Fluorescent Neuronal Cells v2: multi-task, multi-format annotations for deep learning in microscopy.

Fluorescent Neuronal Cells v2 is a collection of fluorescence microscopy images and the corresponding ground-truth annotations, designed to foster innovative research in the domains of Life Sciences and Deep Learning. This dataset encompasses three image collections wherein rodent neuronal cell nuclei and cytoplasm are stained with diverse markers to highlight their anatomical or functional characteristics. Specifically, we release 1874 high-resolution images alongside 750 corresponding ground-truth annotations for several learning tasks, including semantic segmentation, object detection and counting. The contribution is two-fold. First, thanks to the variety of annotations and their accessible formats, we anticipate our work will facilitate methodological advancements in computer vision approaches for segmentation, detection, feature extraction, unsupervised and self-supervised learning, transfer learning, and related areas. Second, by enabling extensive exploration and benchmarking, we hope Fluorescent Neuronal Cells v2 will catalyze breakthroughs in fluorescence microscopy analysis and promote cutting-edge discoveries in life sciences.

How big is Big Data? A comprehensive survey of data production, storage, and streaming in science and industry.

The contemporary surge in data production is fueled by diverse factors, with contributions from numerous stakeholders across various sectors. Comparing the volumes at play among different big data entities is challenging due to the scarcity of publicly available data. This survey aims to offer a comprehensive perspective on the orders of magnitude involved in yearly data generation by some public and private leading organizations, using an array of online sources for estimation. These estimates are based on meaningful, individual data production metrics and plausible per-unit sizes. The primary objective is to offer insights into the comparative scales of major big data players, their sources, and data production flows, rather than striving for precise measurements or incorporating the latest updates. The results are succinctly conveyed through a visual representation of the relative data generation volumes across these entities.

Long-range gene regulation in hormone-dependent cancer.

The human genome is organized into multiple structural layers, ranging from chromosome territories to progressively smaller substructures, such as topologically associating domains (TADs) and chromatin loops. These substructures, collectively referred to as long-range chromatin interactions (LRIs), have a significant role in regulating gene expression. TADs are regions of the genome that harbour groups of genes and regulatory elements that frequently interact with each other and are insulated from other regions, thereby preventing widespread uncontrolled DNA contacts. Chromatin loops formed within TADs through enhancer and promoter interactions are elastic, allowing transcriptional heterogeneity and stochasticity. Over the past decade, it has become evident that the 3D genome structure, also referred to as the chromatin architecture, is central to many transcriptional cellular decisions. In this Review, we delve into the intricate relationship between steroid receptors and LRIs, discussing how steroid receptors interact with and modulate these chromatin interactions. Genetic alterations in the many processes involved in organizing the nuclear architecture are often associated with the development of hormone-dependent cancers. A better understanding of the interplay between architectural proteins and hormone regulatory networks can ultimately be exploited to develop improved approaches for cancer treatment.

SMYD3 represses tumor-intrinsic interferon response in HPV-negative squamous cell carcinoma of the head and neck.

Cancers often display immune escape, but the mechanisms are incompletely understood. Herein, we identify SMYD3 as a mediator of immune escape in human papilloma virus (HPV)-negative head and neck squamous cell carcinoma (HNSCC), an aggressive disease with poor response to immunotherapy with pembrolizumab. SMYD3 depletion induces upregulation of multiple type I interferon (IFN) response and antigen presentation machinery genes in HNSCC cells. Mechanistically, SMYD3 binds to and regulates the transcription of UHRF1, encoding for a reader of H3K9me3, which binds to H3K9me3-enriched promoters of key immune-related genes, recruits DNMT1, and silences their expression. SMYD3 further maintains the repression of immune-related genes through intragenic deposition of H4K20me3. In vivo, Smyd3 depletion induces influx of CD8+ T cells and increases sensitivity to anti-programmed death 1 (PD-1) therapy. SMYD3 overexpression is associated with decreased CD8 T cell infiltration and poor response to neoadjuvant pembrolizumab. These data support combining SMYD3 depletion strategies with checkpoint blockade to overcome anti-PD-1 resistance in HPV-negative HNSCC.

Extrachromosomal DNA Amplification Contributes to Small Cell Lung Cancer Heterogeneity and Is Associated with Worse Outcomes.

Small-cell lung cancer (SCLC) is an aggressive neuroendocrine lung cancer. Oncogenic MYC amplifications drive SCLC heterogeneity, but the genetic mechanisms of MYC amplification and phenotypic plasticity, characterized by neuroendocrine and nonneuroendocrine cell states, are not known. Here, we integrate whole-genome sequencing, long-range optical mapping, single-cell DNA sequencing, and fluorescence in situ hybridization to find extrachromosomal DNA (ecDNA) as a primary source of SCLC oncogene amplifications and driver fusions. ecDNAs bring to proximity enhancer elements and oncogenes, creating SCLC transcription-amplifying units, driving exceptionally high MYC gene dosage. We demonstrate that cell-free nucleosome profiling can noninvasively detect ecDNA amplifications in plasma, facilitating its genome-wide interrogation in SCLC and other cancers. Altogether, our work provides the first comprehensive map of SCLC ecDNA and describes a new mechanism that governs MYC-driven SCLC heterogeneity. ecDNA-enabled transcriptional flexibility may explain the significantly worse survival outcomes of SCLC harboring complex ecDNA amplifications. SIGNIFICANCE: MYC drives SCLC progression, but the genetic basis of MYC-driven SCLC evolution is unknown. Using SCLC as a paradigm, we report how ecDNA amplifications function as MYC-amplifying units, fostering tumor plasticity and a high degree of tumor heterogeneity. This article is highlighted in the In This Issue feature, p. 799.

The glucocorticoid receptor associates with the cohesin loader NIPBL to promote long-range gene regulation.

The cohesin complex is central to chromatin looping, but mechanisms by which these long-range chromatin interactions are formed and persist remain unclear. We demonstrate that interactions between a transcription factor (TF) and the cohesin loader NIPBL regulate enhancer-dependent gene activity. Using mass spectrometry, genome mapping, and single-molecule tracking methods, we demonstrate that the glucocorticoid (GC) receptor (GR) interacts with NIPBL and the cohesin complex at the chromatin level, promoting loop extrusion and long-range gene regulation. Real-time single-molecule experiments show that loss of cohesin markedly diminishes the concentration of TF molecules at specific nuclear confinement sites, increasing TF local concentration and promoting gene regulation. Last, patient-derived acute myeloid leukemia cells harboring cohesin mutations exhibit a reduced response to GCs, suggesting that the GR-NIPBL-cohesin interaction is defective in these patients, resulting in poor response to GC treatment.

Automating cell counting in fluorescent microscopy through deep learning with c-ResUnet.

Counting cells in fluorescent microscopy is a tedious, time-consuming task that researchers have to accomplish to assess the effects of different experimental conditions on biological structures of interest. Although such objects are generally easy to identify, the process of manually annotating cells is sometimes subject to fatigue errors and suffers from arbitrariness due to the operator's interpretation of the borderline cases. We propose a Deep Learning approach that exploits a fully-convolutional network in a binary segmentation fashion to localize the objects of interest. Counts are then retrieved as the number of detected items. Specifically, we introduce a Unet-like architecture, cell ResUnet (c-ResUnet), and compare its performance against 3 similar architectures. In addition, we evaluate through ablation studies the impact of two design choices, (i) artifacts oversampling and (ii) weight maps that penalize the errors on cells boundaries increasingly with overcrowding. In summary, the c-ResUnet outperforms the competitors with respect to both detection and counting metrics (respectively, [Formula: see text] score = 0.81 and MAE = 3.09). Also, the introduction of weight maps contribute to enhance performances, especially in presence of clumping cells, artifacts and confounding biological structures. Posterior qualitative assessment by domain experts corroborates previous results, suggesting human-level performance inasmuch even erroneous predictions seem to fall within the limits of operator interpretation. Finally, we release the pre-trained model and the annotated dataset to foster research in this and related fields.

An intrinsically disordered region-mediated confinement state contributes to the dynamics and function of transcription factors.

Transcription factors (TFs) regulate gene expression by binding to specific consensus motifs within the local chromatin context. The mechanisms by which TFs navigate the nuclear environment as they search for binding sites remain unclear. Here, we used single-molecule tracking and machine-learning-based classification to directly measure the nuclear mobility of the glucocorticoid receptor (GR) in live cells. We revealed two distinct and dynamic low-mobility populations. One accounts for specific binding to chromatin, while the other represents a confinement state that requires an intrinsically disordered region (IDR), implicated in liquid-liquid condensate subdomains. Further analysis showed that the dwell times of both subpopulations follow a power-law distribution, consistent with a broad distribution of affinities on the GR cistrome and interactome. Together, our data link IDRs with a confinement state that is functionally distinct from specific chromatin binding and modulates the transcriptional output by increasing the local concentration of TFs at specific sites.

Preparing Distributed Computing Operations for the HL-LHC Era With Operational Intelligence.

As a joint effort from various communities involved in the Worldwide LHC Computing Grid, the Operational Intelligence project aims at increasing the level of automation in computing operations and reducing human interventions. The distributed computing systems currently deployed by the LHC experiments have proven to be mature and capable of meeting the experimental goals, by allowing timely delivery of scientific results. However, a substantial number of interventions from software developers, shifters, and operational teams is needed to efficiently manage such heterogenous infrastructures. Under the scope of the Operational Intelligence project, experts from several areas have gathered to propose and work on "smart" solutions. Machine learning, data mining, log analysis, and anomaly detection are only some of the tools we have evaluated for our use cases. In this community study contribution, we report on the development of a suite of operational intelligence services to cover various use cases: workload management, data management, and site operations.

Publisher Correction: MSK1 regulates luminal cell differentiation and metastatic dormancy in ER+ breast cancer.

In the version of this Article originally published, the boxes framing the two plots in Fig. 1g were misaligned from the axes due to a technical error. This has now been corrected in all versions of the Article.

MSK1 regulates luminal cell differentiation and metastatic dormancy in ER+ breast cancer.

For many patients with breast cancer, symptomatic bone metastases appear after years of latency. How micrometastatic lesions remain dormant and undetectable before initiating colonization is unclear. Here, we describe a mechanism involved in bone metastatic latency of oestrogen receptor-positive (ER+) breast cancer. Using an in vivo genome-wide short hairpin RNA screening, we identified the kinase MSK1 as an important regulator of metastatic dormancy in breast cancer. In patients with ER+ breast cancer, low MSK1 expression associates with early metastasis. We show that MSK1 downregulation impairs the differentiation of breast cancer cells, increasing their bone homing and growth capacities. MSK1 controls the expression of genes required for luminal cell differentiation, including the GATA3 and FOXA1 transcription factors, by modulating their promoter chromatin status. Our results indicate that MSK1 prevents metastatic progression of ER+ breast cancer, suggesting that stratifying patients with breast cancer as high or low risk for early relapse based on MSK1 expression could improve prognosis.

Loss of Dnmt3a and Dnmt3b does not affect epidermal homeostasis but promotes squamous transformation through PPAR-γ.

The DNA methyltransferase Dnmt3a suppresses tumorigenesis in models of leukemia and lung cancer. Conversely, deregulation of Dnmt3b is thought to generally promote tumorigenesis. However, the role of Dnmt3a and Dnmt3b in many types of cancer remains undefined. Here, we show that Dnmt3a and Dnmt3b are dispensable for homeostasis of the murine epidermis. However, loss of Dnmt3a-but not Dnmt3b-increases the number of carcinogen-induced squamous tumors, without affecting tumor progression. Only upon combined deletion of Dnmt3a and Dnmt3b, squamous carcinomas become more aggressive and metastatic. Mechanistically, Dnmt3a promotes the expression of epidermal differentiation genes by interacting with their enhancers and inhibits the expression of lipid metabolism genes, including PPAR-γ, by directly methylating their promoters. Importantly, inhibition of PPAR-γ partially prevents the increase in tumorigenesis upon deletion of Dnmt3a. Altogether, we demonstrate that Dnmt3a and Dnmt3b protect the epidermis from tumorigenesis and that squamous carcinomas are sensitive to inhibition of PPAR-γ.

GATA6 regulates EMT and tumour dissemination, and is a marker of response to adjuvant chemotherapy in pancreatic cancer.

BACKGROUND AND AIMS: The role of GATA factors in cancer has gained increasing attention recently, but the function of GATA6 in pancreatic ductal adenocarcinoma (PDAC) is controversial. GATA6 is amplified in a subset of tumours and was proposed to be oncogenic, but high GATA6 levels are found in well-differentiated tumours and are associated with better patient outcome. By contrast, a tumour-suppressive function of GATA6 was demonstrated using genetic mouse models. We aimed at clarifying GATA6 function in PDAC. DESIGN: We combined GATA6 silencing and overexpression in PDAC cell lines with GATA6 ChIP-Seq and RNA-Seq data, in order to understand the mechanism of GATA6 functions. We then confirmed some of our observations in primary patient samples, some of which were included in the ESPAC-3 randomised clinical trial for adjuvant therapy. RESULTS: GATA6 inhibits the epithelial-mesenchymal transition (EMT) in vitro and cell dissemination in vivo. GATA6 has a unique proepithelial and antimesenchymal function, and its transcriptional regulation is direct and implies, indirectly, the regulation of other transcription factors involved in EMT. GATA6 is lost in tumours, in association with altered differentiation and the acquisition of a basal-like molecular phenotype, consistent with an epithelial-to-epithelial (ET2) transition. Patients with basal-like GATA6low tumours have a shorter survival and have a distinctly poor response to adjuvant 5-fluorouracil (5-FU)/leucovorin. However, modulation of GATA6 expression in cultured cells does not directly regulate response to 5-FU. CONCLUSIONS: We provide mechanistic insight into GATA6 tumour-suppressive function, its role as a regulator of canonical epithelial differentiation, and propose that loss of GATA6 expression is both prognostic and predictive of response to adjuvant therapy.

Dnmt3a and Dnmt3b Associate with Enhancers to Regulate Human Epidermal Stem Cell Homeostasis.

The genome-wide localization and function of endogenous Dnmt3a and Dnmt3b in adult stem cells are unknown. Here, we show that in human epidermal stem cells, the two proteins bind in a histone H3K36me3-dependent manner to the most active enhancers and are required to produce their associated enhancer RNAs. Both proteins prefer super-enhancers associated to genes that either define the ectodermal lineage or establish the stem cell and differentiated states. However, Dnmt3a and Dnmt3b differ in their mechanisms of enhancer regulation: Dnmt3a associates with p63 to maintain high levels of DNA hydroxymethylation at the center of enhancers in a Tet2-dependent manner, whereas Dnmt3b promotes DNA methylation along the body of the enhancer. Depletion of either protein inactivates their target enhancers and profoundly affects epidermal stem cell function. Altogether, we reveal novel functions for Dnmt3a and Dnmt3b at enhancers that could contribute to their roles in disease and tumorigenesis.

Epigenetic regulation of adult stem cell function.

Understanding the cellular and molecular mechanisms that specify cell lineages throughout development, and that maintain tissue homeostasis during adulthood, is paramount towards our understanding of why we age or develop pathologies such as cancer. Epigenetic mechanisms ensure that genetically identical cells acquire different fates during embryonic development and are therefore essential for the proper progression of development. How they do so is still a matter of intense investigation, but there is sufficient evidence indicating that they act in a concerted manner with inductive signals and tissue-specific transcription factors to promote and stabilize fate changes along the three germ layers during development. In consequence, it is generally hypothesized that epigenetic mechanisms are also required for the continuous maintenance of cell fate during adulthood. However, in vivo models in which different epigenetic factors have been depleted in different tissues do not show overt changes in cell lineage, thus not strongly supporting this view. Instead, the function of some of these factors appears to be primarily associated with tissue functionality, and a strong causal relationship has been established between their misregulation and a diseased state. In this review, we summarize our current knowledge of the role of epigenetic factors in adult stem cell function and tissue homeostasis.