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The liver has the remarkable capacity to regenerate. In the clinic, regeneration is induced by portal vein embolization, which redirects portal blood flow, resulting in liver hypertrophy in locations with increased blood supply, and atrophy of embolized segments. Here, we apply single-cell and single-nucleus transcriptomics on healthy, hypertrophied, and atrophied patient-derived liver samples to explore cell states in the regenerating liver. Our data unveils pervasive upregulation of genes associated with developmental processes, cellular adhesion, and inflammation in post-portal vein embolization liver, disrupted portal-central hepatocyte zonation, and altered cell subtype composition of endothelial and immune cells. Interlineage crosstalk analysis reveals mesenchymal cells as an interaction hub between immune and endothelial cells, and highlights the importance of extracellular matrix proteins in liver regeneration. Moreover, we establish tissue-scale iterative indirect immunofluorescence imaging for high-dimensional spatial analysis of perivascular microenvironments, uncovering changes to tissue architecture in regenerating liver lobules. Altogether, our data is a rich resource revealing cellular and histological changes in human liver regeneration., (© 2024. The Author(s).)

Liver macrophages (LMs) play a central role in acute and chronic liver pathologies. Investigation of these processes in humans as well as the development of diagnostic tools and new therapeutic strategies require in vitro models that closely resemble the in vivo situation. In our study, we sought to gain further insight into the role of LMs in different liver pathologies and into their characteristics after isolation from liver tissue. For this purpose, LMs were characterized in human liver tissue sections using immunohistochemistry and bioinformatic image analysis. Isolated cells were characterized in suspension using FACS analyses and in culture using immunofluorescence staining and laser scanning microscopy as well as functional assays. The majority of our investigated liver tissues were characterized by anti-inflammatory LMs which showed a homogeneous distribution and increased cell numbers in correlation with chronic liver injuries. In contrast, pro-inflammatory LMs appeared as temporary and locally restricted reactions. Detailed characterization of isolated macrophages revealed a complex disease dependent pattern of LMs consisting of pro- and anti-inflammatory macrophages of different origins, regulatory macrophages and monocytes. Our study showed that in most cases the macrophage pattern can be transferred in adherent cultures. The observed exceptions were restricted to LMs with pro-inflammatory characteristics.

Background: We present an image dataset related to automated segmentation and counting of macrophages in diffuse large B-cell lymphoma (DLBCL) tissue sections. For the classification of DLBCL subtypes, as well as for providing a prognosis of the clinical outcome, the analysis of the tumor microenvironment and, particularly, of the different types and functions of tumor-associated macrophages is indispensable. Until now, however, most information about macrophages has been obtained either in a completely indirect way by gene expression profiling or by manual counts in immunohistochemically (IHC) fluorescence-stained tissue samples while automated recognition of single IHC stained macrophages remains a difficult task. In an accompanying publication, a reliable approach to this problem has been established, and a large set of related images has been generated and analyzed., Results: Provided image data comprise (i) fluorescence microscopy images of 44 multiple immunohistostained DLBCL tumor subregions, captured at 4 channels corresponding to CD14, CD163, Pax5, and DAPI; (ii) "cartoon-like" total variation-filtered versions of these images, generated by Rudin-Osher-Fatemi denoising; (iii) an automatically generated mask of the evaluation subregion, based on information from the DAPI channel; and (iv) automatically generated segmentation masks for macrophages (using information from CD14 and CD163 channels), B-cells (using information from Pax5 channel), and all cell nuclei (using information from DAPI channel)., Conclusions: A large set of IHC stained DLBCL specimens is provided together with segmentation masks for different cell populations generated by a reference method for automated image analysis, thus featuring considerable reuse potential., (© The Author(s) 2020. Published by Oxford University Press.)

Background: For analysis of the tumor microenvironment in diffuse large B-cell lymphoma (DLBCL) tissue samples, it is desirable to obtain information about counts and distribution of different macrophage subtypes. Until now, macrophage counts are mostly inferred from gene expression analysis of whole tissue sections, providing only indirect information. Direct analysis of immunohistochemically (IHC) fluorescence stained tissue samples is confronted with several difficulties, e.g. high variability of shape and size of target macrophages and strongly inhomogeneous intensity of staining. Consequently, application of commercial software is largely restricted to very rough analysis modes, and most macrophage counts are still obtained by manual counting in microarrays or high power fields, thus failing to represent the heterogeneity of tumor microenvironment adequately., Methods: We describe a Rudin-Osher-Fatemi (ROF) filter based segmentation approach for whole tissue samples, combining floating intensity thresholding and rule-based feature detection. Method is validated against manual counts and compared with two commercial software kits (Tissue Studio 64, Definiens AG, and Halo, Indica Labs) and a straightforward machine-learning approach in a set of 50 test images. Further, the novel method and both commercial packages are applied to a set of 44 whole tissue sections. Outputs are compared with gene expression data available for the same tissue samples. Finally, the ROF based method is applied to 44 expert-specified tumor subregions for testing selection and subsampling strategies., Results: Among all tested methods, the novel approach is best correlated with manual count (0.9297). Automated detection of evaluation subregions proved to be fully reliable. Comparison with gene expression data obtained for the same tissue samples reveals only moderate to low correlation levels. Subsampling within tumor subregions is possible with results almost identical to full sampling. Mean macrophage size in tumor subregions is 152.5±111.3 μ m 2 ., Conclusions: ROF based approach is successfully applied to detection of IHC stained macrophages in DLBCL tissue samples. The method competes well with existing commercial software kits. In difference to them, it is fully automated, externally repeatable, independent on training data and completely documented. Comparison with gene expression data indicates that image morphometry constitutes an independent source of information about antibody-polarized macrophage occurence and distribution., Competing Interests: Competing interestsThe authors declare that they have no competing interests.

G-quadruplex topologies of telomeric repeat sequences from vertebrates were investigated in the presence of molecular crowding (MC) mimetics, namely polyethylene glycol 200 (PEG), Ficoll 70 as well as Xenopus laevis egg extract by CD and NMR spectroscopy and native PAGE. Here, we show that the conformational behavior of the telomeric repeats in X. laevis egg extract or in Ficoll is notably different from that observed in the presence of PEG. While the behavior of the telomeric repeat in X. laevis egg extract or in Ficoll resembles results obtained under dilute conditions, PEG promotes the formation of high-order parallel topologies. Our data suggest that PEG should not be used as a MC mimetic.

Aromatic proton resonances of proteins are notoriously difficult to assign. Through-bond correlation experiments are preferable over experiments that rely on through-space interactions because they permit aromatic chemical shift assignments to be established independently of the structure determination process. Known experimental schemes involving a magnetization transfer across the Cbeta-Cgamma bond in aromatic side chains either suffer from low efficiency for the relay beyond the Cdelta position, use sophisticated 13C mixing schemes, require probe heads suitable for application of high 13C radio-frequency fields or rely on specialized isotopic labelling patterns. Novel methods are proposed that result in sequential assignment of all aromatic protons in uniformly 13C/15N labelled proteins using standard spectrometer hardware. Pulse sequences consist of routinely used building blocks and are therefore reasonably simple to implement. Ring protons may be correlated with beta-carbons and, alternatively, with amide protons (and nitrogens) or carbonyls in order to take advantage of the superior dispersion of backbone resonances. It is possible to record spectra in a non-selective manner, yielding signals of all aromatic residues, or as amino-acid type selective versions to further reduce ambiguities. The new experiments are demonstrated with four different proteins with molecular weights ranging from 11 kDa to 23 kDa. Their performance is compared with that of (Hbeta)Cbeta(CgammaCdelta)Hdelta and (Hbeta)Cbeta(CgammaCdeltaCepsilon)Hepsilon pulse sequences.