Illuminating Non-genetic Cellular Heterogeneity with Imaging-Based Spatial Proteomics

Trends and Challenges of the Modern Pathology Laboratory for Biopharmaceutical Research Excellence

Pathology, a fundamental discipline that bridges basic scientific discovery to the clinic, is integral to successful drug development. Intrinsically multimodal and multidimensional, anatomic pathology continues to be empowered by advancements in molecular and digital technologies enabling the spatial tissue detection of biomolecules such as genes, transcripts, and proteins. Over the past two decades, breakthroughs in spatial molecular biology technologies and advancements in automation and digitization of laboratory processes have enabled the implementation of higher throughput assays and the generation of extensive molecular data sets from tissue sections in biopharmaceutical research and development research units. It is our goal to provide readers with some rationale, advice, and ideas to help establish a modern molecular pathology laboratory to meet the emerging needs of biopharmaceutical research. This manuscript provides (1) a high-level overview of the current state and future vision for excellence in research pathology practice and (2) shared perspectives on how to optimally leverage the expertise of discovery, toxicologic, and translational pathologists to provide effective spatial, molecular, and digital pathology data to support modern drug discovery. It captures insights from the experiences, challenges, and solutions from pathology laboratories of various biopharmaceutical organizations, including their approaches to troubleshooting and adopting new technologies.

Mapping the Multiscale Proteomic Organization of Cellular and Disease Phenotypes

While the primary sequences of human proteins have been cataloged for over a decade, determining how these are organized into a dynamic collection of multiprotein assemblies, with structures and functions spanning biological scales, is an ongoing venture. Systematic and data-driven analyses of these higher-order structures are emerging, facilitating the discovery and understanding of cellular phenotypes. At present, knowledge of protein localization and function has been primarily derived from manual annotation and curation in resources such as the Gene Ontology, which are biased toward richly annotated genes in the literature. Here, we envision a future powered by data-driven mapping of protein assemblies. These maps can capture and decode cellular functions through the integration of protein expression, localization, and interaction data across length scales and timescales. In this review, we focus on progress toward constructing integrated cell maps that accelerate the life sciences and translational research.

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

The spatial organization of molecules in a cell is essential for their functions. While current methods focus on discerning tissue architecture, cell-cell interactions, and spatial expression patterns, they are limited to the multicellular scale. We present Bento, a Python toolkit that takes advantage of single-molecule information to enable spatial analysis at the subcellular scale. Bento ingests molecular coordinates and segmentation boundaries to perform three analyses: defining subcellular domains, annotating localization patterns, and quantifying gene-gene colocalization. We demonstrate MERFISH, seqFISH + , Molecular Cartography, and Xenium datasets. Bento is part of the open-source Scverse ecosystem, enabling integration with other single-cell analysis tools.

Combination Treatment with Liposomal Doxorubicin and Inductive Moderate Hyperthermia for Sarcoma Saos-2 Cells

Despite efforts in osteosarcoma (OS) research, the role of inductive moderate hyperthermia (IMH) in delivering and enhancing the antitumor effect of liposomal doxorubicin formulations (LDOX) remains unresolved. This study investigated the effect of a combination treatment with LDOX and IMH on Saos-2 human OS cells. We compared cell viability using a trypan blue assay, apoptosis and reactive oxygen species (ROS) measured by flow cytometry and pro-apoptotic Bax protein expression examined by immunocytochemistry in response to IMH (42 MHz frequency, 15 W power for 30 min), LDOX (0.4 μg/mL), and LDOX plus IMH. The lower IC50 value of LDOX at 72 h indicated increased accumulation of the drug in the OS cells. LDOX plus IMH resulted in a 61% lower cell viability compared to no treatment. Moreover, IMH potentiated the LDOX action on the Saos-2 cells by promoting ROS production at temperatures of <42 °C. There was a 12% increase in cell populations undergoing early apoptosis with a less heterogeneous distribution of Bax after combination treatment compared to those treated with LDOX (p < 0.05). Therefore, we determined that IMH could enhance LDOX delivery and its antitumor effect via altered membrane permeabilization, ROS generation, and a lower level of visualized Bax heterogeneity in the Saos-2 cells, suggesting the potential translation of these findings into in vivo studies.

Biological mass spectrometry enables spatiotemporal 'omics: From tissues to cells to organelles

Biological processes unfold across broad spatial and temporal dimensions, and measurement of the underlying molecular world is essential to their understanding. Interdisciplinary efforts advanced mass spectrometry (MS) into a tour de force for assessing virtually all levels of the molecular architecture, some in exquisite detection sensitivity and scalability in space-time. In this review, we offer vignettes of milestones in technology innovations that ushered sample collection and processing, chemical separation, ionization, and 'omics analyses to progressively finer resolutions in the realms of tissue biopsies and limited cell populations, single cells, and subcellular organelles. Also highlighted are methodologies that empowered the acquisition and analysis of multidimensional MS data sets to reveal proteomes, peptidomes, and metabolomes in ever-deepening coverage in these limited and dynamic specimens. In pursuit of richer knowledge of biological processes, we discuss efforts pioneering the integration of orthogonal approaches from molecular and functional studies, both within and beyond MS. With established and emerging community-wide efforts ensuring scientific rigor and reproducibility, spatiotemporal MS emerged as an exciting and powerful resource to study biological systems in space-time.

Global analysis of aging-related protein structural changes uncovers enzyme-polymerization-based control of longevity

Aging is associated with progressive phenotypic changes. Virtually all cellular phenotypes are produced by proteins, and their structural alterations can lead to age-related diseases. However, we still lack comprehensive knowledge of proteins undergoing structural-functional changes during cellular aging and their contributions to age-related phenotypes. Here, we conducted proteome-wide analysis of early age-related protein structural changes in budding yeast using limited proteolysis-mass spectrometry (LiP-MS). The results, compiled in online ProtAge catalog, unraveled age-related functional changes in regulators of translation, protein folding, and amino acid metabolism. Mechanistically, we found that folded glutamate synthase Glt1 polymerizes into supramolecular self-assemblies during aging, causing breakdown of cellular amino acid homeostasis. Inhibiting Glt1 polymerization by mutating the polymerization interface restored amino acid levels in aged cells, attenuated mitochondrial dysfunction, and led to lifespan extension. Altogether, this comprehensive map of protein structural changes enables identifying mechanisms of age-related phenotypes and offers opportunities for their reversal.

Nonmonotone invasion landscape by noise-aware control of metastasis activator levels

A major pharmacological assumption is that lowering disease-promoting protein levels is generally beneficial. For example, inhibiting metastasis activator BACH1 is proposed to decrease cancer metastases. Testing such assumptions requires approaches to measure disease phenotypes while precisely adjusting disease-promoting protein levels. Here we developed a two-step strategy to integrate protein-level tuning, noise-aware synthetic gene circuits into a well-defined human genomic safe harbor locus. Unexpectedly, engineered MDA-MB-231 metastatic human breast cancer cells become more, then less and then more invasive as we tune BACH1 levels up, irrespective of the native BACH1. BACH1 expression shifts in invading cells, and expression of BACH1's transcriptional targets confirm BACH1's nonmonotone phenotypic and regulatory effects. Thus, chemical inhibition of BACH1 could have unwanted effects on invasion. Additionally, BACH1's expression variability aids invasion at high BACH1 expression. Overall, precisely engineered, noise-aware protein-level control is necessary and important to unravel disease effects of genes to improve clinical drug efficacy.

Single-cell subcellular protein localisation using novel ensembles of diverse deep architectures

Unravelling protein distributions within individual cells is vital to understanding their function and state and indispensable to developing new treatments. Here we present the Hybrid subCellular Protein Localiser (HCPL), which learns from weakly labelled data to robustly localise single-cell subcellular protein patterns. It comprises innovative DNN architectures exploiting wavelet filters and learnt parametric activations that successfully tackle drastic cell variability. HCPL features correlation-based ensembling of novel architectures that boosts performance and aids generalisation. Large-scale data annotation is made feasible by our AI-trains-AI approach, which determines the visual integrity of cells and emphasises reliable labels for efficient training. In the Human Protein Atlas context, we demonstrate that HCPL is best performing in the single-cell classification of protein localisation patterns. To better understand the inner workings of HCPL and assess its biological relevance, we analyse the contributions of each system component and dissect the emergent features from which the localisation predictions are derived.

Spatial Proteomics for the Molecular Characterization of Breast Cancer

Breast cancer (BC) is a major global health issue, affecting a significant proportion of the female population and contributing to high rates of mortality. One of the primary challenges in the treatment of BC is the disease's heterogeneity, which can lead to ineffective therapies and poor patient outcomes. Spatial proteomics, which involves the study of protein localization within cells, offers a promising approach for understanding the biological processes that contribute to cellular heterogeneity within BC tissue. To fully leverage the potential of spatial proteomics, it is critical to identify early diagnostic biomarkers and therapeutic targets, and to understand protein expression levels and modifications. The subcellular localization of proteins is a key factor in their physiological function, making the study of subcellular localization a major challenge in cell biology. Achieving high resolution at the cellular and subcellular level is essential for obtaining an accurate spatial distribution of proteins, which in turn can enable the application of proteomics in clinical research. In this review, we present a comparison of current methods of spatial proteomics in BC, including untargeted and targeted strategies. Untargeted strategies enable the detection and analysis of proteins and peptides without a predetermined molecular focus, whereas targeted strategies allow the investigation of a predefined set of proteins or peptides of interest, overcoming the limitations associated with the stochastic nature of untargeted proteomics. By directly comparing these methods, we aim to provide insights into their strengths and limitations and their potential applications in BC research.

Therapy resistance: opportunities created by adaptive responses to targeted therapies in cancer

Normal cells explore multiple states to survive stresses encountered during development and self-renewal as well as environmental stresses such as starvation, DNA damage, toxins or infection. Cancer cells co-opt normal stress mitigation pathways to survive stresses that accompany tumour initiation, progression, metastasis and immune evasion. Cancer therapies accentuate cancer cell stresses and invoke rapid non-genomic stress mitigation processes that maintain cell viability and thus represent key targetable resistance mechanisms. In this Review, we describe mechanisms by which tumour ecosystems, including cancer cells, immune cells and stroma, adapt to therapeutic stresses and describe three different approaches to exploit stress mitigation processes: (1) interdict stress mitigation to induce cell death; (2) increase stress to induce cellular catastrophe; and (3) exploit emergent vulnerabilities in cancer cells and cells of the tumour microenvironment. We review challenges associated with tumour heterogeneity, prioritizing actionable adaptive responses for optimal therapeutic outcomes, and development of an integrative framework to identify and target vulnerabilities that arise from adaptive responses and engagement of stress mitigation pathways. Finally, we discuss the need to monitor adaptive responses across multiple scales and translation of combination therapies designed to take advantage of adaptive responses and stress mitigation pathways to the clinic.

Proximity-Dependent Biotinylation Approaches to Explore the Dynamic Compartmentalized Proteome

In recent years, proximity-dependent biotinylation approaches, including BioID, APEX, and their derivatives, have been widely used to define the compositions of organelles and other structures in cultured cells and model organisms. The associations between specific proteins and given compartments are regulated by several post-translational modifications (PTMs); however, these effects have not been systematically investigated using proximity proteomics. Here, we discuss the progress made in this field and how proximity-dependent biotinylation strategies could elucidate the contributions of PTMs, such as phosphorylation, to the compartmentalization of proteins.

On the Regulation of Mitosis by the Kinetochore, a Macromolecular Complex and Organising Hub of Eukaryotic Organisms

The kinetochore is the multiprotein complex of eukaryotic organisms that is assembled on mitotic or meiotic centromeres to connect centromeric DNA with microtubules. Its function involves the coordinated action of more than 100 different proteins. The kinetochore acts as an organiser hub that establishes physical connections with microtubules and centromere-associated proteins and recruits central protein components of the spindle assembly checkpoint (SAC), an evolutionarily conserved surveillance mechanism of eukaryotic organisms that detects unattached kinetochores and destabilises incorrect kinetochore-microtubule attachments. The molecular communication between the kinetochore and the SAC is highly dynamic and tightly regulated to ensure that cells can progress towards anaphase until each chromosome is properly bi-oriented on the mitotic spindle. This is achieved through an interplay of highly cooperative interactions and concerted phosphorylation/dephosphorylation events that are organised in time and space.This contribution discusses our current understanding of the function, structure and regulation of the kinetochore, in particular, how its communication with the SAC results in the amplification of specific signals to exquisitely control the eukaryotic cell cycle. This contribution also addresses recent advances in machine learning approaches, cell imaging and proteomics techniques that have enhanced our understanding of the molecular mechanisms that ensure the high fidelity and timely segregation of the genetic material every time a cell divides as well as the current challenges in the study of this fascinating molecular machine.

Absolute Quantification of TGF-β Signaling Proteins Using Quantitative Western Blot

Cell signaling governs the basic functions of cells by molecular interactions that involve of many proteins. The abundance of signaling proteins can directly influence cellular responses to external signal, contributing to cellular heterogeneity. Absolute quantification of proteins is important for modeling and understanding the complex signaling network. Here, we introduce how to measure the amount of TGF-β signaling proteins using quantitative immunoblotting. In addition, we discuss how to convert the measurements of protein abundance to the quantities of absolute molecules per cell. This method is generally applicable to the absolute quantification of other proteins.

Multifunctional stimuli-responsive chemogenetic platform for conditional multicolor cell-selective labeling

Multicolor conditional labeling is a powerful tool that can simultaneously and selectively visualize multiple targets for bioimaging analysis of complex biological processes and cellular features. We herein report a multifunctional stimuli-responsive Fluorescence-Activating and absorption-Shifting Tag (srFAST) chemogenetic platform for multicolor cell-selective labeling. This platform comprises stimuli-responsive fluorogenic ligands and the organelle-localizable FAST. The physicochemical properties of the srFAST ligands can be tailored by modifying the optical-tunable hydroxyl group with diverse reactive groups, and their chemical decaging process caused by cell-specific stimuli induces a conditionally activatable fluorescent labeling upon binding with the FAST. Thus, the resulting switch-on srFASTs were designed for on-demand labeling of cells of interest by spatiotemporally precise photo-stimulation or unique cellular feature-dependent activation, including specific endogenous metabolites or enzyme profiles. Furthermore, diverse enzyme-activatable srFAST ligands with distinct colors were constructed and simultaneously exploited for multicolor cell-selective labeling, which allow discriminating and orthogonal labeling of three different cell types with the same protein tag. Our method provides a promising strategy for designing a stimuli-responsive chemogenetic labeling platform via facile molecular engineering of the synthetic ligands, which has great potential for conditional multicolor cell-selective labeling and cellular heterogeneity evaluation.

Comparison of the stimuli-responsive FAST platform (srFAST) proposed in this work with the reported original FAST system (O-FAST). The srFAST could achieve not only conditional selective labeling, but also multicolor selective labeling.