bims-pideca 2024-09-08 papers

bims-pideca

Biomed News

on Class IA PI3K signalling in development and cancer

Issue of 2024‒09‒08
25 papers selected by
Ralitsa Radostinova Madsen, MRC-PPU

Dysfunctional mechanotransduction regulates the progression of PIK3CA-driven vascular malformations.
Free energy landscape of the PI3Kα C-terminal activation.
LIANA+ provides an all-in-one framework for cell-cell communication inference.
ERK synchronizes embryonic cleavages in Drosophila.
mTORC1 Signaling Inhibition Modulates Mitochondrial Function in Frataxin Deficiency.
Cell Painting Gallery: an open resource for image-based profiling.
Leptin and insulin synergize with PIK3CA mutation to enhance PD-L1 mediated immunosuppression in thyroid cancer.
Single-cell chromatin accessibility reveals malignant regulatory programs in primary human cancers.
NCI's Proteomic Data Commons: A Cloud-Based Proteomics Repository Empowering Comprehensive Cancer Analysis Through Cross-Referencing with Genomic and Imaging Data.
Long-term engrafting multilineage hematopoietic cells differentiated from human induced pluripotent stem cells.
Quantitative mapping of proteasome interactomes and substrates using ProteasomeID.
The mTOR pathway controls phosphorylation of BRAF at T401.
scConfluence: single-cell diagonal integration with regularized Inverse Optimal Transport on weakly connected features.
Integrating Vascular Phenotypic and Proteomic Analysis in an Open Microfluidic Platform.
ImmCellTyper facilitates systematic mass cytometry data analysis for deep immune profiling.
Versatile system cores as a conceptual basis for generality in cell and developmental biology.
Efficient generation of human NOTCH ligand-expressing haemogenic endothelial cells as infrastructure for in vitro haematopoiesis and lymphopoiesis.
Recon8D: A metabolic regulome network from oct-omics and machine learning.
Integrative analysis of multi-omics data reveals importance of collagen and the PI3K AKT signalling pathway in CAKUT.
Multi-omic lineage tracing predicts the transcriptional, epigenetic and genetic determinants of cancer evolution.
Integration of mass cytometry and mass spectrometry imaging for spatially resolved single-cell metabolic profiling.
cytoKernel: Robust kernel embeddings for assessing differential expression of single cell data.
Mechanisms that clear mutations drive field cancerization in mammary tissue.
Guide assignment in single-cell CRISPR screens using crispat.
A phosphorylation-controlled switch confers cell cycle-dependent protein relocalization.

bioRxiv. 2024 Aug 23. pii: 2024.08.22.609165. [Epub ahead of print]

Dysfunctional mechanotransduction regulates the progression of PIK3CA-driven vascular malformations.

Wen Yih Aw, Aanya Sawhney, Mitesh Rathod, Chloe P Whitworth, Elizabeth L Doherty, Ethan Madden, Jingming Lu, Kaden Westphal, Ryan Stack, William J Polacheck.

Somatic activating mutations in PIK3CA are common drivers of vascular and lymphatic malformations. Despite common biophysical signatures of tissues susceptible to lesion formation, including compliant extracellular matrix and low rates of perfusion, lesions vary in clinical presentation from localized cystic dilatation to diffuse and infiltrative vascular dysplasia. The mechanisms driving the differences in disease severity and variability in clinical presentation and the role of the biophysical microenvironment in potentiating progression are poorly understood. Here, we investigate the role of hemodynamic forces and the biophysical microenvironment in the pathophysiology of vascular malformations, and we identify hemodynamic shear stress and defective endothelial cell mechanotransduction as key regulators of lesion progression. We found that constitutive PI3K activation impaired flow-mediated endothelial cell alignment and barrier function. We show that defective shear stress sensing in PIK3CA E542K endothelial cells is associated with reduced myosin light chain phosphorylation, junctional instability, and defective recruitment of vinculin to cell-cell junctions. Using 3D microfluidic models of the vasculature, we demonstrate that PIK3CA E542K microvessels apply reduced traction forces and are unaffected by flow interruption. We further found that draining transmural flow resulted in increased sprouting and invasion responses in PIK3CA E542K microvessels. Mechanistically, constitutive PI3K activation decreased cellular and nuclear elasticity resulting in defective cellular tensional homeostasis in endothelial cells which may underlie vascular dilation, tissue hyperplasia, and hypersprouting in PIK3CA -driven venous and lymphatic malformations. Together, these results suggest that defective nuclear mechanics, impaired cellular mechanotransduction, and maladaptive hemodynamic responses contribute to the development and progression of PIK3CA -driven vascular malformations.

DOI: https://doi.org/10.1101/2024.08.22.609165
Comput Struct Biotechnol J. 2024 Dec;23 3118-3131

Free energy landscape of the PI3Kα C-terminal activation.

Danai Maria Kotzampasi, Michail Papadourakis, John E Burke, Zoe Cournia.

  The gene PIK3CA, encoding the catalytic subunit p110α of PI3Kα, is the second most frequently mutated gene in cancer, with the highest frequency oncogenic mutants occurring in the C-terminus of the kinase domain. The C-terminus has a dual function in regulating the kinase, playing a putative auto-inhibitory role for kinase activity and being absolutely essential for binding to the cell membrane. However, the molecular mechanisms by which these C-terminal oncogenic mutations cause PI3Kα overactivation remain unclear. To understand how a spectrum of C-terminal mutations of PI3Kα alter kinase activity compared to the WT, we perform unbiased and biased Molecular Dynamics simulations of several C-terminal mutants and report the free energy landscapes for the C-terminal "closed-to-open" transition in the WT, H1047R, G1049R, M1043L and N1068KLKR mutants. Results are consistent with HDX-MS experimental data and provide a molecular explanation why H1047R and G1049R reorient the C-terminus with a different mechanism compared to the WT and M1043L and N1068KLKR mutants. Moreover, we show that in the H1047R mutant, the cavity, where the allosteric ligands STX-478 and RLY-2608 bind, is more accessible contrary to the WT. This study provides insights into the molecular mechanisms underlying activation of oncogenic PI3Kα by C-terminal mutations and represents a valuable resource for continued efforts in the development of mutant selective inhibitors as therapeutics.

Keywords:  Allostery; Cancer; H1047R; HDX-MS; Lipid kinase; Molecular Dynamics simulations; PI3Kα; PIK3CA

DOI:  https://doi.org/10.1016/j.csbj.2024.07.010
Nat Cell Biol. 2024 Sep 02.

LIANA+ provides an all-in-one framework for cell-cell communication inference.

Daniel Dimitrov, Philipp Sven Lars Schäfer, Elias Farr, Pablo Rodriguez-Mier, Sebastian Lobentanzer, Pau Badia-I-Mompel, Aurelien Dugourd, Jovan Tanevski, Ricardo Omar Ramirez Flores, Julio Saez-Rodriguez.

The growing availability of single-cell and spatially resolved transcriptomics has led to the development of many approaches to infer cell-cell communication, each capturing only a partial view of the complex landscape of intercellular signalling. Here we present LIANA+, a scalable framework built around a rich knowledge base to decode coordinated inter- and intracellular signalling events from single- and multi-condition datasets in both single-cell and spatially resolved data. By extending and unifying established methodologies, LIANA+ provides a comprehensive set of synergistic components to study cell-cell communication via diverse molecular mediators, including those measured in multi-omics data. LIANA+ is accessible at https://github.com/saezlab/liana-py with extensive vignettes ( https://liana-py.readthedocs.io/ ) and provides an all-in-one solution to intercellular communication inference.

DOI: https://doi.org/10.1038/s41556-024-01469-w
Dev Cell. 2024 Aug 27. pii: S1534-5807(24)00487-8. [Epub ahead of print]

ERK synchronizes embryonic cleavages in Drosophila.

Liu Yang, Audrey Zhu, Javed M Aman, David Denberg, Marcus D Kilwein, Robert A Marmion, Alex N T Johnson, Alexey Veraksa, Mona Singh, Martin Wühr, Stanislav Y Shvartsman.

  Extracellular-signal-regulated kinase (ERK) signaling controls development and homeostasis and is genetically deregulated in human diseases, including neurocognitive disorders and cancers. Although the list of ERK functions is vast and steadily growing, the full spectrum of processes controlled by any specific ERK activation event remains unknown. Here, we show how ERK functions can be systematically identified using targeted perturbations and global readouts of ERK activation. Our experimental model is the Drosophila embryo, where ERK signaling at the embryonic poles has thus far only been associated with the transcriptional patterning of the future larva. Through a combination of live imaging and phosphoproteomics, we demonstrated that ERK activation at the poles is also critical for maintaining the speed and synchrony of embryonic cleavages. The presented approach to interrogating phosphorylation networks identifies a hidden function of a well-studied signaling event and sets the stage for similar studies in other organisms.

Keywords:  Cdc25; Cdk1; ERK; cell cycle; cleavages; embryonic; optogenetics; phosphoproteome; sychrony

DOI:  https://doi.org/10.1016/j.devcel.2024.08.004
bioRxiv. 2024 Aug 07. pii: 2024.08.06.606942. [Epub ahead of print]

mTORC1 Signaling Inhibition Modulates Mitochondrial Function in Frataxin Deficiency.

Madison Lehmer, Roberto Zoncu.

Lysosomes regulate mitochondrial function through multiple mechanisms including the master regulator, mechanistic Target of Rapamycin Complex 1 (mTORC1) protein kinase, which is activated at the lysosomal membrane by nutrient, growth factor and energy signals. mTORC1 promotes mitochondrial protein composition changes, respiratory capacity, and dynamics, though the full range of mitochondrial-regulating functions of this protein kinase remain undetermined. We find that acute chemical modulation of mTORC1 signaling decreased mitochondrial oxygen consumption, increased mitochondrial membrane potential and reduced susceptibility to stress-induced mitophagy. In cellular models of Friedreich's Ataxia (FA), where loss of the Frataxin (FXN) protein suppresses Fe-S cluster synthesis and mitochondrial respiration, the changes induced by mTORC1 inhibitors lead to improved cell survival. Proteomic-based profiling uncover compositional changes that could underlie mTORC1-dependent modulation of FXN-deficient mitochondria. These studies highlight mTORC1 signaling as a regulator of mitochondrial composition and function, prompting further evaluation of this pathway in the context of mitochondrial disease.

DOI: https://doi.org/10.1101/2024.08.06.606942
Nat Methods. 2024 Sep 02.

Cell Painting Gallery: an open resource for image-based profiling.

Erin Weisbart, Ankur Kumar, John Arevalo, Anne E Carpenter, Beth A Cimini, Shantanu Singh.

DOI: https://doi.org/10.1038/s41592-024-02399-z
Exp Cell Res. 2024 Aug 27. pii: S0014-4827(24)00320-3. [Epub ahead of print]442(2): 114229

Leptin and insulin synergize with PIK3CA mutation to enhance PD-L1 mediated immunosuppression in thyroid cancer.

Kainan Wu, Yuerong Chen, Runsheng Guo, Qingtan Zeng, Yue Yu.

  The incidence of thyroid cancer keeps rising and obesity emerges as an important risk factor for thyroid cancer, but the underlying mechanism is far from clear. Here, we hypothesize that leptin and insulin, two hormones closely related to obesity, may contribute to the pathogenesis of thyroid cancer. By using a combination of assays like CRISPR KO, cancer cell-T cell co-culture, ApoLive-Glo™ multiplex assay and syngeneic mouse model, we show that PD-L1 protein levels are increased dose-dependently by leptin or insulin in multiple thyroid cancer cell lines. Leptin and insulin converge to activate the PI3K-AKT pathway to enhance PD-L1 expression and activity. In addition, we use CRISPR KO to generate human thyroid cancer cells expressing WT PIK3CA or PIK3CA-E545K mutant. PIK3CA- E545K mutation makes the thyroid cancer cells to produce more PD-L1 protein upon leptin or insulin treatment. Thus, leptin and insulin synergize with PIK3CA mutation to enhance PD-L1 expression. Dual blockade of leptin and insulin signaling pathways reduces tumor size in a syngeneic mouse model. Our study suggests that understanding the interaction between genetic mutation and obesity is crucial for comprehensively assessing thyroid cancer risk and developing effective treatment strategies.

Keywords:  Insulin; Leptin; Obesity; PD-L1; PIK3CA; Thyroid cancer

DOI:  https://doi.org/10.1016/j.yexcr.2024.114229
Science. 2024 Sep 06. 385(6713): eadk9217

Single-cell chromatin accessibility reveals malignant regulatory programs in primary human cancers.

Cancer Genome Atlas Analysis Network‡

To identify cancer-associated gene regulatory changes, we generated single-cell chromatin accessibility landscapes across eight tumor types as part of The Cancer Genome Atlas. Tumor chromatin accessibility is strongly influenced by copy number alterations that can be used to identify subclones, yet underlying cis-regulatory landscapes retain cancer type-specific features. Using organ-matched healthy tissues, we identified the "nearest healthy" cell types in diverse cancers, demonstrating that the chromatin signature of basal-like-subtype breast cancer is most similar to secretory-type luminal epithelial cells. Neural network models trained to learn regulatory programs in cancer revealed enrichment of model-prioritized somatic noncoding mutations near cancer-associated genes, suggesting that dispersed, nonrecurrent, noncoding mutations in cancer are functional. Overall, these data and interpretable gene regulatory models for cancer and healthy tissue provide a framework for understanding cancer-specific gene regulation.

DOI: https://doi.org/10.1126/science.adk9217
Cancer Res Commun. 2024 Sep 03.

NCI's Proteomic Data Commons: A Cloud-Based Proteomics Repository Empowering Comprehensive Cancer Analysis Through Cross-Referencing with Genomic and Imaging Data.

Ratna R Thangudu, Michael Holck, Deepak Singhal, Alexander Pilozzi, Nathan Edwards, Paul A Rudnick, Marcin J Domagalski, Padmini Chilappagari, Lei Ma, Yi Xin, Toan Le, Kristen Nyce, Rekha Chaudhary, Karen A Ketchum, Aaron Maurais, Brian Connolly, Michael Riffle, Matthew C Chambers, Brendan MacLean, Michael J MacCoss, Peter B McGarvey, Anand Basu, John Otridge, Esmeralda Casas-Silva, Sudha Venkatachari, Henry Rodriguez, Xu Zhang.

Proteomics has emerged as a powerful tool for studying cancer biology, developing diagnostics, and therapies. With the continuous improvement and widespread availability of high-throughput proteomic technologies, the generation of large-scale proteomic data has become more common in cancer research, and there is a growing need for resources that support the sharing and integration of multi-omics datasets. Such datasets require extensive metadata including clinical, biospecimen and experimental and workflow annotations that are crucial for data interpretation and reanalysis. The need to integrate, analyze, and share these data has led to the development of National Cancer Institute's (NCI) Proteomic Data Commons (PDC), accessible at https://pdc.cancer.gov. As a specialized repository within the NCI Cancer Research Data Commons (CRDC), PDC enables researchers to locate and analyze proteomic data from various cancer types and connect with genomic and imaging data available for the same samples in other CRDC nodes. Presently, PDC houses annotated data from nearly 140 datasets across 19 cancer types, generated by several large-scale cancer research programs with cohort sizes exceeding 100 samples (tumor and associated normal when available). In this paper, we review the current state of PDC in cancer research, discuss the opportunities and challenges associated with data sharing in proteomics, and propose future directions for the resource.

DOI: https://doi.org/10.1158/2767-9764.CRC-24-0243
Nat Biotechnol. 2024 Sep 02.

Long-term engrafting multilineage hematopoietic cells differentiated from human induced pluripotent stem cells.

Elizabeth S Ng, Gulcan Sarila, Jacky Y Li, Hasindu S Edirisinghe, Ritika Saxena, Shicheng Sun, Freya F Bruveris, Tanya Labonne, Nerida Sleebs, Alexander Maytum, Raymond Y Yow, Chantelle Inguanti, Ali Motazedian, Vincenzo Calvanese, Sandra Capellera-Garcia, Feiyang Ma, Hieu T Nim, Mirana Ramialison, Constanze Bonifer, Hanna K A Mikkola, Edouard G Stanley, Andrew G Elefanty.

Hematopoietic stem cells (HSCs) derived from human induced pluripotent stem cells (iPS cells) have important biomedical applications. We identified differentiation conditions that generate HSCs defined by robust long-term multilineage engraftment in immune-deficient NOD,B6.Prkdcscid Il2rgtm1Wjl/SzJ KitW41/W41 mice. We guided differentiating iPS cells, as embryoid bodies in a defined culture medium supplemented with retinyl acetate, through HOXA-patterned mesoderm to hemogenic endothelium specified by bone morphogenetic protein 4 and vascular endothelial growth factor (VEGF). Removal of VEGF facilitated an efficient endothelial-to-hematopoietic transition, evidenced by release into the culture medium of CD34+ blood cells, which were cryopreserved. Intravenous transplantation of two million thawed CD34+ cells differentiated from four independent iPS cell lines produced multilineage bone marrow engraftment in 25-50% of immune-deficient recipient mice. These functionally defined, multipotent CD34+ hematopoietic cells, designated iPS cell-derived HSCs (iHSCs), produced levels of engraftment similar to those achieved following umbilical cord blood transplantation. Our study provides a step toward the goal of generating HSCs for clinical translation.

DOI: https://doi.org/10.1038/s41587-024-02360-7
Elife. 2024 Sep 04. pii: RP93256. [Epub ahead of print]13

Quantitative mapping of proteasome interactomes and substrates using ProteasomeID.

Aleksandar Bartolome, Julia C Heiby, Domenico Di Fraia, Ivonne Heinze, Hannah Knaudt, Ellen Spaeth, Omid Omrani, Alberto Minetti, Maleen Hofmann, Joanna M Kirkpatrick, Therese Dau, Alessandro Ori.

  Proteasomes are essential molecular machines responsible for the degradation of proteins in eukaryotic cells. Altered proteasome activity has been linked to neurodegeneration, auto-immune disorders and cancer. Despite the relevance for human disease and drug development, no method currently exists to monitor proteasome composition and interactions in vivo in animal models. To fill this gap, we developed a strategy based on tagging of proteasomes with promiscuous biotin ligases and generated a new mouse model enabling the quantification of proteasome interactions by mass spectrometry. We show that biotin ligases can be incorporated in fully assembled proteasomes without negative impact on their activity. We demonstrate the utility of our method by identifying novel proteasome-interacting proteins, charting interactomes across mouse organs, and showing that proximity-labeling enables the identification of both endogenous and small-molecule-induced proteasome substrates.

Keywords:  biochemistry; chemical biology; human; mass spectrometry; mouse; proteasome; protein degradation; proteomics; proximity labelling

DOI:  https://doi.org/10.7554/eLife.93256
Cell Commun Signal. 2024 Sep 02. 22(1): 428

The mTOR pathway controls phosphorylation of BRAF at T401.

Daniel Christen, Manuel Lauinger, Melanie Brunner, Jörn Dengjel, Tilman Brummer.

BRAF serves as a gatekeeper of the RAS/RAF/MEK/ERK pathway, which plays a crucial role in homeostasis. Since aberrant signalling of this axis contributes to cancer and other diseases, it is tightly regulated by crosstalk with the PI3K/AKT/mTOR pathway and ERK mediated feedback loops. For example, ERK limits BRAF signalling through phosphorylation of multiple residues. One of these, T401, is widely considered as an ERK substrate following acute pathway activation by growth factors. Here, we demonstrate that prominent T401 phosphorylation (pT401) of endogenous BRAF is already observed in the absence of acute stimulation in various cell lines of murine and human origin. Importantly, the BRAF/RAF1 inhibitor naporafenib, the MEK inhibitor trametinib and the ERK inhibitor ulixertinib failed to reduce pT401 levels in these settings, supporting an alternative ERK-independent pathway to T401 phosphorylation. In contrast, the mTOR inhibitor torin1 and the dual-specific PI3K/mTOR inhibitor dactolisib significantly suppressed pT401 levels in all investigated cell types, in both a time and concentration dependent manner. Conversely, genetic mTOR pathway activation by oncogenic RHEB (Q64L) and mTOR (S2215Y and R2505P) mutants substantially increased pT401, an effect that was reverted by dactolisib and torin1 but not by trametinib. We also show that shRNAmir mediated depletion of the mTORC1 complex subunit Raptor significantly enhanced the suppression of T401 phosphorylation by a low torin1 dose, while knockdown of the mTORC2 complex subunit Rictor was less effective. Using mass spectrometry, we provide further evidence that torin1 suppresses the phosphorylation of T401, S405 and S409 but not of other important regulatory phosphorylation sites such as S446, S729 and S750. In summary, our data identify the mTOR axis and its inhibitors of (pre)clinical relevance as novel modulators of BRAF phosphorylation at T401.

DOI: https://doi.org/10.1186/s12964-024-01808-2
Nat Commun. 2024 Sep 05. 15(1): 7762

scConfluence: single-cell diagonal integration with regularized Inverse Optimal Transport on weakly connected features.

Jules Samaran, Gabriel Peyré, Laura Cantini.

The abundance of unpaired multimodal single-cell data has motivated a growing body of research into the development of diagonal integration methods. However, the state-of-the-art suffers from the loss of biological information due to feature conversion and struggles with modality-specific populations. To overcome these crucial limitations, we here introduce scConfluence, a method for single-cell diagonal integration. scConfluence combines uncoupled autoencoders on the complete set of features with regularized Inverse Optimal Transport on weakly connected features. We extensively benchmark scConfluence in several single-cell integration scenarios proving that it outperforms the state-of-the-art. We then demonstrate the biological relevance of scConfluence in three applications. We predict spatial patterns for Scgn, Synpr and Olah in scRNA-smFISH integration. We improve the classification of B cells and Monocytes in highly heterogeneous scRNA-scATAC-CyTOF integration. Finally, we reveal the joint contribution of Fezf2 and apical dendrite morphology in Intra Telencephalic neurons, based on morphological images and scRNA.

DOI: https://doi.org/10.1038/s41467-024-51382-x
ACS Nano. 2024 Aug 29.

Integrating Vascular Phenotypic and Proteomic Analysis in an Open Microfluidic Platform.

Sangmin Jung, Sunghun Cheong, Yoonho Lee, Jungseub Lee, Jihye Lee, Min-Seok Kwon, Young Sun Oh, Taewan Kim, Sungjae Ha, Sung Jae Kim, Dong Hyun Jo, Jihoon Ko, Noo Li Jeon.

  This research introduces a vascular phenotypic and proteomic analysis (VPT) platform designed to perform high-throughput experiments on vascular development. The VPT platform utilizes an open-channel configuration that facilitates angiogenesis by precise alignment of endothelial cells, allowing for a 3D morphological examination and protein analysis. We study the effects of antiangiogenic agents─bevacizumab, ramucirumab, cabozantinib, regorafenib, wortmannin, chloroquine, and paclitaxel─on cytoskeletal integrity and angiogenic sprouting, observing an approximately 50% reduction in sprouting at higher drug concentrations. Precise LC-MS/MS analyses reveal global protein expression changes in response to four of these drugs, providing insights into the signaling pathways related to the cell cycle, cytoskeleton, cellular senescence, and angiogenesis. Our findings emphasize the intricate relationship between cytoskeletal alterations and angiogenic responses, underlining the significance of integrating morphological and proteomic data for a comprehensive understanding of angiogenesis. The VPT platform not only advances our understanding of drug impacts on vascular biology but also offers a versatile tool for analyzing proteome and morphological features across various models beyond blood vessels.

Keywords:  angiogenesis; drug screening; image analysis; microphysiological system; open microfluidics; proteomics

DOI:  https://doi.org/10.1021/acsnano.4c05537
Elife. 2024 Sep 06. pii: RP95494. [Epub ahead of print]13

ImmCellTyper facilitates systematic mass cytometry data analysis for deep immune profiling.

Jing Sun, Desmond Choy, Nicolas Sompairac, Shirin Jamshidi, Michele Mishto, Shahram Kordasti.

  Mass cytometry is a cutting-edge high-dimensional technology for profiling marker expression at the single-cell level, advancing clinical research in immune monitoring. Nevertheless, the vast data generated by cytometry by time-of-flight (CyTOF) poses a significant analytical challenge. To address this, we describe ImmCellTyper (https://github.com/JingAnyaSun/ImmCellTyper), a novel toolkit for CyTOF data analysis. This framework incorporates BinaryClust, an in-house developed semi-supervised clustering tool that automatically identifies main cell types. BinaryClust outperforms existing clustering tools in accuracy and speed, as shown in benchmarks with two datasets of approximately 4 million cells, matching the precision of manual gating by human experts. Furthermore, ImmCellTyper offers various visualisation and analytical tools, spanning from quality control to differential analysis, tailored to users' specific needs for a comprehensive CyTOF data analysis solution. The workflow includes five key steps: (1) batch effect evaluation and correction, (2) data quality control and pre-processing, (3) main cell lineage characterisation and quantification, (4) in-depth investigation of specific cell types; and (5) differential analysis of cell abundance and functional marker expression across study groups. Overall, ImmCellTyper combines expert biological knowledge in a semi-supervised approach to accurately deconvolute well-defined main cell lineages, while maintaining the potential of unsupervised methods to discover novel cell subsets, thus facilitating high-dimensional immune profiling.

Keywords:  CyTOF; computational biology; computational framework; human; immune profiling; immunology; inflammation; systems biology

DOI:  https://doi.org/10.7554/eLife.95494
Cell Syst. 2024 Aug 28. pii: S2405-4712(24)00209-6. [Epub ahead of print]

Versatile system cores as a conceptual basis for generality in cell and developmental biology.

Elisa Gallo, Stefano De Renzis, James Sharpe, Roberto Mayor, Jonas Hartmann.

  The discovery of general principles underlying the complexity and diversity of cellular and developmental systems is a central and long-standing aim of biology. While new technologies collect data at an ever-accelerating rate, there is growing concern that conceptual progress is not keeping pace. We contend that this is due to a paucity of conceptual frameworks that support meaningful generalizations. This led us to develop the core and periphery (C&P) hypothesis, which posits that many biological systems can be decomposed into a highly versatile core with a large behavioral repertoire and a specific periphery that configures said core to perform one particular function. Versatile cores tend to be widely reused across biology, which confers generality to theories describing them. Here, we introduce this concept and describe examples at multiple scales, including Turing patterning, actomyosin dynamics, multi-cellular morphogenesis, and vertebrate gastrulation. We also sketch its evolutionary basis and discuss key implications and open questions. We propose that the C&P hypothesis could unlock new avenues of conceptual progress in mesoscale biology.

Keywords:  cell behavior; conceptual framework; foundations of cell and developmental biology; generality; generative principles; systems biology; theoretical biology; tissue self-organization

DOI:  https://doi.org/10.1016/j.cels.2024.08.001
Nat Commun. 2024 Sep 04. 15(1): 7698

Efficient generation of human NOTCH ligand-expressing haemogenic endothelial cells as infrastructure for in vitro haematopoiesis and lymphopoiesis.

Shicheng Sun, Ali Motazedian, Jacky Y Li, Kevin Wijanarko, Joe Jiang Zhu, Kothila Tharmarajah, Kathleen A Strumila, Anton Shkaruta, L Rayburn Nigos, Jacqueline V Schiesser, Yi Yu, Paul J Neeson, Elizabeth S Ng, Andrew G Elefanty, Edouard G Stanley.

Arterial endothelial cells (AECs) are the founder cells for intraembryonic haematopoiesis. Here, we report a method for the efficient generation of human haemogenic DLL4+ AECs from pluripotent stem cells (PSC). Time-series single-cell RNA-sequencing reveals the dynamic evolution of haematopoiesis and lymphopoiesis, generating cell types with counterparts present in early human embryos, including stages marked by the pre-haematopoietic stem cell genes MECOM/EVI1, MLLT3 and SPINK2. DLL4+ AECs robustly support lymphoid differentiation, without the requirement for exogenous NOTCH ligands. Using this system, we find IL7 acts as a morphogenic factor determining the fate choice between the T and innate lymphoid lineages and also plays a role in regulating the relative expression level of RAG1. Moreover, we document a developmental pathway by which human RAG1+ lymphoid precursors give rise to the natural killer cell lineage. Our study describes an efficient method for producing lymphoid progenitors, providing insights into their endothelial and haematopoietic ontogeny, and establishing a platform to investigate the development of the human blood system.

DOI: https://doi.org/10.1038/s41467-024-51974-7
bioRxiv. 2024 Aug 19. pii: 2024.08.17.608400. [Epub ahead of print]

Recon8D: A metabolic regulome network from oct-omics and machine learning.

Ryan Schildcrout, Kirk Smith, Rupa Bhowmick, Suraj Menon, Minali Kapadia, Emily Kurtz, Anya Coffeen-Vandeven, Sriram Chandrasekaran.

The complexity and incompleteness of metabolic-regulatory networks make it challenging to predict metabolomes from other omics. Using machine learning, we predicted metabolomic variation across ~1000 different cancer cell lines from matched oct-omics data: genomics, epigenomics (histone post-translational modifications (PTMs) and DNA-methylation), transcriptomics, RNA splicing, miRNA-omics, proteomics, and phosphoproteomics. Overall, the metabolome is tightly associated with the transcriptome, while miRNAs, phosphoproteins and histone PTMs have the highest metabolic information per feature. Metabolites in peripheral metabolism are predictable via levels of corresponding enzymes, while those in central metabolism require combinatorial predictors in signaling and redox pathways, and may not reflect corresponding pathway expression. We reconstruct multiomic interaction subnetworks for highly predictable metabolites, and YAP1 signaling emerged as a top global predictor across 4 omic layers. We prioritize predictive multiomic features for single-cell and spatial metabolomics assays. Top predictors were enriched for synthetic-lethal interactions and synergistic combination therapies that target compensatory metabolic modulators.

DOI: https://doi.org/10.1101/2024.08.17.608400
Sci Rep. 2024 Sep 05. 14(1): 20731

Integrative analysis of multi-omics data reveals importance of collagen and the PI3K AKT signalling pathway in CAKUT.

Jumamurat R Bayjanov, Cenna Doornbos, Ozan Ozisik, Woosub Shin, Núria Queralt-Rosinach, Daphne Wijnbergen, Jean-Sébastien Saulnier-Blache, Joost P Schanstra, Bénédicte Buffin-Meyer, Julie Klein, José M Fernández, Rajaram Kaliyaperumal, Anaïs Baudot, Peter A C 't Hoen, Friederike Ehrhart.

Congenital Anomalies of the Kidney and Urinary Tract (CAKUT) is the leading cause of childhood chronic kidney failure and a significant cause of chronic kidney disease in adults. Genetic and environmental factors are known to influence CAKUT development, but the currently known disease mechanism remains incomplete. Our goal is to identify affected pathways and networks in CAKUT, and thereby aid in getting a better understanding of its pathophysiology. With this goal, the miRNome, peptidome, and proteome of over 30 amniotic fluid samples of patients with non-severe CAKUT was compared to patients with severe CAKUT. These omics data sets were made findable, accessible, interoperable, and reusable (FAIR) to facilitate their integration with external data resources. Furthermore, we analysed and integrated the omics data sets using three different bioinformatics strategies: integrative analysis with mixOmics, joint dimensionality reduction and pathway analysis. The three bioinformatics analyses provided complementary features, but all pointed towards an important role for collagen in CAKUT development and the PI3K-AKT signalling pathway. Additionally, several key genes (CSF1, IGF2, ITGB1, and RAC1) and microRNAs were identified. We published the three analysis strategies as containerized workflows. These workflows can be applied to other FAIR data sets and help gaining knowledge on other rare diseases.

DOI: https://doi.org/10.1038/s41598-024-71721-8
Nat Commun. 2024 Sep 01. 15(1): 7609

Multi-omic lineage tracing predicts the transcriptional, epigenetic and genetic determinants of cancer evolution.

F Nadalin, M J Marzi, M Pirra Piscazzi, P Fuentes-Bravo, S Procaccia, M Climent, P Bonetti, C Rubolino, B Giuliani, I Papatheodorou, J C Marioni, F Nicassio.

Cancer is a highly heterogeneous disease, where phenotypically distinct subpopulations coexist and can be primed to different fates. Both genetic and epigenetic factors may drive cancer evolution, however little is known about whether and how such a process is pre-encoded in cancer clones. Using single-cell multi-omic lineage tracing and phenotypic assays, we investigate the predictive features of either tumour initiation or drug tolerance within the same cancer population. Clones primed to tumour initiation in vivo display two distinct transcriptional states at baseline. Remarkably, these states share a distinctive DNA accessibility profile, highlighting an epigenetic basis for tumour initiation. The drug tolerant niche is also largely pre-encoded, but only partially overlaps the tumour-initiating one and evolves following two genetically and transcriptionally distinct trajectories. Our study highlights coexisting genetic, epigenetic and transcriptional determinants of cancer evolution, unravelling the molecular complexity of pre-encoded tumour phenotypes.

DOI: https://doi.org/10.1038/s41467-024-51424-4
Nat Methods. 2024 Aug 29.

Integration of mass cytometry and mass spectrometry imaging for spatially resolved single-cell metabolic profiling.

Joana B Nunes, Marieke E Ijsselsteijn, Tamim Abdelaal, Rick Ursem, Manon van der Ploeg, Martin Giera, Bart Everts, Ahmed Mahfouz, Bram Heijs, Noel F C C de Miranda.

The integration of spatial omics technologies can provide important insights into the biology of tissues. Here we combined mass spectrometry imaging-based metabolomics and imaging mass cytometry-based immunophenotyping on a single tissue section to reveal metabolic heterogeneity at single-cell resolution within tissues and its association with specific cell populations such as cancer cells or immune cells. This approach has the potential to greatly increase our understanding of tissue-level interplay between metabolic processes and their cellular components.

DOI: https://doi.org/10.1038/s41592-024-02392-6
bioRxiv. 2024 Aug 19. pii: 2024.08.16.608287. [Epub ahead of print]

cytoKernel: Robust kernel embeddings for assessing differential expression of single cell data.

Tusharkanti Ghosh, Ryan M Baxter, Souvik Seal, Victor G Lui, Pratyaydipta Rudra, Thao Vu, Elena Wy Hsieh, Debashis Ghosh.

High-throughput sequencing of single-cell data can be used to rigorously evlauate cell specification and enable intricate variations between groups or conditions. Many popular existing methods for differential expression target differences in aggregate measurements (mean, median, sum) and limit their approaches to detect only global differential changes. We present a robust method for differential expression of single-cell data using a kernel-based score test, cytoKernel. cytoKernel is specifically designed to assess the differential expression of single cell RNA sequencing and high-dimensional flow or mass cytometry data using the full probability distribution pattern. cytoKernel is based on kernel embeddings which employs the probability distributions of the single cell data, by calculating the pairwise divergence/distance between distributions of subjects. It can detect both patterns involving aggregate changes, as well as more elusive variations that are often overlooked due to the multimodal characteristics of single cell data. We performed extensive benchmarks across both simulated and real data sets from mass cytometry data and single-cell RNA sequencing. The cytoKernel procedure effectively controls the False Discovery Rate (FDR) and shows favourable performance compared to existing methods. The method is able to identify more differential patterns than existing approaches. We apply cytoKernel to assess gene expression and protein marker expression differences from cell subpopulations in various publicly available single-cell RNAseq and mass cytometry data sets. The methods described in this paper are implemented in the open-source R package cytoKernel, which is freely available from Bioconductor at \url{http://bioconductor.org/packages/cytoKernel}.

DOI: https://doi.org/10.1101/2024.08.16.608287
Nature. 2024 Sep;633(8028): 198-206

Mechanisms that clear mutations drive field cancerization in mammary tissue.

Grand Challenge PRECISION consortium

Oncogenic mutations are abundant in the tissues of healthy individuals, but rarely form tumours1-3. Yet, the underlying protection mechanisms are largely unknown. To resolve these mechanisms in mouse mammary tissue, we use lineage tracing to map the fate of wild-type and Brca1-/-;Trp53-/- cells, and find that both follow a similar pattern of loss and spread within ducts. Clonal analysis reveals that ducts consist of small repetitive units of self-renewing cells that give rise to short-lived descendants. This offers a first layer of protection as any descendants, including oncogenic mutant cells, are constantly lost, thereby limiting the spread of mutations to a single stem cell-descendant unit. Local tissue remodelling during consecutive oestrous cycles leads to the cooperative and stochastic loss and replacement of self-renewing cells. This process provides a second layer of protection, leading to the elimination of most mutant clones while enabling the minority that by chance survive to expand beyond the stem cell-descendant unit. This leads to fields of mutant cells spanning large parts of the epithelial network, predisposing it for transformation. Eventually, clone expansion becomes restrained by the geometry of the ducts, providing a third layer of protection. Together, these mechanisms act to eliminate most cells that acquire somatic mutations at the expense of driving the accelerated expansion of a minority of cells, which can colonize large areas, leading to field cancerization.

DOI: https://doi.org/10.1038/s41586-024-07882-3
Bioinformatics. 2024 Sep 06. pii: btae535. [Epub ahead of print]

Guide assignment in single-cell CRISPR screens using crispat.

Jana M Braunger, Britta Velten.

MOTIVATION: Pooled single cell CRISPR screens have emerged as a powerful tool in functional genomics to probe the effect of genetic interventions at scale. A crucial step in the analysis of the resulting data is the assignment of cells to gRNAs corresponding to a specific genetic intervention. However, this step is challenging due to a lack of systematic benchmarks and accessible software to apply and compare different guide assignment strategies. To address this, we here propose crispat (CRISPR guide assignment tool), a Python package to facilitate the choice of a suitable guide assignment strategy for single cell CRISPR screens.RESULTS: We demonstrate the package on four single cell CRISPR interference screens at low multiplicity of infection from two studies, where crispat identifies strong differences in the number of assigned cells, downregulation of the target genes and number of discoveries across different guide assignment strategies, highlighting the need for a suitable guide assignment strategy to obtain optimal power in single cell CRISPR screens.
AVAILABILITY: Crispat is implemented in python, the source code, installation instructions and tutorials can be found at https://github.com/velten-group/crispat and it can be installed from PyPI (https://pypi.org/project/crispat/). Code to reproduce all findings in this paper is available at https://github.com/velten-group/crispat_analysis, as well as at https://zenodo.org/records/13373265.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DOI: https://doi.org/10.1093/bioinformatics/btae535
Nat Cell Biol. 2024 Aug 29.

A phosphorylation-controlled switch confers cell cycle-dependent protein relocalization.

Xiaofu Cao, Shiying Huang, Mateusz M Wagner, Yuan-Ting Cho, Din-Chi Chiu, Krista M Wartchow, Artur Lazarian, Laura Beth McIntire, Marcus B Smolka, Jeremy M Baskin.

Tools for acute manipulation of protein localization enable elucidation of spatiotemporally defined functions, but their reliance on exogenous triggers can interfere with cell physiology. This limitation is particularly apparent for studying mitosis, whose highly choreographed events are sensitive to perturbations. Here we exploit the serendipitous discovery of a phosphorylation-controlled, cell cycle-dependent localization change of the adaptor protein PLEKHA5 to develop a system for mitosis-specific protein recruitment to the plasma membrane that requires no exogenous stimulus. Mitosis-enabled anchor-away/recruiter system comprises an engineered, 15 kDa module derived from PLEKHA5 capable of recruiting functional protein cargoes to the plasma membrane during mitosis, either through direct fusion or via GFP-GFP nanobody interaction. Applications of the mitosis-enabled anchor-away/recruiter system include both knock sideways to rapidly extract proteins from their native localizations during mitosis and conditional recruitment of lipid-metabolizing enzymes for mitosis-selective editing of plasma membrane lipid content, without the need for exogenous triggers or perturbative synchronization methods.

DOI: https://doi.org/10.1038/s41556-024-01495-8