Consensus tissue domain detection in spatial omics data using multiplex image labeling with regional morphology (MILWRM).

Spatially resolved molecular assays provide high dimensional genetic, transcriptomic, proteomic, and epigenetic information in situ and at various resolutions. Pairing these data across modalities with histological features enables powerful studies of tissue pathology in the context of an intact microenvironment and tissue structure. Increasing dimensions across molecular analytes and samples require new data science approaches to functionally annotate spatially resolved molecular data.

GammaGateR: semi-automated marker gating for single-cell multiplexed imaging.

Motivation: Multiplexed immunofluorescence (mIF) is an emerging assay for multichannel protein imaging that can decipher cell-level spatial features in tissues. However, existing automated cell phenotyping methods, such as clustering, face challenges in achieving consistency across experiments and often require subjective evaluation. As a result, mIF analyses often revert to marker gating based on manual thresholding of raw imaging data.

Molecular cartography uncovers evolutionary and microenvironmental dynamics in sporadic colorectal tumors.

Colorectal cancer exhibits dynamic cellular and genetic heterogeneity during progression from precursor lesions toward malignancy. Analysis of spatial multi-omic data from 31 human colorectal specimens enabled phylogeographic mapping of tumor evolution that revealed individualized progression trajectories and accompanying microenvironmental and clonal alterations. Phylogeographic mapping ordered genetic events, classified tumors by their evolutionary dynamics, and placed clonal regions along global pseudotemporal progression trajectories encompassing the chromosomal instability (CIN+) and hypermutated (HM) pathways.

GammaGateR: semi-automated marker gating for single-cell multiplexed imaging.

Motivation: Multiplexed immunofluorescence (mIF) is an emerging assay for multichannel protein imaging that can decipher cell-level spatial features in tissues. However, existing automated cell phenotyping methods, such as clustering, face challenges in achieving consistency across experiments and often require subjective evaluation. As a result, mIF analyses often revert to marker gating based on manual thresholding of raw imaging data.

Detection of Treatment Response in Triple-Negative Breast Tumors to Paclitaxel Using MRI Cell Size Imaging.

Background: Breast cancer treatment response evaluation using the response evaluation criteria in solid tumors (RECIST) guidelines, based on tumor volume changes, has limitations, prompting interest in novel imaging markers for accurate therapeutic effect determination.

Purpose: To use MRI-measured cell size as a new imaging biomarker for assessing chemotherapy response in breast cancer.

Study Type: Longitudinal; animal model.

Multiplex immunohistochemistry and high-throughput image analysis for evaluation of spatial tumor immune cell markers in human breast cancer.

Background: The clinicopathological significance of spatial tumor-infiltrating lymphocytes (TILs) subpopulations is not well studied due to lack of high-throughput scalable methodology for studies with large human sample sizes.

Objective: Establishing a cyclic fluorescent multiplex immunohistochemistry (mIHC/IF) method coupled with computer-assisted high-throughput quantitative analysis to evaluate associations of six TIL markers (CD3, CD8, CD20, CD56, FOXP3, and PD-L1) with clinicopathological factors of breast cancer.

Methods: Our 5-plex mIHC/IF staining was shown to be reliable and highly sensitive for labeling three biomarkers per tissue section.

Selective Cell Size MRI Differentiates Brain Tumors from Radiation Necrosis.

Unlabelled: Brain metastasis is a common characteristic of late-stage lung cancers. High doses of targeted radiotherapy can control tumor growth in the brain but can also result in radiotherapy-induced necrosis. Current methods are limited for distinguishing whether new parenchymal lesions following radiotherapy are recurrent tumors or radiotherapy-induced necrosis, but the clinical management of these two classes of lesions differs significantly.

MIRIAM: A machine and deep learning single-cell segmentation and quantification pipeline for multi-dimensional tissue images.

Increasingly, highly multiplexed tissue imaging methods are used to profile protein expression at the single-cell level. However, a critical limitation is the lack of robust cell segmentation tools for tissue sections. We present Multiplexed Image Resegmentation of Internal Aberrant Membranes (MIRIAM) that combines (a) a pipeline for cell segmentation and quantification that incorporates machine learning-based pixel classification to define cellular compartments, (b) a novel method for extending incomplete cell membranes, and (c) a deep learning-based cell shape descriptor.

Quantifying and correcting slide-to-slide variation in multiplexed immunofluorescence images.

Motivation: Multiplexed imaging is a nascent single-cell assay with a complex data structure susceptible to technical variability that disrupts inference. These in situ methods are valuable in understanding cell-cell interactions, but few standardized processing steps or normalization techniques of multiplexed imaging data are available.

Results: We implement and compare data transformations and normalization algorithms in multiplexed imaging data.

Supermeres are functional extracellular nanoparticles replete with disease biomarkers and therapeutic targets.

Extracellular vesicles and exomere nanoparticles are under intense investigation as sources of clinically relevant cargo. Here we report the discovery of a distinct extracellular nanoparticle, termed supermere. Supermeres are morphologically distinct from exomeres and display a markedly greater uptake in vivo compared with small extracellular vesicles and exomeres.

MCMICRO: a scalable, modular image-processing pipeline for multiplexed tissue imaging.

Highly multiplexed tissue imaging makes detailed molecular analysis of single cells possible in a preserved spatial context. However, reproducible analysis of large multichannel images poses a substantial computational challenge. Here, we describe a modular and open-source computational pipeline, MCMICRO, for performing the sequential steps needed to transform whole-slide images into single-cell data.

Induction of apically mistrafficked epiregulin disrupts epithelial polarity via aberrant EGFR signaling.

In polarized MDCK cells, disruption of the tyrosine-based YXXΦ basolateral trafficking motif (Y156A) in the epidermal growth factor receptor (EGFR) ligand epiregulin (EREG), results in its apical mistrafficking and transformation in vivo. However, the mechanisms underlying these dramatic effects are unknown. Using a doxycycline-inducible system in 3D Matrigel cultures, we now show that induction of Y156A EREG in fully formed MDCK cysts results in direct and complete delivery of mutant EREG to the apical cell surface.

MRI-cytometry: Mapping nonparametric cell size distributions using diffusion MRI.

Purpose: This report introduces and validates a new diffusion MRI-based method, termed MRI-cytometry, which can noninvasively map intravoxel, nonparametric cell size distributions in tissues.

Methods: MRI was used to acquire diffusion MRI signals with a range of diffusion times and gradient factors, and a model was fit to these data to derive estimates of cell size distributions. We implemented a 2-step fitting method to avoid noise-induced artificial peaks and provide reliable estimates of tumor cell size distributions.

Succinate Produced by Intestinal Microbes Promotes Specification of Tuft Cells to Suppress Ileal Inflammation.

Background & Aims: Countries endemic for parasitic infestations have a lower incidence of Crohn's disease (CD) than nonendemic countries, and there have been anecdotal reports of the beneficial effects of helminths in CD patients. Tuft cells in the small intestine sense and direct the immune response against eukaryotic parasites. We investigated the activities of tuft cells in patients with CD and mouse models of intestinal inflammation.

Magnetic resonance imaging of mean cell size in human breast tumors.

Purpose: Cell size is a fundamental characteristic of all tissues, and changes in cell size in cancer reflect tumor status and response to treatments, such as apoptosis and cell-cycle arrest. Unfortunately, cell size can currently be obtained only by pathological evaluation of tumor tissue samples obtained invasively. Previous imaging approaches are limited to preclinical MRI scanners or require relatively long acquisition times that are impractical for clinical imaging.

In vivo magnetic resonance imaging of treatment-induced apoptosis.

Imaging apoptosis could provide an early and specific means to monitor tumor responses to treatment. To date, despite numerous attempts to develop molecular imaging approaches, there is still no widely-accepted and reliable method for in vivo imaging of apoptosis. We hypothesized that the distinct cellular morphologic changes associated with treatment-induced apoptosis, such as cell shrinkage, cytoplasm condensation, and DNA fragmentation, can be detected by temporal diffusion spectroscopy imaging (TDSI).

Transfer of Functional Cargo in Exomeres.

Exomeres are a recently discovered type of extracellular nanoparticle with no known biological function. Herein, we describe a simple ultracentrifugation-based method for separation of exomeres from exosomes. Exomeres are enriched in Argonaute 1-3 and amyloid precursor protein.

Interpreting heterogeneity in intestinal tuft cell structure and function.

Intestinal tuft cells are a morphologically unique cell type, best characterized by striking microvilli that form an apical tuft. These cells represent approximately 0.5% of gut epithelial cells depending on location.

Single-Cell Computational Strategies for Lineage Reconstruction in Tissue Systems.

Function at the organ level manifests itself from a heterogeneous collection of cell types. Cellular heterogeneity emerges from developmental processes by which multipotent progenitor cells make fate decisions and transition to specific cell types through intermediate cell states. Although genetic experimental strategies such as lineage tracing have provided insights into cell lineages, recent developments in single-cell technologies have greatly increased our ability to interrogate distinct cell types, as well as transitional cell states in tissue systems.

Unsupervised Trajectory Analysis of Single-Cell RNA-Seq and Imaging Data Reveals Alternative Tuft Cell Origins in the Gut.

Modern single-cell technologies allow multiplexed sampling of cellular states within a tissue. However, computational tools that can infer developmental cell-state transitions reproducibly from such single-cell data are lacking. Here, we introduce p-Creode, an unsupervised algorithm that produces multi-branching graphs from single-cell data, compares graphs with differing topologies, and infers a statistically robust hierarchy of cell-state transitions that define developmental trajectories.

Optimized multiplex immunofluorescence single-cell analysis reveals tuft cell heterogeneity.

Intestinal tuft cells are a rare, poorly understood cell type recently shown to be a critical mediator of type 2 immune response to helminth infection. Here, we present advances in segmentation algorithms and analytical tools for multiplex immunofluorescence (MxIF), a platform that enables iterative staining of over 60 antibodies on a single tissue section. These refinements have enabled a comprehensive analysis of tuft cell number, distribution, and protein expression profiles as a function of anatomical location and physiological perturbations.