Systems Engineering of Stem Cell Fate

University of Minnesota Ph.D. dissertation. August 2015. Major: Chemical Engineering. Advisors: Wei-Shou Hu, Catherine Verfaillie. 1 computer file (PDF); 242 pages.Recent advances in the derivation of functional cells from pluripotent stem cells have raised hope for cell therapy to treat liver ailments. They have enhanced the prospects of developing reliable in vitro models for liver diseases and drug toxicity screening. A differentiation protocol mimicking key signaling cues of embryonic development was developed to direct stem cells (ES) towards the hepatic fate and express key hepatic markers and functions. While these results are encouraging, most directed differentiations from stem cells to the target cell types are hampered by lack of functional maturity, cell heterogeneity and low cell yields limiting their translation to the clinic. These cells are therefore refereed to hepatocyte-like cells (HLCs). An integrative strategy was employed including both experimental techniques as well as a systems-based analysis towards enhancing the product quality and yields of HLCs. Functional maturity was enhanced by initiating three dimensional spheroid formation upon differentiation. Enrichment of hepatic cells using selective medium conditions was performed to obtain higher fraction of cells with the desired properties. Cell expansion was incorporated during differentiation to improve cell yields. Several additional strategies have been used to increase hepatocyte maturity in literature including co-culture and transfection with transcription factors. These methods including ours have shown improvement, however a universal gap to maturation is still present when compared to primary hepatocytes. Comparison of transcriptome data of differentiation to embryonic liver development can elucidate the genetic roadblocks preventing ES cells from reaching the functional maturity of their tissue counterparts. Transcriptome data was compiled from various depositories for mouse fetal liver development (from E8.5 to post-natal). Transcriptome data was obtained during the time course of our human hepatic differentiation protocol and was augmented with human in vitro hepatic differentiation data in the public depository. Interestingly, majority of the HLCs are similar irrespective of the cell source and protocol. The entire cohort of HLCs clustered separately from the primary hepatocytes and adult liver indicating an inherent roadblock to maturation. The transcriptome data of human ES hepatic differentiations was then integrated with mouse liver development using a unique approach. This allowed us to identify the corresponding development stage at which the in vitro stem cell differentiation is blocked. The analysis uncovered a pivotal gene set with contrasting profiles in ES differentiation and mouse liver development that merit combinatorial genetic intervention to enhance maturation of ES derived hepatocytes. Thus, one can envision the availability of stem cell based liver therapies in the not so distant future

Application of -omics knowledge yields enhanced bioprocess performance

The classic phrase to describe cell culture is “every cell line is different.” The unfortunate part of this idiom is the actual concealment of a crucial lack of fundamental understanding. Furthermore the phrase ignores the substantial success achieved to date in developing robust industrial cell culture platforms that are applied to all cell lines regardless of their intrinsic variation. At Biogen, our cell culture medium platform is agnostic to CHO host cell line, and the platform can accommodate this inherent genomic variation as cell lines come from different host backgrounds. This is also an opportunity for -omics work then as the differences in cell line performance can be linked back to fundamental differences within those host cell lines. However, the power of -omics technologies to influence process optimization is limited by the difficulty and time scale for execution and interpreting such studies. Our approach to -omics implementation has been to utilize multiple targeted investigations and combine the learnings into an implementation strategy focused on enhancing the efficiency of manufacturing. Metabolic flux analysis was used to establish a baseline knowledge of central metabolism in the Biogen platform. The next step was to incorporate transcriptomics and proteomics with our metabolomics knowledge. With Biogen’s toolbox of CHO host cell lines, this approach identified intrinsic host cell line differences as well as unique limitations in cell culture. Specifically, we have determined sources of novel metabolic inhibitors that suppress cell growth as well as differences in lactate and ammonium metabolism that split according to host cell source. These conclusions ultimately lead to the optimized platform process yielding the desired product quality. Determining these differences led to an increased growth rate in scale up for cell lines from a more sensitive host as well as maintaining robust cell growth and productivity in production bioreactors. Ultimately still “every cell line is different.” Yet the more we know, the more opportunities there are to exploit both the similarities and the differences

Process optimization for high volumetric productivity with product quality control

High commercial demands of biotherapeutics require high volumetric productivities to accommodate their production with the existing manufacturing infrastructure. While titers are exceeding 5 grams per liter in fed-batch processes, it is imperative that these processes result in consistent and desirable product quality. Here we describe a fed batch process optimization effort resulting in significant increased titer than the initial process. During the optimization, we identified a medium component capable of impacting productivity and two different critical product quality attributes. Through complex screening, the component concentration was shown to be proportional to these product quality modifications in opposing directions, thereby requiring a careful optimization of the delivery range. One of these modifications was recapitulated in a cell free system with media and protein indicating that this was not a result of shift in cellular metabolism unlike the other modification. The mechanism of action and strategies to mitigate this issue were also evaluated. Through this work, a well-controlled process without impacting productivity during large scale manufacturing was designed

Metabolic network reconstruction and genome-scale model of butanol-producing strain Clostridium beijerinckii NCIMB 8052

<p>Abstract</p> <p>Background</p> <p>Solventogenic clostridia offer a sustainable alternative to petroleum-based production of butanol--an important chemical feedstock and potential fuel additive or replacement. <it>C. beijerinckii </it>is an attractive microorganism for strain design to improve butanol production because it (i) naturally produces the highest recorded butanol concentrations as a byproduct of fermentation; and (ii) can co-ferment pentose and hexose sugars (the primary products from lignocellulosic hydrolysis). Interrogating <it>C. beijerinckii </it>metabolism from a systems viewpoint using constraint-based modeling allows for simulation of the global effect of genetic modifications.</p> <p>Results</p> <p>We present the first genome-scale metabolic model (<it>i</it>CM925) for <it>C. beijerinckii</it>, containing 925 genes, 938 reactions, and 881 metabolites. To build the model we employed a semi-automated procedure that integrated genome annotation information from KEGG, BioCyc, and The SEED, and utilized computational algorithms with manual curation to improve model completeness. Interestingly, we found only a 34% overlap in reactions collected from the three databases--highlighting the importance of evaluating the predictive accuracy of the resulting genome-scale model. To validate <it>i</it>CM925, we conducted fermentation experiments using the NCIMB 8052 strain, and evaluated the ability of the model to simulate measured substrate uptake and product production rates. Experimentally observed fermentation profiles were found to lie within the solution space of the model; however, under an optimal growth objective, additional constraints were needed to reproduce the observed profiles--suggesting the existence of selective pressures other than optimal growth. Notably, a significantly enriched fraction of actively utilized reactions in simulations--constrained to reflect experimental rates--originated from the set of reactions that overlapped between all three databases (<it>P </it>= 3.52 × 10^-9, Fisher's exact test). Inhibition of the hydrogenase reaction was found to have a strong effect on butanol formation--as experimentally observed.</p> <p>Conclusions</p> <p>Microbial production of butanol by <it>C. beijerinckii </it>offers a promising, sustainable, method for generation of this important chemical and potential biofuel. <it>i</it>CM925 is a predictive model that can accurately reproduce physiological behavior and provide insight into the underlying mechanisms of microbial butanol production. As such, the model will be instrumental in efforts to better understand, and metabolically engineer, this microorganism for improved butanol production.</p

The road to regenerative liver therapies: The triumphs, trials and tribulations

The liver is one of the few organs that possess a high capacity to regenerate after liver failure or liver damage. The parenchymal cells of the liver, hepatocytes, contribute to the majority of the regeneration process. Thus, hepatocyte transplantation presents an alternative method to treating liver damage. However, shortage of hepatocytes and difficulties in maintaining primary hepatocytes still remain key obstacles that researchers must overcome before hepatocyte transplantation can be used in clinical practice. The unique properties of pluripotent stem cells (PSCs) and induced pluripotent stem cells (iPSCs) have provided an alternative approach to generating enough functional hepatocytes for cellular therapy. In this review, we will present a brief overview on the current state of hepatocyte differentiation from PSCs and iPSCs. Studies of liver regenerative processes using different cell sources (adult liver stem cells, hepatoblasts, hepatic progenitor cells, etc.) will be described in detail as well as how this knowledge can be applied towards optimizing culture conditions for the maintenance and differentiation of these cells towards hepatocytes. As the outlook of stem cell-derived therapy begins to look more plausible, researchers will need to address the challenges we must overcome in order to translate stem cell research to clinical applications.status: publishe

Cell Expansian During Directed Differentiation Of Stem Cells Toward The Hepatic Lineage

The differentiation of human pluripotent stem cells toward the hepatocyte lineage can potentially provide an unlimited source of functional hepatocytes for transplantation and extracorporeal bioartificial liver applications. It is anticipated that the quantities of cells needed for these applications will be in the order of 109-1010 cells, because of the size of the liver. An ideal differentiation protocol would be to enable directed differentiation to the hepatocyte lineage with simultaneous cell expansion. We introduced a cell expansion stage after the commitment of human embryonic stem cells to the endodermal lineage, to allow for at least an eightfold increase in cell number, with continuation of cell maturation toward the hepatocyte lineage. The progressive changes in the transcriptome were measured by expression array, and the expression dynamics of certain lineage markers was measured by mass cytometry during the differentiation and expansion process. The findings revealed that while cells were expanding they were also capable of progressing in their differentiation toward the hepatocyte lineage. In addition, our transcriptome, protein and functional studies, including albumin secretion, drug-induced CYP450 expression and urea production, all indicated that the hepatocyte-like cells obtained with or without cell expansion are very similar. This method of simultaneous cell expansion and hepatocyte differentiation should facilitate obtaining large quantities of cells for liver cell applications.status: publishe

Pattern of complementary and alternative medicine use in pediatric oncology patients in a South Indian hospital

Background: Even though the use of complementary and alternative medicines (CAMs) is thought to be more prevalent among pediatric cancer patients, no studies have been reported on a South Indian population. Objectives: This study aimed to investigate the prevalence of the use of CAMs among pediatric cancer patients in a tertiary care South Indian hospital. Patients and methods: Two hundred and seventy-seven pediatric cancer patients who received conventional therapy for the treatment of various types of cancer were enrolled from a pediatric oncology department in South India. Results: Of the enrolled children, 7.58% used CAMs, of which the most commonly used was Ayurveda followed by Siddha. Most of the CAM users were upper middle class. There were no statistically significant differences between the usage of CAMs and baseline characteristics except for socioeconomic status. None of the parents of the enrolled children disclosed their CAM treatment to an oncologist. Conclusion: Parents must be educated about CAM therapy and advised to discuss all treatment-related issues with an oncologist. Pharmacists can play a bridging role between oncologists and parents, and other healthcare professionals should also be familiar with the benefits and disadvantages of using CAM therapy to be able to guide the parents

Biologically Consistent Annotation of Metabolomics Data

Annotation of metabolites remains a major challenge in liquid chromatography–mass spectrometry (LC–MS) based untargeted metabolomics. The current gold standard for metabolite identification is to match the detected feature with an authentic standard analyzed on the same equipment and using the same method as the experimental samples. However, there are substantial practical challenges in applying this approach to large data sets. One widely used annotation approach is to search spectral libraries in reference databases for matching metabolites; however, this approach is limited by the incomplete coverage of these libraries. An alternative computational approach is to match the detected features to candidate chemical structures based on their mass and predicted fragmentation pattern. Unfortunately, both of these approaches can match multiple identities with a single feature. Another issue is that annotations from different tools often disagree. This paper presents a novel LC–MS data annotation method, termed <b>Bio</b>logically <b>C</b>onsistent <b>An</b>notation (BioCAn), that combines the results from database searches and in silico fragmentation analyses and places these results into a relevant biological context for the sample as captured by a metabolic model. We demonstrate the utility of this approach through an analysis of CHO cell samples. The performance of BioCAn is evaluated against several currently available annotation tools, and the accuracy of BioCAn annotations is verified using high-purity analytical standards