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DNA breaks, in particular double-strand breaks (DSBs), produced by radiation and radiomimetic agents are amongst the most toxic forms of DNA damage, in part because they are associated with extensive oxidative chemical modification at the break termini. Prior to the completion of DSB repair, the chemically modified termini associated with radiation-induced damage must be removed. A number of DNA processing enzymes have been implicated in the processing of these ‘dirty ends’, but our knowledge of this process remains limited. Here, we demonstrate a role for the 5’-3’ exonuclease SNM1A in this process. Cells disrupted for SNM1A are sensitive to radiation and radiomimetic agents and show defects in the resolution of the lethal DSB damage they induce. SNM1A is recruited and retained to the sites of complex DNA damage via the concerted action of three highly conserved interaction domains the PBZ, UBZ and PIP box, mediating interactions with poly-ADP-ribose chains, PCNA and the ubiquitinated form of PCNA, respectively. Consistent with its unprecedented capacity to digest DNA containing a wide range of chemically modified nucleotides, we found that SNM1A can resect DNA containing oxidative lesions representative of those induced by radiation damage at break termini. Taken together, our work reveals a crucial role for SNM1A in the repair of toxic DNA breaks.

Measuring diffusion dynamics in living cells is essential for the understanding of molecular interactions. While various techniques have been used to explore such characteristics in the plasma membrane, this is less developed for measurements inside the cytosol. An example of cytosolic action is the import of proteins into peroxisomes, via the peroxisomal import receptor PEX5. Here, we combined advanced microscopy and spectroscopy techniques such as fluorescence correlation spectroscopy (FCS) and super-resolution STED microscopy to present a detailed characterization of the diffusion and interaction dynamics of PEX5. Among other features, we disclose a slow diffusion of PEX5, independent of aggregation or target binding, but associated with cytosolic interaction partners via its N-terminal domain. This sheds new light on the functionality of the receptor in the cytosol. Besides specific insights, our study highlights the potential of using complementary microscopy tools to decipher molecular interactions in the cytosol via studying their diffusion dynamics.SummaryThe peroxisomal import receptor PEX5 transports newly synthesized proteins from the cytosol to the peroxisomal matrix. Here the cytosolic diffusion and interaction dynamics of PEX5 are characterized by advanced microscopic spectroscopy methods, revealing a so far unknown interaction partner.

The megakaryocyte/erythroid Transient Myeloproliferative Disorder (TMD) in newborns with Down Syndrome (DS) occurs when N-terminal truncating mutations of the hemopoietic transcription factor GATA1, that produce GATA1short protein (GATA1s), are acquired early in development. Prior work has shown that murine GATA1s, by itself, causes a transient yolk sac myeloproliferative disorder. However, it is unclear where in the hemopoietic cellular hierarchy GATA1s exerts its effects to produce this myeloproliferative state. Here, through a detailed examination of hemopoiesis from murine GATA1s ES cells and GATA1s embryos we define defects in erythroid and megakaryocytic differentiation that occur relatively in hemopoiesis. GATA1s causes an arrest late in erythroid differentiationin vivo, and even more profoundly in ES-cell derived cultures, with a marked reduction of Ter-119 cells and reduced erythroid gene expression. In megakaryopoiesis, GATA1s causes a differentiation delay at a specific stage, with accumulation of immature, kit-expressing CD41himegakaryocytic cells. In this specific megakaryocytic compartment, there are increased numbers of GATA1s cells in S-phase of cell cycle and reduced number of apoptotic cells compared to GATA1 cells in the same cell compartment. There is also a delay in maturation of these immature GATA1s megakaryocytic lineage cells compared to GATA1 cells at the same stage of differentiation. Finally, even when GATA1s megakaryocytic cells mature, they mature aberrantly with altered megakaryocyte-specific gene expression and activity of the mature megakaryocyte enzyme, acetylcholinesterase. These studies pinpoint the hemopoietic compartment where GATA1s megakaryocyte myeloproliferation occurs, defining where molecular studies should now be focussed to understand the oncogenic action of GATA1s.Scientific CategoryHaematopoiesis and Stem CellsKey PointsGATA1s-induced stage-specific differentiation delay increases immature megakaryocytesin vivoandin vitro, during development.Differentiation delay is associated with increased numbers of cells in S-phase and reduced apoptosis.

In this paper we demonstrate the application of object detection networks for the classification and localization of cells in fluorescence microscopy. We benchmark two leading object detection algorithms across multiple challenging 2-D microscopy datasets as well as develop and demonstrate an algorithm which can localize and image cells in 3-D, in real-time. Furthermore, we exploit the fast processing of these algorithms and develop a simple and effective Augmented Reality (AR) system for fluorescence microscopy systems. Object detection networks are well-known high performance networks famously applied to the task of identifying and localizing objects in photography images. Here we show their application and efficiency for localizing cells in fluorescence microscopy images. Object detection algorithms are typically trained on many thousands of images, which can be prohibitive within the biological sciences due to the cost of imaging and annotating large amounts of data. Through taking different cell types and assays as an example, we show that with some careful considerations it is possible to achieve very high performance with datasets with as few as 26 images present. Using our approach, it is possible for relatively non-skilled users to automate detection of cell classes with a variety of appearances and enable new avenues for automation of conventionally manual fluorescence microscopy acquisition pipelines.

The diffusion dynamics in the cellular plasma membrane provide crucial insights into molecular interactions, organization, and bioactivity. Beam-scanning fluorescence correlation spectroscopy combined with super-resolution stimulated emission depletion nanoscopy (scanning STED–FCS) measures such dynamics with high spatial and temporal resolution. It reveals nanoscale diffusion characteristics by measuring the molecular diffusion in conventional confocal mode and super-resolved STED mode sequentially for each pixel along the scanned line. However, to directly link the spatial and the temporal information, a method that simultaneously measures the diffusion in confocal and STED modes is needed. Here, to overcome this problem, we establish an advanced STED–FCS measurement method, line interleaved excitation scanning STED–FCS (LIESS–FCS), that discloses the molecular diffusion modes at different spatial positions with a single measurement. It relies on fast beam-scanning along a line with alternating laser illumination that yields, for each pixel, the apparent diffusion coefficients for two different observation spot sizes (conventional confocal and super-resolved STED). We demonstrate the potential of the LIESS–FCS approach with simulations and experiments on lipid diffusion in model and live cell plasma membranes. We also apply LIESS–FCS to investigate the spatiotemporal organization of glycosylphosphatidylinositol-anchored proteins in the plasma membrane of live cells, which, interestingly, show multiple diffusion modes at different spatial positions.

A variety of self-interacting domains, defined at different levels of resolution, have been described in mammalian genomes. These include Chromatin Compartments (A and B)1, Topologically Associated Domains (TADs)2,3, contact domains4,5, sub-TADs6, insulated neighbourhoods7 and frequently interacting regions (FIREs)8. Whereas many studies have found the organisation of self-interacting domains to be conserved across cell types389, some do form in a lineage-specific manner6710. However, it is not clear to what degree such tissue-specific structures result from processes related to gene activity such as enhancer-promoter interactions or whether they form earlier during lineage commitment and are therefore likely to be prerequisite for promoting gene expression. To examine these models of genome organisation in detail, we used a combination of high-resolution chromosome conformation capture, a newly-developed form of quantitative fluorescence in-situ hybridisation and super-resolution imaging to study a 70 kb self-interacting domain containing the mouse α-globin locus. To understand how this self-interacting domain is established, we studied the region when the genes are inactive and during erythroid differentiation when the genes are progressively switched on. In contrast to many current models of long-range gene regulation, we show that an erythroid-specific, decompacted self-interacting domain, delimited by convergent CTCF/cohesin binding sites, forms prior to the onset of robust gene expression. Using previously established mouse models we show that formation of the self-interacting domain does not rely on interactions between the α-globin genes and their enhancers. As there are also no tissue-specific changes in CTCF binding, then formation of the domain may simply depend on the presence of activated lineage-specific cis-elements driving a transcription-independent mechanism for opening chromatin throughout the 70 kb region to create a permissive environment for gene expression. These findings are consistent with a model of loop-extrusion in which all segments of chromatin, within a region delimited by CTCF boundary elements, can contact each other. Our findings suggest that activation of tissue-specific element(s)within such a self-interacting region is sufficient to influence all chromatin within the domain.

Scanning Fluorescence Correlation Spectroscopy (scanning FCS) is a variant of conventional point FCS that allows molecular diffusion at multiple locations to be measured simultaneously. It enables disclosure of potential spatial heterogeneity in molecular diffusion dynamics and also the acquisition of a large amount of FCS data at the same time, providing large statistical accuracy. Here, we optimize the processing and analysis of these large-scale acquired sets of FCS data. On one hand we present FoCuS-scan, scanning FCS software that provides an end-to-end solution for processing and analysing scanning data acquired on commercial turnkey confocal systems. On the other hand, we provide a thorough characterisation of large-scale scanning FCS data over its intended time-scales and applications and propose a unique solution for the bias and variance observed when studying slowly diffusing species. Our manuscript enables researchers to straightforwardly utilise scanning FCS as a powerful technique for measuring diffusion across a broad range of physiologically relevant length scales without specialised hardware or expensive software.

A major challenge in cell and developmental biology is the automated identification and quantitation of cells in complex multilayered tissues. We developed CytoCensus: an easily deployed implementation of supervised machine learning that extends convenient 2D ‘point-and-click’ user training to 3D detection of cells in challenging datasets with ill-defined cell boundaries. In tests on such datasets, CytoCensus outperforms other freely available image analysis software in accuracy and speed of cell detection. We used CytoCensus to count stem cells and their progeny, and to quantify individual cell divisions from time-lapse movies of explanted Drosophila larval brains, comparing wild-type and mutant phenotypes. We further illustrate the general utility and future potential of CytoCensus by analysing the 3D organisation of multiple cell classes in Zebrafish retinal organoids and cell distributions in mouse embryos. CytoCensus opens the possibility of straightforward and robust automated analysis of developmental phenotypes in complex tissues., eLife digest There are around 200 billion cells in the human brain that are generated by a small pool of rapidly dividing stem cells. For the brain to develop correctly, these stem cells must produce an appropriate number of each type of cell in the right place, at the right time. However, it remains unclear how individual stem cells in the brain know when and where to divide. To answer this question, Hailstone et al. studied the larvae of fruit flies, which use similar genes and mechanisms as humans to control brain development. This involved devising a new method for extracting the brains of developing fruit flies and keeping the intact tissue alive for up to 24 hours while continuously imaging individual cells in three dimensions. Manually tracking the division of each cell across multiple frames of a time-lapse is extremely time consuming. To tackle this problem, Hailstone et al. created a tool called CytoCensus, which uses machine learning to automatically identify stem cells from three-dimensional images and track their rate of division over time. Using the CytoCensus tool, Hailstone et al. identified a gene that controls the diverse rates at whichstem cells divide in the brain. Earlier this year some of the same researchers also published a study showing that this gene regulates a well-known cancer-related protein using an unconventional mechanism. CytoCensus was also able to detect cells in other developing tissues, including the embryos of mice. In the future, this tool could aid research into diseases that affect complex tissues, such as neurodegenerative disorders and cancer.

The lateral organization of molecules in the cellular plasma membrane plays an important role in cellular signaling. A critical parameter for membrane molecular organization is how the membrane lipids are packed (or ordered). Polarity sensitive dyes are powerful tools to characterize such lipid membrane order, employing for example confocal and two-photon microscopy. The investigation of potential lipid nanodomains, however, requires the use of super resolution microscopy. Here, we test the performance of the polarity sensitive membrane dyes Di-4-ANEPPDHQ, Di-4-AN(F)EPPTEA and NR12S in super resolution STED microscopy. Measurements on cell-derived membrane vesicles, in the plasma membrane of live cells, and on single virus particles show the high potential of these dyes for probing nanoscale membrane heterogeneity.

Diffusion and interaction dynamics of molecules at the plasma membrane play an important role in cellular signalling. These have been suggested to be strongly associated with the actin cytoskeleton. Here, we utilise super-resolution STED microscopy combined with fluorescence correlation spectroscopy (STED-FCS) to access the sub-diffraction diffusion regime of different fluorescent lipid analogues and GPI-anchored proteins (GPI-APs) in the cellular plasma membrane, and compare it to the diffusion regime of these molecules in cell-derived actin-free giant plasma membrane vesicles (GPMVs). We show that phospholipids and sphingomyelin, which undergo hindered diffusion in the live cell membrane, diffuse freely in the GPMVs. In contrast to sphingomyelin, which is transiently trapped on molecular-scale complexes in intact cells, diffusion of the ganglioside lipid GM1 suggests transient incorporation into nanodomains, which is less influenced by the actin cortex. Finally, our data on GPI-APs indicate two molecular pools in living cells, one pool showing high mobility with trapped and compartmentalized diffusion, and the other forming immobile clusters both of which disappear in GPMVs. Our data underlines the crucial role of the actin cortex in maintaining hindered diffusion modes of most but not all membrane molecules.