Evaluation of an in vitro model of hepatic inflammatory response by gene expression profiling

Effects of Pro-Inflammatory Cytokines on Hepatic Metabolism in Primary Human Hepatocytes

Three decades of hepatocyte transplantation have confirmed such a cell-based approach as an adjunct or alternative treatment to solid organ transplantation. Donor cell survival and engraftment were indirectly measured by hepatospecific secretive or released metabolites, such as ammonia metabolism in urea cycle defects. In cases of sepsis or viral infection, ammonia levels can significantly and abruptly increase in these recipients, erroneously implying rejection. Pro-inflammatory cytokines associated with viral or bacterial infections are known to affect many liver functions, including drug-metabolizing enzymes and hepatic transport activities. We examined the influence of pro-inflammatory cytokines in primary human hepatocytes, isolated from both normal donors or patients with metabolic liver diseases. Different measures of hepatocyte functions, including ammonia metabolism and phase 1-3 metabolism, were performed. All the hepatic functions were profoundly and significantly suppressed after exposure to concentrations of from 0.1 to 10 ng/mL of different inflammatory cytokines, alone and in combination. Our data indicate that, like phase I metabolism, suppression of phase II/III and ammonia metabolism occurs in hepatocytes exposed to pro-inflammatory cytokines in the absence of cell death. Such inflammatory events do not necessarily indicate a rejection response or loss of the cell graft, and these systemic inflammatory signals should be carefully considered when the immunosuppressant regiment is reduced or relieved in a hepatocyte transplantation recipient in response to such alleged rejection.

Macrophage derived TNFα promotes hepatic reprogramming to Warburg-like metabolism

During infection, hepatocytes must undergo a reprioritization of metabolism, termed metabolic reprogramming. Hepatic metabolic reprogramming in response to infection begins within hours of infection, suggesting a mechanism closely linked to pathogen recognition. Following injection with polyinosinic:polycytidylic acid, a mimic of viral infection, a robust hepatic innate immune response could be seen involving the TNFα pathway at 2 h. Repeated doses led to the adoption of Warburg-like metabolism in the liver as determined by in vivo metabolic imaging, expression analyses, and metabolomics. Hepatic macrophages, Kupffer cells, were able to induce Warburg-like metabolism in hepatocytes in vitro via TNFα. Eliminating macrophages in vivo or blocking TNFα in vitro or in vivo resulted in abrogation of the metabolic phenotype, establishing an immune-metabolic axis in hepatic metabolic reprogramming. Overall, we suggest that macrophages, as early sensors of pathogens, instruct hepatocytes via TNFα to undergo metabolic reprogramming to cope with challenges to homeostasis initiated by infection. This work not only addresses a key component of end-organ physiology, but also raises questions about the side effects of biologics in the treatment of inflammatory diseases. KEY MESSAGES: • Hepatocytes develop Warburg-like metabolism in vivo during viral infection. • Macrophage TNFα promotes expression of glycolytic enzymes in hepatocytes. • Blocking this immune-metabolic axis abrogates Warburg-like metabolism in the liver. • Implications for patients being treated for inflammatory diseases with biologics.

The liver is a metabolic and immunologic organ: A reconsideration of metabolic decompensation due to infection in inborn errors of metabolism (IEM)

Metabolic decompensation in inborn errors of metabolism (IEM) is characterized by a rapid deterioration in metabolic status leading to life-threatening biochemical perturbations (e.g. hypoglycemia, hyperammonemia, acidosis, organ failure). Infection is the major cause of metabolic decompensation in patients with IEM. We hypothesized that activation of the immune system during infection leads to further perturbations in end-organ metabolism resulting in increased morbidity. To address this, we established model systems of metabolic decompensation due to infection. Using these systems, we have described the pathologic mechanisms of metabolic decompensation as well as changes in hepatic metabolic reserve associated with infection. First and foremost, our studies have demonstrated that the liver experiences a significant local innate immune response during influenza infection that modulates hepatic metabolism. Based on these findings, we are the first to suggest that the role of the liver as a metabolic and immunologic organ is central in the pathophysiology of metabolic decompensation due to infection in IEM. The dual function of the liver as a major metabolic regulator and a lymphoid organ responsible for immunosurveillance places this organ at risk for hepatotoxicity. Mobilization of hepatic reserve and the regenerative capacity of a healthy liver compensates for this calculated risk. However, activation of the hepatic innate immune system may be deleterious in IEM. Based on this assertion, strategies aimed at modulating the innate immune response may be a viable target for intervention in the treatment of hepatic metabolic decompensation.

Transcriptional and metabolic flux profiling of triadimefon effects on cultured hepatocytes

Conazoles are a class of azole fungicides used to prevent fungal growth in agriculture, for treatment of fungal infections, and are found to be tumorigenic in rats and/or mice. In this study, cultured primary rat hepatocytes were treated to two different concentrations (0.3 and 0.15 mM) of triadimefon, which is a tumorigenic conazole in rat and mouse liver, on a temporal basis with daily media change. Following treatment, cells were harvested for microarray data ranging from 6 to 72 h. Supernatant was collected daily for three days, and the concentrations of various metabolites in the media and supernatant were quantified. Gene expression changes were most significant following exposure to 0.3 mM triadimefon and were characterized mainly by metabolic pathways related to carbohydrate, lipid and amino acid metabolism. Correspondingly, metabolic network flexibility analysis demonstrated a switch from fatty acid synthesis to fatty acid oxidation in cells exposed to triadimefon. It is likely that fatty acid oxidation is active in order to supply energy required for triadimefon detoxification. In 0.15 mM triadimefon treatment, the hepatocytes are able to detoxify the relatively low concentration of triadimefon with less pronounced changes in hepatic metabolism.

Long-term superior performance of a stem cell/hepatocyte device for the treatment of acute liver failure

Cell-based technologies to support/restore organ function represent one of the most promising avenues in the treatment of acute liver failure (ALF). Recently, mesenchymal stem cells (MSCs) have been reported as a new therapeutic for inflammatory conditions. Here, we demonstrate the efficacy of MSCs, when cocultured with hepatocytes, to provide combination hepatic and antiinflammatory therapy in the setting of ALF. MSCs were shown to have multiple beneficial effects in vitro that were relevant in a therapeutic context, including (1) hepatocellular functional support, (2) secretion of molecules that inhibit hepatocyte apoptosis, and (3) modulation of an acute phase response by hepatocytes cultured in ALF-induced serum. In addition, we show that the MSC secretome is dynamically changed in response to serum exposure from ALF rats. We then conducted a therapeutic trial of liver assist devices (LADs). LADs containing cocultures of MSCs and hepatocytes provided a greater survival benefit compared to other coculture and monocellular control LADs. Treatment with MSC-hepatocyte devices was associated with specific improvements in hepatic functional and histological parameters as well as decreasing inflammatory serum cytokine levels, validating a combined therapeutic effect. Moreover, MSC coculture reduced the overall cell mass of the device by an order of magnitude. These findings demonstrate the importance of nonparenchymal cells in the cellular composition of LADs, and strongly support the integration of MSCs into hepatocyte-coculture-based LADs as a potential destination therapy for ALF.

Identification of global transcriptional dynamics

Background

One of the challenges in exploiting high throughput measurement techniques such as microarrays is the conversion of the vast amounts of data obtained into relevant knowledge. Of particular importance is the identification of the intrinsic response of a transcriptional experiment and the characterization of the underlying dynamics.

Methodology and Findings

The proposed algorithm seeks to provide the researcher a summary as to various aspects relating to the dynamic progression of a biological system, rather than that of individual genes. The approach is based on the identification of smaller number of expression motifs that define the transcriptional state of the system which quantifies the deviation of the cellular response from a control state in the presence of an external perturbation. The approach is demonstrated with a number of data sets including a synthetic base case and four animal studies. The synthetic dataset will be used to establish the response of the algorithm on a “null” dataset, whereas the four different experimental datasets represent a spectrum of possible time course experiments in terms of the degree of perturbation associated with the experiment as well as representing a wide range of temporal sampling strategies. This wide range of experimental datasets will thus allow us to explore the performance of the proposed algorithm and determine its ability identify relevant information.

Conclusions and Significance

In this work, we present a computational approach which operates on high throughput temporal gene expression data to assess the information content of the experiment, identify dynamic markers of important processes associated with the experimental perturbation, and summarize in a concise manner the evolution of the system over time with respect to the experimental perturbation.

Assessing the information content of short time series expression data

Due to experimental constraints, the sampling of biological system with microarray data is severely constrained. In similar fashion to sampling theory of signals, the under-sampling of a system oftentimes leads to sub-optimal results from which it is difficult to draw proper conclusions. In our work we create a mathematical framework which will show that the sampling methodology for short time series microarray data may lead to data whose ability to distinguish non-random behavior within the biological system is severely constrained.

Micropatterning of living cells by laser-guided direct writing: application to fabrication of hepatic-endothelial sinusoid-like structures

Here, we describe a simple protocol for the design and construction of a laser-guided direct writing (LGDW) system able to micropattern the self-assembly of liver sinusoid-like structures with micrometer resolution in vitro. To the best of our knowledge, LGDW is the only technique able to pattern cells "on the fly" with micrometer precision on arbitrary matrices, including soft gels such as Matrigel. By micropatterning endothelial cells on Matrigel, one can control the self-assembly of vascular structures and associated liver tissue. LGDW is therefore uniquely suited for studying the role of tissue architecture and mechanical properties at the single-cell resolution, and for studying the effects of heterotypic cell-cell interactions underlying processes such as liver morphogenesis, differentiation and angiogenesis. The total time required to carry out this protocol is typically 7 h.

Analysis of time-series gene expression data: methods, challenges, and opportunities

Monitoring the change in expression patterns over time provides the distinct possibility of unraveling the mechanistic drivers characterizing cellular responses. Gene arrays measuring the level of mRNA expression of thousands of genes simultaneously provide a method of high-throughput data collection necessary for obtaining the scope of data required for understanding the complexities of living organisms. Unraveling the coherent complex structures of transcriptional dynamics is the goal of a large family of computational methods aiming at upgrading the information content of time-course gene expression data. In this review, we summarize the qualitative characteristics of these approaches, discuss the main challenges that this type of complex data present, and, finally, explore the opportunities in the context of developing mechanistic models of cellular response.

In vitro liver tissue model established from transgenic mice: role of HIF-1alpha on hypoxic gene expression

The instability of the hepatocyte phenotype in vitro has limited the ability to quantitatively investigate regulation of stress responses of the liver. Here, we adopt a tissue-engineering approach to form stable liver tissue in vitro by forming collagen "sandwich" cultures of transgenic murine hepatocytes harboring a regulatory gene of interest flanked by loxP sites. The floxed gene is excised in a subset of cultures by transfection with adenovirus carrying the gene for Cre-recombinase, thereby generating wild-type and null liver tissues from a single animal. In this study, we specifically investigated the role of hypoxia inducible factor 1 alpha (HIF-1alpha) in the hepatocellular response to hypoxia. Using high-density oligonucleotide arrays, we examined genome-wide gene expression after 8 h of hypoxia in wild-type and HIF- 1alpha null hepatocyte cultures. We identified more than 130 genes differentially expressed under hypoxia involved in metabolic adaptation, angiogenic signaling, immediate early response, and cell cycle regulation. Real-time polymerase chain reaction analysis verified that known hypoxia-responsive genes such as glucose transporter-1 and vascular endothelial growth factor were induced in a HIF-1alpha-dependent manner under hypoxia. Our results demonstrate the potential to integrate in vitro tissue models with transgenic and microarray technologies for the study of physiologic stress responses.

Bioinformatics analysis of the early inflammatory response in a rat thermal injury model

Background

Thermal injury is among the most severe forms of trauma and its effects are both local and systemic. Response to thermal injury includes cellular protection mechanisms, inflammation, hypermetabolism, prolonged catabolism, organ dysfunction and immuno-suppression. It has been hypothesized that gene expression patterns in the liver will change with severe burns, thus reflecting the role the liver plays in the response to burn injury. Characterizing the molecular fingerprint (i.e., expression profile) of the inflammatory response resulting from burns may help elucidate the activated mechanisms and suggest new therapeutic intervention. In this paper we propose a novel integrated framework for analyzing time-series transcriptional data, with emphasis on the burn-induced response within the context of the rat animal model. Our analysis robustly identifies critical expression motifs, indicative of the dynamic evolution of the inflammatory response and we further propose a putative reconstruction of the associated transcription factor activities.

Results

Implementation of our algorithm on data obtained from an animal (rat) burn injury study identified 281 genes corresponding to 4 unique profiles. Enrichment evaluation upon both gene ontologies and transcription factors, verifies the inflammation-specific character of the selections and the rationalization of the burn-induced inflammatory response. Conducting the transcription network reconstruction and analysis, we have identified transcription factors, including AHR, Octamer Binding Proteins, Kruppel-like Factors, and cell cycle regulators as being highly important to an organism's response to burn response. These transcription factors are notable due to their roles in pathways that play a part in the gross physiological response to burn such as changes in the immune response and inflammation.

Conclusion

Our results indicate that our novel selection/classification algorithm has been successful in selecting out genes with play an important role in thermal injury. Additionally, we have demonstrated the value of an integrative approach in identifying possible points of intervention, namely the activation of certain transcription factors that govern the organism's response.

Toxicogenomics: a pivotal piece in the puzzle of toxicological research

Toxicogenomics, resulting from the merge of conventional toxicology with functional genomics, being the scientific field studying the complex interactions between the cellular genome, toxic agents in the environment, organ dysfunction and disease state. When an organism is exposed to a toxic agent the cells respond by altering the pattern of gene expression. Genes are transcribed into mRNA, which in turn is translated into proteins that serve in a variety of cellular functions. Toxicogenomics through microarray technology, offers large-scale detection and quantification of mRNA transcripts, related to alterations in mRNA stability or gene regulation. This may prove advantageous in toxicological research. In the present review, the applications of toxicogenomics, especially to mechanistic and predictive toxicology are reported. The limitations arising from the use of this technology are also discussed. Additionally, a brief report of other approaches, using other -omic technologies (proteomics and metabonomics) that overcome limitations and give global information related to toxicity, is included.

A high-throughput microfluidic real-time gene expression living cell array

The dynamics of gene expression are fundamental to the coordination of cellular responses. Measurement of temporal gene expression patterns is currently limited to destructive low-throughput techniques such as northern blotting, reverse transcription polymerase chain reaction (RT-PCR), and DNA microarrays. We report a scalable experimental platform that combines microfluidic addressability with quantitative live cell imaging of fluorescent protein transcriptional reporters to achieve real-time characterization of gene expression programs in living cells. Integrated microvalve arrays control row-seeding and column-stimulation of 256 nanoliter-scale bioreactors to create a high density matrix of stimulus-response experiments. We demonstrate the approach in the context of hepatic inflammation by acquiring approximately 5000 single-time-point measurements in each automated and unattended experiment. Experiments can be assembled in hours and perform the equivalent of months of conventional experiments. By enabling efficient investigation of dynamic gene expression programs, this technology has the potential to make significant impacts in basic science, drug development, and clinical medicine.

Detecting genetic predisposition for complicated clinical outcomes after burn injury

Sepsis, septic shock and organ failure are common among patients with moderate to severe burns. The inability of demographic and clinical factors to identify patients at high risk for such complications suggests that genetic variation may influence clinical outcome. Moreover, the genetic predisposition to death from infection has been estimated to be greater than for cardiovascular disease or cancer . While it is widely accepted that genetic factors influence many complex disease processes, controversy has emerged regarding the most appropriate methods for detection and even the validity of many published allelic associations . This article will review the few studies of genetic predisposition that have been conducted in the setting of burn injury, then discuss some of the obstacles and potential approaches for the discovery of additional allelic associations.

Integration of technologies for hepatic tissue engineering

The liver is the largest internal organ in the body, responsible for over 500 metabolic, regulatory, and immune functions. Loss of liver function leads to liver failure which causes over 25,000 deaths/year in the United States. Efforts in the field of hepatic tissue engineering include the design of bioartificial liver systems to prolong patient's lives during liver failure, for drug toxicity screening and for the study of liver regeneration, ischemia/reperfusion injury, fibrosis, viral infection, and inflammation. This chapter will overview the current state-of-the-art in hepatology including isolated perfused liver, culture of liver slices and tissue explants, hepatocyte culture on collagen "sandwich" and spheroids, coculture of hepatocytes with non-parenchymal cells, and the integration of these culture techniques with microfluidics and reactor design. This work will discuss the role of oxygen and medium composition in hepatocyte culture and present promising new technologies for hepatocyte proliferation and function. We will also discuss liver development, architecture, and function as they relate to these culture techniques. Finally, we will review current opportunities and major challenges in integrating cell culture, bioreactor design, and microtechnology to develop new systems for novel applications.