Identification of spatial co-expression patterns and intra-tissue heterogeneity in spatially resolved transcriptomics by region-specific denoising

We are pleased to introduce a first-of-its-kind tool that combines in-silico region detection and missing value estimation for spatially resolved transcriptomics. Spatial transcriptomics by 10X Visium (ST) is a new technology used to dissect gene and cell spatial organization. Analyzing this new type of data has two main challenges: automatically annotating the major tissue regions and excessive zero values of gene expression due to high dropout rates. We developed a computational tool—MIST—that addresses both challenges by automatically identifying tissue regions and estimating missing gene-expression values for each detected region. We validated MIST detected regions across multiple datasets using manual annotation on the histological staining images as references. We also demonstrated that MIST can accurately recover ST’s missing values through hold-out experiments. Furthermore, we showed that MIST could identify intra-tissue heterogeneity and recover spatial gene-gene co-expression signals. We therefore strongly encourage using MIST before downstream ST analysis because it provides unbiased region annotations and enables accurately denoised spatial gene-expression profiles.

Rotational Activity Around an Obstacle in 2D Cardiac Tissue in Presence of Cellular Heterogeneity

Waves of electrical excitation rotating around an obstacle is one of the important mechanisms of dangerous cardiac arrhythmias occurring in the heart damaged by post-infarction scar. Such a scar also has a border zone around it, which has electrophysiological properties different from the rest of normal myocardial tissue. Spatial patterns of wave rotation in the presence of such tissue heterogeneity are poorly studied. In this paper we perform a comprehensive numerical study of various regimes of rotation of a wave in a plane layer of the ventricular tissue around an obstacle surrounded by a gray zone. We use a TP06 cellular ionic model which reproduces the electrophysiological properties cardiomyocytes in the left ventricle of human heart. We vary the extent of obstacle and gray zone and study the pattern of wave rotation and its period. We observed different regimes of wave rotation that can be subdivided into several classes: (1) functional rotation and (2) scar rotation regimes, which were identified in the previous studies, and new (3) gray zone rotation regime: where the wave instead of rotation around the obstacle, rotates around the gray zone (an area of tissue heterogeneity) itself. For each class, the period of rotation is determined by different factors, which we discuss and quantify. We also found that due to regional pathological remodeling of myocardial tissue, we can obtain additional regimes associated with dynamical instabilities of two types which may affect or not affect the period of rotation.

Diffusion-Weighted Imaging and Mapping of T1 and T2 Relaxation Time for Evaluation of Chronic Renal Allograft Rejection in a Translational Mouse Model

We hypothesized that multiparametric MRI is able to non-invasively assess, characterize and monitor renal allograft pathology in a translational mouse model of chronic allograft rejection. Chronic rejection was induced by allogenic kidney transplantation (ktx) of BALB/c-kidneys into C57BL/6-mice (n = 23). Animals after isogenic ktx (n = 18) and non-transplanted healthy animals (n = 22) served as controls. MRI sequences (7T) were acquired 3 and 6 weeks after ktx and quantitative T1, T2 and apparent diffusion coefficient (ADC) maps were calculated. In addition, in a subset of animals, histological changes after ktx were evaluated. Chronic rejection was associated with a significant prolongation of T1 time compared to isogenic ktx 3 (1965 ± 53 vs. 1457 ± 52 ms, p < 0.001) and 6 weeks after surgery (1899 ± 79 vs. 1393 ± 51 ms, p < 0.001). While mean T2 times and ADC were not significantly different between allogenic and isogenic kidney grafts, histogram-based analysis of ADC revealed significantly increased tissue heterogeneity in allografts at both time points (standard derivation/entropy/interquartile range, p < 0.05). Correspondingly, histological analysis showed severe inflammation, graft fibrosis and tissue heterogeneity in allogenic but not in isogenic kidney grafts. In conclusion, renal diffusion weighted imaging and mapping of T2 and T1 relaxation times enable detection of chronic renal allograft rejection in mice. The combined quantitative assessment of mean values and histograms provides non-invasive information of chronic changes in renal grafts and allows longitudinal monitoring.

Three-dimensional label-free histological imaging of whole organs by microtomy-assisted autofluorescence tomography

Three-dimensional (3D) histology is vitally important to characterize disease-induced tissue heterogeneity at the individual cell level. However, it remains a scientific challenge for both high-quality 3D imaging and volumetric reconstruction. Here we propose a label-free, automated, and ready-to-use 3D histological imaging technique, termed microtomy-assisted autofluorescence tomography with ultraviolet excitation (MATE). With the combination of block-face imaging and serial microtome sectioning, MATE can achieve rapid and label-free imaging of paraffin-embedded whole organs at an acquisition speed of 1 cm3 per 4 hours with a voxel resolution of 1.2 × 1.2 × 10 μm3. We demonstrate that MATE enables simultaneous visualization of cell nuclei, fiber tracts, and blood vessels in mouse/human brains without tissue staining or clearing. Moreover, diagnostic features, such as nuclear size and packing density, can be quantitatively extracted with high accuracy. MATE is augmented to the current slide-based 2D histology, holding great promise for facilitating histopathological interpretation at the cell level to analyze complex tissue heterogeneity in 3D.Significance StatementConventional 3D histology based on spatial registration of serial histochemically-stained thin tissue slices is fundamentally labor-intensive and inaccurate. Here, we propose a rapid and label-free 3D histological imaging technique (i.e., MATE) that enables high-resolution imaging of complex whole organs without tissue staining or clearing. MATE is fully automated to provide a series of distortion- and registration-free images with intrinsic absorption-based contrast, demonstrating great potential as a routine tissue analysis tool that can seamlessly fit into the current clinical practice to facilitate the applications of histopathological interpretation at the subcellular level.

Tissue heterogeneity is prevalent in gene expression studies

Lack of reproducibility in gene expression studies is a serious issue being actively addressed by the biomedical research community. Besides established factors such as batch effects and incorrect sample annotations, we recently reported tissue heterogeneity, a consequence of unintended profiling of cells of other origins than the tissue of interest, as a source of variance. Although tissue heterogeneity exacerbates irreproducibility, its prevalence in gene expression data remains unknown. Here, we systematically analyse 2 667 publicly available gene expression datasets covering 76 576 samples. Using two independent data compendia and a reproducible, open-source software pipeline, we find a prevalence of tissue heterogeneity in gene expression data that affects between 1 and 40% of the samples, depending on the tissue type. We discover both cases of severe heterogeneity, which may be caused by mistakes in annotation or sample handling, and cases of moderate heterogeneity, which are likely caused by tissue infiltration or sample contamination. Our analysis establishes tissue heterogeneity as a widespread phenomenon in publicly available gene expression datasets, which constitutes an important source of variance that should not be ignored. Consequently, we advocate the application of quality-control methods such as BioQC to detect tissue heterogeneity prior to mining or analysing gene expression data.

Recalcitrance of Corn Straw Significantly Correlated to the Heterogeneity in Physicochemical Properties of Cell Wall

Background: Tissue heterogeneity significantly influences the overall saccharification efficiency of plant biomass. However, the mechanisms of specific organ or tissue recalcitrance to enzymatic deconstruction are generally complicated and unclear. A multidimensional analysis for the four parts from twelve corn cultivars was conducted.Results: The results showed that leaf, sheath, pith and rind of corn straw exhibited remarkable heterogeneity in chemical composition, physical structure and cell type, which resulted in the different recalcitrance to enzymatic hydrolysis. High values of lignin, hemicelluloses, degree of polymerization and crystallinity index were critical for the increased recalcitrance, while high value of neutral detergent soluble and pore size generated weak recalcitrance. Interestingly, pore traits of cell wall, especial for microcosmic interface structure, seemed to be a crucial factor that correlated to cellulase adsorption and further affected saccharification.Conclusions: Tissue heterogeneity in physical-chemical traits of cell wall influences the overall saccharification efficiency of biomass. Furthermore, the holistic outlook of cell wall interface is indispensable to understand the recalcitrance and promote the biomass conversion.