RESUMO
In a proof of principle study, we have applied an automated fluorescence toponome imaging system (TIS) to examine whether TIS can find protein network structures, distinguishing cancerous from normal colon tissue present in a surgical sample from the same patient. By using a three symbol code and a power of combinatorial molecular discrimination (PCMD) of 2(21) per subcellular data point in one single tissue section, we demonstrate an in situ protein network structure, visualized as a mosaic of 6813 protein clusters (combinatorial molecular phenotype or CMPs), in the cancerous part of the colon. By contrast, in the histologically normal colon, TIS identifies nearly 5 times the number of protein clusters as compared to the cancerous part (32 009). By subcellular visualization procedures, we found that many cell surface membrane molecules were closely associated with the cell cytoskeleton as unique CMPs in the normal part of the colon, while the same molecules were disassembled in the cancerous part, suggesting the presence of dysfunctional cytoskeleton-membrane complexes. As expected, glandular and stromal cell signatures were found, but interestingly also found were potentially TIS signatures identifying a very restricted subset of cells expressing several putative stem cell markers, all restricted to the cancerous tissue. The detection of these signatures is based on the extreme searching depth, high degree of dimensionality, and subcellular resolution capacity of TIS. These findings provide the technological rationale for the feasibility of a complete colon cancer toponome to be established by massive parallel high throughput/high content TIS mapping.
Assuntos
Colo/metabolismo , Neoplasias do Colo/metabolismo , Proteínas/análise , Proteômica/métodos , Análise por Conglomerados , Corantes Fluorescentes/química , Humanos , Microscopia de Fluorescência , Proteínas/química , Proteínas/classificaçãoRESUMO
We have recently described the MELC/TIS fluorescence robot technology that is capable of colocalizing at least a hundred different molecular cell components in one cell. The technology reveals new hierarchical properties of protein network organisation, referred to as the toponome, in which topologically confined protein clusters are interlocked within the structural framework of the cell. In this study we have applied MELC/TIS to construct a three-dimensional toponome map of the cell nucleus of a single human hepatocyte undergoing apoptosis. The map reveals six different spatially separated toponome domains in the nuclear interior of one apoptotic cell. In the drive to decipher the apoptosis-specific molecular network on the single cell level, the present toponome map is a first milestone towards the construction of much larger maps addressing hundreds of molecular cell components across the stages of apoptosis.
Assuntos
Apoptose/fisiologia , Núcleo Celular , Hepatócitos , Imageamento Tridimensional/métodos , Núcleo Celular/química , Núcleo Celular/metabolismo , Células Cultivadas , Hepatócitos/citologia , Hepatócitos/fisiologia , Humanos , Microscopia de Fluorescência/métodosRESUMO
Background: The delay from onset of the first symptoms to a definite ALS diagnosis depends also on the elusiveness of the initial clinical manifestations. The lack of disease-specific biomarkers to detect early pathology when ALS is supposed complicates the situation. This latency reduces the therapeutic time frame, in which neuron-rescuing strategies exert their greatest chance to work. Various biomarkers are currently promised, but none of them are specific enough to allow monitoring of disease progression. This, as well as the heterogeneity of the disease concerning clinical onset pattern and survival rates, makes difficult the correct stratification of patients into clinical trials, masking the potential positive outcome in some patients.Objective: Our main objective is to establish and test an early diagnostic tool based on microscopic immune cell monitoring of ALS patients' blood samples by using the Toponome Imaging System (TIS).Methods: TIS is based on automatically controlled microscopic device involving conjugated dye-tag incubation, protein-tag-dye-imaging, and tag-dye bleaching (1). This leads to the collection of at least 21 cycle images of fixated peripheral blood mononuclear cells (PBMCs) isolated from freshly drawn blood of ALS patients and healthy "control" donors. Resulting data sets contain combinatorial molecular information about the spatial protein network, called toponome. The PBMC toponome architectures are quantitatively analyzed as a threshold-binary code with 1 = protein is present and 0 = protein is absent.Results: Preliminary screening data of PBMCs from 4 ALS patients reveal a subpopulation of lymphocytes expressing a specific surface protein pattern, called "ALS toponome". These aberrant T cells could not be found in blood samples of controls. We observe that the number of these cells correlate with the ALS progression rate of patients, supporting the conclusion that these cells may be causal for the disease.Discussion and conclusion: Although these findings open up a potential strategy to detect early ALS disease and to monitor disease progression, a statistical analysis with many more patients, as well as data based differentiation to other neurodegenerative diseases, is mandatory. A clinical trial initiated by our faceALS foundation with at least 60 patients classified in three subsets (1. control, 2. ALS, and 3. Multiple Sclerosis (MS)) and in close cooperation with leading ALS centres in Germany is still in progress. The detection of specific and/or aberrant immune cells in blood samples of ALS patients may provide a key to understand disease onset and progression, could be used for the "staging" of disease, and contribute to effective therapy options.
RESUMO
We have correlated transcriptomics, proteomics and toponomics analyses of hippocampus tissue of inbred C57BL/6 mice to analyse the interrelationship of expressed genes and proteins at different levels of organization. We find that transcriptome and proteome levels of function as well as the topological organization of synaptic protein clusters, detected by toponomics at physiological sites of hippocampus CA3 region, are all largely conserved between different mice. While the number of different synaptic states, characterized by distinct synaptic protein clusters, is enormous (>155,000), these states together form synaptic networks defining distinct and mutually exclusive territories in the hippocampus tissue. The findings provide insight in the systems biology of gene expression on transcriptome, proteome and toponome levels of function in the same brain subregion. The approach will lay the ground for designing studies of neurodegeneration in mouse models and human brains.
Assuntos
Perfilação da Expressão Gênica/métodos , Hipocampo/metabolismo , Proteômica/métodos , Animais , Eletroforese em Gel Bidimensional , Hipocampo/anatomia & histologia , Masculino , Camundongos , Camundongos Endogâmicos C57BL , Microscopia de FluorescênciaRESUMO
The fluorescence robot imaging technology multi-epitope-ligand-cartography/toponome imaging system has revolutionized the field of proteomics/functional genomics, because it enables the investigator to locate and decipher functional protein networks, the toponome, consisting of hundreds of different proteins in a single cell or tissue section. The technology has been proven to solve key problems in biology and therapy research. It has uncovered a new cellular transdifferentiation mechanism of vascular cells giving rise to myogenic cells in situ and in vivo; a finding that has led to efficient cell therapy models of muscle disorders, and discovered a new target protein in sporadic amyotrophic lateral sclerosis by hierarchical protein network analysis, a finding that has been confirmed by a mouse knockout model. A lead target protein in tumor cells that controls cell polarization as a mechanism that is fundamental for migration and metastasis formation has also been uncovered, and new functional territories in the CNS defined by high-dimensional synaptic protein clusters have been unveiled. The technology can be effectively interlocked with genomics and proteomics to optimize time-to-market and the overall attrition rate of new drugs. This review outlines major proofs of principle with an emphasis on neurotoponomics.
Assuntos
Proteínas do Tecido Nervoso/análise , Organelas/química , Proteômica/métodos , Biologia de Sistemas , Animais , HumanosRESUMO
Immune surveillance of tumour cells is an important function of CD8 T lymphocytes, which has failed in cancer for reasons still unknown in many respect but mainly related to cellular processes in the tumour microenvironment. Applying imaging cycler microscopy to analyse the immune contexture in a human skin cancer we could identify and map 7,000 distinct cell surface-associated multi-protein assemblies. The resulting combinatorial geometry-based high-functional resolution led to discovery of a mechanism of T cell trapping in the epidermis, which involves SPIKE, a network of suprabasal keratinocyte projections piercing and interconnecting CD8 T cells. It appears initiated by clusters of infrabasal T and dendritic cells connected via cell projections across a fractured basal lamina to suprabasal keratinocytes and T lymphocytes.
Assuntos
Neoplasias Cutâneas/imunologia , Neoplasias Cutâneas/metabolismo , Subpopulações de Linfócitos T/imunologia , Subpopulações de Linfócitos T/metabolismo , Microambiente Tumoral/imunologia , Antígenos de Superfície/metabolismo , Biomarcadores , Linfócitos T CD4-Positivos/imunologia , Linfócitos T CD4-Positivos/metabolismo , Linfócitos T CD4-Positivos/patologia , Linfócitos T CD8-Positivos/imunologia , Linfócitos T CD8-Positivos/metabolismo , Linfócitos T CD8-Positivos/patologia , Imunofluorescência , Humanos , Queratinócitos/metabolismo , Modelos Biológicos , Neoplasias Cutâneas/patologiaRESUMO
Functional super-resolution (fSR) microscopy is based on the automated toponome imaging system (TIS). fSR-TIS provides insight into the myriad of different cellular functionalities by direct imaging of large subcellular protein networks in morphologically intact cells and tissues, referred to as the toponome. By cyclical fluorescence imaging of at least 100 molecular cell components, fSR-TIS overcomes the spectral limitations of fluorescence microscopy, which is the essential condition for the detection of protein network structures in situ/in vivo. The resulting data sets precisely discriminate between cell types, subcellular structures, cell states and diseases (fSR). With up to 16 bits per protein, the power of combinatorial molecular discrimination (PCMD) is at least 2(100) per subcellular data point. It provides the dimensionality necessary to uncover thousands of distinct protein clusters including their subcellular hierarchies controlling protein network topology and function in the one cell or tissue section. Here we review the technology and findings showing that functional protein networks of the cell surface in different cancers encompass the same hierarchical and spatial coding principle, but express cancer-specific toponome codes within that scheme (referred to as TIS codes). Findings suggest that TIS codes, extracted from large-scale toponome data, have the potential to be next-generation biomarkers because of their cell type and disease specificity. This is functionally substantiated by the observation that blocking toponome-specific lead proteins results in disassembly of molecular networks and loss of function.
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Biomarcadores Tumorais/metabolismo , Imageamento Tridimensional/métodos , Microscopia de Fluorescência/métodos , Imagem Molecular/métodos , Descoberta de Drogas , Humanos , Proteínas/metabolismoRESUMO
In Toponomics, the function protein pattern in cells or tissue (the toponome) is imaged and analyzed for applications in toxicology, new drug development and patient-drug-interaction. The most advanced imaging technique is robot-driven multi-parameter fluorescence microscopy. This technique is capable of co-mapping hundreds of proteins and their distribution and assembly in protein clusters across a cell or tissue sample by running cycles of fluorescence tagging with monoclonal antibodies or other affinity reagents, imaging, and bleaching in situ. The imaging results in complex multi-parameter data composed of one slice or a 3D volume per affinity reagent. Biologists are particularly interested in the localization of co-occurring proteins, the frequency of co-occurrence and the distribution of co-occurring proteins across the cell. We present an interactive visual analysis approach for the evaluation of multi-parameter fluorescence microscopy data in toponomics. Multiple, linked views facilitate the definition of features by brushing multiple dimensions. The feature specification result is linked to all views establishing a focus+context visualization in 3D. In a new attribute view, we integrate techniques from graph visualization. Each node in the graph represents an affinity reagent while each edge represents two co-occurring affinity reagent bindings. The graph visualization is enhanced by glyphs which encode specific properties of the binding. The graph view is equipped with brushing facilities. By brushing in the spatial and attribute domain, the biologist achieves a better understanding of the function protein patterns of a cell. Furthermore, an interactive table view is integrated which summarizes unique fluorescence patterns. We discuss our approach with respect to a cell probe containing lymphocytes and a prostate tissue section.
Assuntos
Gráficos por Computador , Microscopia de Fluorescência/estatística & dados numéricos , Proteômica/estatística & dados numéricos , Interpretação Estatística de Dados , Humanos , Imageamento Tridimensional/estatística & dados numéricos , Linfócitos/metabolismo , Masculino , Proteínas de Neoplasias/metabolismo , Neoplasias da Próstata/metabolismoRESUMO
The toponome imaging technology MELC/TIS was applied to analyze prostate cancer tissue. By cyclical imaging procedures, we detected 2100 cell surface protein clusters in a single tissue section. This study provides the whole data set, a new kind of high dimensional data space, solely based on the structure-bound architecture of an in situ protein network, a putative fraction of the tissue code of prostate cancer. It is visualized as a colored mosaic composed of distinct protein clusters, together forming a motif expressed exclusively on the cell surface of neoplastic cells in prostate acini. Cell type specific expression of this motif, found in this preliminary study, suggests that high-throughput toponome analyses of a larger number of cases will provide insight into disease specific protein networks.