bims-pideca 2024-10-06 papers

bims-pideca

Biomed News

on Class IA PI3K signalling in development and cancer

Issue of 2024–10–06
twenty-six papers selected by
Ralitsa Radostinova Madsen, MRC-PPU

Single molecule Lipid Biosensors Mitigate Inhibition of Endogenous Effector Proteins.
Automated single-cell omics end-to-end framework with data-driven batch inference.
High-throughput optimized prime editing mediated endogenous protein tagging for pooled imaging of protein localization.
The scaffolding protein IQGAP1 enhances EGFR signaling by Promoting Oligomerization and Preventing Degradation.
Impact of essential genes on the success of genome editing experiments generating 3313 new genetically engineered mouse lines.
OrgaMapper: a robust and easy-to-use workflow for analyzing organelle positioning.
Capturing Autoinhibited PDK1 Reveals the Linker's Regulatory Role, Informing Innovative Inhibitor Design.
The art of seeing the elephant in the room: 2D embeddings of single-cell data do make sense.
Correction of a widespread bias in pooled chemical genomics screens improves their interpretability.
LYCHOS is a human hybrid of a plant-like PIN transporter and a GPCR.
Cell fixation improves performance of in situ crosslinking mass spectrometry while preserving cellular ultrastructure.
Quantitative evaluation of DNA damage repair dynamics to elucidate predictors of autism vs. cancer in individuals with germline PTEN variants.
A peptide encoded by upstream open reading frame of MYC binds to tropomyosin receptor kinase B and promotes glioblastoma growth in mice.
Cholesterol binding to VCAM-1 promotes vascular inflammation.
Daily life in the Open Biologist's second job, as a Data Curator.
Cross-expression analysis reveals patterns of coordinated gene expression in spatial transcriptomics.
Spatiotemporal control of kinases and the biomolecular tools to trace activity.
IGF-1 and insulin receptors in LepRb neurons jointly regulate body growth, bone mass, reproduction, and metabolism.
Defining precancer: a grand challenge for the cancer community.
Pervasive mislocalization of pathogenic coding variants underlying human disorders.
Regression of postprandial cardiac hypertrophy in burmese pythons is mediated by FoxO1.
Spatially exploring RNA biology in archival formalin-fixed paraffin-embedded tissues.
Assessing and mitigating batch effects in large-scale omics studies.
SCIP: A scalable, reproducible, and open-source pipeline for morphological profiling image cytometry and microscopy data.
Endothelial YAP/TAZ activation promotes atherosclerosis in a mouse model of Hutchinson-Gilford progeria syndrome.
Single-cell transcriptomes identify patient-tailored therapies for selective co-inhibition of cancer clones.

bioRxiv. 2024 Sep 16. pii: 2024.09.11.612480. [Epub ahead of print]

Single molecule Lipid Biosensors Mitigate Inhibition of Endogenous Effector Proteins.

Victoria Holmes, Morgan M C Ricci, Claire C Weckerly, Michael Worcester, Gerald R V Hammond.

Genetically encoded lipid biosensors are essential cell biological tools. They are the only technique that provide real time, spatially resolved kinetic data for lipid dynamics in living cells. Despite clear strengths, these tools also carry significant drawbacks; most notably, lipid molecules bound to biosensors cannot engage with their effectors, causing inhibition. Here, we show that although PI 3-kinase (PI3K)-mediated activation of Akt is not significantly reduced in a cell population transfected with a PH-Akt1 PIP 3 /PI(3,4)P 2 biosensor, single cells expressing the PH-Akt at visible levels (used for live-cell imaging) have no activated Akt at all. Tagging endogenous AKT1 with neonGreen at its genomic locus reveals its EGF-mediated translocation to the plasma membrane, accumulating at densities of ~0.3 molecules/ µ m 2 . Co-transfection with the PH-Akt biosensor or other PIP 3 biosensors completely blocks this translocation, despite robust recruitment of the biosensors. A partial inhibition is even observed with PI(3,4)P 2 -selective biosensor. However, we found that expressing lipid biosensors at low levels, comparable with those of endogenous AKT, produced no such inhibition. Helpfully, these single-molecule biosensors revealed improved dynamic range and kinetic fidelity compared with over-expressed biosensor. This approach represents a less invasive way to probe spatiotemporal dynamics of the PI3K pathway in living cells.

DOI: https://doi.org/10.1101/2024.09.11.612480
Cell Syst. 2024 Sep 28. pii: S2405-4712(24)00267-9. [Epub ahead of print]

Automated single-cell omics end-to-end framework with data-driven batch inference.

Yuan Wang, William Thistlethwaite, Alicja Tadych, Frederique Ruf-Zamojski, Daniel J Bernard, Antonio Cappuccio, Elena Zaslavsky, Xi Chen, Stuart C Sealfon, Olga G Troyanskaya.

  To facilitate single-cell multi-omics analysis and improve reproducibility, we present single-cell pipeline for end-to-end data integration (SPEEDI), a fully automated end-to-end framework for batch inference, data integration, and cell-type labeling. SPEEDI introduces data-driven batch inference and transforms the often heterogeneous data matrices obtained from different samples into a uniformly annotated and integrated dataset. Without requiring user input, it automatically selects parameters and executes pre-processing, sample integration, and cell-type mapping. It can also perform downstream analyses of differential signals between treatment conditions and gene functional modules. SPEEDI's data-driven batch-inference method works with widely used integration and cell-typing tools. By developing data-driven batch inference, providing full end-to-end automation, and eliminating parameter selection, SPEEDI improves reproducibility and lowers the barrier to obtaining biological insight from these valuable single-cell datasets. The SPEEDI interactive web application can be accessed at https://speedi.princeton.edu/. A record of this paper's transparent peer review process is included in the supplemental information.

Keywords:  batch identification; cell-type mapping; information theory; integration; scATAC-seq; scRNA-seq; single-cell genomics

DOI:  https://doi.org/10.1016/j.cels.2024.09.003
bioRxiv. 2024 Sep 17. pii: 2024.09.16.613361. [Epub ahead of print]

High-throughput optimized prime editing mediated endogenous protein tagging for pooled imaging of protein localization.

Henry M Sanchez, Tomer Lapidot, Ophir Shalem.

The subcellular organization of proteins carries important information on cellular state and gene function, yet currently there are no technologies that enable accurate measurement of subcellular protein localizations at scale. Here we develop an approach for pooled endogenous protein tagging using prime editing, which coupled with an optical readout and sequencing, provides a snapshot of proteome organization in a manner akin to perturbation-based CRISPR screens. We constructed a pooled library of 17,280 pegRNAs designed to exhaustively tag 60 endogenous proteins spanning diverse localization patterns and explore a large space of genomic and pegRNA design parameters. Pooled measurements of tagging efficiency uncovered both genomic and pegRNA features associated with increased efficiency, including epigenetic states and interactions with transcription. We integrate pegRNA features into a computational model with predictive value for tagging efficiency to constrain the design space of pegRNAs for large-scale peptide knock-in. Lastly, we show that combining in-situ pegRNA sequencing with high-throughput deep learning image analysis, enables exploration of subcellular protein localization patterns for many proteins in parallel following a single pooled lentiviral transduction, setting the stage for scalable studies of proteome dynamics across cell types and environmental perturbations.

DOI: https://doi.org/10.1101/2024.09.16.613361
J Biol Chem. 2024 Sep 30. pii: S0021-9258(24)02346-9. [Epub ahead of print] 107844

The scaffolding protein IQGAP1 enhances EGFR signaling by Promoting Oligomerization and Preventing Degradation.

V Siddartha Yerramilli, Guanyu Lin, Jessica L Reisinger, Rachel M Hemmerlin, Samantha K Lindberg, Karin Plante, Alonzo H Ross, Arne Gericke, Suzanne Scarlata.

IQGAP1 is a large, multi-domain scaffold that connects and modulates different signaling networks including the one initiated by epidermal growth factor (EGF). In this study, we have used live cell fluorescence imaging methods along with other biochemical techniques to follow the mechanisms used by IQGAP1 to enhance EGF signaling. We show that IQGAP1 enhances EGF signaling by promoting the oligomerization of its receptor, EGFR, upon EGF addition along with concurrent IQGAP oligomerization. Using cellular markers, we find that IQGAP1 promotes the plasma membrane localization of EGFR and promotes association to one of its phosphoinositide lipid pathway ligands, PI(3,4,5)P3. Additionally, we find that binding of EGFR to IQGAP1 protects EGFR from lysosomal degradation. Taken together, our results show that IQGAP1 enhances EGF-mediated pathway progression through mechanisms that augment simple scaffolding activities.

DOI: https://doi.org/10.1016/j.jbc.2024.107844
Sci Rep. 2024 09 30. 14(1): 22626

Impact of essential genes on the success of genome editing experiments generating 3313 new genetically engineered mouse lines.

International Mouse Phenotyping Consortium

  The International Mouse Phenotyping Consortium (IMPC) systematically produces and phenotypes mouse lines with presumptive null mutations to provide insight into gene function. The IMPC now uses the programmable RNA-guided nuclease Cas9 for its increased capacity and flexibility to efficiently generate null alleles in the C57BL/6N strain. In addition to being a valuable novel and accessible research resource, the production of 3313 knockout mouse lines using comparable protocols provides a rich dataset to analyze experimental and biological variables affecting in vivo gene engineering with Cas9. Mouse line production has two critical steps - generation of founders with the desired allele and germline transmission (GLT) of that allele from founders to offspring. A systematic evaluation of the variables impacting success rates identified gene essentiality as the primary factor influencing successful production of null alleles. Collectively, our findings provide best practice recommendations for using Cas9 to generate alleles in mouse essential genes, many of which are orthologs of genes linked to human disease.

Keywords:  Cas9; Genome editing; Knockout; Mouse

DOI:  https://doi.org/10.1038/s41598-024-72418-8
BMC Biol. 2024 Sep 30. 22(1): 220

OrgaMapper: a robust and easy-to-use workflow for analyzing organelle positioning.

Christopher Schmied, Michael Ebner, Paula Samsó, Rozemarijn Van Der Veen, Volker Haucke, Martin Lehmann.

   BACKGROUND: Eukaryotic cells are highly compartmentalized by a variety of organelles that carry out specific cellular processes. The position of these organelles within the cell is elaborately regulated and vital for their function. For instance, the position of lysosomes relative to the nucleus controls their degradative capacity and is altered in pathophysiological conditions. The molecular components orchestrating the precise localization of organelles remain incompletely understood. A confounding factor in these studies is the fact that organelle positioning is surprisingly non-trivial to address e.g., perturbations that affect the localization of organelles often lead to secondary phenotypes such as changes in cell or organelle size. These phenotypes could potentially mask effects or lead to the identification of false positive hits. To uncover and test potential molecular components at scale, accurate and easy-to-use analysis tools are required that allow robust measurements of organelle positioning.
RESULTS: Here, we present an analysis workflow for the faithful, robust, and quantitative analysis of organelle positioning phenotypes. Our workflow consists of an easy-to-use Fiji plugin and an R Shiny App. These tools enable users without background in image or data analysis to (1) segment single cells and nuclei and to detect organelles, (2) to measure cell size and the distance between detected organelles and the nucleus, (3) to measure intensities in the organelle channel plus one additional channel, (4) to measure radial intensity profiles of organellar markers, and (5) to plot the results in informative graphs. Using simulated data and immunofluorescent images of cells in which the function of known factors for lysosome positioning has been perturbed, we show that the workflow is robust against common problems for the accurate assessment of organelle positioning such as changes of cell shape and size, organelle size and background.
CONCLUSIONS: OrgaMapper is a versatile, robust, and easy-to-use automated image analysis workflow that can be utilized in microscopy-based hypothesis testing and screens. It effectively allows for the mapping of the intracellular space and enables the discovery of novel regulators of organelle positioning.

Keywords:  Data analysis; Fiji; Image analysis; ImageJ; Organelle position; R; Segmentation; Shiny

DOI:  https://doi.org/10.1186/s12915-024-02015-8
J Chem Inf Model. 2024 Sep 30.

Capturing Autoinhibited PDK1 Reveals the Linker's Regulatory Role, Informing Innovative Inhibitor Design.

Liang Xu, Hyunbum Jang, Ruth Nussinov.

PDK1 is crucial for PI3K/AKT/mTOR and Ras/MAPK cancer signaling. It phosphorylates AKT in a PIP3-dependent but S6K, SGK, and RSK kinases in a PIP3-independent manner. Unlike its substrates, its autoinhibited monomeric state has been unclear, likely due to its low population time, and phosphorylation in the absence of PIP3 has been puzzling too. Here, guided by experimental data, we constructed models and performed all-atom molecular dynamics simulations. In the autoinhibited PDK1 conformation that resembles autoinhibited AKT, binding of the linker between the kinase and PH domains to the PIF-binding pocket promotes the formation of the Glu130-Lys111 salt bridge and weakens the association of the kinase domain with the PH domain, shifting the population from the autoinhibited state to states accessible to the membrane and its kinase substrates. The interaction of the substrates' hydrophobic motif and the PDK1 PIF-binding pocket facilitates the release of the autoinhibition even in the absence of PIP3. Phosphorylation of the serine-rich motif within the linker further attenuates the association of the PH domain with the kinase domain. These suggest that while the monomeric autoinhibited state is relatively stable, it can readily shift to its active, catalysis-prone state to phosphorylate its diverse substrates. Our findings reveal the PDK1 activation mechanism and discover the regulatory role of PDK1's linker, which lead to two innovative linker-based inhibitor strategies: (i) locking the autoinhibited PDK1 through optimization of the interactions of AKT inhibitors with the PH domain of PDK1 and (ii) analogs (small molecules or peptidomimetics) that mimic the linker interactions with the PIF-binding pocket.

DOI: https://doi.org/10.1021/acs.jcim.4c01392
PLoS Comput Biol. 2024 Oct;20(10): e1012403

The art of seeing the elephant in the room: 2D embeddings of single-cell data do make sense.

Jan Lause, Philipp Berens, Dmitry Kobak.

A recent paper claimed that t-SNE and UMAP embeddings of single-cell datasets are "specious" and fail to capture true biological structure. The authors argued that such embeddings are as arbitrary and as misleading as forcing the data into an elephant shape. Here we show that this conclusion was based on inadequate and limited metrics of embedding quality. More appropriate metrics quantifying neighborhood and class preservation reveal the elephant in the room: while t-SNE and UMAP embeddings of single-cell data do not preserve high-dimensional distances, they can nevertheless provide biologically relevant information.

DOI: https://doi.org/10.1371/journal.pcbi.1012403
Mol Syst Biol. 2024 Sep 30.

Correction of a widespread bias in pooled chemical genomics screens improves their interpretability.

Lili M Kim, Horia Todor, Carol A Gross.

  Chemical genomics is a powerful and increasingly accessible technique to probe gene function, gene-gene interactions, and antibiotic synergies and antagonisms. Indeed, multiple large-scale pooled datasets in diverse organisms have been published. Here, we identify an artifact arising from uncorrected differences in the number of cell doublings between experiments within such datasets. We demonstrate that this artifact is widespread, show how it causes spurious gene-gene and drug-drug correlations, and present a simple but effective post hoc method for removing its effects. Using several published datasets, we demonstrate that this correction removes spurious correlations between genes and conditions, improving data interpretability and revealing new biological insights. Finally, we determine experimental factors that predispose a dataset for this artifact and suggest a set of experimental and computational guidelines for performing pooled chemical genomics experiments that will maximize the potential of this powerful technique.

Keywords:  Bacterial Screens; Chemical Genomics; Data Analysis; Error Correction; Pooled Screens

DOI:  https://doi.org/10.1038/s44320-024-00069-y
Nature. 2024 Oct 02.

LYCHOS is a human hybrid of a plant-like PIN transporter and a GPCR.

Charles Bayly-Jones, Christopher J Lupton, Alastair C Keen, Shuqi Dong, Chantel Mastos, Wentong Luo, Chunyi Qian, Gareth D Jones, Hari Venugopal, Yong-Gang Chang, Ronald J Clarke, Michelle L Halls, Andrew M Ellisdon.

Lysosomes have crucial roles in regulating eukaryotic metabolism and cell growth by acting as signalling platforms to sense and respond to changes in nutrient and energy availability1. LYCHOS (GPR155) is a lysosomal transmembrane protein that functions as a cholesterol sensor, facilitating the cholesterol-dependent activation of the master protein kinase mechanistic target of rapamycin complex 1 (mTORC1)2. However, the structural basis of LYCHOS assembly and activity remains unclear. Here we determine several high-resolution cryo-electron microscopy structures of human LYCHOS, revealing a homodimeric transmembrane assembly of a transporter-like domain fused to a G-protein-coupled receptor (GPCR) domain. The class B2-like GPCR domain is captured in the apo state and packs against the surface of the transporter-like domain, providing an unusual example of a GPCR as a domain in a larger transmembrane assembly. Cholesterol sensing is mediated by a conserved cholesterol-binding motif, positioned between the GPCR and transporter domains. We reveal that the LYCHOS transporter-like domain is an orthologue of the plant PIN-FORMED (PIN) auxin transporter family, and has greater structural similarity to plant auxin transporters than to known human transporters. Activity assays support a model in which the LYCHOS transporter and GPCR domains coordinate to sense cholesterol and regulate mTORC1 activation.

DOI: https://doi.org/10.1038/s41586-024-08012-9
Nat Commun. 2024 Oct 02. 15(1): 8537

Cell fixation improves performance of in situ crosslinking mass spectrometry while preserving cellular ultrastructure.

Andrew R M Michael, Bruno C Amaral, Kallie L Ball, Kristen H Eiriksson, David C Schriemer.

Crosslinking mass spectrometry (XL-MS) has the potential to map the interactome of the cell with high resolution and depth of coverage. However, current in vivo XL-MS methods are hampered by crosslinkers that demonstrate low cell permeability and require long reaction times. Consequently, interactome sampling is not high and long incubation times can distort the cell, bringing into question the validity any protein interactions identified by the method. We address these issues with a fast formaldehyde-based fixation method applied prior to the introduction of secondary crosslinkers. Using human A549 cells and a range of reagents, we show that 4% formaldehyde fixation with membrane permeabilization preserves cellular ultrastructure and simultaneously improves reaction conditions for in situ XL-MS. Protein labeling yields can be increased even for nominally membrane-permeable reagents, and surprisingly, high-concentration formaldehyde does not compete with conventional amine-reactive crosslinking reagents. Prefixation with permeabilization uncouples cellular dynamics from crosslinker dynamics, enhancing control over crosslinking yield and permitting the use of any chemical crosslinker.

DOI: https://doi.org/10.1038/s41467-024-52844-y
PLoS Comput Biol. 2024 Oct 02. 20(10): e1012449

Quantitative evaluation of DNA damage repair dynamics to elucidate predictors of autism vs. cancer in individuals with germline PTEN variants.

Ruipeng Wei, Masahiro Hitomi, Tammy Sadler, Lamis Yehia, Daniela Calvetti, Jacob Scott, Charis Eng.

Persons with germline variants in the tumor suppressor gene phosphatase and tensin homolog, PTEN, are molecularly diagnosed with PTEN hamartoma tumor syndrome (PHTS). PHTS confers high risks of specific malignancies, and up to 23% of the patients are diagnosed with autism spectrum disorder (ASD) and/or developmental delay (DD). The accurate prediction of these two seemingly disparate phenotypes (cancer vs. ASD/DD) for PHTS at the individual level remains elusive despite the available statistical prevalence of specific phenotypes of the syndrome at the population level. The pleiotropy of the syndrome may, in part, be due to the alterations of the key multi-functions of PTEN. Maintenance of genome integrity is one of the key biological functions of PTEN, but no integrative studies have been conducted to quantify the DNA damage response (DDR) in individuals with PHTS and to relate to phenotypes and genotypes. In this study, we used 43 PHTS patient-derived lymphoblastoid cell lines (LCLs) to investigate the associations between DDR and PTEN genotypes and/or clinical phenotypes ASD/DD vs. cancer. The dynamics of DDR of γ-irradiated LCLs were analyzed using the exponential decay mathematical model to fit temporal changes in γH2AX levels which report the degree of DNA damage. We found that PTEN nonsense variants are associated with less efficient DNA damage repair ability resulting in higher DNA damage levels at 24 hours after irradiation compared to PTEN missense variants. Regarding PHTS phenotypes, LCLs from PHTS individuals with ASD/DD showed faster DNA damage repairing rate than those from patients without ASD/DD or cancer. We also applied the reaction-diffusion partial differential equation (PDE) mathematical model, a tumor cell growth model with a DNA damage term, to accurately describe the DDR process in the LCLs. For each LCL, we can derive parameters of the PDE. Then we averaged the numerical results by PHTS phenotypes. By performing simple subtraction of two subgroup average results, we found that PHTS-ASD/DD is associated with higher live cell density at lower DNA damage level but lower cell density level at higher DNA damage level compared to LCLs from individuals with PHTS-cancer and PHTS-neither.

DOI: https://doi.org/10.1371/journal.pcbi.1012449
Sci Transl Med. 2024 Oct 02. 16(767): eadk9524

A peptide encoded by upstream open reading frame of MYC binds to tropomyosin receptor kinase B and promotes glioblastoma growth in mice.

Fanying Li, Kailin Yang, Xinya Gao, Maolei Zhang, Danling Gu, Xujia Wu, Chenfei Lu, Qiulian Wu, Deobrat Dixit, Ryan C Gimple, Yongping You, Stephen C Mack, Yu Shi, Tiebang Kang, Sameer A Agnihotri, Michael D Taylor, Jeremy N Rich, Nu Zhang, Xiuxing Wang.

MYC promotes tumor growth through multiple mechanisms. Here, we show that, in human glioblastomas, the variant MYC transcript encodes a 114-amino acid peptide, MYC pre-mRNA encoded protein (MPEP), from the upstream open reading frame (uORF) MPEP. Secreted MPEP promotes patient-derived xenograft tumor growth in vivo, independent of MYC through direct binding, and activation of tropomyosin receptor kinase B (TRKB), which induces downstream AKT-mTOR signaling. Targeting MPEP through genetic ablation reduced growth of patient-derived 4121 and 3691 glioblastoma stem cells. Administration of an MPEP-neutralizing antibody in combination with a small-molecule TRKB inhibitor reduced glioblastoma growth in patient-derived xenograft tumor-bearing mice. The overexpression of MPEP in surgical glioblastoma specimens predicted a poor prognosis, supporting its clinical relevance. In summary, our results demonstrate that tumor-specific translation of a MYC-associated uORF promotes glioblastoma growth, suggesting a new therapeutic strategy for glioblastoma.

DOI: https://doi.org/10.1126/scitranslmed.adk9524
bioRxiv. 2024 Sep 18. pii: 2024.09.17.613543. [Epub ahead of print]

Cholesterol binding to VCAM-1 promotes vascular inflammation.

John P Kennelly, Xu Xiao, Yajing Gao, Sumin Kim, Soon-Gook Hong, Miranda Villanueva, Alessandra Ferrari, Lauri Vanharanta, Alexander Nguyen, Rohith T Nagari, Nikolas R Burton, Marcus J Tol, Andrew P Becker, Min Jae Lee, Elina Ikonen, Keriann M Backus, Julia J Mack, Peter Tontonoz.

Hypercholesterolemia has long been implicated in endothelial cell (EC) dysfunction, but the mechanisms by which excess cholesterol causes vascular pathology are incompletely understood. Here we used a cholesterol-mimetic probe to map cholesterol-protein interactions in primary human ECs and discovered that cholesterol binds to and stabilizes the adhesion molecule VCAM-1. We show that accessible plasma membrane (PM) cholesterol in ECs is acutely responsive to inflammatory stimuli and that the nonvesicular cholesterol transporter Aster-A regulates VCAM-1 stability in activated ECs by controlling the size of this pool. Deletion of Aster-A in ECs increases VCAM-1 protein, promotes immune cell recruitment to vessels, and impairs pulmonary immune homeostasis. Conversely, depleting cholesterol from the endothelium in vivo dampens VCAM-1 induction in response to inflammatory stimuli. These findings identify cholesterol binding to VCAM-1 as a key step during EC activation and provide a biochemical explanation for the ability of excess membrane cholesterol to promote immune cell recruitment to the endothelium.

DOI: https://doi.org/10.1101/2024.09.17.613543
Wellcome Open Res. 2024 ;9 523

Daily life in the Open Biologist's second job, as a Data Curator.

Livia C T Scorza, Tomasz Zieliński, Irina Kalita, Alessia Lepore, Meriem El Karoui, Andrew J Millar.

   Background: Data reusability is the driving force of the research data life cycle. However, implementing strategies to generate reusable data from the data creation to the sharing stages is still a significant challenge. Even when datasets supporting a study are publicly shared, the outputs are often incomplete and/or not reusable. The FAIR (Findable, Accessible, Interoperable, Reusable) principles were published as a general guidance to promote data reusability in research, but the practical implementation of FAIR principles in research groups is still falling behind. In biology, the lack of standard practices for a large diversity of data types, data storage and preservation issues, and the lack of familiarity among researchers are some of the main impeding factors to achieve FAIR data. Past literature describes biological curation from the perspective of data resources that aggregate data, often from publications.
Methods: Our team works alongside data-generating, experimental researchers so our perspective aligns with publication authors rather than aggregators. We detail the processes for organizing datasets for publication, showcasing practical examples from data curation to data sharing. We also recommend strategies, tools and web resources to maximize data reusability, while maintaining research productivity.
Conclusion: We propose a simple approach to address research data management challenges for experimentalists, designed to promote FAIR data sharing. This strategy not only simplifies data management, but also enhances data visibility, recognition and impact, ultimately benefiting the entire scientific community.

Keywords:  FAIR; Open science; accessibility; biological data; data curation; data sharing; datasets; metadata.; repositories; reproducibility

DOI:  https://doi.org/10.12688/wellcomeopenres.22899.1
bioRxiv. 2024 Sep 21. pii: 2024.09.17.613579. [Epub ahead of print]

Cross-expression analysis reveals patterns of coordinated gene expression in spatial transcriptomics.

Ameer Sarwar, Mara Rue, Leon French, Helen Cross, Xiaoyin Chen, Jesse Gillis.

Spatial transcriptomics promises to transform our understanding of tissue biology by molecularly profiling individual cells in situ. A fundamental question they allow us to ask is how nearby cells orchestrate their gene expression. To investigate this, we introduce cross-expression, a novel framework for discovering gene pairs that coordinate their expression across neighboring cells. Just as co-expression quantifies synchronized gene expression within the same cells, cross-expression measures coordinated gene expression between spatially adjacent cells, allowing us to understand tissue gene expression programs with single cell resolution. Using this framework, we recover ligand-receptor partners and discover gene combinations marking anatomical regions. More generally, we create cross-expression networks to find gene modules with orchestrated expression patterns. Finally, we provide an efficient R package to facilitate cross-expression analysis, quantify effect sizes, and generate novel visualizations to better understand spatial gene expression programs.

DOI: https://doi.org/10.1101/2024.09.17.613579
J Biol Chem. 2024 Oct 01. pii: S0021-9258(24)02348-2. [Epub ahead of print] 107846

Spatiotemporal control of kinases and the biomolecular tools to trace activity.

Jeremy C Burton, Fredejah Royer, Neil J Grimsey.

The delicate balance of cell physiology is implicitly tied to the expression and activation of proteins. Post-translational modifications offer a tool to dynamically switch protein activity on and off to orchestrate a wide range of protein-protein interactions to tune signal transduction during cellular homeostasis and pathological responses. There is a growing acknowledgment that subcellular locations of kinases define the spatial network of potential scaffolds, adaptors, and substrates. These highly ordered and localized biomolecular microdomains confer a spatially distinct bias in the outcomes of kinase activity. Furthermore, they may hold essential clues to the underlying mechanisms that promote disease. Developing tools to dissect the spatiotemporal activation of kinases is critical to reveal these mechanisms and promote the development of spatially targeted kinase inhibitors. Here, we discuss the spatial regulation of kinases, the tools used to detect their activity, and their potential impact on human health.

DOI: https://doi.org/10.1016/j.jbc.2024.107846
bioRxiv. 2024 Sep 20. pii: 2024.09.20.614140. [Epub ahead of print]

IGF-1 and insulin receptors in LepRb neurons jointly regulate body growth, bone mass, reproduction, and metabolism.

Mengjie Wang, Piotr J Czernik, Beata Lecka-Czernik, Yong Xu, Jennifer W Hill.

Leptin receptor (LepRb)-expressing neurons are known to link body growth and reproduction, but whether these functions are mediated via insulin-like growth factor 1 receptor (IGF1R) signaling is unknown. IGF-1 and insulin can bind to each other's receptors, permitting IGF-1 signaling in the absence of IGF1R. Therefore, we created mice lacking IGF1R exclusively in LepRb neurons (IGF1R LepRb mice) and simultaneously lacking IGF1R and insulin receptor (IR) in LepRb neurons (IGF1R/IR LepRb mice) and then characterized their body growth, bone morphology, reproductive and metabolic functions. We found that IGF1R and IR in LepRb neurons were required for normal timing of pubertal onset, while IGF1R in LepRb neurons played a predominant role in regulating adult fertility and exerted protective effects against reproductive aging. Accompanying these reproductive deficits, IGF1R LepRb mice and IGF1R/IR LepRb mice had transient growth retardation. Notably, IGF1R in LepRb neurons was indispensable for normal trabecular and cortical bone mass accrual in both sexes. These findings suggest that IGF1R in LepRb neurons is involved in the interaction among body growth, bone development, and reproduction. Though only mild changes in body weight were detected, simultaneous deletion of IGF1R and IR in LepRb neurons caused dramatically increased fat mass composition, decreased lean mass composition, lower energy expenditure, and locomotor activity in both sexes. Male IGF1R/IR LepRb mice exhibited impaired insulin sensitivity. These findings suggest that IGF1R and IR in LepRb neurons jointly regulated body composition, energy balance, and glucose homeostasis. Taken together, our studies identified the sex-dependent complex roles of IGF1R and IR in LepRb neurons in regulating body growth, reproduction, and metabolism.

DOI: https://doi.org/10.1101/2024.09.20.614140
Nat Rev Cancer. 2024 Oct 01.

Defining precancer: a grand challenge for the cancer community.

Precancer Think Tank Team

The term 'precancer' typically refers to an early stage of neoplastic development that is distinguishable from normal tissue owing to molecular and phenotypic alterations, resulting in abnormal cells that are at least partially self-sustaining and function outside of normal cellular cues that constrain cell proliferation and survival. Although such cells are often histologically distinct from both the corresponding normal and invasive cancer cells of the same tissue origin, defining precancer remains a challenge for both the research and clinical communities. Once sufficient molecular and phenotypic changes have occurred in the precancer, the tissue is identified as a 'cancer' by a histopathologist. While even diagnosing cancer can at times be challenging, the determination of invasive cancer is generally less ambiguous and suggests a high likelihood of and potential for metastatic disease. The 'hallmarks of cancer' set out the fundamental organizing principles of malignant transformation but exactly how many of these hallmarks and in what configuration they define precancer has not been clearly and consistently determined. In this Expert Recommendation, we provide a starting point for a conceptual framework for defining precancer, which is based on molecular, pathological, clinical and epidemiological criteria, with the goal of advancing our understanding of the initial changes that occur and opportunities to intervene at the earliest possible time point.

DOI: https://doi.org/10.1038/s41568-024-00744-0
Cell. 2024 Sep 25. pii: S0092-8674(24)01021-3. [Epub ahead of print]

Pervasive mislocalization of pathogenic coding variants underlying human disorders.

Jessica Lacoste, Marzieh Haghighi, Shahan Haider, Chloe Reno, Zhen-Yuan Lin, Dmitri Segal, Wesley Wei Qian, Xueting Xiong, Tanisha Teelucksingh, Esteban Miglietta, Hamdah Shafqat-Abbasi, Pearl V Ryder, Rebecca Senft, Beth A Cimini, Ryan R Murray, Chantal Nyirakanani, Tong Hao, Gregory G McClain, Frederick P Roth, Michael A Calderwood, David E Hill, Marc Vidal, S Stephen Yi, Nidhi Sahni, Jian Peng, Anne-Claude Gingras, Shantanu Singh, Anne E Carpenter, Mikko Taipale.

Widespread sequencing has yielded thousands of missense variants predicted or confirmed as disease causing. This creates a new bottleneck: determining the functional impact of each variant-typically a painstaking, customized process undertaken one or a few genes and variants at a time. Here, we established a high-throughput imaging platform to assay the impact of coding variation on protein localization, evaluating 3,448 missense variants of over 1,000 genes and phenotypes. We discovered that mislocalization is a common consequence of coding variation, affecting about one-sixth of all pathogenic missense variants, all cellular compartments, and recessive and dominant disorders alike. Mislocalization is primarily driven by effects on protein stability and membrane insertion rather than disruptions of trafficking signals or specific interactions. Furthermore, mislocalization patterns help explain pleiotropy and disease severity and provide insights on variants of uncertain significance. Our publicly available resource extends our understanding of coding variation in human diseases.

DOI: https://doi.org/10.1016/j.cell.2024.09.003
Proc Natl Acad Sci U S A. 2024 Oct 08. 121(41): e2408719121

Regression of postprandial cardiac hypertrophy in burmese pythons is mediated by FoxO1.

Thomas G Martin, Dakota R Hunt, Stephen J Langer, Yuxiao Tan, Christopher C Ebmeier, Leslie A Leinwand.

  As ambush-hunting predators that consume large prey after long intervals of fasting, Burmese pythons evolved with unique adaptations for modulating organ structure and function. Among these is cardiac hypertrophy that develops within three days following a meal (Andersen et al., 2005, Secor, 2008), which we previously showed was initiated by circulating growth factors (Riquelme et al., 2011). Postprandial cardiac hypertrophy in pythons also rapidly regresses with subsequent fasting (Secor, 2008); however, the molecular mechanisms that regulate the dynamic cardiac remodeling in pythons during digestion are largely unknown. In this study, we employed a multiomics approach coupled with targeted molecular analyses to examine remodeling of the python ventricular transcriptome and proteome throughout digestion. We found that forkhead box protein O1 (FoxO1) signaling was suppressed prior to hypertrophy development and then activated during regression, which coincided with decreased and then increased expression, respectively, of FoxO1 transcriptional targets involved in proteolysis. To define the molecular mechanistic role of FoxO1 in hypertrophy regression, we used cultured mammalian cardiomyocytes treated with postfed python plasma. Hypertrophy regression both in pythons and in vitro coincided with activation of FoxO1-dependent autophagy; however, the introduction of a FoxO1-specific inhibitor prevented both regression of cell size and autophagy activation. Finally, to determine whether FoxO1 activation could induce regression, we generated an adenovirus expressing a constitutively active FoxO1. FoxO1 activation was sufficient to prevent and reverse postfed plasma-induced hypertrophy, which was partially prevented by autophagy inhibition. Our results indicate that modulation of FoxO1 activity contributes to the dynamic ventricular remodeling in postprandial Burmese pythons.

Keywords:  Burmese python; FoxO1; autophagy; cardiac hypertrophy; hypertrophy regression

DOI:  https://doi.org/10.1073/pnas.2408719121
Cell. 2024 Sep 25. pii: S0092-8674(24)01019-5. [Epub ahead of print]

Spatially exploring RNA biology in archival formalin-fixed paraffin-embedded tissues.

Zhiliang Bai, Dingyao Zhang, Yan Gao, Bo Tao, Daiwei Zhang, Shuozhen Bao, Archibald Enninful, Yadong Wang, Haikuo Li, Graham Su, Xiaolong Tian, Ningning Zhang, Yang Xiao, Yang Liu, Mark Gerstein, Mingyao Li, Yi Xing, Jun Lu, Mina L Xu, Rong Fan.

  The capability to spatially explore RNA biology in formalin-fixed paraffin-embedded (FFPE) tissues holds transformative potential for histopathology research. Here, we present pathology-compatible deterministic barcoding in tissue (Patho-DBiT) by combining in situ polyadenylation and computational innovation for spatial whole transcriptome sequencing, tailored to probe the diverse RNA species in clinically archived FFPE samples. It permits spatial co-profiling of gene expression and RNA processing, unveiling region-specific splicing isoforms, and high-sensitivity transcriptomic mapping of clinical tumor FFPE tissues stored for 5 years. Furthermore, genome-wide single-nucleotide RNA variants can be captured to distinguish malignant subclones from non-malignant cells in human lymphomas. Patho-DBiT also maps microRNA regulatory networks and RNA splicing dynamics, decoding their roles in spatial tumorigenesis. Single-cell level Patho-DBiT dissects the spatiotemporal cellular dynamics driving tumor clonal architecture and progression. Patho-DBiT stands poised as a valuable platform to unravel rich RNA biology in FFPE tissues to aid in clinical pathology evaluation.

Keywords:  RNA biology; clinical FFPE tissue; histopathology; microRNA; single-nucleotide RNA variants; spatial omics; spatiotemporal dynamics; splicing isoforms; whole transcriptome

DOI:  https://doi.org/10.1016/j.cell.2024.09.001
Genome Biol. 2024 Oct 03. 25(1): 254

Assessing and mitigating batch effects in large-scale omics studies.

Ying Yu, Yuanbang Mai, Yuanting Zheng, Leming Shi.

Batch effects in omics data are notoriously common technical variations unrelated to study objectives, and may result in misleading outcomes if uncorrected, or hinder biomedical discovery if over-corrected. Assessing and mitigating batch effects is crucial for ensuring the reliability and reproducibility of omics data and minimizing the impact of technical variations on biological interpretation. In this review, we highlight the profound negative impact of batch effects and the urgent need to address this challenging problem in large-scale omics studies. We summarize potential sources of batch effects, current progress in evaluating and correcting them, and consortium efforts aiming to tackle them.

DOI: https://doi.org/10.1186/s13059-024-03401-9
Cytometry A. 2024 Oct 01.

SCIP: A scalable, reproducible, and open-source pipeline for morphological profiling image cytometry and microscopy data.

Maxim Lippeveld, Daniel Peralta, Andrew Filby, Yvan Saeys.

  Imaging flow cytometry (IFC) provides single-cell imaging data at a high acquisition rate. It is increasingly used in image-based profiling experiments consisting of hundreds of thousands of multi-channel images of cells. Currently available software solutions for processing microscopy data can provide good results in downstream analysis, but are limited in efficiency and scalability, and often ill-adapted to IFC data. In this work, we propose Scalable Cytometry Image Processing (SCIP), a Python software that efficiently processes images from IFC and standard microscopy datasets. We also propose a file format for efficiently storing IFC data. We showcase our contributions on two large-scale microscopy and one IFC datasets, all of which are publicly available. Our results show that SCIP can extract the same kind of information as other tools, in a much shorter time and in a more scalable manner.

Keywords:  data analysis; distributed computing; feature extraction; imaging flow cytometry; machine learning

DOI:  https://doi.org/10.1002/cyto.a.24896
J Clin Invest. 2024 Oct 01. pii: e173448. [Epub ahead of print]

Endothelial YAP/TAZ activation promotes atherosclerosis in a mouse model of Hutchinson-Gilford progeria syndrome.

Ana Barettino, Cristina González-Gómez, Pilar Gonzalo, María J Andrés-Manzano, Carlos R Guerrero, Francisco M Espinosa, Rosa M Carmona, Yaazan Blanco, Beatriz Dorado, Carlos Torroja, Fátima Sánchez-Cabo, Ana Quintas, Alberto Benguría, Ana Dopazo, Ricardo García, Ignacio Benedicto, Vicente Andrés.

  Hutchinson-Gilford progeria syndrome (HGPS) is an extremely rare disease caused by the expression of progerin, an aberrant protein produced by a point mutation in the LMNA gene. HGPS patients show accelerated aging and die prematurely mainly from complications of atherosclerosis such as myocardial infarction, heart failure, or stroke. However, the mechanisms underlying HGPS vascular pathology remain ill defined. We used single-cell RNA sequencing to characterize the aorta in progerin-expressing LmnaG609G/G609G mice and wild-type controls, with a special focus on endothelial cells (ECs). HGPS ECs showed gene expression changes associated with extracellular matrix alterations, increased leukocyte extravasation, and activation of the yes-associated protein 1/transcriptional activator with PDZ-binding domain (YAP/TAZ) mechanosensing pathway, all validated by different techniques. Atomic force microscopy experiments demonstrated stiffer subendothelial extracellular matrix in progeroid aortas, and ultrasound assessment of live HGPS mice revealed disturbed aortic blood flow, both key inducers of the YAP/TAZ pathway in ECs. YAP/TAZ inhibition with verteporfin reduced leukocyte accumulation in the aortic intimal layer and decreased atherosclerosis burden in progeroid mice. Our findings identify endothelial YAP/TAZ signaling as a key mechanism of HGPS vascular disease and open a new avenue for the development of YAP/TAZ targeting drugs to ameliorate progerin-induced atherosclerosis.

Keywords:  Aging; Atherosclerosis; Cardiovascular disease; Endothelial cells; Vascular biology

DOI:  https://doi.org/10.1172/JCI173448
Nat Commun. 2024 Oct 03. 15(1): 8579

Single-cell transcriptomes identify patient-tailored therapies for selective co-inhibition of cancer clones.

Aleksandr Ianevski, Kristen Nader, Kyriaki Driva, Wojciech Senkowski, Daria Bulanova, Lidia Moyano-Galceran, Tanja Ruokoranta, Heikki Kuusanmäki, Nemo Ikonen, Philipp Sergeev, Markus Vähä-Koskela, Anil K Giri, Anna Vähärautio, Mika Kontro, Kimmo Porkka, Esa Pitkänen, Caroline A Heckman, Krister Wennerberg, Tero Aittokallio.

Intratumoral cellular heterogeneity necessitates multi-targeting therapies for improved clinical benefits in advanced malignancies. However, systematic identification of patient-specific treatments that selectively co-inhibit cancerous cell populations poses a combinatorial challenge, since the number of possible drug-dose combinations vastly exceeds what could be tested in patient cells. Here, we describe a machine learning approach, scTherapy, which leverages single-cell transcriptomic profiles to prioritize multi-targeting treatment options for individual patients with hematological cancers or solid tumors. Patient-specific treatments reveal a wide spectrum of co-inhibitors of multiple biological pathways predicted for primary cells from heterogenous cohorts of patients with acute myeloid leukemia and high-grade serous ovarian carcinoma, each with unique resistance patterns and synergy mechanisms. Experimental validations confirm that 96% of the multi-targeting treatments exhibit selective efficacy or synergy, and 83% demonstrate low toxicity to normal cells, highlighting their potential for therapeutic efficacy and safety. In a pan-cancer analysis across five cancer types, 25% of the predicted treatments are shared among the patients of the same tumor type, while 19% of the treatments are patient-specific. Our approach provides a widely-applicable strategy to identify personalized treatment regimens that selectively co-inhibit malignant cells and avoid inhibition of non-cancerous cells, thereby increasing their likelihood for clinical success.

DOI: https://doi.org/10.1038/s41467-024-52980-5