Cytomics, the human cytome project and systems biology: top-down resolution of the molecular biocomplexity of organisms by single cell analysis

Investigating the Mechanistic of Danhong Injection in Brain Damage Caused by Cardiac I/R Injury via Bioinformatics, Computer Simulation, and Experimental Validation

OBJECTIVE

Cardiac ischemia-reperfusion (I/R) injury has negative effects on the brain and can even lead to the occurrence of ischemic stroke. Clinical evidence shows that Danhong injection (DHI) protects the heart and brain following ischemic events. This study investigated the mechanisms and key active compounds underlying the therapeutic effect of DHI against brain damage induced by cardiac I/R injury.

METHODS

The gene expression omnibus database provided GSE66360 and GSE22255 data sets. The R programming language was used to identify the common differentially expressed genes (cDEGs). Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed, and protein-protein interaction network was constructed. Active compounds of DHI were collected from the Traditional Chinese Medicine Systems Pharmacology database. Molecular docking and molecular dynamics simulations were performed. The MMPBSA method was used to calculate the binding-free energy. The pkCSM server and DruLiTo software were used for Absorption, Distribution, metabolism, excretion, and toxicity (ADMET) analysis and drug-likeness analysis. Finally, in vitro experiments were conducted to validate the results.

RESULTS

A total of 27 cDEGs had been identified. The PPI and enrichment results indicated that TNF-α was considered to be the core target. A total of 80 active compounds were retrieved. The molecular docking results indicated that tanshinone I (TSI), tanshinone IIA (TSIIA), and hydroxyl safflower yellow A (HSYA) were selected as core active compounds. Molecular dynamics verification revealed that the conformations were relatively stable without significant fluctuations. MMPBSA analysis revealed that the binding energies of TSI, TSIIA, and HSYA with TNF-α were -36.01, -21.71, and -14.80 kcal/mol, respectively. LEU57 residue of TNF-α has the highest contribution. TSI and TSIIA passed both the ADMET analysis and drug-likeness screening, whereas HSYA did not. Experimental verification confirmed that DHI and TSIIA reduced the expression of TNF-α, NLRP3, and IL-1β in the injured H9C2 and rat brain microvascular endothelial cells.

CONCLUSION

TNF-α can be considered to be a key target for BD-CI/R. TSIIA in DHI exerts a significant inhibitory effect on the inflammatory damage of BD-CI/R, providing new insights for future drug development.

A cytomics-on-a-chip platform and diagnostic model stratifies risk for oral lichenoid conditions

OBJECTIVE

A small fraction of oral lichenoid conditions (OLC) have potential for malignant transformation. Distinguishing OLCs from other oral potentially malignant disorders (OPMDs) can help prevent unnecessary concern or testing, but accurate identification by nonexpert clinicians is challenging due to overlapping clinical features. In this study, the authors developed a 'cytomics-on-a-chip' tool and integrated predictive model for aiding the identification of OLCs.

STUDY DESIGN

All study subjects underwent both scalpel biopsy for histopathology and brush cytology. A predictive model and OLC Index comprising clinical, demographic, and cytologic features was generated to discriminate between subjects with lichenoid (OLC+) (N = 94) and nonlichenoid (OLC-) (N = 237) histologic features in a population with OPMDs.

RESULTS

The OLC Index discriminated OLC+ and OLC- subjects with area under the curve (AUC) of 0.76. Diagnostic accuracy of the OLC Index was not significantly different from expert clinician impressions, with AUC of 0.81 (P = .0704). Percent agreement was comparable across all raters, with 83.4% between expert clinicians and histopathology, 78.3% between OLC Index and expert clinician, and 77.3% between OLC Index and histopathology.

CONCLUSIONS

The cytomics-on-a-chip tool and integrated diagnostic model have the potential to facilitate both the triage and diagnosis of patients presenting with OPMDs and OLCs.

Proteomic identification of biomarkers of skeletal muscle disorders

Disease-specific biomarkers play a central diagnostic and therapeutic role in muscle pathology. Serum levels of a variety of muscle-derived enzymes are routinely used for the detection of muscle damage in diagnostic procedures, as well as for the monitoring of physical training status in sports medicine. Over the last few years, the systematic application of mass spectrometry-based proteomics for studying skeletal muscle degeneration has greatly expanded the range of muscle biomarkers, including new fiber-associated proteins involved in muscle transformation, muscular atrophy, muscular dystrophy, motor neuron disease, inclusion body myositis, myotonia, hypoxia, diabetes, obesity and sarcopenia of old age. These mass spectrometric studies have clearly established skeletal muscle proteomics as a reliable method for the identification of novel indicators of neuromuscular diseases.

Interoperability of time series cytometric data: a cross platform approach for modeling tumor heterogeneity

The cell cycle, with its highly conserved features, is a fundamental driver for the temporal control of cell proliferation-while abnormal control and modulation of the cell cycle are characteristic of tumor cells. The principal aim in cancer biology is to seek an understanding of the origin and nature of innate and acquired heterogeneity at the cellular level, driven principally by temporal and functional asynchrony. A major bottleneck when mathematically modeling these biological systems is the lack of interlinked structured experimental data. This often results in the in silico models failing to translate the specific hypothesis into parameterized terms that enable robust validation and hence would produce suitable prediction tools rather than just simulation tools. The focus has been on linking data originating from different cytometric platforms and cell-based event analysis to inform and constrain the input parameters of a compartmental cell cycle model, hence partly measuring and deconvolving cell cycle heterogeneity within a tumor population. Our work has addressed the concept that the interoperability of cytometric data, derived from different cytometry platforms, can complement as well as enhance cellular parameters space, thus providing a more broader and in-depth view of the cellular systems. The initial aim was to enable the cell cycle model to deliver an improved integrated simulation of the well-defined and constrained biological system. From a modeling perspective, such a cross platform approach has provided a paradigm shift from conventional cross-validation approaches, and from a bioinformatics perspective, novel computational methodology has been introduced for integrating and mapping continuous data with cross-sectional data. This establishes the foundation for developing predictive models and in silico tracking and prediction of tumor progression

Early detection in head and neck cancer - current state and future perspectives

Survival and quality of life in head and neck cancer are directly linked to the size of the primary tumor at first detection. In order to achieve substantial gain at these issues, both, primary prevention and secondary prevention, which is early detection of malignant lesions at a small size, have to be improved. So far, there is not only a lack in the necessary infrastructure not only in Germany, but rather worldwide, but additionally the techniques developed so far for early detection have a significance and specificity too low as to warrant safe implementation for screening programs. However, the advancements recently achieved in endoscopy and in quantitative analysis of hypocellular specimens open new perspectives for secondary prevention. Chromoendoscopy and narrow band imaging (NBI) pinpoint suspicious lesions more easily, confocal endomicroscopy and optical coherence tomography obtain optical sections through those lesions, and hyperspectral imaging classifies lesions according to characteristic spectral signatures. These techniques therefore obtain optical biopsies. Once a "bloody" biopsy has been taken, the plethora of parameters that can be quantified objectively has been increased and could be the basis for an objective and quantitative classification of epithelial lesions (multiparametric cytometry, quantitative histology). Finally, cytomics and proteomics approaches, and lab-on-the-chip technology might help to identify patients at high-risk. Sensitivity and specificity of these approaches have to be validated, yet, and some techniques have to be adapted for the specific conditions for early detection of head and neck cancer. On this background it has to be stated that it is still a long way to go until a population based screening for head and neck cancer is available. The recent results of screening for cancer of the prostate and breast highlight the difficulties implemented in such a task.

The use of hepatocytes to investigate drug toxicity

The liver is very active in metabolizing foreign compounds and the major target for toxicity caused by drugs. Hepatotoxicity may be the result of the drug itself or, more frequently, a result of the bioactivation process and the production of reactive metabolites. Prioritization of compounds based on human hepatotoxicity potential is currently a key unmet need in drug discovery, as it can become a major problem for several lead compounds in later stages of the drug discovery pipeline. Therefore, evaluation of potential hepatotoxicity represents a critical step in the development of new drugs. Cultured hepatocytes are increasingly used by the pharmaceutical industry for the screening of hepatotoxic potential of new molecules. Hepatocytes in culture retain hepatic key functions and constitute a valuable tool to identify chemically induced cellular damage. Their use has notably contributed to the understanding of mechanisms responsible for hepatotoxicity (disruption of cellular energy status, alteration of Ca(2+) homeostasis, inhibition of transport systems, metabolic activation, oxidative stress, covalent binding, etc.). Assessment of current cytotoxicity and hepatic-specific biochemical effects is limited by the inability to measure a wide spectrum of potential mechanistic changes involved in the drug-induced toxic injury. A convenient selection of endpoints allows a multiparametric evaluation of drug toxicity. In this regard, cytomic, proteomic, toxicogenomic and metabonomic approaches help to define patterns of hepatotoxicity for early identification of potential adverse effects of the drug to the liver.

[Cytomics and predictive medicine for oncology]

One hundred and fifty years after Virchow introduced his fundamental concept of cellular pathology, we now have tools that allow us to unravel the mechanisms of single living cells on a previously unprecedented level of detail. By exploring the molecular cellular phenotype, multiparametric cytometry not only detects specific cellular functions in general but also offers insights into the interaction of single subunits of proteins (e.g., growth factor receptors). Several quantitative and objective techniques allow analysis of single-cell preparations as well as tissue sections to obtain data on different cellular parameters. This opens the way to quantitative and objective histology, which in the future may be possible even without blood or the need to make an incision. To use this huge amount of data for treatment decisions in an individual patient, novel bioinformatic concepts are needed in order to predict the individual course of a disease. The concept of cytomics centers on the cell as the integral unit of all life and explores diseases starting from the cell and going to subcellular units (top-down analysis).

A perspective for biomedical data integration: design of databases for flow cytometry

Background

The integration of biomedical information is essential for tackling medical problems. We describe a data model in the domain of flow cytometry (FC) allowing for massive management, analysis and integration with other laboratory and clinical information. The paper is concerned with the proper translation of the Flow Cytometry Standard (FCS) into a relational database schema, in a way that facilitates end users at either doing research on FC or studying specific cases of patients undergone FC analysis

Results

The proposed database schema provides integration of data originating from diverse acquisition settings, organized in a way that allows syntactically simple queries that provide results significantly faster than the conventional implementations of the FCS standard. The proposed schema can potentially achieve up to 8 orders of magnitude reduction in query complexity and up to 2 orders of magnitude reduction in response time for data originating from flow cytometers that record 256 colours. This is mainly achieved by managing to maintain an almost constant number of data-mining procedures regardless of the size and complexity of the stored information.

Conclusion

It is evident that using single-file data storage standards for the design of databases without any structural transformations significantly limits the flexibility of databases. Analysis of the requirements of a specific domain for integration and massive data processing can provide the necessary schema modifications that will unlock the additional functionality of a relational database.

Development of analytical methods for multiplex bio-assay with inductively coupled plasma mass spectrometry

Advances in the development of highly multiplexed bio-analytical assays with inductively coupled plasma mass spectrometry (ICP-MS) detection are discussed. Use of novel reagents specifically designed for immunological methods utilizing elemental analysis is presented. The major steps of method development, including selection of elements for tags, validation of tagged reagents, and examples of multiplexed assays, are considered in detail. The paper further describes experimental protocols for elemental tagging of antibodies, immunostaining of live and fixed human leukemia cells, and preparation of samples for ICP-MS analysis. Quantitative analysis of surface antigens on model cell lines using a cocktail of seven lanthanide labeled antibodies demonstrated high specificity and concordance with conventional immunophenotyping.

Cytomics: A multiparametric, dynamic approach to cell research

Cytomics aims to determine the molecular phenotype of single cells. Within the context of the -omics, cytomics allows the investigation of multiple biochemical features of the heterogeneous cellular systems known as the cytomes. Cytomics can be considered as the science of single cell-based analyses that links genomics and proteomics with the dynamics of cell and tissue function, as modulated by external influences. Inherent to cytomics are the use of sensitive, scarcely invasive, fluorescence-based multiparametric methods and the event-integrating concept of individual cells to understand the complexity and behaviour of tissues and organisms. Among cytomic technologies, flow cytometry, confocal laser scanning microscopy and laser capture microdissection are of great relevance. Other recent technologies based on single cell bioimaging and bioinformatic tools become important in drug discovery and toxicity testing, because of both high-content and high-troughput. The multiparametric capacity of cytomics is very useful for the identification, characterization and isolation of stem cell populations. In our experience, flow cytometry is a powerful and versatile tool that allows quantitative analysis of single molecules, prokaryotic and eukaryotic cells for basic, biotechnological, environmental and clinical studies. The dynamic nature of cytomic assays leads to a real-time kinetic approach based on sequential examination of different single cells from a population undergoing a dynamic process, the in fluxo level. Finally, cytomic technologies may provide in vitro methods alternative to laboratory animals for toxicity assessment.

Cytomics - importance of multimodal analysis of cell function and proliferation in oncology

Cancer is a highly complex and heterogeneous disease involving a succession of genetic changes (frequently caused or accompanied by exogenous trauma), and resulting in a molecular phenotype that in turn results in a malignant specification. The development of malignancy has been described as a multistep process involving self-sufficiency in growth signals, insensitivity to antigrowth signals, evasion of apoptosis, limitless replicative potential, sustained angiogenesis, and finally tissue invasion and metastasis. The quantitative analysis of networking molecules within the cells might be applied to understand native-state tissue signalling biology, complex drug actions and dysfunctional signalling in transformed cells, that is, in cancer cells. High-content and high-throughput single-cell analysis can lead to systems biology and cytomics. The application of cytomics in cancer research and diagnostics is very broad, ranging from the better understanding of the tumour cell biology to the identification of residual tumour cells after treatment, to drug discovery. The ultimate goal is to pinpoint in detail these processes on the molecular, cellular and tissue level. A comprehensive knowledge of these will require tissue analysis, which is multiplex and functional; thus, vast amounts of data are being collected from current genomic and proteomic platforms for integration and interpretation as well as for new varieties of updated cytomics technology. This overview will briefly highlight the most important aspects of this continuously developing field.

A three-symbol code for organized proteomes based on cyclical imaging of protein locations

BACKGROUND

A major challenge in the post genomic era is to map and decipher the functional molecular networks of proteins directly in a cell or a tissue. This task requires technologies for the colocalization of random numbers of different molecular components (e.g. proteins) in one sample in one experiment.

METHODS

Multi-epitope-ligand-"kartographie" (MELK) was developed as a microscopic imaging technology running cycles of iterative fluorescence tagging, imaging, and bleaching, to colocalize a large number of proteins in one sample (morphologically intact routinely fixed cells or tissue).

RESULTS

In the present study, 18 different cell surface proteins were colocalized by MELK in cells and tissue sections in different compartments of the human immune system. From the resulting sets of multidimensional binary vectors the most prominent groups of protein-epitope arrangements were extracted and imaged as protein "toponome" maps providing direct insight in the higher order topological organization of immune compartments uncovering new tissue domains. The data sets suggest that protein networks, topologically organized in proteomes in situ, obey a unique protein-colocation and -anticolocation code describable by three symbols.

CONCLUSION

The technology has the potential to colocalize hundreds of proteins and other molecular components in one sample and may offer many applications in biology and medicine.

3D parallel coordinate systems--a new data visualization method in the context of microscopy-based multicolor tissue cytometry

BACKGROUND

Presentation of multiple interactions is of vital importance in the new field of cytomics. Quantitative analysis of multi- and polychromatic stained cells in tissue will serve as a basis for medical diagnosis and prediction of disease in forthcoming years. A major problem associated with huge interdependent data sets is visualization. Therefore, alternative and easy-to-handle strategies for data visualization as well as data meta-evaluation (population analysis, cross-correlation, co-expression analysis) were developed.

METHODS

To facilitate human comprehension of complex data, 3D parallel coordinate systems have been developed and used in automated microscopy-based multicolor tissue cytometry (MMTC). Frozen sections of human skin were stained using the combination anti-CD45-PE, anti-CD14-APC, and SytoxGreen as well as the appropriate single and double negative controls. Stained sections were analyzed using automated confocal laser microscopy and semiquantitative MMTC-analysis with TissueQuest 2.0. The 3D parallel coordinate plots are generated from semiquantitative immunofluorescent data of single cells. The 2D and 3D parallel coordinate plots were produced by further processing using the Matlab environment (Mathworks, USA).

RESULTS

Current techniques in data visualization primarily utilize scattergrams, where two parameters are plotted against each other on linear or logarithmic scales. However, data evaluation on cartesian x/y-scattergrams is, in general, only of limited value in multiparameter analysis. Dot plots suffer from serious problems, and in particular, do not meet the requirements of polychromatic high-context tissue cytometry of millions of cells. The 3D parallel coordinate plot replaces the vast amount of scattergrams that are usually needed for the cross-correlation analysis. As a result, the scientist is able to perform the data meta-evaluation by using one single plot. On the basis of 2D parallel coordinate systems, a density isosurface is created for representing the event population in an intuitive way.

CONCLUSIONS

The proposed method opens new possibilities to represent and explore multidimensional data in the perspective of cytomics and other life sciences, e.g., DNA chip array technology. Current protocols in immunofluorescence permit simultaneous staining of up to 17 markers. Showing the cross-correlation between these markers requires 136 scattergrams, which is a prohibitively high number. The improved data visualization method allows the observation of such complex patterns in only one 3D plot and could take advantage of the latest developments in 3D imaging.

Slide-based cytometry for cytomics--a minireview

In the postgenomic era, to gain the most detailed quantitative data from biological specimens has become increasingly important in the emerging new fields of high-content and high-throughput single-cell analysis for systems biology and cytomics. Areas of research and diagnosis with the demand to virtually measure "anything" in the cell include immunophenotyping, rare cell detection and characterization in the case of stem cells and residual tumor cells, tissue analysis, and drug discovery. Systemic analysis is also a prerequisite for predictive medicine by genomics, proteomics, and cytomics. This issue of Cytometry Part A is dedicated to innovative concepts of system wide single cells analysis and manipulation, new technologies, data analysis and display, and, finally, quality assessment. The manuscripts to these chapters are provided by cutting edge experts in the fields. This overview will briefly highlight the most important aspects of this continuously developing field.

Tissue microarrays as a platform for proteomic investigation

Tissue microarrays have become an essential tool in translational pathology. They are used to confirm results from other experimental platforms, such as expression microarrays, as well as a primary tool to explore the expression profile of proteins by immunohistochemical analysis. Tissue microarrays are routinely used molecular epidemiology, drug development and determining the diagnostic, prognostic and predictive value of new biomarkers. By applying traditional protein based assays, as well as novel assays to the platform, tissue microarrays have gained a new utility as a proteomic tool for both basic science as well as clinical investigation. This article will explore the new approaches that are being applied to tissue microarrays to, characterize the human proteome, and new technologies that allow tissue microarrays to function as a protein array.

Cytomics as a new potential for drug discovery

At the single-cell level in conjunction with data-pattern analysis, high-content screening by image analysis or flow cytometry of clinical cell- or tissue-section samples provides differential molecular profiles for the personalized prediction of therapy-dependent disease progression in patients. The molecular reverse-engineering of these molecular profiles, which is the exploration of molecular pathways, backwards, to the origin of the observed molecular differentials, by systems biology has the potential to detect new drug targets in knowledge spaces, typically inaccessible to traditional hypotheses. Furthermore, predictive medicine, by cytomics in stratified patient groups, opens a new way for personalized (or individualized) medicine, as well as for the early detection of adverse drug reactions in patients.

Hyperchromatic cytometry principles for cytomics using slide based cytometry

BACKGROUND

Polychromatic analysis of biological specimens has become increasingly important because of the emerging new fields of high-content and high-throughput single cell analysis for systems biology and cytomics. Combining different technologies and staining methods, multicolor analysis can be pushed forward to measure anything stainable in a cell. We term this approach hyperchromatic cytometry and present different components suitable for achieving this task. For cell analysis, slide based cytometry (SBC) technologies are ideal as, unlike flow cytometry, they are non-consumptive, i.e. the analyzed sample is fixed on the slide and can be reanalyzed following restaining of the object.

METHODS AND RESULTS

We demonstrate various approaches for hyperchromatic analysis on a SBC instrument, the Laser Scanning Cytometer. The different components demonstrated here include (1) polychromatic cytometry (staining of the specimen with eight or more different fluorochromes simultaneously), (2) iterative restaining (using the same fluorochrome for restaining and subsequent reanalysis), (3) differential photobleaching (differentiating fluorochromes by their different photostability), (4) photoactivation (activating fluorescent nanoparticles or photocaged dyes), and (5) photodestruction (destruction of FRET dyes). Based on the ability to relocate cells that are immobilized on a microscope slide with a precision of approximately 1 microm, identical cells can be reanalyzed on the single cell level after manipulation steps.

CONCLUSION

With the intelligent combination of several different techniques, the hyperchromatic cytometry approach allows to quantify and analyze all components of relevance on the single cell level. The information gained per specimen is only limited by the number of available antibodies and sterical hindrance.

Novel aspects of systems biology and clinical cytomics

The area of Cytomics and Systems Biology became of great impact during the last years. In some fields of the leading cytometric techniques it represents the cutting edge today. Many different applications/variations of multicolor staining were developed for flow- or slide-based cytometric analysis of suspensions and sections to whole animal analysis. Multispectral optical imaging can be used for studying immunological and tumorigenic processes. New methods resulted in the establishment of lipidomics as the systemic research of lipids and their behavior. All of these development push the systemic approach of the analysis of biological specimens to enhance the outcome in the clinic and in drug discovery programs.