Role of Phospholipid Oxidation Products in Atherosclerosis
Sangderk LeeKonstantin G. BirukovCasey E. RomanoskiJames R. SpringsteadAldons J. LusisJudith A. Berliner
192
Citation
138
Reference
10
Related Paper
Citation Trend
Abstract:
There is increasing clinical evidence that phospholipid oxidation products (Ox-PL) play a role in atherosclerosis. This review focuses on the mechanisms by which Ox-PL interact with endothelial cells, monocyte/macrophages, platelets, smooth muscle cells, and HDL to promote atherogenesis. In the past few years major progress has been made in identifying these mechanisms. It has been recognized that Ox-PL promote phenotypic changes in these cell types that have long-term consequences for the vessel wall. Individual Ox-PL responsible for specific cellular effects have been identified. A model of the configuration of bioactive truncated Ox-PL within membranes has been developed that demonstrates that the oxidized fatty acid moiety protrudes into the aqueous phase, rendering it accessible for receptor recognition. Receptors and signaling pathways for individual Ox-PL species are now determined and receptor independent signaling pathways identified. The effects of Ox-PL are mediated both by gene regulation and transcription independent processes. It has now become apparent that Ox-PL affects multiple genes and pathways, some of which are proatherogenic and some are protective. However, at concentrations that are likely present in the vessel wall in atherosclerotic lesions, the effects promote atherogenesis. There have also been new insights on enzymes that metabolize Ox-PL and the significance of these enzymes for atherosclerosis. With the knowledge we now have of the regulation and effects of Ox-PL in different vascular cell types, it should be possible to design experiments to test the role of specific Ox-PL on the development of atherosclerosis.Keywords:
Cell type
Abstract Although cell-in-cell structure was noted 100 years ago, the molecular mechanisms of ‘entering’ and the destination of cell-in-cell remain largely unclear. It takes place among the same type of cells (homotypic cell-in-cell) or different types of cells (heterotypic cell-in-cell). Cell-in-cell formation affects both effector cells and their host cells in multiple aspects, while cell-in-cell death is under more intensive investigation. Given that cell-in-cell has an important role in maintaining homeostasis, aberrant cell-in-cell process contributes to the etiopathology in humans. Indeed, cell-in-cell is observed in many pathological processes of human diseases. In this review, we intend to discuss the biological models of cell-in-cell structures under physiological and pathological status.
Cell type
Cell–cell interaction
Cell Signaling
Cite
Citations (34)
Abstract Cell-free RNA (cfRNA) can be used to noninvasively measure dynamic and longitudinal physiological changes throughout the body. While there is considerable effort in the liquid biopsy field to determine disease tissue-of-origin, pathophysiology occurs at the cellular level. Here, we describe two approaches to identify cell type contributions to cfRNA. First we used Tabula Sapiens , a transcriptomic cell atlas of the human body to computationally deconvolve the cell-free transcriptome into a sum of cell type specific transcriptomes, thus revealing the spectrum of cell types readily detectable in the blood. Second, we used individual tissue transcriptomic cell atlases in combination with the Human Protein Atlas RNA consensus dataset to create cell type signature scores which can be used to infer the implicated cell types from cfRNA for a variety of diseases. Taken together, these results demonstrate that cfRNA reflects cellular contributions in health and disease from diverse cell types, potentially enabling determination of pathophysiological changes of many cell types from a single blood test.
Cell type
Cite
Citations (11)
ABSTRACT Hereditary diseases manifest clinically in certain tissues, however their affected cell types typically remain elusive. Single-cell expression studies showed that overexpression of disease-associated genes may point to the affected cell types. Here, we developed a method that infers disease-affected cell types from the preferential expression of disease-associated genes in cell types (PrEDiCT). We applied PrEDiCT to single-cell expression data of six human tissues, to infer the cell types affected in 1,113 hereditary diseases. Overall, we identified 110 cell types affected by 714 diseases. We corroborated our findings by literature text-mining and recapitulation in mouse corresponding tissues. Based on these findings, we explored features of disease-affected cell types and cell classes, highlighted cell types affected by mitochondrial diseases and heritable cancers, and identified diseases that perturb intercellular communication. This study expands our understanding of disease mechanisms and cellular vulnerability.
Cell type
Mendelian inheritance
Cite
Citations (0)
A radioactivity-based assay was developed to define the participation of radioactively labeled cell types within the milieu of unlabeled partners in multigeneric aggregates. The cell types in these multigeneric aggregations consisted of various combinations of 21 strains representing five genera of human oral bacteria. The coaggregation properties of each cell type, when paired individually with various strains, were delineated and were unchanged when the microbes took part in the more complex multigeneric aggregations. Competition between homologous labeled and unlabeled cells for binding to a partner cell type was achieved only when the homologous cells were mixed together before the addition of their partner cells. Attempts to displace a labeled cell type from an aggregate by subsequent addition of a large excess of the same unlabeled cell type were unsuccessful, which suggested that the forces that bound different cell types together were very strong and the cell-to-cell interactions were stable. However, a cell type that exhibited only lactose-reversible coaggregations with partners was easily and selectively released by the addition of lactose to multigeneric aggregates otherwise consisting solely of lactose-nonreversible cell-to-cell interactions. This not only indicates the independent nature of individual coaggregations but also suggests the involvement of lectinlike adhesins in these sugar-inhibitable coaggregations. Although the molecular mechanisms responsible for multigeneric aggregations are unknown, the principle of a common partner cell type serving as a bridge between two otherwise noncoaggregating cell types was firmly established by the observation of sequential addition of one cell type to another. Thus, competition, bridging, coaggregate stability, independent nature of interactions, and partner specificity are the key principles of adherence that form the framework for continued studies of multigeneric aggregates. While the human oral cavity is a prime example of a complex microbial community, collectively the community appears to consist of simple and testable individual interactions.
Cell type
Cell membrane
Cite
Citations (106)
Summary Induced pluripotent stem cells (iPS) and direct lineage programming offer promising autologous and patient-specific sources of cells for personalized drug-testing and cell-based therapy. Before these engineered cells can be widely used, it is important to evaluate how well the engineered cell types resemble their intended target cell types. We have developed a method to generate CellScore, a cell identity score that can be used to evaluate the success of an engineered cell type in relation to both its initial and desired target cell type, which are used as references. Of 20 cell transitions tested, the most successful transitions were the iPS cells (CellScore > 0.9), while other transitions (e.g. induced hepatocytes or motor neurons) indicated incomplete transitions (CellScore < 0.5). In principle, the method can be applied to any engineered cell undergoing a cell transition, where transcription profiles are available for the reference cell types and the engineered cell type. Highlights A curated standard dataset of transcription profiles from normal cell types was created. CellScore evaluates the cell identity of engineered cell types, using the curated dataset. CellScore considers the initial and desired target cell type. CellScore identifies the most successfully engineered clones for further functional testing.
Cell type
Cite
Citations (1)
Abstract The ability of parental and transformed mouse C3H (10T1/2) cells to grow when held at a graded series of cell shapes (flat to round) was studied using substrata of decreasing adhesivity. The parental cells showed a decrease in growth when they reached the most rounded configurations. In contrast, transformed cells proliferated at the same rate regardless of cell shape. In addition, when transformed cells were serially passaged at low density on highly adhesive plastic, which maintained cells in a flat configuration, a reversion from the transformed phenotype to a non‐transformed phenotype occurred with the concomitant return of growth control by cell shape. However, when transformed cells were passaged at low density on a substratum which prevented cell spreading, the reversion to the parental phenotype did not occur and the cells escaped the growth control of cell shape and remained tumorigenic. Thus, in this cell system it appears that a change in cell configuration can dictate whether or not the transformed and neoplastic phenotype will be expressed.
Reversion
Neoplastic transformation
Cite
Citations (33)
Abstract Disease phenotypes, serving as valuable descriptors for delineating the spectrum of human pathologies, play a critical role in understanding disease mechanisms. Integration of these phenotypes with single-cell RNA sequencing (scRNA-seq) data facilitates the elucidation of potential associations between phenotypes and specific cell types underlying them, which sheds light on the underlying physiological processes related to these phenotypes. In this study, we utilized scRNA-seq data to infer potential associations between rare disease phenotypes and cell types. Differential expression and co-expression analyses of genes linked to abnormal phenotypes were employed as metrics to identify the involved cell types. Comparative assessments were made against existing phenotype-cell type associations documented in the literature. Our findings underscore the utility of differential expression and co-expression analyses in identifying significant relationships. Moreover, co-expression analysis unveils cell types potentially linked to abnormal phenotypes not extensively characterized in prior studies. Key points - Cell types underling rare disease phenotypes remain largely unknown - Single-cell RNA-seq data from healthy tissues can be analyzed to reveal these cell types - We employed differential expression and co-expression analysis to identify cell types associated with rare disease phenotypes - We validated our results with known relations described in the literature
Cell type
RNA-Seq
Expression (computer science)
Cite
Citations (1)
Mendelian diseases tend to manifest clinically in certain tissues, yet their affected cell types typically remain elusive. Single-cell expression studies showed that overexpression of disease-associated genes may point to the affected cell types. Here, we developed a method that infers disease-affected cell types from the preferential expression of disease-associated genes in cell types (PrEDiCT). We applied PrEDiCT to single-cell expression data of six human tissues, to infer the cell types affected in Mendelian diseases. Overall, we inferred the likely affected cell types for 328 diseases. We corroborated our findings by literature text-mining, expert validation, and recapitulation in mouse corresponding tissues. Based on these findings, we explored characteristics of disease-affected cell types, showed that diseases manifesting in multiple tissues tend to affect similar cell types, and highlighted cases where gene functions could be used to refine inference. Together, these findings expand the molecular understanding of disease mechanisms and cellular vulnerability.
Cell type
Mendelian inheritance
Cite
Citations (2)
Every type of cell has its own special features that differentiate its members qualitatively from cells of other types. Within the same type of cells, however, every single cell also has its own unique characteristics that deviate itself from other individual cells, although they are alike collectively. These kinds of individual differences between cells are described here as cell individuality, which says basically that, within a cell population or even within a multicellular organism, every cell is a unique individual living being; and no single cell could be completely identical to another, regardless of how similar to each other they are. The individuality of a single cell can be represented by all sorts of cell characteristics, which are countless and range from physiological activities to molecular constituents. These individual differences in cell characteristics are generally presented much more in degree or in quantity, rather than in kind or in quality. Moreover, such cell individuality or quantitative variations within or even between cell populations may also play a basic role in the pathogenesis of disease, and particularly in the susceptibility of cells to the disease process.
Multicellular organism
Cell type
Pathogenesis
Cite
Citations (9)
Cell type
Neoplastic transformation
Cite
Citations (307)