Bernhard M. Schuldt

A bioinformatic assay for pluripotency in human cells.

Pluripotent stem cells (PSCs) are defined by their potential to generate all cell types of an organism. The standard assay for pluripotency of mouse PSCs is cell transmission through the germline, but for human PSCs researchers depend on indirect methods such as differentiation into teratomas in immunodeficient mice. Here we report PluriTest, a robust open-access bioinformatic assay of pluripotency in human cells based on their gene expression profiles.

iPSCORE: A Resource of 222 iPSC Lines Enabling Functional Characterization of Genetic Variation across a Variety of Cell Types.

Summary Large-scale collections of induced pluripotent stem cells (iPSCs) could serve as powerful model systems for examining how genetic variation affects biology and disease. Here we describe the iPSCORE resource: a collection of systematically derived and characterized iPSC lines from 222 ethnically diverse individuals that allows for both familial and association-based genetic studies. iPSCORE lines are pluripotent with high genomic integrity (no or low numbers of somatic copy-number variants) as determined using high-throughput RNA-sequencing and genotyping arrays, respectively. Using iPSCs from a family of individuals, we show that iPSC-derived cardiomyocytes demonstrate gene expression patterns that cluster by genetic background, and can be used to examine variants associated with physiological and disease phenotypes. The iPSCORE collection contains representative individuals for risk and non-risk alleles for 95% of SNPs associated with human phenotypes through genome-wide association studies. Our study demonstrates the utility of iPSCORE for examining how genetic variants influence molecular and physiological traits in iPSCs and derived cell lines.

A guide to stem cell identification: progress and challenges in system-wide predictive testing with complex biomarkers.

We have developed a first generation tool for the unbiased identification and characterization of human pluripotent stem cells, termed PluriTest. This assay utilizes all the information contained on a microarray and abandons the conventional stem cell marker concept. Stem cells are defined by the ability to replenish themselves and to differentiate into more mature cell types. As differentiation potential is a property that cannot be directly proven in the stem cell state, biologists have to rely on correlative measurements in stem cells associated with differentiation potential. Unfortunately, most, if not all, of those markers are only valid within narrow limits of specific experimental systems. Microarray technologies and recently next‐generation sequencing have revolutionized how cellular phenotypes can be characterized on a systems‐wide level. Here we discuss the challenges PluriTest and similar global assays need to address to fulfill their enormous potential for industrial, diagnostic and therapeutic applications.

PhysioSpace: Relating Gene Expression Experiments from Heterogeneous Sources Using Shared Physiological Processes

Relating expression signatures from different sources such as cell lines, in vitro cultures from primary cells and biopsy material is an important task in drug development and translational medicine as well as for tracking of cell fate and disease progression. Especially the comparison of large scale gene expression changes to tissue or cell type specific signatures is of high interest for the tracking of cell fate in (trans-) differentiation experiments and for cancer research, which increasingly focuses on shared processes and the involvement of the microenvironment. These signature relation approaches require robust statistical methods to account for the high biological heterogeneity in clinical data and must cope with small sample sizes in lab experiments and common patterns of co-expression in ubiquitous cellular processes. We describe a novel method, called PhysioSpace, to position dynamics of time series data derived from cellular differentiation and disease progression in a genome-wide expression space. The PhysioSpace is defined by a compendium of publicly available gene expression signatures representing a large set of biological phenotypes. The mapping of gene expression changes onto the PhysioSpace leads to a robust ranking of physiologically relevant signatures, as rigorously evaluated via sample-label permutations. A spherical transformation of the data improves the performance, leading to stable results even in case of small sample sizes. Using PhysioSpace with clinical cancer datasets reveals that such data exhibits large heterogeneity in the number of significant signature associations. This behavior was closely associated with the classification endpoint and cancer type under consideration, indicating shared biological functionalities in disease associated processes. Even though the time series data of cell line differentiation exhibited responses in larger clusters covering several biologically related patterns, top scoring patterns were highly consistent with a priory known biological information and separated from the rest of response patterns.

Power-laws and the use of pluripotent stem cell lines

It is widely accepted that the (now reversed) Bush administration’s decision to restrict federal funding for human embryonic stem cell (hESC) research to a few “eligible” hESC lines is responsible for the sustained preferential use of a small subset of hESC lines (principally the H1 and H9 lines) in basic and preclinical research. Yet, international hESC usage patterns, in both permissive and restrictive political environments, do not correlate with a specific type of stem cell policy. Here we conducted a descriptive analysis of hESC line usage and compared the ability of policy-driven processes and collaborative processes inherent to biomedical research to recapitulate global hESC usage patterns. We find that current global hESC usage can be modelled as a cumulative advantage process, independent of restrictive or permissive policy influence, suggesting a primarily innovation-driven (rather than policy-driven) mechanism underlying human pluripotent stem cell usage in preclinical research.

Assessment of Established Techniques to Determine Developmental and Malignant Potential of Human Pluripotent Stem Cells

The International Stem Cell Initiative compared several commonly used approaches to assess human pluripotent stem cells (PSC). PluriTest predicts pluripotency through bioinformatic analysis of the transcriptomes of undifferentiated cells, whereas, embryoid body (EB) formation in vitro and teratoma formation in vivo provide direct tests of differentiation. Here we report that EB assays, analyzed after differentiation under neutral conditions and under conditions promoting differentiation to ectoderm, mesoderm, or endoderm lineages, are sufficient to assess the differentiation potential of PSCs. However, teratoma analysis by histologic examination and by TeratoScore, which estimates differential gene expression in each tumor, not only measures differentiation but also allows insight into a PSC’s malignant potential. Each of the assays can be used to predict pluripotent differentiation potential but, at this stage of assay development, only the teratoma assay provides an assessment of pluripotency and malignant potential, which are both relevant to the pre-clinical safety assessment of PSCs.The International Stem Cell Initiative tests methods in a multisite study to detect pluripotency and teratoma formation (PluriTest, Embryoid Body and Teratoma methods) in human pluripotent stem cells. Here, the authors provide guidelines for their application: only the teratoma assay offers evidence of malignant potential.The International Stem Cell Initiative compared several commonly used approaches to assess human pluripotent stem cells (PSC). PluriTest predicts pluripotency through bioinformatic analysis of the transcriptomes of undifferentiated cells, whereas, embryoid body (EB) formation in vitro and teratoma formation in vivo provide direct tests of differentiation. Here we report that EB assays, analyzed after differentiation under neutral conditions and under conditions promoting differentiation to ectoderm, mesoderm, or endoderm lineages, are sufficient to assess the differentiation potential of PSCs. However, teratoma analysis by histologic examination and by TeratoScore, which estimates differential gene expression in each tumor, not only measures differentiation but also allows insight into a PSC’s malignant potential. Each of the assays can be used to predict pluripotent differentiation potential but, at this stage of assay development, only the teratoma assay provides an assessment of pluripotency and malignant potential, which are both relevant to the pre-clinical safety assessment of PSCs. The International Stem Cell Initiative tests methods in a multisite study to detect pluripotency and teratoma formation (PluriTest, Embryoid Body and Teratoma methods) in human pluripotent stem cells. Here, the authors provide guidelines for their application: only the teratoma assay offers evidence of malignant potential.

Basic Approaches to Gene Expression Analysis of Stem Cells by Microarrays

This chapter covers gene expression analysis by microarray to study and characterize stem cells. In a case-study scenario, we describe basic bioinformatic methodologies used to answer common questions in microarray experiments involving one or more stem cell populations. Service providers or departmental core labs usually carry out sample preparation, hybridization, and scanning of microarrays. Therefore, in this chapter, we focus on the state-of-the-art data analysis that avoids common pitfalls and introduces the reader to important controls that yield robust biologically relevant results. We describe evaluation of differentially expressed genes, clustering methods, gene-set enrichment analysis, and gene network discovery methods that can be used to formulate meaningful biological insights as well as suggest new wet lab experiments.

Utilizing Regulatory Networks for Pluripotency Assessment in Stem Cells

Pluripotency is a term in cell biology describing a unique state present in distinct stem cell lines, which were either established from the inner cell mass of the mammalian embryo or derived from somatic cells that have been reprogrammed to induced pluripotent stem cells. Pluripotent stem cells are continuously self-renewing, and their differentiation capacity enables them to develop into all derivatives of the three germ layers of a gastrulating embryo (endoderm, ectoderm, mesoderm). Both human embryonic stem cells (hESC) and human-induced pluripotent stem cells (hiPSC) are virtually indistinguishable, at least based on their global RNA expression patterns. Yet, after these in vitro cell cultures have been generated, the cell lines’ pluripotent properties may change considerably on the genetic and/or epigenetic level as a consequence of long-term propagation. Among other unphysiological changes, cell lines might acquire aneuploidies, loose physiological imprinting marks, or develop differentiation biases favoring one cell lineage over the other. As a result, stem cell researchers have to continuously monitor each stem cell line’s integrity, transcriptional profile, and functional properties. Regulatory transcription factors, protein-protein interactions, and signaling networks govern the pluripotent state. As a consequence, emerging small- and large-scale perturbations to these gene regulatory networks mediate the outlined unfavorable changes to the pluripotent phenotype. Here, we describe a reliable bioinformatic framework called PluriTest for confirmation and assessment of pluripotency as an animal-free, fast, and inexpensive way based on genome-wide transcriptional RNA profiles from microarrays. Additionally, we discuss future developments using RNA expression profiling for pluripotency assessment.

What Can Networks Do for You

This chapter aims at demonstrating the utility of network approaches in classification and outlier detection tasks in the context of stem cell biology and related fields. With modern high-through-put methods it has now become easier and cheaper to accurately measure thousands of features on a genome-wide scale than to define a low number of markers that can be tested, for example with low throughput RT-PCR assays. Typically the number of potential markers exceeds the number of experiments by several orders of magnitude. Therefore the significance – let alone mechanistic involvement – of each possible feature cannot be guaranteed from the data alone. Fortunately, easy-to-use implementations of many powerful network based algorithms have been made freely available so one can readily employ these advanced algorithms on new high-content datasets.

PluriTest: molecular diagnostic assay for pluripotency in human stem cells

To provide an alternative to the teratoma assay for testing pluripotency in human stem cells, we developed a bioinformatic alternative assay called PluriTest. PluriTest assesses a cell’s pluripotency based on global gene expression data as determined by microarray analysis. As a web-based assay, PluriTest provides easy access for stem cell researchers to a comprehensive alternative to the teratoma assay. PluriTest can be used as a standard measure of pluripotency as well as a resource providing information beyond what the teratoma assay reports. In this chapter we will outline how to use the PluriTest as a routine measurement of pluripotency. Furthermore we will provide some explanations concerning the biological and computational principles underlying PluriTest and provide some context-specific interpretations of PluriTest results.