IBEX: A versatile multiplex optical imaging approach for deep phenotyping and spatial analysis of cells in complex tissues

Abstract

The diverse composition of mammalian tissues poses challenges for understanding the cell–cell interactions required for organ homeostasis and how spatial relationships are perturbed during disease. Existing methods such as single-cell genomics, lacking a spatial context, and traditional immunofluorescence, capturing only two to six molecular features, cannot resolve these issues. Imaging technologies have been developed to address these problems, but each possesses limitations that constrain widespread use. Here we report a method that overcomes major impediments to highly multiplex tissue imaging. “Iterative bleaching extends multiplexity” (IBEX) uses an iterative staining and chemical bleaching method to enable high-resolution imaging of >65 parameters in the same tissue section without physical degradation. IBEX can be employed with various types of conventional microscopes and permits use of both commercially available and user-generated antibodies in an “open” system to allow easy adjustment of staining panels based on ongoing marker discovery efforts. We show how IBEX can also be used with amplified staining methods for imaging strongly fixed tissues with limited epitope retention and with oligonucleotide-based staining, allowing potential cross-referencing between flow cytometry, cellular indexing of transcriptomes and epitopes by sequencing, and IBEX analysis of the same tissue. To facilitate data processing, we provide an open-source platform for automated registration of iterative images. IBEX thus represents a technology that can be rapidly integrated into most current laboratory workflows to achieve high-content imaging to reveal the complex cellular landscape of diverse organs and tissues.

A New Protocol of Computer-Assisted Image Analysis Highlights the Presence of Hemocytes in the Regenerating Cephalic Tentacles of Adult Pomacea canaliculata

“…Molecular information about P. canaliculata and its hemocytes is increasing [ 31 , 36 , 37 , 38 ] but, to our knowledge, no specific cell markers have been described for tracking circulating [ 25 , 31 ] or tissue-resident [ 30 , 36 , 39 ] hemocytes. In absence of cell markers, the most advanced techniques of image analysis [ 28 ] cannot be applied, and other methods must be developed to time-effectively and reliably document hemocyte presence in P. canaliculata tissues. This could also pave the way for studies concerning the effects of hemocyte depletion on organ regeneration.…”

“…The increasing availability of molecular data and cell markers opened the possibility for advanced image analysis, both through flow cytometry and optical microscopy. The most advanced methods of image analysis can identify a variety of cell types in the context of healthy and pathological tissues relying on the availability of multiple cell markers [ 28 ]. In the absence of specific cell markers, advanced flow cytometry can help [ 29 ], but it does not provide information about tissue contextualization [ 28 ].…”

“…The most advanced methods of image analysis can identify a variety of cell types in the context of healthy and pathological tissues relying on the availability of multiple cell markers [ 28 ]. In the absence of specific cell markers, advanced flow cytometry can help [ 29 ], but it does not provide information about tissue contextualization [ 28 ]. To our knowledge, no specific molecular markers are available for tracking tissue and circulating hemocytes in P. canaliculata [ 25 , 30 , 31 ], hampering hemocyte quantification outside the hemolymph.…”

Quantitative Assessment of Experimental Ocular Inflammatory Disease

“…This is seen in the recent application of deep learning to EAU (27). Alternative powerful technologies are also available; using bioluminescent reporters, can delineate sequential cell population specific patterns of infiltration (28,29), and multi-optical imaging approaches can produce data on phenotype and the spatial relationship between different cell types (30). Objective measurements, that provide a more granular multi-modal analysis of the state of the tissue, can then form the basis for quantifying the impact of treatment on ocular disease not limited to a single time-point but integrated across a longer disease course.…”

Multi-Parameter Quantitative Imaging of Tumor Microenvironments Reveals Perivascular Immune Niches Associated with Anti-Tumor Immunity

“…Multiplexed imaging and spatially resolved sequencing technologies have revealed complex cellular organization across tissue types and diverse pathological conditions (Gerner et al, 2012; Gerdes et al, 2013; Giesen et al, 2014; Liu et al, 2015; Gerner et al, 2017; Li et al, 2017; Petrovas et al, 2017; Gut et al, 2018; Mao et al, 2018; Lin et al, 2018; Keren et al, 2018; Ak et al, 2019; Vickovic et al, 2019; Eng et al, 2019; Nearchou et al, 2019; Radtke et al, 2020; Schürch et al, 2020; Plumlee et al, 2021; Gern et al, 2021; Leal et al, 2021). Advanced computational and statistical approaches applied to such datasets allow quantification of various spatial properties, such as cellular distance relationships, preferential cell-cell associations, and organization of tissue microenvironments (Caicedo et al, 2017; Schapiro et al, 2017; Coutu et al, 2018; Goltsev et al, 2018; Eling et al, 2020; Schürch et al, 2020; Stoltzfus et al, 2020a; Dries et al, 2021).…”