ESICCC as a systematic computational framework for evaluation, selection, and integration of cell-cell communication inference methods

Cell-cell communication (CCC) is critical for determining cell fates and functions in multicellular organisms. With the advent of single-cell RNA-sequencing (scRNA-seq) and spatial transcriptomics (ST), an increasing number of CCC inference methods have been developed. Nevertheless, a thorough comparison of their performances is yet to be conducted. To fill this gap, we developed a systematic benchmark framework called ESICCC to evaluate 18 ligand-receptor (LR) inference methods and five ligand/receptor-target inference methods using a total of 116 data sets, including 15 ST data sets, 15 sets of cell line perturbation data, two sets of cell type-specific expression/proteomics data, and 84 sets of sampled or unsampled scRNA-seq data. We evaluated and compared the agreement, accuracy, robustness, and usability of these methods. Regarding accuracy evaluation, RNAMagnet, CellChat, and scSeqComm emerge as the three best-performing methods for intercellular ligand-receptor inference based on scRNA-seq data, whereas stMLnet and HoloNet are the best methods for predicting ligand/receptor-target regulation using ST data. To facilitate the practical applications, we provide a decision-tree-style guideline for users to easily choose best tools for their specific research concerns in CCC inference, and develop an ensemble pipeline CCCbank that enables versatile combinations of methods and databases. Moreover, our comparative results also uncover several critical influential factors for CCC inference, such as prior interaction information, ligand-receptor scoring algorithm, intracellular signaling complexity, and spatial relationship, which may be considered in the future studies to advance the development of new methodologies.

Reduced exosomal L-Plastin is responsible for radiation-induced bystander effect

Radiation-induced bystander effects (RIBE) are discussed as relevant processes during radiotherapy. Irradiated cells are suggested to release growth-inhibitory/DNA-damaging factors transported to non-irradiated cells. However, the molecular nature of this phenomenon has not yet been resolved. We aimed at identifying the growth-inhibitory factor(s) transmitted to non-irradiated cells. RIBE-competent PC3 cells were used to produce conditioned medium (CM) after exposure to ionizing radiation. Indicator cells were incubated with CM and clonogenic survival as well as cell proliferation were determined as endpoints. A549 indicator cells exhibited a bystander effect upon incubation with CM from irradiated PC3 cells. This bystander effect was not due to DNA-damaging factors, but a radiation-triggered reduction of mitogenic/clonogenic activity present in CM. Several tumor cells, but not normal fibroblasts secrete this factor, whose release is reduced by irradiation. We identified L-Plastin to be responsible for the mitogenic/clonogenic activity. Removal of L-Plastin from CM by immunoprecipitation or siRNA-mediated knockdown of L-Plastin expression resulted in loss or reduction of mitogenic/clonogenic activity transmitted via CM, respectively. Exosome-transported L-Plastin was constitutively Ser5-phosphorylated, indicative of its bioactive conformation. In summary, we observed production and exosomal secretion of L-Plastin by cancer cells. Via exosome-transmitted L-Plastin, tumors induce clonogenic and mitogenic activity in cancer and normal cells of the tumor microenvironment. Irradiation inhibits L-Plastin production targeting both cancer cells and the tumor niche and may explain the high impact of radiotherapy in tumor control.

Tools for Pathogen Proteomics: Fishing with Biomimetic Nanosponges

The identification of the major virulence factors that drive pathogenicity is critical for gaining insight into the underlying molecular mechanisms of diseases. Although genetic approaches combined with functional analyses have markedly increased the rate of virulence factor discovery, the divergence between genome and proteome can impair the identification of important markers, in particular, of those that act in concert or depend on specific environmental factors. Recently, membrane-coated nanomaterials mimicking source cells of interest have emerged as powerful tools that can be used for improved tumor targeting and as "nanotraps" to capture chemokines and bacterial toxins. In this issue of ACS Nano, Lapek et al. demonstrate that membrane-coated nanosponges in combination with quantitative proteomics can also be used as efficient "fishing devices" for the identification of cell-type-specific virulence factors.

Protein biomarkers for early detection of diseases: The decisive contribution of combinatorial peptide ligand libraries

The present review deals with biomarker discovery, especially in regard to sample treatment via combinatorial peptide ligand libraries, perhaps the only technique at present allowing deep exploration of biological fluids and tissue extracts in search for low- to very-low-abundance proteins, which could possibly mark the onset of most pathologies. Early-stage biomarkers, in fact, might be the only way to detect the beginning of most diseases thus permitting proper intervention and care. The following cancers are reviewed, with lists of potential biomarkers suggested in various reports: hepatocellular carcinoma, ovarian cancer, breast cancer and pancreatic cancer, together with some other interesting applications. Although panels of proteins have been presented, with robust evidence, as potential early-stage biomarkers in these different pathologies, their approval by FDA as novel biomarkers in routine clinical chemistry settings would require plenty of additional work and efforts from the pharma industry. The science environment in universities could simply not afford such heavy monetary investments.

SIGNIFICANCE

After more than 16years of search for novel biomarkers, to be used in a clinical chemistry set-up, via proteomic analysis (mostly in biological fluids) it was felt a critical review was due. In the present report, though, only papers reporting biomarker discovery via combinatorial peptide ligand libraries are listed and assessed, since this methodology seems to be the most advanced one for digging in depth into low-to very-low-abundance proteins, which might represent important biomarkers for the onset of pathologies. In particular, a large survey has been made for the following diseases, since they appear to have a large incidence on human population and/or represent fatal diseases: ovarian cancer, breast cancer, pancreatic cancer and hepatocellular carcinoma.

Use of Foodomics for Control of Food Processing and Assessing of Food Safety

Food chain, food safety, and food-processing sectors face new challenges due to globalization of food chain and changes in the modern consumer preferences. In addition, gradually increasing microbial resistance, changes in climate, and human errors in food handling remain a pending barrier for the efficient global food safety management. Consequently, a need for development, validation, and implementation of rapid, sensitive, and accurate methods for assessment of food safety often termed as foodomics methods is required. Even though, the growing role of these high-throughput foodomic methods based on genomic, transcriptomic, proteomic, and metabolomic techniques has yet to be completely acknowledged by the regulatory agencies and bodies. The sensitivity and accuracy of these methods are superior to previously used standard analytical procedures and new methods are suitable to address a number of novel requirements posed by the food production sector and global food market.

Cell-selective proteomics for biological discovery

Cells alter the proteome to respond to environmental and developmental cues. Global analysis of proteomic responses is of limited value in heterogeneous environments, where there is no 'average' cell. Advances in sequencing, protein labeling, mass spectrometry, and data analysis have fueled recent progress in the investigation of specific subpopulations of cells in complex systems. Here we highlight recently developed chemical tools that enable cell-selective proteomic analysis of complex biological systems, from bacterial pathogens to whole animals.

Proteomic Analysis of Secreted Proteins from Cell Microenvironment

Cell microenvironment consists of various types of cells which communicate with each other by vast number of secreted proteins. An unbiased profiling of these secreted proteins on a global scale is often critical for understanding the intercellular signaling in an autocrine or paracrine manner. Mass spectrometry-based proteomics has become one of the most popular technology for characterization of the secreted proteins. In this chapter, we discuss the standard workflow for secreted proteins characterization, including harvesting secreted proteins from conditioned media, digesting the obtained proteins, liquid chromatography-mass spectrometry analysis, and downstream data analysis.

Identification, Quantification, and Site Localization of Protein Posttranslational Modifications via Mass Spectrometry-Based Proteomics

Posttranslational modifications (PTMs) are important biochemical processes for regulating various signaling pathways and determining specific cell fate. Mass spectrometry (MS)-based proteomics has been developed extensively in the past decade and is becoming the standard approach for systematic characterization of different PTMs on a global scale. In this chapter, we will explain the biological importance of various PTMs, summarize key innovations in PTMs enrichment strategies, high-performance liquid chromatography (HPLC)-based fractionation approaches, mass spectrometry detection methods, and lastly bioinformatic tools for PTMs related data analysis. With great effort in recent years by the proteomics community, highly efficient enriching methods and comprehensive resources have been developed. This chapter will specifically focus on five major types of PTMs; phosphorylation, glycosylation, ubiquitination/sumosylation, acetylation, and methylation.

Proteomics of cell-cell interactions in health and disease

The mechanisms of cell-cell communications are now under intense study by proteomic approaches. Proteomics has unraveled changes in protein profiling as the result of cell interactions mediated by ligand/receptor, hormones, soluble factors, and the content of extracellular vesicles. Besides being a brief overview of the main and profitable methodologies now available (evaluating theory behind the methods, their usefulness, and pitfalls), this review focuses on-from a proteome perspective-some signaling pathways and post-translational modifications (PTMs), which are essential for understanding ischemic lesions and their recovery in two vital organs in mammals, the heart, and the kidney. Knowledge of misdirection of the proteome during tissue recovery, such as represented by the convergence between fibrosis and cancer, emerges as an important tool in prognosis. Proteomics of cell-cell interaction is also especially useful for understanding how stem cells interact in injured tissues, anticipating clues for rational therapeutic interventions. In the effervescent field of induced pluripotency and cell reprogramming, proteomic studies have shown what proteins from specialized cells contribute to the recovery of infarcted tissues. Overall, we conclude that proteomics is at the forefront in helping us to understand the mechanisms that underpin prevalent pathological processes.

Enhancing the discovery and development of immunotherapies for cancer using quantitative and systems pharmacology: Interleukin-12 as a case study

Recent clinical successes of immune checkpoint modulators have unleashed a wave of enthusiasm associated with cancer immunotherapy. However, this enthusiasm is dampened by persistent translational hurdles associated with cancer immunotherapy that mirror the broader pharmaceutical industry. Specifically, the challenges associated with drug discovery and development stem from an incomplete understanding of the biological mechanisms in humans that are targeted by a potential drug and the financial implications of clinical failures. Sustaining progress in expanding the clinical benefit provided by cancer immunotherapy requires reliably identifying new mechanisms of action. Along these lines, quantitative and systems pharmacology (QSP) has been proposed as a means to invigorate the drug discovery and development process. In this review, I discuss two central themes of QSP as applied in the context of cancer immunotherapy. The first theme focuses on a network-centric view of biology as a contrast to a "one-gene, one-receptor, one-mechanism" paradigm prevalent in contemporary drug discovery and development. This theme has been enabled by the advances in wet-lab capabilities to assay biological systems at increasing breadth and resolution. The second theme focuses on integrating mechanistic modeling and simulation with quantitative wet-lab studies. Drawing from recent QSP examples, large-scale mechanistic models that integrate phenotypic signaling-, cellular-, and tissue-level behaviors have the potential to lower many of the translational hurdles associated with cancer immunotherapy. These include prioritizing immunotherapies, developing mechanistic biomarkers that stratify patient populations and that reflect the underlying strength and dynamics of a protective host immune response, and facilitate explicit sharing of our understanding of the underlying biology using mechanistic models as vehicles for dialogue. However, creating such models require a modular approach that assumes that the biological networks remain similar in health and disease. As oncogenesis is associated with re-wiring of these biological networks, I also describe an approach that combines mechanistic modeling with quantitative wet-lab experiments to identify ways in which malignant cells alter these networks, using Interleukin-12 as an example. Collectively, QSP represents a new holistic approach that may have profound implications for how translational science is performed.

Eavesdropping on altered cell-to-cell signaling in cancer by secretome profiling

In the past decade, cumulative clinical experiences with molecular targeted therapies and immunotherapies for cancer have promoted a shift in our conceptual understanding of cancer. This view shifted from viewing solid tumors as a homogeneous mass of malignant cells to viewing tumors as heterogeneous structures that are dynamically shaped by intercellular interactions among the variety of stromal, immune, and malignant cells present within the tumor microenvironment. As in any dynamic system, identifying how cells communicate to maintain homeostasis and how this communication is altered during oncogenesis are key hurdles for developing therapies to restore normal tissue homeostasis. Here, I discuss tissues as dynamic systems, using the mammary gland as an example, and the evolutionary concepts applied to oncogenesis. Drawing from these concepts, I present 2 competing hypotheses for how intercellular communication might be altered during oncogenesis. As an initial test of these competing hypotheses, a recent secretome comparison between normal human mammary and HER2+ breast cancer cell lines suggested that the particular proteins secreted by the malignant cells reflect a convergent evolutionary path associated with oncogenesis in a specific anatomical niche, despite arising in different individuals. Overall, this study illustrates the emerging power of secretome proteomics to probe, in an unbiased way, how intercellular communication changes during oncogenesis.

Signal, transduction, and the hematopoietic stem cell

The hematopoietic stem cell (HSC) is a unique cell positioned highest in the hematopoietic hierarchical system. The HSC has the ability to stay in quiescence, to self-renew, or to differentiate and generate all lineages of blood cells. The path to be actualized is influenced by signals that derive from the cell's microenvironment, which activate molecular pathways inside the cell. Signaling pathways are commonly organized through inducible protein-protein interactions, mediated by adaptor proteins that link activated receptors to cytoplasmic effectors. This review will focus on the signaling molecules and how they work in concert to determine the HSC's fate.