Epigenetic changes in human model KMT2A leukemias highlight early events during leukemogenesis.

Chromosomal translocations involving KMT2A gene are one of the most common genetic alterations found in pediatric acute myeloid leukemias (AML) although the molecular mechanisms that initiate the disease remain incompletely defined. To elucidate these initiating events we have used a human model system of AML driven by the KMT2A-MLLT3 (KM3) fusion. More specifically, we investigated changes in DNA methylation, histone modifications, and chromatin accessibility at each stage of our model system and correlated these with expression changes. We observe the development of a profound hypomethylation phenotype in the early stages of leukemic transformation after KM3 addition along with loss of expression of stem cell associated genes along with skewed expression in other genes such as S100A8/9 implicated in leukemogenesis. In addition, early increases in the expression of the lysine demethylase KDM4B was functionally linked to these expression changes as well as other key transcription factors. Remarkably, our ATAC-seq data showed that there were relatively few leukemiaspecific changes and the vast majority corresponded to open chromatin regions and transcription factor clusters previously observed in other cell types. Integration of the gene expression and epigenetic changes revealed the adenylate cyclase gene ADCY9 as an essential gene in KM3-AML, and suggest the potential for autocrine signalling through the chemokine receptor CCR1 and CCL23 ligand. Together, our results suggest that KM3 induces subtle changes in the epigenome while co-opting the normal transcriptional machinery to drive leukemogenesis.

Whole genome and transcriptome analysis of a novel AML cell line with a normal karyotype.

Acute myeloid leukemia (AML) occurs when hematopoietic progenitor cells acquire genetic defects blocking the regulation of normal growth and differentiation. Although recurrent translocations have been identified in AML, almost half of adult AML patients present with a normal karyotype (NK-AML). While cell line models exist to study AML, they frequently have abnormal/unstable karyotypes, while primary cells from NK-AML patients are difficult to maintain in vitro. Here we provide a thorough molecular characterization of a recently established cell line, CG-SH, which has normal cytogenetics, representing a useful new model for NK-AML. Using high-throughput DNA sequencing, we first defined the genetic background of this cell line. In addition to identifying potentially deleterious SNVs in genes relevant to AML, we also found insertions in both GATA2 and EZH2, two genes previously linked to AML. We further characterized the growth of this model system in vitro with a cytokine mix that promotes faster cell growth. We assessed gene expression changes after the addition of cytokines to the culture media and found differential expression in genes implicated in proliferation, apoptosis and differentiation. Our results provide a detailed molecular characterization of genetic defects in this cell line derived from an NK-AML patient.

Harnessing virtual machines to simplify next-generation DNA sequencing analysis.

MOTIVATION: The growth of next-generation sequencing (NGS) has not only dramatically accelerated the pace of research in the field of genomics, but it has also opened the door to personalized medicine and diagnostics. The resulting flood of data has led to the rapid development of large numbers of bioinformatic tools for data analysis, creating a challenging situation for researchers when choosing and configuring a variety of software for their analysis, and for other researchers trying to replicate their analysis. As NGS technology continues to expand from the research environment into clinical laboratories, the challenges associated with data analysis have the potential to slow the adoption of this technology. RESULTS: Here we discuss the potential of virtual machines (VMs) to be used as a method for sharing entire installations of NGS software (bioinformatic 'pipelines'). VMs are created by programs designed to allow multiple operating systems to co-exist on a single physical machine, and they can be made following the object-oriented paradigm of encapsulating data and methods together. This allows NGS data to be distributed within a VM, along with the pre-configured software for its analysis. Although VMs have historically suffered from poor performance relative to native operating systems, we present benchmarking results demonstrating that this reduced performance can now be minimized. We further discuss the many potential benefits of VMs as a solution for NGS analysis and describe several published examples. Lastly, we consider the benefits of VMs in facilitating the introduction of NGS technology into the clinical environment. CONTACT: brian.wilhelm@umontreal.ca.

A comparative transcriptomic, fluxomic and metabolomic analysis of the response of Saccharomyces cerevisiae to increases in NADPH oxidation.

BACKGROUND: Redox homeostasis is essential to sustain metabolism and growth. We recently reported that yeast cells meet a gradual increase in imposed NADPH demand by progressively increasing flux through the pentose phosphate (PP) and acetate pathways and by exchanging NADH for NADPH in the cytosol, via a transhydrogenase-like cycle. Here, we studied the mechanisms underlying this metabolic response, through a combination of gene expression profiling and analyses of extracellular and intracellular metabolites and 13 C-flux analysis. RESULTS: NADPH oxidation was increased by reducing acetoin to 2,3-butanediol in a strain overexpressing an engineered NADPH-dependent butanediol dehydrogenase cultured in the presence of acetoin. An increase in NADPH demand to 22 times the anabolic requirement for NADPH was accompanied by the intracellular accumulation of PP pathway metabolites consistent with an increase in flux through this pathway. Increases in NADPH demand were accompanied by the successive induction of several genes of the PP pathway. NADPH-consuming pathways, such as amino-acid biosynthesis, were upregulated as an indirect effect of the decrease in NADPH availability. Metabolomic analysis showed that the most extreme modification of NADPH demand resulted in an energetic problem. Our results also highlight the influence of redox status on aroma production. CONCLUSIONS: Combined 13 C-flux, intracellular metabolite levels and microarrays analyses revealed that NADPH homeostasis, in response to a progressive increase in NADPH demand, was achieved by the regulation, at several levels, of the PP pathway. This pathway is principally under metabolic control, but regulation of the transcription of PP pathway genes can exert a stronger effect, by redirecting larger amounts of carbon to this pathway to satisfy the demand for NADPH. No coordinated response of genes involved in NADPH metabolism was observed, suggesting that yeast has no system for sensing NADPH/NADP+ ratio. Instead, the induction of NADPH-consuming amino-acid pathways in conditions of NADPH limitation may indirectly trigger the transcription of a set of PP pathway genes.

A constraint-based model analysis of the metabolic consequences of increased NADPH oxidation in Saccharomyces cerevisiae.

Controlling the amounts of redox cofactors to manipulate metabolic fluxes is emerging as a useful approach to optimizing byproduct yields in yeast biotechnological processes. Redox cofactors are extensively interconnected metabolites, so predicting metabolite patterns is challenging and requires in-depth knowledge of how the metabolic network responds to a redox perturbation. Our aim was to analyze comprehensively the metabolic consequences of increased cytosolic NADPH oxidation during yeast fermentation. Using a genetic device based on the overexpression of a modified 2,3-butanediol dehydrogenase catalyzing the NADPH-dependent reduction of acetoin into 2,3-butanediol, we increased the NADPH demand to between 8 and 40-fold the anabolic demand. We developed (i) a dedicated constraint-based model of yeast fermentation and (ii) a constraint-based modeling method based on the dynamical analysis of mass distribution to quantify the in vivo contribution of pathways producing NADPH to the maintenance of redox homeostasis. We report that yeast responds to NADPH oxidation through a gradual increase in the flux through the PP and acetate pathways, providing 80% and 20% of the NADPH demand, respectively. However, for the highest NADPH demand, the model reveals a saturation of the PP pathway and predicts an exchange between NADH and NADPH in the cytosol that may be mediated by the glycerol-DHA futile cycle. We also reveal the contribution of mitochondrial shuttles, resulting in a net production of NADH in the cytosol, to fine-tune the NADH/NAD(+) balance. This systems level study helps elucidate the physiological adaptation of yeast to NADPH perturbation. Our findings emphasize the robustness of yeast to alterations in NADPH metabolism and highlight the role of the glycerol-DHA cycle as a redox valve, providing additional NADPH from NADH under conditions of very high demand.

Comparative analysis of missing value imputation methods to improve clustering and interpretation of microarray experiments.

BACKGROUND: Microarray technologies produced large amount of data. In a previous study, we have shown the interest of k-Nearest Neighbour approach for restoring the missing gene expression values, and its positive impact of the gene clustering by hierarchical algorithm. Since, numerous replacement methods have been proposed to impute missing values (MVs) for microarray data. In this study, we have evaluated twelve different usable methods, and their influence on the quality of gene clustering. Interestingly we have used several datasets, both kinetic and non kinetic experiments from yeast and human. RESULTS: We underline the excellent efficiency of approaches proposed and implemented by Bo and co-workers and especially one based on expected maximization (EM_array). These improvements have been observed also on the imputation of extreme values, the most difficult predictable values. We showed that the imputed MVs have still important effects on the stability of the gene clusters. The improvement on the clustering obtained by hierarchical clustering remains limited and, not sufficient to restore completely the correct gene associations. However, a common tendency can be found between the quality of the imputation method and the gene cluster stability. Even if the comparison between clustering algorithms is a complex task, we observed that k-means approach is more efficient to conserve gene associations. CONCLUSIONS: More than 6.000.000 independent simulations have assessed the quality of 12 imputation methods on five very different biological datasets. Important improvements have so been done since our last study. The EM_array approach constitutes one efficient method for restoring the missing expression gene values, with a lower estimation error level. Nonetheless, the presence of MVs even at a low rate is a major factor of gene cluster instability. Our study highlights the need for a systematic assessment of imputation methods and so of dedicated benchmarks. A noticeable point is the specific influence of some biological dataset.