we surprisingly find that homogeneous aneuploid populations of hPSCs proliferate unlike aneuploid non-transformed somatic cells. Instead, in mosaic populations, cell non-autonomous competition between neighboring diploid and aneuploid hPSCs eliminates less fit aneuploid cells. Aneuploid hPSCs with lower Myc or higher p53 levels relative to diploid neighbors are outcompeted but conversely gain a selective advantage when Myc and p53 relative abundance switches. Thus, although hPSCs frequently missegregate chromosomes and inherently tolerate aneuploidy, Myc- and p53-driven cell competition preserves their genome integrity. These findings have important implications for the use of hPSCs in regenerative medicine and for how diploid human embryos are established despite the prevalence of aneuploidy during early development.

DOI: https://doi.org/10.1101/2024.05.08.593217
Mol Cell Proteomics. 2024 May 20. pii: S1535-9476(24)00080-X. [Epub ahead of print] 100790

Fully automated workflow for integrated sample digestion and Evotip loading enabling high-throughput clinical proteomics.

Anders H Kverneland, Florian Harking, Joel Mario Vej-Nielsen, Magnus Huusfeldt, Dorte B Bekker-Jensen, Inge Marie Svane, Nicolai Bache, Jesper V Olsen.

  Protein identification and quantification is an important tool for biomarker discovery. With the increased sensitivity and speed of modern mass spectrometers, sample-preparation remains a bottleneck for studying large cohorts. To address this issue, we prepared and evaluated a simple and efficient workflow on the Opentrons OT-2 (OT-2) robot that combines sample digestion, cleanup and loading on Evotips in a fully automated manner, allowing the processing of up to 192 samples in 6 hours. Analysis of 192 automated HeLa cell sample preparations consistently identified ∼8000 protein groups and ∼130,000 peptide precursors with an 11.5 minute active LC gradient with the Evosep One and narrow-window data-independent acquisition with the Orbitrap Astral mass spectrometer providing a throughput of 100-samples-per-day. Our results demonstrate a highly sensitive workflow yielding both reproducibility and stability at low sample inputs. The workflow is optimized for minimal sample starting amount to reduce the costs for reagents needed for sample preparation, which is critical when analyzing large biological cohorts. Building on the digesting workflow, we incorporated an automated phosphopeptide enrichment step using magnetic Ti-IMAC beads. This allows for a fully automated proteome and phosphoproteome sample preparation in a single step with high sensitivity. Using the integrated digestion and Evotip loading workflow, we evaluated the effects of cancer immune therapy on the plasma proteome in metastatic melanoma patients.

Keywords:  Mass spectrometry; biomarker discovery; cancer immune therapy; plasma proteomics; workflow automation

DOI:  https://doi.org/10.1016/j.mcpro.2024.100790
Mol Cell. 2024 May 20. pii: S1097-2765(24)00393-9. [Epub ahead of print]

mTORC1-CTLH E3 ligase regulates the degradation of HMG-CoA synthase 1 through the Pro/N-degron pathway.

Sang Ah Yi, Sara Sepic, Brenda A Schulman, Alban Ordureau, Heeseon An.

  Mammalian target of rapamycin (mTOR) senses changes in nutrient status and stimulates the autophagic process to recycle amino acids. However, the impact of nutrient stress on protein degradation beyond autophagic turnover is incompletely understood. We report that several metabolic enzymes are proteasomal targets regulated by mTOR activity based on comparative proteome degradation analysis. In particular, 3-hydroxy-3-methylglutaryl (HMG)-coenzyme A (CoA) synthase 1 (HMGCS1), the initial enzyme in the mevalonate pathway, exhibits the most significant half-life adaptation. Degradation of HMGCS1 is regulated by the C-terminal to LisH (CTLH) E3 ligase through the Pro/N-degron motif. HMGCS1 is ubiquitylated on two C-terminal lysines during mTORC1 inhibition, and efficient degradation of HMGCS1 in cells requires a muskelin adaptor. Importantly, modulating HMGCS1 abundance has a dose-dependent impact on cell proliferation, which is restored by adding a mevalonate intermediate. Overall, our unbiased degradomics study provides new insights into mTORC1 function in cellular metabolism: mTORC1 regulates the stability of limiting metabolic enzymes through the ubiquitin system.

Keywords:  CTLH; GID; HMGCS1; degradomics; mTOR; mTORC1; mevalonate pathway; sterol; ubiquitin; ubiquitin-proteasome system

DOI:  https://doi.org/10.1016/j.molcel.2024.04.026
Nat Struct Mol Biol. 2024 May 21.

eIF4A1 enhances LARP1-mediated translational repression during mTORC1 inhibition.

Yuichi Shichino, Tomokazu Yamaguchi, Kazuhiro Kashiwagi, Mari Mito, Mari Takahashi, Takuhiro Ito, Nicholas T Ingolia, Keiji Kuba, Shintaro Iwasaki.

Eukaryotic translation initiation factor (eIF)4A-a DEAD-box RNA-binding protein-plays an essential role in translation initiation. Recent reports have suggested helicase-dependent and helicase-independent functions for eIF4A, but the multifaceted roles of eIF4A have not been fully explored. Here we show that eIF4A1 enhances translational repression during the inhibition of mechanistic target of rapamycin complex 1 (mTORC1), an essential kinase complex controlling cell proliferation. RNA pulldown followed by sequencing revealed that eIF4A1 preferentially binds to mRNAs containing terminal oligopyrimidine (TOP) motifs, whose translation is rapidly repressed upon mTORC1 inhibition. This selective interaction depends on a La-related RNA-binding protein, LARP1. Ribosome profiling revealed that deletion of EIF4A1 attenuated the translational repression of TOP mRNAs upon mTORC1 inactivation. Moreover, eIF4A1 increases the interaction between TOP mRNAs and LARP1 and, thus, ensures stronger translational repression upon mTORC1 inhibition. Our data show the multimodality of eIF4A1 in modulating protein synthesis through an inhibitory binding partner and provide a unique example of the repressive role of a universal translational activator.

DOI: https://doi.org/10.1038/s41594-024-01321-7
EMBO J. 2024 May 22.

Circadian regulation of macromolecular complex turnover and proteome renewal.

Estere Seinkmane, Anna Edmondson, Sew Y Peak-Chew, Aiwei Zeng, Nina M Rzechorzek, Nathan R James, James West, Jack Munns, David Cs Wong, Andrew D Beale, John S O'Neill.

  Although costly to maintain, protein homeostasis is indispensable for normal cellular function and long-term health. In mammalian cells and tissues, daily variation in global protein synthesis has been observed, but its utility and consequences for proteome integrity are not fully understood. Using several different pulse-labelling strategies, here we gain direct insight into the relationship between protein synthesis and abundance proteome-wide. We show that protein degradation varies in-phase with protein synthesis, facilitating rhythms in turnover rather than abundance. This results in daily consolidation of proteome renewal whilst minimising changes in composition. Coupled rhythms in synthesis and turnover are especially salient to the assembly of macromolecular protein complexes, particularly the ribosome, the most abundant species of complex in the cell. Daily turnover and proteasomal degradation rhythms render cells and mice more sensitive to proteotoxic stress at specific times of day, potentially contributing to daily rhythms in the efficacy of proteasomal inhibitors against cancer. Our findings suggest that circadian rhythms function to minimise the bioenergetic cost of protein homeostasis through temporal consolidation of protein turnover.

Keywords:  Circadian; Proteostasis; Ribosome; SILAC

DOI:  https://doi.org/10.1038/s44318-024-00121-5
Nat Protoc. 2024 May 20.

An MSstats workflow for detecting differentially abundant proteins in large-scale data-independent acquisition mass spectrometry experiments with FragPipe processing.

Devon Kohler, Mateusz Staniak, Fengchao Yu, Alexey I Nesvizhskii, Olga Vitek.

Technological advances in mass spectrometry and proteomics have made it possible to perform larger-scale and more-complex experiments. The volume and complexity of the resulting data create major challenges for downstream analysis. In particular, next-generation data-independent acquisition (DIA) experiments enable wider proteome coverage than more traditional targeted approaches but require computational workflows that can manage much larger datasets and identify peptide sequences from complex and overlapping spectral features. Data-processing tools such as FragPipe, DIA-NN and Spectronaut have undergone substantial improvements to process spectral features in a reasonable time. Statistical analysis tools are needed to draw meaningful comparisons between experimental samples, but these tools were also originally designed with smaller datasets in mind. This protocol describes an updated version of MSstats that has been adapted to be compatible with large-scale DIA experiments. A very large DIA experiment, processed with FragPipe, is used as an example to demonstrate different MSstats workflows. The choice of workflow depends on the user's computational resources. For datasets that are too large to fit into a standard computer's memory, we demonstrate the use of MSstatsBig, a companion R package to MSstats. The protocol also highlights key decisions that have a major effect on both the results and the processing time of the analysis. The MSstats processing can be expected to take 1-3 h depending on the usage of MSstatsBig. The protocol can be run in the point-and-click graphical user interface MSstatsShiny or implemented with minimal coding expertise in R.

DOI: https://doi.org/10.1038/s41596-024-01000-3
Cell. 2024 May 23. pii: S0092-8674(24)00462-8. [Epub ahead of print]187(11): 2599-2600

Toward new horizons in cell biology.

Cell Editorial Team

This 50th Anniversary Focus on Cell Biology looks at where the field is going. What big principles are emerging? What's making cell biology research thrive? We're celebrating by showcasing how this classic field is forging ahead.

DOI: https://doi.org/10.1016/j.cell.2024.04.036
Cell. 2024 May 23. pii: S0092-8674(24)00461-6. [Epub ahead of print]187(11): 2633-2651

Establishing a conceptual framework for holistic cell states and state transitions.

Susanne M Rafelski, Julie A Theriot.

Cell states were traditionally defined by how they looked, where they were located, and what functions they performed. In this post-genomic era, the field is largely focused on a molecular view of cell state. Moving forward, we anticipate that the observables used to define cell states will evolve again as single-cell imaging and analytics are advancing at a breakneck pace via the collection of large-scale, systematic cell image datasets and the application of quantitative image-based data science methods. This is, therefore, a key moment in the arc of cell biological research to develop approaches that integrate the spatiotemporal observables of the physical structure and organization of the cell with molecular observables toward the concept of a holistic cell state. In this perspective, we propose a conceptual framework for holistic cell states and state transitions that is data-driven, practical, and useful to enable integrative analyses and modeling across many data types.

DOI: https://doi.org/10.1016/j.cell.2024.04.035
Brief Bioinform. 2024 Mar 27. pii: bbae233. [Epub ahead of print]25(3):

Error modelled gene expression analysis (EMOGEA) provides a superior overview of time course RNA-seq measurements and low count gene expression.

Jasmine Barra, Federico Taverna, Fabian Bong, Ibrahim Ahmed, Tobias K Karakach.

  Temporal RNA-sequencing (RNA-seq) studies of bulk samples provide an opportunity for improved understanding of gene regulation during dynamic phenomena such as development, tumor progression or response to an incremental dose of a pharmacotherapeutic. Moreover, single-cell RNA-seq (scRNA-seq) data implicitly exhibit temporal characteristics because gene expression values recapitulate dynamic processes such as cellular transitions. Unfortunately, temporal RNA-seq data continue to be analyzed by methods that ignore this ordinal structure and yield results that are often difficult to interpret. Here, we present Error Modelled Gene Expression Analysis (EMOGEA), a framework for analyzing RNA-seq data that incorporates measurement uncertainty, while introducing a special formulation for those acquired to monitor dynamic phenomena. This method is specifically suited for RNA-seq studies in which low-count transcripts with small-fold changes lead to significant biological effects. Such transcripts include genes involved in signaling and non-coding RNAs that inherently exhibit low levels of expression. Using simulation studies, we show that this framework down-weights samples that exhibit extreme responses such as batch effects allowing them to be modeled with the rest of the samples and maintain the degrees of freedom originally envisioned for a study. Using temporal experimental data, we demonstrate the framework by extracting a cascade of gene expression waves from a well-designed RNA-seq study of zebrafish embryogenesis and an scRNA-seq study of mouse pre-implantation and provide unique biological insights into the regulation of genes in each wave. For non-ordinal measurements, we show that EMOGEA has a much higher rate of true positive calls and a vanishingly small rate of false negative discoveries compared to common approaches. Finally, we provide two packages in Python and R that are self-contained and easy to use, including test data.

Keywords:  Bulk RNA-seq; analysis of temporal data; error modeling; low-signal gene; single-cell RNA-seq

DOI:  https://doi.org/10.1093/bib/bbae233
Diabetes. 2024 Jun 01. 73(6): 856-863

Glucose Regulation of β-Cell KATP Channels: It Is Time for a New Model!

Matthew J Merrins, Richard G Kibbey.

An agreed-upon consensus model of glucose-stimulated insulin secretion from healthy β-cells is essential for understanding diabetes pathophysiology. Since the discovery of the KATP channel in 1984, an oxidative phosphorylation (OxPhos)-driven rise in ATP has been assumed to close KATP channels to initiate insulin secretion. This model lacks any evidence, genetic or otherwise, that mitochondria possess the bioenergetics to raise the ATP/ADP ratio to the triggering threshold, and conflicts with genetic evidence demonstrating that OxPhos is dispensable for insulin secretion. It also conflates the stoichiometric yield of OxPhos with thermodynamics, and overestimates OxPhos by failing to account for established features of β-cell metabolism, such as leak, anaplerosis, cataplerosis, and NADPH production that subtract from the efficiency of mitochondrial ATP production. We have proposed an alternative model, based on the spatial and bioenergetic specializations of β-cell metabolism, in which glycolysis initiates insulin secretion. The evidence for this model includes that 1) glycolysis has high control strength over insulin secretion; 2) glycolysis is active at the correct time to explain KATP channel closure; 3) plasma membrane-associated glycolytic enzymes control KATP channels; 4) pyruvate kinase has favorable bioenergetics, relative to OxPhos, for raising ATP/ADP; and 5) OxPhos stalls before membrane depolarization and increases after. Although several key experiments remain to evaluate this model, the 1984 model is based purely on circumstantial evidence and must be rescued by causal, mechanistic experiments if it is to endure.

DOI: https://doi.org/10.2337/dbi23-0032
Sci Rep. 2024 05 22. 14(1): 11719

Optical sensor reveals the hidden influence of cell dissociation on adhesion measurements.

Kinga Dóra Kovács, Zoltán Szittner, Beatrix Magyaródi, Beatrix Péter, Bálint Szabó, Alexa Vörös, Nicolett Kanyó, Inna Székács, Robert Horvath.

Cell adhesion experiments are important in tissue engineering and for testing new biologically active surfaces, prostheses, and medical devices. Additionally, the initial state of adhesion (referred to as nascent adhesion) plays a key role and is currently being intensively researched. A critical step in handling all adherent cell types is their dissociation from their substrates for further processing. Various cell dissociation methods and reagents are used in most tissue culture laboratories (here, cell dissociation from the culture surface, cell harvesting, and cell detachment are used interchangeably). Typically, the dissociated cells are re-adhered for specific measurements or applications. However, the impact of the choice of dissociation method on cell adhesion in subsequent measurements, especially when comparing the adhesivity of various surfaces, is not well clarified. In this study, we demonstrate that the application of a label-free optical sensor can precisely quantify the effect of cell dissociation methods on cell adhesivity, both at the single-cell and population levels. The optical measurements allow for high-resolution monitoring of cellular adhesion without interfering with the physiological state of the cells. We found that the choice of reagent significantly alters cell adhesion on various surfaces. Our results clearly demonstrate that biological conclusions about cellular adhesion when comparing various surfaces are highly dependent on the employed dissociation method. Neglecting the choice of cellular dissociation can lead to misleading conclusions when evaluating cell adhesion data from various sources and comparing the adhesivity of two different surfaces (i.e., determining which surface is more or less adhesive).

DOI: https://doi.org/10.1038/s41598-024-61485-6
JVS Vasc Sci. 2024 ;5 100193

Hyperoxia impairs induced pluripotent stem cell-derived endothelial cells and drives an atherosclerosis-like transcriptional phenotype.

Sean M Carr, Katherine Owsiany, Ottis Scrivner, Dylan McLaughlin, Hanjoong Jo, Luke P Brewster, Katherine E Hekman.

  Background: Induced pluripotent stem cells (iPSCs) directed to endothelial identity (iPSC-ECs) are emerging as a potent tool for regenerative medicine in vascular disease. However, iPSC-ECs lose expression of key identity markers under standard in vitro conditions, limiting their clinical applications.Methods: To model physiological in vivo conditions, we examined the bioenergetics, presence of key cell markers, and proliferative and angiogenic capacity in iPSC-ECs at late and early passage under hyperoxic (21%) and physiological (4%) oxygen concentrations.
Results: Physoxia resulted in relative preservation of mitochondrial bioenergetic activity, as well as CD144 expression in late passage iPSC-ECs, but not proliferative capacity or tube formation. Single cell RNA sequencing (scRNA-seq) revealed that late passage hyperoxic iPSC-ECs develop an endothelial-to-mesenchymal phenotype. Comparing scRNA-seq data from iPSC-ECs and from atherosclerotic ECs revealed overlap of their transcriptional phenotypes.
Conclusions: Taken together, our studies demonstrate that physiological 4% oxygen culture conditions were sufficient to improve mitochondrial function in high passage cells, but alone was insufficient to preserve angiogenic capacity. Furthermore, late passage cells under typical conditions take on an endothelial-to-mesenchymal phenotype with similarities to ECs found in atherosclerosis.

Keywords:  Atherosclerosis; Endothelial cells; Hypoxia; Induced pluripotent stem cells; Peripheral arterial disease; Physoxia; Regenerative medicine

DOI:  https://doi.org/10.1016/j.jvssci.2024.100193
Nat Commun. 2024 May 23. 15(1): 4387

In-depth organic mass cytometry reveals differential contents of 3-hydroxybutanoic acid at the single-cell level.

Shaojie Qin, Yi Zhang, Mingying Shi, Daiyu Miao, Jiansen Lu, Lu Wen, Yu Bai.

Comprehensive single-cell metabolic profiling is critical for revealing phenotypic heterogeneity and elucidating the molecular mechanisms underlying biological processes. However, single-cell metabolomics remains challenging because of the limited metabolite coverage and inability to discriminate isomers. Herein, we establish a single-cell metabolomics platform for in-depth organic mass cytometry. Extended single-cell analysis time guarantees sufficient MS/MS acquisition for metabolite identification and the isomers discrimination while online sampling ensures the high-throughput of the method. The largest number of identified metabolites (approximately 600) are achieved in single cells and fine subtyping of MCF-7 cells is first demonstrated by an investigation on the differential levels of 3-hydroxybutanoic acid among clusters. Single-cell transcriptome analysis reveals differences in the expression of 3-hydroxybutanoic acid downstream antioxidative stress genes, such as metallothionein 2 (MT2A), while a fluorescence-activated cell sorting assay confirms the positive relationship between 3-hydroxybutanoic acid and target proteins; these results suggest that the heterogeneity of 3-hydroxybutanoic acid provides cancer cells with different ability to resist surrounding oxidative stress. Our method paves the way for deep single-cell metabolome profiling and investigations on the physiological and pathological processes that occur during cancer.

DOI: https://doi.org/10.1038/s41467-024-48865-2
Proc Natl Acad Sci U S A. 2024 May 28. 121(22): e2407886121

Protecting scientific integrity in an age of generative AI.

Wolfgang Blau, Vinton G Cerf, Juan Enriquez, Joseph S Francisco, Urs Gasser, Mary L Gray, Mark Greaves, Barbara J Grosz, Kathleen Hall Jamieson, Gerald H Haug, John L Hennessy, Eric Horvitz, David I Kaiser, Alex John London, Robin Lovell-Badge, Marcia K McNutt, Martha Minow, Tom M Mitchell, Susan Ness, Shobita Parthasarathy, Saul Perlmutter, William H Press, Jeannette M Wing, Michael Witherell.

DOI: https://doi.org/10.1073/pnas.2407886121
EMBO J. 2024 May 21.

Origins of cancer: ain't it just mature cells misbehaving?

Charles J Cho, Jeffrey W Brown, Jason C Mills.

  A pervasive view is that undifferentiated stem cells are alone responsible for generating all other cells and are the origins of cancer. However, emerging evidence demonstrates fully differentiated cells are plastic, can be coaxed to proliferate, and also play essential roles in tissue maintenance, regeneration, and tumorigenesis. Here, we review the mechanisms governing how differentiated cells become cancer cells. First, we examine the unique characteristics of differentiated cell division, focusing on why differentiated cells are more susceptible than stem cells to accumulating mutations. Next, we investigate why the evolution of multicellularity in animals likely required plastic differentiated cells that maintain the capacity to return to the cell cycle and required the tumor suppressor p53. Finally, we examine an example of an evolutionarily conserved program for the plasticity of differentiated cells, paligenosis, which helps explain the origins of cancers that arise in adults. Altogether, we highlight new perspectives for understanding the development of cancer and new strategies for preventing carcinogenic cellular transformations from occurring.

Keywords:  Differentiation; Multicellularity; Plasticity; Stem Cell; p53

DOI:  https://doi.org/10.1038/s44318-024-00099-0