scholarly journals Reconstruction of consensus tissue-specific metabolic models

2018 ◽  
Author(s):  
Sara Correia ◽  
Bruno Costa ◽  
Miguel Rocha
Keyword(s):  
Cell Line ◽  
Case Studies ◽  
Cancer Metabolism ◽  
Cell Types ◽  
Tissue Cell ◽  
Tissue Specific ◽  
Metabolic Phenotypes ◽  
Distinct Cell ◽  
Metabolic Models ◽  
Genome Scale

AbstractGenome-Scale Metabolic Models have shown promising results in biomedical applications, such as understanding cancer metabolism and drug discovery. However, to take full advantage of these models there is the need to address the representation and simulation of the metabolic phenotypes of distinct cell types. With this aim, several algorithms have been recently proposed to reconstruct tissue-specific metabolic models based on available data. Here, the most promising were implemented and used to reconstruct models for two case studies, using omics data from distinct sources. The set of obtained models were compared and analyzed, being shown they are highly variable and that no combination of algorithm and data source can achieve models with acceptable phenotype predictions. We propose an algorithm to achieve a consensus model from the set of models available for a given tissue/cell line, and to improve it given functional data (e.g. known metabolic tasks). The results show that the resulting models are more accurate, both considering the prediction of known metabolic phenotypes and of experimental data not used in the model construction. Two case studies used for model validation consider healthy hepatocytes and a glioblastoma cell line. The open-source implementation of the algorithms is provided, together with the models built, in a software container, allowing full reproducibility, and representing by itself a contribution for the community.

Reconstruction of tissue-specific genome-scale metabolic models for human cancer stem cells

2021 ◽  
pp. 105177
Author(s):  
Tânia Barata ◽  
Vítor Vieira ◽  
Rúben Rodrigues ◽  
Ricardo Pires das Neves ◽  
Miguel Rocha
Keyword(s):  
Stem Cells ◽  
Cancer Stem Cells ◽  
Human Cancer ◽  
Tissue Specific ◽  
Metabolic Models ◽  
Genome Scale

scholarly journals RMetD2: a tool for integration of relative transcriptomics data into Genome-scale metabolic models

2019 ◽  
Author(s):  
Cheng Zhang ◽  
Sunjae Lee ◽  
Gholamreza Bidkhori ◽  
Rui Benfeitas ◽  
Alen Lovric ◽  
...  
Keyword(s):  
Case Studies ◽  
State Of The Art ◽  
Differentially Expressed ◽  
Systems Medicine ◽  
Transcriptomics Data ◽  
Altered Metabolism ◽  
Metabolic Models ◽  
Genome Scale ◽  
Potential Use ◽  
Single Set

AbstractRelative Metabolic Differences version 2 (RMetD2) is a tool for integration of differentially expressed (DE) genes into genome-scale metabolic models (GEMs) for revealing the altered metabolism between two biological conditions. This method provides a robust evaluation of the metabolism by using flux ranges instead of a single set of flux distributions. RMetD2 classifies reactions into three different groups, namely up-regulated, down-regulated and unchanged, which enables systematic interpretation of the metabolic differences between two different conditions. We employed this method in three different case studies using mice and human datasets, and compared it with state-of-the-art methods used for studying condition-specific metabolic differences using GEMs. We observed that RMetD2 is capable of capturing experimentally-observed features that are missed by other methods, highlighting its potential use in biotechnology and systems medicine applications. RMetD2 is implemented in Matlab and it is available without any limitation at https://sourceforge.net/projects/rmetd.

scholarly journals Comparison of metabolic states using genome-scale metabolic models

2021 ◽  
Vol 17 (11) ◽  
pp. e1009522
Author(s):  
Chaitra Sarathy ◽  
Marian Breuer ◽  
Martina Kutmon ◽  
Michiel E. Adriaens ◽  
Chris T. Evelo ◽  
...  
Keyword(s):  
Metabolic Networks ◽  
Biological Significance ◽  
Tca Cycle ◽  
Cell Types ◽  
Knowledge Bases ◽  
Objective Functions ◽  
Functional Differences ◽  
Metabolic States ◽  
Metabolic Models ◽  
Genome Scale

Genome-scale metabolic models (GEMs) are comprehensive knowledge bases of cellular metabolism and serve as mathematical tools for studying biological phenotypes and metabolic states or conditions in various organisms and cell types. Given the sheer size and complexity of human metabolism, selecting parameters for existing analysis methods such as metabolic objective functions and model constraints is not straightforward in human GEMs. In particular, comparing several conditions in large GEMs to identify condition- or disease-specific metabolic features is challenging. In this study, we showcase a scalable, model-driven approach for an in-depth investigation and comparison of metabolic states in large GEMs which enables identifying the underlying functional differences. Using a combination of flux space sampling and network analysis, our approach enables extraction and visualisation of metabolically distinct network modules. Importantly, it does not rely on known or assumed objective functions. We apply this novel approach to extract the biochemical differences in adipocytes arising due to unlimited vs blocked uptake of branched-chain amino acids (BCAAs, considered as biomarkers in obesity) using a human adipocyte GEM (iAdipocytes1809). The biological significance of our approach is corroborated by literature reports confirming our identified metabolic processes (TCA cycle and Fatty acid metabolism) to be functionally related to BCAA metabolism. Additionally, our analysis predicts a specific altered uptake and secretion profile indicating a compensation for the unavailability of BCAAs. Taken together, our approach facilitates determining functional differences between any metabolic conditions of interest by offering a versatile platform for analysing and comparing flux spaces of large metabolic networks.

scholarly journals Cell and tissue type independent age-associated DNA methylation changes are not rare but common

2018 ◽  
Author(s):  
Tianyu Zhu ◽  
Shijie C Zheng ◽  
Dirk S. Paul ◽  
S. Horvath ◽  
Andrew E. Teschendorff
Keyword(s):  
Dna Methylation ◽  
Cell Types ◽  
Tissue Type ◽  
Tissue Cell ◽  
Cell Type ◽  
Tissue Specific ◽  
Cell Tissue ◽  
A Cell ◽  
High Degree ◽  
Do So

AbstractAge-associated DNA methylation changes have been widely reported across many different tissue and cell types. Epigenetic ‘clocks’ that can predict chronological age with a surprisingly high degree of accuracy appear to do so independently of tissue and cell-type, suggesting that a component of epigenetic drift is cell-type independent. However, the relative amount of age-associated DNAm changes that are specific to a cell or tissue type versus the amount that occurs independently of cell or tissue type is unclear and a matter of debate, with a recent study concluding that most epigenetic drift is tissue-specific. Here, we perform a novel comprehensive statistical analysis, including matched multi cell-type and multi-tissue DNA methylation profiles from the same individuals and adjusting for cell-type heterogeneity, demonstrating that a substantial amount of epigenetic drift, possibly over 70%, is shared between significant numbers of different tissue/cell types. We further show that ELOVL2 is not unique and that many other CpG sites, some mapping to genes in the Wnt and glutamate receptor signaling pathways, are altered with age across at least 10 different cell/tissue types. We propose that while most age-associated DNAm changes are shared between cell-types that the putative functional effect is likely to be tissue-specific.

scholarly journals Transcriptome Analysis of Adult C. elegans Cells Reveals Tissue-specific Gene and Isoform Expression

2017 ◽  
Author(s):  
Rachel Kaletsky ◽  
Vicky Yao ◽  
April Williams ◽  
Alexi M. Runnels ◽  
Sean B. King ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Cell Types ◽  
Tissue Cell ◽  
Specific Gene ◽  
Specific Information ◽  
Large Set ◽  
Tissue Specific ◽  
C Elegans ◽  
Cellular Expression ◽  
Adult Cell

AbstractThe biology and behavior of adults differ substantially from those of developing animals, and cell-specific information is critical for deciphering the biology of multicellular animals. Thus, adult tissue-specific transcriptomic data are critical for understanding molecular mechanisms that control their phenotypes. We used adult cell-specific isolation to identify the transcriptomes of C. elegans’ four major tissues (or “tissue-ome”), identifying ubiquitously expressed and tissue-specific “super-enriched” genes. These data newly reveal the hypodermis’ metabolic character, suggest potential worm-human tissue orthologies, and identify tissue-specific changes in the Insulin/IGF-1 signaling pathway. Tissue-specific alternative splicing analysis identified a large set of collagen isoforms and a neuron-specific CREB isoform. Finally, we developed a machine learning-based prediction tool for 70 sub-tissue cell types, which we used to predict cellular expression differences in IIS/FOXO signaling, stage-specific TGF-b activity, and basal vs. memory-induced CREB transcription. Together, these data provide a rich resource for understanding the biology governing multicellular adult animals

scholarly journals ExoBow: A transgenic strategy to study CD63 exosomes in vivo

2021 ◽  
Author(s):  
Bárbara Adem ◽  
Nuno Bastos ◽  
Carolina F. Ruivo ◽  
Patrícia F. Vieira ◽  
Barbara Seidler ◽  
...  
Keyword(s):  
Fluorescent Proteins ◽  
Cell Types ◽  
Genetically Engineered ◽  
Tissue Cell ◽  
Cell Type ◽  
Distinct Cell ◽  
Genetically Engineered Mouse Model ◽  
Conditional Expression ◽  
Organ Tissue

ABSTRACTExosomes are described as central players in a myriad of biological processes. However, the available methodologies to study their function in complex biological systems in vivo are still very limited. The biodistribution of endogenously produced exosomes, the ability to trace their spontaneous flow in order to identify the cell types they interact with, remains a major challenge. New tools to identify comprehensive networks of communication established by exosomes originated in distinct cell types in vivo, are fundamental for a better understanding of their biology. Here, we describe the development of a genetically engineered mouse model that allows the expression of the mouse CD63 exosomal marker fused with one (monocolor) or up to four fluorescent proteins (multireporter), the ExoBow. The genetic design of the ExoBow transgene allows the conditional expression of the reporters in any tissue/cell-type in an inducible or non-inducible fashion. In addition, communication mediated by CD63 positive (CD63+) exosomes can be identified amongst the same tissue/cell types using the multireporter version of the model, in order to map intra-organ/tissue communication. We demonstrate the applicability of the ExoBow transgene in normal physiological conditions and in the context of cancer, using pancreas as a working model. The ExoBow comprises a unique strategy to identify intra- and inter-organ/cell-type communication mediated by CD63+ exosomes. We believe this tool will contribute for a better understanding of the complex interactions occurring in vivo that underly the biology of exosomes in health and disease.

Fine Structure of the Malpighian Tubules of the Mosquito, Culex pipiens

1971 ◽  
Vol 29 ◽  
pp. 402-403
Author(s):  
Brendan Clifford
Keyword(s):  
Fine Structure ◽  
Culex Pipiens ◽  
Stellate Cell ◽  
Malpighian Tubule ◽  
Cell Types ◽  
Instar Larva ◽  
Malpighian Tubules ◽  
Calliphora Erythrocephala ◽  
Distinct Cell ◽  
Basal Plasma

An ultrastructural investigation of the Malpighian tubules of the fourth instar larva of Culex pipiens was undertaken as part of a continuing study of the fine structure of transport epithelia.Each of the five Malpighian tubules was found to be morphologically identical and regionally undifferentiated. Two distinct cell types, the primary and stellate, were found intermingled along the length of each tubule. The ultrastructure of the stellate cell was previously described in the Malpighian tubule of the blowfly, Calliphora erythrocephala by Berridge and Oschman.The basal plasma membrane of the primary cell is extremely irregular, giving rise to a complex interconnecting network of basal channels. The compartments of cytoplasm entrapped within this system of basal infoldings contain mitochondria, free ribosomes, and small amounts of rough endoplasmic reticulum. The mitochondria are distinctive in that the cristae run parallel to the long axis of the organelle.

Ultrastructural Study of a differentiating human colon carcinoma cell line

1990 ◽  
Vol 48 (3) ◽  
pp. 208-209
Author(s):  
Sylvie Polak-Charcon ◽  
Mehrdad Hekmati ◽  
Yehuda Ben Shaul
Keyword(s):  
Cell Line ◽  
Morphological Changes ◽  
Secretory Granules ◽  
Human Colon ◽  
Cell Types ◽  
Culture Conditions ◽  
Morphological Evidence ◽  
Human Colon Carcinoma Cell ◽  
Colon Cell

The epithelium of normal human colon mucosa “in vivo” exhibits a gradual pattern of differentiation as undifferentiated stem cells from the base of the crypt of “lieberkuhn” rapidly divide, differentiate and migrate toward the free surface. The major differentiated cell type of the intestine observed are: absorptive cells displaying brush border, goblet cells containing mucous granules, Paneth and endocrine cells containing dense secretory granules. These different cell types are also found in the intestine of the 13-14 week old embryo.We present here morphological evidence showing that HT29, an adenocarcinoma of the human colon cell line, can differentiate into various cell types by changing the growth and culture conditions and mimic morphological changes found during development of the intestine in the human embryo.HT29 cells grown in tissue-culture dishes in DMEM and 10% FCS form at late confluence a multilayer of morphologically undifferentiated cell culture covered with irregular microvilli, and devoid of tight junctions (Figs 1-3).

scholarly journals NF-κB in Cancer Immunity: Friend or Foe?

Cells ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 355
Author(s):  
Guilhem Lalle ◽  
Julie Twardowski ◽  
Yenkel Grinberg-Bleyer
Keyword(s):  
Immune Responses ◽  
Therapeutic Potential ◽  
Cell Types ◽  
Transcriptional Activators ◽  
New Class ◽  
Complex Interactions ◽  
Cancer Immunity ◽  
Distinct Cell ◽  
Cancer Initiation ◽  
Cancer Outcome

The emergence of immunotherapies has definitely proven the tight relationship between malignant and immune cells, its impact on cancer outcome and its therapeutic potential. In this context, it is undoubtedly critical to decipher the transcriptional regulation of these complex interactions. Following early observations demonstrating the roles of NF-κB in cancer initiation and progression, a series of studies converge to establish NF-κB as a master regulator of immune responses to cancer. Importantly, NF-κB is a family of transcriptional activators and repressors that can act at different stages of cancer immunity. In this review, we provide an overview of the selective cell-intrinsic contributions of NF-κB to the distinct cell types that compose the tumor immune environment. We also propose a new view of NF-κB targeting drugs as a new class of immunotherapies for cancer.

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