A 5:2 intermittent fasting regimen ameliorates NASH and fibrosis and blunts HCC development via hepatic PPARα and PCK1.

The role and molecular mechanisms of intermittent fasting (IF) in non-alcoholic steatohepatitis (NASH) and its transition to hepatocellular carcinoma (HCC) are unknown. Here, we identified that an IF 5:2 regimen prevents NASH development as well as ameliorates established NASH and fibrosis without affecting total calorie intake. Furthermore, the IF 5:2 regimen blunted NASH-HCC transition when applied therapeutically. The timing, length, and number of fasting cycles as well as the type of NASH diet were critical parameters determining the benefits of fasting. Combined proteome, transcriptome, and metabolome analyses identified that peroxisome-proliferator-activated receptor alpha (PPARα) and glucocorticoid-signaling-induced PCK1 act co-operatively as hepatic executors of the fasting response. In line with this, PPARα targets and PCK1 were reduced in human NASH. Notably, only fasting initiated during the active phase of mice robustly induced glucocorticoid signaling and free-fatty-acid-induced PPARα signaling. However, hepatocyte-specific glucocorticoid receptor deletion only partially abrogated the hepatic fasting response. In contrast, the combined knockdown of Ppara and Pck1 in vivo abolished the beneficial outcomes of fasting against inflammation and fibrosis. Moreover, overexpression of Pck1 alone or together with Ppara in vivo lowered hepatic triglycerides and steatosis. Our data support the notion that the IF 5:2 regimen is a promising intervention against NASH and subsequent liver cancer.

Histopathological biomarkers for predicting the tumour accumulation of nanomedicines.

The clinical prospects of cancer nanomedicines depend on effective patient stratification. Here we report the identification of predictive biomarkers of the accumulation of nanomedicines in tumour tissue. By using supervised machine learning on data of the accumulation of nanomedicines in tumour models in mice, we identified the densities of blood vessels and of tumour-associated macrophages as key predictive features. On the basis of these two features, we derived a biomarker score correlating with the concentration of liposomal doxorubicin in tumours and validated it in three syngeneic tumour models in immunocompetent mice and in four cell-line-derived and six patient-derived tumour xenografts in mice. The score effectively discriminated tumours according to the accumulation of nanomedicines (high versus low), with an area under the receiver operating characteristic curve of 0.91. Histopathological assessment of 30 tumour specimens from patients and of 28 corresponding primary tumour biopsies confirmed the score's effectiveness in predicting the tumour accumulation of liposomal doxorubicin. Biomarkers of the tumour accumulation of nanomedicines may aid the stratification of patients in clinical trials of cancer nanomedicines.

pyHiM: a new open-source, multi-platform software package for spatial genomics based on multiplexed DNA-FISH imaging.

Genome-wide ensemble sequencing methods improved our understanding of chromatin organization in eukaryotes but lack the ability to capture single-cell heterogeneity and spatial organization. To overcome these limitations, new imaging-based methods have emerged, giving rise to the field of spatial genomics. Here, we present pyHiM, a user-friendly python toolbox specifically designed for the analysis of multiplexed DNA-FISH data and the reconstruction of chromatin traces in individual cells. pyHiM employs a modular architecture, allowing independent execution of analysis steps and customization according to sample specificity and computing resources. pyHiM aims to facilitate the democratization and standardization of spatial genomics analysis.

A finely segmented semi-monolithic detector tailored for high-resolution PET.

BACKGROUND: Preclinical research and organ-dedicated applications use and require high (spatial-)resolution positron emission tomography (PET) detectors to visualize small structures (early) and understand biological processes at a finer level of detail. Researchers seeking to improve detector and image spatial resolution have explored various detector designs. Current commercial high-resolution systems often employ finely pixelated or monolithic scintillators, each with its limitations. PURPOSE: We present a semi-monolithic detector, tailored for high-resolution PET applications with a spatial resolution in the range of 1 mm or better, merging concepts of monolithic and pixelated crystals. The detector features LYSO slabs measuring (24 × 10 × 1) mm3, coupled to a 12 × 12 readout channel photosensor with 4 mm pitch. The slabs are grouped in two arrays of 44 slabs each to achieve a higher optical photon density despite the fine segmentation. METHODS: We employ a fan beam collimator for fast calibration to train machine-learning-based positioning models for all three dimensions, including slab identification and depth-of-interaction (DOI), utilizing gradient tree boosting (GTB). The data for all dimensions was acquired in less than 2 h. Energy calculation was based on a position-dependent energy calibration. Using an analytical timing calibration, time skews were corrected for coincidence timing resolution (CTR) estimation. RESULTS: Leveraging machine-learning-based calibration in all three dimensions, we achieved high detector spatial resolution: down to 1.18 mm full width at half maximum (FWHM) detector spatial resolution and 0.75 mm mean absolute error (MAE) in the planar-monolithic direction, and 2.14 mm FWHM and 1.03 mm MAE for DOI at an energy window of (435-585) keV. Correct slab interaction identification in planar-segmented direction exceeded 80%, alongside an energy resolution of 12.7% and a CTR of 450 ps FWHM. CONCLUSIONS: The introduced finely segmented, high-resolution slab detector demonstrates appealing performance characteristics suitable for high-resolution PET applications. The current benchtop-based detector calibration routine allows these detectors to be used in PET systems.

Mitotic bookmarking redundancy by nuclear receptors in pluripotent cells.

Mitotic bookmarking transcription factors (TFs) are thought to mediate rapid and accurate reactivation after mitotic gene silencing. However, the loss of individual bookmarking TFs often leads to the deregulation of only a small proportion of their mitotic targets, raising doubts on the biological significance and importance of their bookmarking function. Here we used targeted proteomics of the mitotic bookmarking TF ESRRB, an orphan nuclear receptor, to discover a large redundancy in mitotic binding among members of the protein super-family of nuclear receptors. Focusing on the nuclear receptor NR5A2, which together with ESRRB is essential in maintaining pluripotency in mouse embryonic stem cells, we demonstrate conjoint bookmarking activity of both factors on promoters and enhancers of a large fraction of active genes, particularly those most efficiently reactivated in G1. Upon fast and simultaneous degradation of both factors during mitotic exit, hundreds of mitotic targets of ESRRB/NR5A2, including key players of the pluripotency network, display attenuated transcriptional reactivation. We propose that redundancy in mitotic bookmarking TFs, especially nuclear receptors, confers robustness to the reestablishment of gene regulatory networks after mitosis.

Improving the Timing Resolution of Positron Emission Tomography Detectors Using Boosted Learning-A Residual Physics Approach.

Artificial intelligence (AI) is entering medical imaging, mainly enhancing image reconstruction. Nevertheless, improvements throughout the entire processing, from signal detection to computation, potentially offer significant benefits. This work presents a novel and versatile approach to detector optimization using machine learning (ML) and residual physics. We apply the concept to positron emission tomography (PET), intending to improve the coincidence time resolution (CTR). PET visualizes metabolic processes in the body by detecting photons with scintillation detectors. Improved CTR performance offers the advantage of reducing radioactive dose exposure for patients. Modern PET detectors with sophisticated concepts and read-out topologies represent complex physical and electronic systems requiring dedicated calibration techniques. Traditional methods primarily depend on analytical formulations successfully describing the main detector characteristics. However, when accounting for higher-order effects, additional complexities arise matching theoretical models to experimental reality. Our work addresses this challenge by combining traditional calibration with AI and residual physics, presenting a highly promising approach. We present a residual physics-based strategy using gradient tree boosting and physics-guided data generation. The explainable AI framework SHapley Additive exPlanations (SHAPs) was used to identify known physical effects with learned patterns. In addition, the models were tested against basic physical laws. We were able to improve the CTR significantly (more than 20%) for clinically relevant detectors of 19 mm height, reaching CTRs of 185 ps (450-550 keV).

Near-field coded-mask technique and its potential for proton therapy monitoring.

Objective.Prompt-gamma imaging encompasses several approaches to the online monitoring of the beam range or deposited dose distribution in proton therapy. We test one of the imaging techniques - a coded mask approach - both experimentally and via simulations.Approach.Two imaging setups have been investigated experimentally. Each of them comprised a structured tungsten collimator in the form of a modified uniformly redundant array mask and a LYSO:Ce scintillation detector of fine granularity. The setups differed in detector dimensions and operation mode (1D or 2D imaging). A series of measurements with radioactive sources have been conducted, testing the performance of the setups for near-field gamma imaging. Additionally, Monte Carlo simulations of a larger setup of the same type were conducted, investigating its performance with a realistic gamma source distribution occurring during proton therapy.Main results.The images of point-like sources reconstructed from two small-scale prototypes' data using the maximum-likelihood expectation maximisation algorithm constitute the experimental proof of principle for the near-field coded-mask imaging modality, both in the 1D and the 2D mode. Their precision allowed us to calibrate out certain systematic offsets appearing due to the limited alignment accuracy of setup elements. The simulation of the full-scale setup yielded a mean distal falloff retrieval precision of 0.72 mm in the studies for beam energy range 89.5-107.9 MeV and with 1 × 108protons (a typical number for distal spots). The implemented algorithm of image reconstruction is relatively fast-a typical procedure needs several seconds.Significance.Coded-mask imaging appears a valid option for proton therapy monitoring. The results of simulations let us conclude that the proposed full-scale setup is competitive with the knife-edge-shaped and the multi-parallel slit cameras investigated by other groups.

Spatially Resolved Multi-Omics Single-Cell Analyses Inform Mechanisms of Immune Dysfunction in Pancreatic Cancer.

BACKGROUND & AIMS: As pancreatic ductal adenocarcinoma (PDAC) continues to be recalcitrant to therapeutic interventions, including poor response to immunotherapy, albeit effective in other solid malignancies, a more nuanced understanding of the immune microenvironment in PDAC is urgently needed. We aimed to unveil a detailed view of the immune micromilieu in PDAC using a spatially resolved multimodal single-cell approach. METHODS: We applied single-cell RNA sequencing, spatial transcriptomics, multiplex immunohistochemistry, and mass cytometry to profile the immune compartment in treatment-naïve PDAC tumors and matched adjacent normal pancreatic tissue, as well as in the systemic circulation. We determined prognostic associations of immune signatures and performed a meta-analysis of the immune microenvironment in PDAC and lung adenocarcinoma on single-cell level. RESULTS: We provided a spatially resolved fine map of the immune landscape in PDAC. We substantiated the exhausted phenotype of CD8 T cells and immunosuppressive features of myeloid cells, and highlighted immune subsets with potentially underappreciated roles in PDAC that diverged from immune populations within adjacent normal areas, particularly CD4 T cell subsets and natural killer T cells that are terminally exhausted and acquire a regulatory phenotype. Differential analysis of immune phenotypes in PDAC and lung adenocarcinoma revealed the presence of extraordinarily immunosuppressive subtypes in PDAC, along with a distinctive immune checkpoint composition. CONCLUSIONS: Our study sheds light on the multilayered immune dysfunction in PDAC and presents a holistic view of the immune landscape in PDAC and lung adenocarcinoma, providing a comprehensive resource for functional studies and the exploration of therapeutically actionable targets in PDAC.

Excessive self-grooming, gene dysregulation and imbalance between the striosome and matrix compartments in the striatum of Shank3 mutant mice.

Autism is characterized by atypical social communication and stereotyped behaviors. Mutations in the gene encoding the synaptic scaffolding protein SHANK3 are detected in 1-2% of patients with autism and intellectual disability, but the mechanisms underpinning the symptoms remain largely unknown. Here, we characterized the behavior of Shank3 Δ11/Δ11 mice from 3 to 12 months of age. We observed decreased locomotor activity, increased stereotyped self-grooming and modification of socio-sexual interaction compared to wild-type littermates. We then used RNAseq on four brain regions of the same animals to identify differentially expressed genes (DEGs). DEGs were identified mainly in the striatum and were associated with synaptic transmission (e.g., Grm2, Dlgap1), G-protein-signaling pathways (e.g., Gnal, Prkcg1, and Camk2g), as well as excitation/inhibition balance (e.g., Gad2). Downregulated and upregulated genes were enriched in the gene clusters of medium-sized spiny neurons expressing the dopamine 1 (D1-MSN) and the dopamine 2 receptor (D2-MSN), respectively. Several DEGs (Cnr1, Gnal, Gad2, and Drd4) were reported as striosome markers. By studying the distribution of the glutamate decarboxylase GAD65, encoded by Gad2, we showed that the striosome compartment of Shank3 Δ11/Δ11 mice was enlarged and displayed much higher expression of GAD65 compared to wild-type mice. Altogether, these results indicate altered gene expression in the striatum of Shank3-deficient mice and strongly suggest, for the first time, that the excessive self-grooming of these mice is related to an imbalance in the striatal striosome and matrix compartments.

An interactive murine single-cell atlas of the lung responses to radiation injury.

Radiation Induced Lung Injury (RILI) is one of the main limiting factors of thorax irradiation, which can induce acute pneumonitis as well as pulmonary fibrosis, the latter being a life-threatening condition. The order of cellular and molecular events in the progression towards fibrosis is key to the physiopathogenesis of the disease, yet their coordination in space and time remains largely unexplored. Here, we present an interactive murine single cell atlas of the lung response to irradiation, generated from C57BL6/J female mice. This tool opens the door for exploration of the spatio-temporal dynamics of the mechanisms that lead to radiation-induced pulmonary fibrosis. It depicts with unprecedented detail cell type-specific radiation-induced responses associated with either lung regeneration or the failure thereof. A better understanding of the mechanisms leading to lung fibrosis will help finding new therapeutic options that could improve patients' quality of life.

A specific molecular signature in SARS-CoV-2-infected kidney biopsies.

Acute kidney injury is one of the most important complications in patients with COVID-19 and is considered a negative prognostic factor with respect to patient survival. The occurrence of direct infection of the kidney by SARS-CoV-2, and its contribution to the renal deterioration process, remain controversial issues. By studying 32 renal biopsies from patients with COVID-19, we verified that the major pathological feature of COVID-19 is acute tubular injury (ATI). Using single-molecule fluorescence in situ hybridization, we showed that SARS-CoV-2 infected living renal cells and that infection, which paralleled renal angiotensin-converting enzyme 2 expression levels, was associated with increased death. Mechanistically, a transcriptomic analysis uncovered specific molecular signatures in SARS-CoV-2-infected kidneys as compared with healthy kidneys and non-COVID-19 ATI kidneys. On the other hand, we demonstrated that SARS-CoV-2 and hantavirus, 2 RNA viruses, activated different genetic networks despite triggering the same pathological lesions. Finally, we identified X-linked inhibitor of apoptosis-associated factor 1 as a critical target of SARS-CoV-2 infection. In conclusion, this study demonstrated that SARS-CoV-2 can directly infect living renal cells and identified specific druggable molecular targets that can potentially aid in the design of novel therapeutic strategies to preserve renal function in patients with COVID-19.

Analysis of a convex time skew calibration for light sharing-based PET detectors.

Objective.Positron emission tomography (PET) detectors providing attractive coincidence time resolutions (CTRs) offer time-of-flight information, resulting in an improved signal-to-noise ratio of the PET image. In applications with photosensor arrays that employ timestampers for individual channels, timestamps typically are not time synchronized, introducing time skews due to different signal pathways. The scintillator topology and transportation of the scintillation light might provoke further skews. If not accounted for these effects, the achievable CTR deteriorates. We studied a convex timing calibration based on a matrix equation. In this work, we extended the calibration concept to arbitrary structures targeting different aspects of the time skews and focusing on optimizing the CTR performance for detector characterization. The radiation source distribution, the stability of the estimations, and the energy dependence of calibration data are subject to the analysis.Approach.A coincidence setup, equipped with a semi-monolithic detector comprising 8 LYSO slabs, each 3.9 mm × 31.9 mm × 19.0 mm, and a one-to-one coupled detector with 8 × 8 LYSO segments of 3.9 mm × 3.9 mm × 19.0 mm volume is used. Both scintillators utilize a dSiPM (DPC3200-22-44, Philips Digital Photon Counting) operated in first photon trigger. The calibration was also conducted with solely one-to-one coupled detectors and extrapolated for a slab-only setup.Main results.All analyzed hyperparameters show a strong influence on the calibration. Using multiple radiation positions improved the skew estimation. The statistical significance of the calibration dataset and the utilized energy window was of great importance. Compared to a one-to-one coupled detector pair achieving CTRs of 224 ps the slab detector configuration reached CTRs down to 222 ps, demonstrating that slabs can compete with a clinically used segmented detector design.Significance.This is the first work that systematically studies the influence of hyperparameters on skew estimation and proposes an extension to arbitrary calibration structures (e.g. scintillator volumes) of a known calibration technique.

HT-smFISH: a cost-effective and flexible workflow for high-throughput single-molecule RNA imaging.

The ability to visualize RNA in its native subcellular environment by using single-molecule fluorescence in situ hybridization (smFISH) has reshaped our understanding of gene expression and cellular functions. A major hindrance of smFISH is the difficulty to perform systematic experiments in medium- or high-throughput formats, principally because of the high cost of generating the individual fluorescent probe sets. Here, we present high-throughput smFISH (HT-smFISH), a simple and cost-efficient method for imaging hundreds to thousands of single endogenous RNA molecules in 96-well plates. HT-smFISH uses RNA probes transcribed in vitro from a large pool of unlabeled oligonucleotides. This allows the generation of individual probes for many RNA species, replacing commercial DNA probe sets. HT-smFISH thus reduces costs per targeted RNA compared with many smFISH methods and is easily scalable and flexible in design. We provide a protocol that combines oligo pool design, probe set generation, optimized hybridization conditions and guidelines for image acquisition and analysis. The pipeline requires knowledge of standard molecular biology tools, cell culture and fluorescence microscopy. It is achievable in ~20 d. In brief, HT-smFISH is tailored for medium- to high-throughput screens that image RNAs at single-molecule sensitivity.

Digitalization impacts the COVID-19 pandemic and the stringency of government measures.

COVID-19 poses a significant burden to populations worldwide. Although the pandemic has accelerated digital transformation, little is known about the influence of digitalization on pandemic developments. Therefore, this country-level study aims to explore the impact of pre-pandemic digital adoption on COVID-19 outcomes and government measures. Using the Digital Adoption Index (DAI), we examined the association between countries' digital preparedness levels and COVID-19 cases, deaths, and stringency indices (SI) of government measures until March 2021. Gradient Tree Boosting based algorithm pinpointed essential features related to COVID-19 trends, such as digital adoption, populations' smoker fraction, age, and poverty. Subsequently, regression analyses indicated that higher DAI was associated with significant declines in new cases (ß = - 362.25/pm; p < 0.001) and attributed deaths (ß = - 5.53/pm; p < 0.001) months after the peak. When plotting DAI against the SI normalized for the starting day, countries with higher DAI adopted slightly more stringent government measures (ß = 4.86; p < 0.01). Finally, a scoping review identified 70 publications providing valuable arguments for our findings. Countries with higher DAI before the pandemic show a positive trend in handling the pandemic and facilitate the implementation of more decisive governmental measures. Further distribution of digital adoption may have the potential to attenuate the impact of COVID-19 cases and deaths.

New Wound Management of Driveline Infections with Cold Atmospheric Plasma.

The use of ventricular assist devices as a bridge to transplant or as destination therapy has increased. Wound complications increase morbidity in this cohort. Cold atmospheric plasma is a source of reactive oxygen and nitrogen species and can reduce the microbial load in skin wounds without negative effects on the surrounding tissue. We evaluated our cold atmospheric plasma treatment for LVAD driveline infections in a retrospective single-center study for peri- and postintervention outcome analysis. Between April 2019 and September 2019, 15 male patients were included (5 HVAD, 10 HeartMate III). The wounds were treated for a mean of 368.5 s with a reduction of bacterial load in treated wounds in 60% of patients, regardless of the pathogen. The most common pathogen was staphylococcus aureus (n = 8 patients). There was a significant reduction of the wound scale (scale 2.80 vs. 1.18; p < 0.001) plus a significant reduction in size (16.08 vs. 1.90 cm3; p = 0.047). Seven patients (46.6%) were free from any signs of local or systemic infection during 1-year follow-up. Five patients (33%) received a heart transplantation. Cold atmospheric plasma treatment is a potent, safe, and painless adjuvant technique for treating driveline infection without the need for repeating surgical interventions.

A semi-monolithic detector providing intrinsic DOI-encoding and sub-200 ps CRT TOF-capabilities for clinical PET applications.

BACKGROUND: Current clinical positron emission tomography (PET) systems utilize detectors where the scintillator typically contains single elements of 3-6-mm width and about 20-mm height. While providing good time-of-flight performance, this design limits the spatial resolution and causes radial astigmatism as the depth-of-interaction (DOI) remains unknown. PURPOSE: We propose an alternative, aiming to combine the advantages of current detectors with the DOI capabilities shown for monolithic concepts, based on semi-monolithic scintillators (slabs). Here, the optical photons spread along one dimension enabling DOI-encoding with a still small readout area beneficial for timing performance. METHODS: An array of eight monolithic LYSO slabs of dimensions 3.9 × 32 × 19 mm3 was read out by a 64-channel photosensor containing digital SiPMs (DPC3200-22-44, Philips Digital Photon Counting). The position estimation in the detector's monolithic and DOI direction was based on a calibration with a fan beam collimator and the machine learning technique gradient tree boosting (GTB). RESULTS: We achieved a positioning performance in terms of mean absolute error (MAE) of 1.44 mm for the monolithic direction and 2.12 mm for DOI considering a wide energy window of 300-700 keV. The energy resolution was determined to be 11.3%, applying a positional-dependent energy calibration. We established both an analytical and machine-learning-based timing calibration approach and applied them for a first-photon trigger. The analytical timing calibration corrects for electronic and optical time skews leading to 240 ps coincidence resolving time (CRT) for a pair of slab-detectors. The CRT was significantly improved by utilizing GTB to predict the time difference based on specific training data and applied on top of the analytical calibration. We achieved 209 ps for the wide energy window and 198 ps for a narrow selection around the photopeak (411-561 keV). To maintain the detector's sensitivity, no filters were applied to the data during processing. CONCLUSION: Overall, the semi-monolithic detector provides attractive performance characteristics. Especially, a good CRT can be achieved while introducing DOI capabilities to the detector, making the concept suitable for clinical PET scanners.

Frequency-selective signal enhancement by a passive dual coil resonator for magnetic particle imaging.

Objective.Magnetic particle imaging (MPI) visualizes the spatial distribution of magnetic nanoparticles. MPI already provides excellent temporal and good spatial resolution, however, to achieve translation into clinics, further advances in the fields of sensitivity, image reconstruction and tracer performance are needed. In this work, we propose a novel concept to enhance the MPI signal and image resolution by a purely passive receive coil insert for a preclinical MPI system.Approach.The passive dual coil resonator (pDCR) provides frequency-selective signal enhancement. This is enabled by the adaptable resonance frequency of the pDCR network, which is galvanically isolated from the MPI system and composed of two coaxial solenoids connected via a capacitor. The pDCR aims to enhance frequency components related to high mixing orders, which are crucial to achieve high spatial resolution.Main Results.In this study, system matrix measurements and image acquisitions of a resolution phantom are carried out to evaluate the performance of the pDCR compared to the integrated receive unit of the preclinical MPI and a dedicated rat-sized receive coil. Frequency-selective signal increase and spatial resolution enhancement are demonstrated.Significance.Common dedicated receive coils come along with noise-matched receive networks, which makes them costly and difficult to reproduce. The presented pDCR is a purely passive coil insert that gets along without any additional receive electronics. Therefore, it is cost-efficient, easy-to-handle and adaptable to other MPI scanners and potentially other applications providing the basis for a new breed of passive MPI receiver systems.

FISH-quant v2: a scalable and modular tool for smFISH image analysis.

Regulation of RNA abundance and localization is a key step in gene expression control. Single-molecule RNA fluorescence in situ hybridization (smFISH) is a widely used single-cell-single-molecule imaging technique enabling quantitative studies of gene expression and its regulatory mechanisms. Today, these methods are applicable at a large scale, which in turn come with a need for adequate tools for data analysis and exploration. Here, we present FISH-quant v2, a highly modular tool accessible for both experts and non-experts. Our user-friendly package allows the user to segment nuclei and cells, detect isolated RNAs, decompose dense RNA clusters, quantify RNA localization patterns and visualize these results both at the single-cell level and variations within the cell population. This tool was validated and applied on large-scale smFISH image data sets, revealing diverse subcellular RNA localization patterns and a surprisingly high degree of cell-to-cell heterogeneity.

Sensitive visualization of SARS-CoV-2 RNA with CoronaFISH.

The current COVID-19 pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The positive-sense single-stranded RNA virus contains a single linear RNA segment that serves as a template for transcription and replication, leading to the synthesis of positive and negative-stranded viral RNA (vRNA) in infected cells. Tools to visualize vRNA directly in infected cells are critical to analyze the viral replication cycle, screen for therapeutic molecules, or study infections in human tissue. Here, we report the design, validation, and initial application of FISH probes to visualize positive or negative RNA of SARS-CoV-2 (CoronaFISH). We demonstrate sensitive visualization of vRNA in African green monkey and several human cell lines, in patient samples and human tissue. We further demonstrate the adaptation of CoronaFISH probes to electron microscopy. We provide all required oligonucleotide sequences, source code to design the probes, and a detailed protocol. We hope that CoronaFISH will complement existing techniques for research on SARS-CoV-2 biology and COVID-19 pathophysiology, drug screening, and diagnostics.

piRNAs initiate transcriptional silencing of spermatogenic genes during C. elegans germline development.

Eukaryotic genomes harbor invading transposable elements that are silenced by PIWI-interacting RNAs (piRNAs) to maintain genome integrity in animal germ cells. However, whether piRNAs also regulate endogenous gene expression programs remains unclear. Here, we show that C. elegans piRNAs trigger the transcriptional silencing of hundreds of spermatogenic genes during spermatogenesis, promoting sperm differentiation and function. This silencing signal requires piRNA-dependent small RNA biogenesis and loading into downstream nuclear effectors, which correlates with the dynamic reorganization of two distinct perinuclear biomolecular condensates present in germ cells. In addition, the silencing capacity of piRNAs is temporally counteracted by the Argonaute CSR-1, which targets and licenses spermatogenic gene transcription. The spatial and temporal overlap between these opposing small RNA pathways contributes to setting up the timing of the spermatogenic differentiation program. Thus, our work identifies a prominent role for piRNAs as direct regulators of endogenous transcriptional programs during germline development and gamete differentiation.