Discovering networks of perturbed biological processes in hepatocyte cultures

Dedifferentiation of Primary Hepatocytes is Accompanied with Reorganization of Lipid Metabolism Indicated by Altered Molecular Lipid and miRNA Profiles

Aim: Primary human hepatocytes (PHHs) undergo dedifferentiation upon the two-dimensional (2D) culture, which particularly hinders their utility in long-term in vitro studies. Lipids, as a major class of biomolecules, play crucial roles in cellular energy storage, structure, and signaling. Here, for the first time, we mapped the alterations in the lipid profile of the dedifferentiating PHHs and studied the possible role of lipids in the loss of the phenotype of PHHs. Simultaneously, differentially expressed miRNAs associated with changes in the lipids and fatty acids (FAs) of the dedifferentiating PHHs were investigated. Methods: PHHs were cultured in monolayer and their phenotype was monitored morphologically, genetically, and biochemically for five days. The lipid and miRNA profile of the PHHs were analyzed by mass spectrometry and Agilent microarray, respectively. In addition, 24 key genes involved in the metabolism of lipids and FAs were investigated by qPCR. Results: The typical morphology of PHHs was lost from day 3 onward. Additionally, ALB and CYP genes were downregulated in the cultured PHHs. Lipidomics revealed a clear increase in the saturated fatty acids (SFA) and monounsaturated fatty acids (MUFA) containing lipids, but a decrease in the polyunsaturated fatty acids (PUFA) containing lipids during the dedifferentiation of PHHs. In line with this, FASN, SCD, ELOVL1, ELOVL3, and ELOVL7 were upregulated but ELOVL2 was downregulated in the dedifferentiated PHHs. Furthermore, differentially expressed miRNAs were identified, and the constantly upregulated miR-27a and miR-21, and downregulated miR-30 may have regulated the synthesis, accumulation and secretion of PHH lipids during the dedifferentiation. Conclusion: Our results showed major alterations in the molecular lipid species profiles, lipid-metabolizing enzyme expression as wells as miRNA profiles of the PHHs during their prolonged culture, which in concert could play important roles in the PHHs’ loss of phenotype. These findings promote the understanding from the dedifferentiation process and could help in developing optimal culture conditions, which better meet the needs of the PHHs and support their original phenotype.

Transcriptomic Analysis of Hepatic Cells in Multicellular Organotypic Liver Models

Liver homeostasis requires the presence of both parenchymal and non-parenchymal cells (NPCs). However, systems biology studies of the liver have primarily focused on hepatocytes. Using an organotypic three-dimensional (3D) hepatic culture, we report the first transcriptomic study of liver sinusoidal endothelial cells (LSECs) and Kupffer cells (KCs) cultured with hepatocytes. Through computational pathway and interaction network analyses, we demonstrate that hepatocytes, LSECs and KCs have distinct expression profiles and functional characteristics. Our results show that LSECs in the presence of KCs exhibit decreased expression of focal adhesion kinase (FAK) signaling, a pathway linked to LSEC dedifferentiation. We report the novel result that peroxisome proliferator-activated receptor alpha (PPARα) is transcribed in LSECs. The expression of downstream processes corroborates active PPARα signaling in LSECs. We uncover transcriptional evidence in LSECs for a feedback mechanism between PPARα and farnesoid X-activated receptor (FXR) that maintains bile acid homeostasis; previously, this feedback was known occur only in HepG2 cells. We demonstrate that KCs in 3D liver models display expression patterns consistent with an anti-inflammatory phenotype when compared to monocultures. These results highlight the distinct roles of LSECs and KCs in maintaining liver function and emphasize the need for additional mechanistic studies of NPCs in addition to hepatocytes in liver-mimetic microenvironments.

Mechanistic evaluation of primary human hepatocyte culture using global proteomic analysis reveals a selective dedifferentiation profile

The application of primary human hepatocytes following isolation from human tissue is well accepted to be compromised by the process of dedifferentiation. This phenomenon reduces many unique hepatocyte functions, limiting their use in drug disposition and toxicity assessment. The aetiology of dedifferentiation has not been well defined, and further understanding of the process would allow the development of novel strategies for sustaining the hepatocyte phenotype in culture or for improving protocols for maturation of hepatocytes generated from stem cells. We have therefore carried out the first proteomic comparison of primary human hepatocyte differentiation. Cells were cultured for 0, 24, 72 and 168 h as a monolayer in order to permit unrestricted hepatocyte dedifferentiation, so as to reveal the causative signalling pathways and factors in this process, by pathway analysis. A total of 3430 proteins were identified with a false detection rate of <1 %, of which 1117 were quantified at every time point. Increasing numbers of significantly differentially expressed proteins compared with the freshly isolated cells were observed at 24 h (40 proteins), 72 h (118 proteins) and 168 h (272 proteins) (p < 0.05). In particular, cytochromes P450 and mitochondrial proteins underwent major changes, confirmed by functional studies and investigated by pathway analysis. We report the key factors and pathways which underlie the loss of hepatic phenotype in vitro, particularly those driving the large-scale and selective remodelling of the mitochondrial and metabolic proteomes. In summary, these findings expand the current understanding of dedifferentiation should facilitate further development of simple and complex hepatic culture systems.

Summarizing cellular responses as biological process networks

Background

Microarray experiments can simultaneously identify thousands of genes that show significant perturbation in expression between two experimental conditions. Response networks, computed through the integration of gene interaction networks with expression perturbation data, may themselves contain tens of thousands of interactions. Gene set enrichment has become standard for summarizing the results of these analyses in terms functionally coherent collections of genes such as biological processes. However, even these methods can yield hundreds of enriched functions that may overlap considerably.

Results

We describe a new technique called Markov chain Monte Carlo Biological Process Networks (MCMC-BPN) capable of reporting a highly non-redundant set of links between processes that describe the molecular interactions that are perturbed under a specific biological context. Each link in the BPN represents the perturbed interactions that serve as the interfaces between the two processes connected by the link.

We apply MCMC-BPN to publicly available liver-related datasets to demonstrate that the networks formed by the most probable inter-process links reported by MCMC-BPN show high relevance to each biological condition. We show that MCMC-BPN’s ability to discern the few key links from in a very large solution space by comparing results from two other methods for detecting inter-process links.

Conclusions

MCMC-BPN is successful in using few inter-process links to explain as many of the perturbed gene-gene interactions as possible. Thereby, BPNs summarize the important biological trends within a response network by reporting a digestible number of inter-process links that can be explored in greater detail.

RIDDLE: reflective diffusion and local extension reveal functional associations for unannotated gene sets via proximity in a gene network

The growing availability of large-scale functional networks has promoted the development of many successful techniques for predicting functions of genes. Here we extend these network-based principles and techniques to functionally characterize whole sets of genes. We present RIDDLE (Reflective Diffusion and Local Extension), which uses well developed guilt-by-association principles upon a human gene network to identify associations of gene sets. RIDDLE is particularly adept at characterizing sets with no annotations, a major challenge where most traditional set analyses fail. Notably, RIDDLE found microRNA-450a to be strongly implicated in ocular diseases and development. A web application is available at http://www.functionalnet.org/RIDDLE.

Primary hepatocyte cultures for pharmaco-toxicological studies: at the busy crossroad of various anti-dedifferentiation strategies

Continuously increasing understanding of the molecular triggers responsible for the onset of diseases, paralleled by an equally dynamic evolution of chemical synthesis and screening methods, offers an abundance of pharmacological agents with a potential to become new successful drugs. However, before patients can benefit of newly developed pharmaceuticals, stringent safety filters need to be applied to weed out unfavourable drug candidates. Cost effectiveness and the need to identify compound liabilities, without exposing humans to unnecessary risks, has stimulated the shift of the safety studies to the earliest stages of drug discovery and development. In this regard, in vivo relevant organotypic in vitro models have high potential to revolutionize the preclinical safety testing. They can enable automation of the process, to match the requirements of high-throughput screening approaches, while satisfying ethical considerations. Cultures of primary hepatocytes became already an inherent part of the preclinical pharmaco-toxicological testing battery, yet their routine use, particularly for long-term assays, is limited by the progressive deterioration of liver-specific features. The availability of suitable hepatic and other organ-specific in vitro models is, however, of paramount importance in the light of changing European legal regulations in the field of chemical compounds of different origin, which gradually restrict the use of animal studies for safety assessment, as currently witnessed in cosmetic industry. Fortunately, research groups worldwide spare no effort to establish hepatic in vitro systems. In the present review, both classical and innovative methodologies to stabilize the in vivo-like hepatocyte phenotype in culture of primary hepatocytes are presented and discussed.

Prediction of disease and phenotype associations from genome-wide association studies

BACKGROUND

Genome wide association studies (GWAS) have proven useful as a method for identifying genetic variations associated with diseases. In this study, we analyzed GWAS data for 61 diseases and phenotypes to elucidate common associations based on single nucleotide polymorphisms (SNP). The study was an expansion on a previous study on identifying disease associations via data from a single GWAS on seven diseases.

METHODOLOGY/PRINCIPAL FINDINGS

Adjustments to the originally reported study included expansion of the SNP dataset using Linkage Disequilibrium (LD) and refinement of the four levels of analysis to encompass SNP, SNP block, gene, and pathway level comparisons. A pair-wise comparison between diseases and phenotypes was performed at each level and the Jaccard similarity index was used to measure the degree of association between two diseases/phenotypes. Disease relatedness networks (DRNs) were used to visualize our results. We saw predominant relatedness between Multiple Sclerosis, type 1 diabetes, and rheumatoid arthritis for the first three levels of analysis. Expected relatedness was also seen between lipid- and blood-related traits.

CONCLUSIONS/SIGNIFICANCE

The predominant associations between Multiple Sclerosis, type 1 diabetes, and rheumatoid arthritis can be validated by clinical studies. The diseases have been proposed to share a systemic inflammation phenotype that can result in progression of additional diseases in patients with one of these three diseases. We also noticed unexpected relationships between metabolic and neurological diseases at the pathway comparison level. The less significant relationships found between diseases require a more detailed literature review to determine validity of the predictions. The results from this study serve as a first step towards a better understanding of seemingly unrelated diseases and phenotypes with similar symptoms or modes of treatment.