Is the Gelatinous Matrix of Nassellaria (Radiolaria) a Strategy for Coping With Oligotrophy? DOI Creative Commons
Natalia Llopis Monferrer, Sarah Romac, Manon Laget

et al.

Environmental Microbiology, Journal Year: 2025, Volume and Issue: 27(5)

Published: May 1, 2025

Radiolaria are heterotrophic protists abundant in the world's oceans, playing important roles biogeochemical cycles. Some host photosynthetic algae, contributing to primary production. Such mixotrophic behaviour is believed explain their success oligotrophic waters, notably Collodaria, exclusively radiolarians within a gelatinous matrix. Yet, understanding of ecology limited direct observations, as they have so far withstood reproduction culture and lack genome data. Sampling California Current revealed abundant, rarely observed Nassellaria genus Phlebarachnium, characterised live Phylogenetic reconstruction ribosomal DNA suggests that distantly related lineages independently developed ability produce matrix ~150 million years ago. By matching physical samples with genetic data, we identified these organisms global datasets, revealing affinity for conditions. Co-occurrence networks showed distinct biogeography patterns matrix-forming compared those without. Results suggest might be an adaptation increasing effective volume, favouring prey capture, creating larger microenvironment symbionts, thus promoting ecological nutrient-depleted waters. This study advances our poorly known eukaryotic groups, specifically when evolution occurs across lineages.

Language: Английский

A key role of PIEZO2 mechanosensitive ion channel in adipose sensory innervation DOI Creative Commons
Yu Wang, Yunxiao Zhang,

Verina H. Leung

et al.

Cell Metabolism, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Compared with the well-established functions of sympathetic innervation, role sensory afferents in adipose tissues remains less understood. Recent work has revealed anatomical and physiological significance innervation; however, its molecular underpinning unclear. Here, using organ-targeted single-cell RNA sequencing, we identified mechanoreceptor PIEZO2 as one most prevalent receptors fat-innervating dorsal root ganglia (DRG) neurons. deletion neurons induced transcriptional programs tissue resembling activation, mirroring DRG ablation. Conversely, a gain-of-function mutant shifted phenotypes opposite direction. These results indicate that plays major regulation tissues. This discovery opens new avenues for exploring mechanosensation organs not traditionally considered mechanically active, such tissues, therefore sheds light on broader regulating organ function homeostasis.

Language: Английский

Citations

1
Multiplexed dynamic control of temperature to probe and observe mammalian cells DOI
William Benman, Pavan Iyengar, Thomas R. Mumford

et al.

Cell Systems, Journal Year: 2025, Volume and Issue: 16(3), P. 101234 - 101234

Published: March 1, 2025

Language: Английский

Citations

1
Geometric deep learning and multiple-instance learning for 3D cell-shape profiling DOI Creative Commons

Matt De Vries,

Lucas Dent, Nathan Curry

et al.

Cell Systems, Journal Year: 2025, Volume and Issue: 16(3), P. 101229 - 101229

Published: March 1, 2025

The three-dimensional (3D) morphology of cells emerges from complex cellular and environmental interactions, serving as an indicator cell state function. In this study, we used deep learning to discover representations understand states. This study introduced MorphoMIL, a computational pipeline combining geometric attention-based multiple-instance profile 3D nuclear shapes. We point-cloud input captured morphological signatures at single-cell population levels, accounting for phenotypic heterogeneity. applied these methods over 95,000 melanoma treated with clinically relevant cytoskeleton-modulating chemical genetic perturbations. accurately predicted drug perturbations Our framework revealed subtle changes associated perturbations, key shapes correlating signaling activity, interpretable insights into cell-state MorphoMIL demonstrated superior performance generalized across diverse datasets, paving the way scalable, high-throughput profiling in discovery. A record paper's transparent peer review process is included supplemental information.

Language: Английский

Citations

1
ZNF574 is a quality control factor for defective ribosome biogenesis intermediates DOI
Jared F. Akers,

Michael LaScola,

Adrian Bothe

et al.

Molecular Cell, Journal Year: 2025, Volume and Issue: unknown

Published: May 1, 2025

Language: Английский

Citations

1
The Single-Cell Landscape of Peripheral and Tumor-Infiltrating Immune Cells in Hpv- Hnscc DOI
Rômulo G. Galvani, Adolfo Rojas, Bruno Fernandes Matuck

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Syncytial therapeutics: Receptor-specific and direct-to-cytosol biologic drug delivery mediated by measles fusion complex DOI
Víctor García, Casim A. Sarkar, Brenda M. Ogle

et al.

Journal of Controlled Release, Journal Year: 2025, Volume and Issue: 380, P. 967 - 975

Published: Feb. 22, 2025

Language: Английский

Citations

0
Cecelia: a multifunctional image analysis toolbox for decoding spatial cellular interactions and behaviour DOI Creative Commons
Dominik Schienstock, Jyh Liang Hor, Sapna Devi

et al.

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: Feb. 24, 2025

Abstract With the ever-increasing complexity of microscopy modalities, it is imperative to have computational workflows that enable researchers process and perform in-depth quantitative analysis resulting images. However, allow flexible, interactive intuitive from raw images analysed data are lacking for many experimental use-cases. Notably, integrated software solutions complex 3D live cell sorely needed. To address this, we present Cecelia, a toolbox integrates various open-source packages into coherent management suite make multidimensional image accessible non-specialists. We describe application Cecelia several immunologically relevant scenarios development an unbiased approach distinguish dynamic behaviours imaging data. available as package with Shiny app interface ( https://github.com/schienstockd/cecelia ). envision this framework its approaches will be broad use biological researchers.

Language: Английский

Citations

0
Systematic Comparison of FBS and Medium Variation Effect on Key Cellular Processes Using Morphological Profiling DOI Creative Commons
Timofey Lebedev,

Alesya M. Mikheeva,

Valentina A. Gasca

et al.

Cells, Journal Year: 2025, Volume and Issue: 14(5), P. 336 - 336

Published: Feb. 25, 2025

Although every cell biologist knows the importance of selecting right growth conditions and it is well known that composition medium may vary depending on a product brand or lot affecting many cellular processes, still those effects are poorly systematized. We addressed this issue by comparing effect 12 fetal bovine sera (FBS) eight media from different brands morphological functional parameters five types: lung adenocarcinoma, neuroblastoma, glioblastoma, embryonic kidney, colorectal cancer cells. Using high-throughput imaging, we compared proliferation; performed profiling based imaging 561,519 cells; measured extracellular regulated kinases (ERK1/2) activity, mitochondria potential, lysosome accumulation; sensitivity to drugs, response EGF stimulation, ability differentiate. found changes in proliferation morphology were independent, associated with differences potential cell's Surprisingly, most drastic detected serum-free conditions, where choice affected survival EGF. Overall, our data be used improve reproducibility experiments involving cultures, 28 44 can explored through Shinyapp.

Language: Английский

Citations

0
Correlative light and electron microscopy reveals the fine circuit structure underlying evidence accumulation in larval zebrafish DOI Creative Commons
Jonathan Boulanger-Weill, F. Kampf, Richard Schalek

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: March 15, 2025

Accumulating information is a critical component of most circuit computations in the brain across species, yet its precise implementation at synaptic level remains poorly understood. Dissecting such neural circuits vertebrates requires knowledge functional properties and ability to directly correlate dynamics with underlying wiring diagram same animal. Here we combine calcium imaging ultrastructural reconstruction, using visual motion accumulation paradigm larval zebrafish. Using connectomic analyses functionally identified cells computational modeling, show that bilateral inhibition, disinhibition, recurrent connectivity are prominent motifs for sensory within anterior hindbrain. We also demonstrate similar insights about structure-function relationship this can be obtained through complementary methods involving cell-specific morphological labeling via photo-conversion neuronal response types. used our unique ground truth datasets train test novel classifier algorithm, allowing us assign labels neurons from libraries where lacking. The resulting feature-rich library identities connectomes enabled constrain biophysically realistic network model hindbrain reproduce observed make testable predictions future experiments. Our work exemplifies power hypothesis-driven electron microscopy paired recordings gain mechanistic into signal processing provides framework dissecting vertebrates.

Language: Английский

Citations

0
Enhancing cell instance segmentation in scanning electron microscopy images via a deep contour closing operator DOI Creative Commons

Florian Robert,

Alexia Calovoulos,

Laurent Facq

et al.

Computers in Biology and Medicine, Journal Year: 2025, Volume and Issue: 190, P. 109972 - 109972

Published: April 4, 2025

Accurately segmenting and individualizing cells in scanning electron microscopy (SEM) images is a highly promising technique for elucidating tissue architecture oncology. While current artificial intelligence (AI)-based methods are effective, errors persist, necessitating time-consuming manual corrections, particularly areas where the quality of cell contours image poor requires gap filling. This study presents novel AI-driven approach refining boundary delineation to improve instance-based segmentation SEM images, also reducing necessity residual correction. A convolutional neural network (CNN) Closing Operator (COp-Net) introduced address gaps contours, effectively filling regions with deficient or absent information. The takes as input contour probability maps potentially inadequate missing information outputs corrected delineations. lack training data was addressed by generating low integrity using tailored partial differential equation (PDE). To ensure reproducibility, COp-Net weights source code solving PDE publicly available at https://github.com/Florian-40/CellSegm. We showcase efficacy our augmenting precision both private from patient-derived xenograft (PDX) hepatoblastoma tissues accessible datasets. proposed closing operator exhibits notable improvement tested datasets, achieving respectively close 50% (private data) 10% (public increase accurately-delineated proportion compared state-of-the-art methods. Additionally, need corrections significantly reduced, therefore facilitating overall digitalization process. Our results demonstrate enhancement accuracy instance segmentation, challenging compromises boundaries, Therefore, work should ultimately facilitate tumour bioarchitecture onconanotomy field.

Language: Английский

Citations

0