SOS genes are rapidly induced while translesion synthesis polymerase activity is temporally regulated.

The DNA damage inducible SOS response in bacteria serves to increase survival of the species at the cost of mutagenesis. The SOS response first initiates error-free repair followed by error-prone repair. Here, we have employed a multi-omics approach to elucidate the temporal coordination of the SOS response. Escherichia coli was grown in batch cultivation in bioreactors to ensure highly controlled conditions, and a low dose of the antibiotic ciprofloxacin was used to activate the SOS response while avoiding extensive cell death. Our results show that expression of genes involved in error-free and error-prone repair were both induced shortly after DNA damage, thus, challenging the established perception that the expression of error-prone repair genes is delayed. By combining transcriptomics and a sub-proteomics approach termed signalomics, we found that the temporal segregation of error-free and error-prone repair is primarily regulated after transcription, supporting the current literature. Furthermore, the heterology index (i.e., the binding affinity of LexA to the SOS box) was correlated to the maximum increase in gene expression and not to the time of induction of SOS genes. Finally, quantification of metabolites revealed increasing pyrimidine pools as a late feature of the SOS response. Our results elucidate how the SOS response is coordinated, showing a rapid transcriptional response and temporal regulation of mutagenesis on the protein and metabolite levels.

Genome-wide association study for Streptococcus iniae in Nile tilapia (Oreochromis niloticus) identifies a significant QTL for disease resistance.

Streptococcus iniae is a problematic gram-positive bacterium negatively affecting Nile tilapia (Oreochromis niloticus), one of the main aquacultural species produced worldwide. The aim of this study was to identify the genetic architecture of survival to S. iniae and identify single nucleotide polymorphism (SNPs) linked to quantitative trait loci (QTL) related to survival to S. iniae challenge. With this purpose, Nile tilapia from the Spring Genetics breeding program were sent to a controlled S. iniae challenge test where phenotypes were scored as dead for fish that died during challenge test and survivors for the fish alive at the termination of the test. Additionally, fin-clip samples from all fish in the test were collected for DNA extraction. Out of 1904 fish in the challenge test, tissue samples of 321 fish were sent for genotyping using double digest restriction site associated DNA sequencing (ddRADseq). After quality control and filtering, 9,085 SNPs were used to perform a genome-wide association study (GWAS). A significant signal in LG8 was observed indicating association with survival to S. iniae challenge, with SNPs explaining from 12% to 26% of the genetic variance. To demonstrate the usefulness of marker assisted selection (MAS) to selectively breed fish for survival to S. iniae, offspring of breeding candidates classified as "resistant" and "susceptible" based on haplotypes of the four most significant markers were sent to a controlled S. iniae challenge test. At the end of the test, the differences in mortality between the two groups were strikingly different with a final cumulative percent mortality of less than 1% and 73% for offspring from "resistant" and "susceptible" parents, respectively. These results demonstrate that MAS for improved resistance to S. iniae is feasible.

Prediction of recurrence from metabolites and expression of TOP2A and EZH2 in prostate cancer patients treated with radiotherapy.

BACKGROUND: The dual upregulation of TOP2A and EZH2 gene expression has been proposed as a biomarker for recurrence in prostate cancer patients to be treated with radical prostatectomy. A low tissue level of the metabolite citrate has additionally been connected to aggressive disease and recurrence in this patient group. However, for radiotherapy prostate cancer patients, few prognostic biomarkers have been suggested. The main aim of this study was to use an integrated tissue analysis to evaluate metabolites and expression of TOP2A and EZH2 as predictors for recurrence among radiotherapy patients. METHODS: From 90 prostate cancer patients (56 received neoadjuvant hormonal treatment), 172 transrectal ultrasound-guided (TRUS) biopsies were collected prior to radiotherapy. Metabolic profiles were acquired from fresh frozen TRUS biopsies using high resolution-magic angle spinning MRS. Histopathology and immunohistochemistry staining for TOP2A and EZH2 were performed on TRUS biopsies containing cancer cells (n = 65) from 46 patients, where 24 of these patients (n = 31 samples) received hormonal treatment. Eleven radical prostatectomy cohorts of a total of 2059 patients were used for validation in a meta-analysis. RESULTS: Among radiotherapy patients with up to 11 years of follow-up, a low level of citrate was found to predict recurrence, p = 0.001 (C-index = 0.74). Citrate had a higher predictive ability compared with individual clinical variables, highlighting its strength as a potential biomarker for recurrence. The dual upregulation of TOP2A and EZH2 was suggested as a biomarker for recurrence, particularly for patients not receiving neoadjuvant hormonal treatment, p = 0.001 (C-index = 0.84). While citrate was a statistically significant biomarker independent of hormonal treatment status, the current study indicated a potential of glutamine, glutamate and choline as biomarkers for recurrence among patients receiving neoadjuvant hormonal treatment, and glucose among patients not receiving neoadjuvant hormonal treatment. CONCLUSION: Using an integrated approach, our study shows the potential of citrate and the dual upregulation of TOP2A and EZH2 as biomarkers for recurrence among radiotherapy patients.

Applying genetic technologies to combat infectious diseases in aquaculture.

Disease and parasitism cause major welfare, environmental and economic concerns for global aquaculture. In this review, we examine the status and potential of technologies that exploit genetic variation in host resistance to tackle this problem. We argue that there is an urgent need to improve understanding of the genetic mechanisms involved, leading to the development of tools that can be applied to boost host resistance and reduce the disease burden. We draw on two pressing global disease problems as case studies-sea lice infestations in salmonids and white spot syndrome in shrimp. We review how the latest genetic technologies can be capitalised upon to determine the mechanisms underlying inter- and intra-species variation in pathogen/parasite resistance, and how the derived knowledge could be applied to boost disease resistance using selective breeding, gene editing and/or with targeted feed treatments and vaccines. Gene editing brings novel opportunities, but also implementation and dissemination challenges, and necessitates new protocols to integrate the technology into aquaculture breeding programmes. There is also an ongoing need to minimise risks of disease agents evolving to overcome genetic improvements to host resistance, and insights from epidemiological and evolutionary models of pathogen infestation in wild and cultured host populations are explored. Ethical issues around the different approaches for achieving genetic resistance are discussed. Application of genetic technologies and approaches has potential to improve fundamental knowledge of mechanisms affecting genetic resistance and provide effective pathways for implementation that could lead to more resistant aquaculture stocks, transforming global aquaculture.

FunHoP analysis reveals upregulation of mitochondrial genes in prostate cancer.

Mitochondrial activity in cancer cells has been central to cancer research since Otto Warburg first published his thesis on the topic in 1956. Although Warburg proposed that oxidative phosphorylation in the tricarboxylic acid (TCA) cycle was perturbed in cancer, later research has shown that oxidative phosphorylation is activated in most cancers, including prostate cancer (PCa). However, more detailed knowledge on mitochondrial metabolism and metabolic pathways in cancers is still lacking. In this study we expand our previously developed method for analyzing functional homologous proteins (FunHoP), which can provide a more detailed view of metabolic pathways. FunHoP uses results from differential expression analysis of RNA-Seq data to improve pathway analysis. By adding information on subcellular localization based on experimental data and computational predictions we can use FunHoP to differentiate between mitochondrial and non-mitochondrial processes in cancerous and normal prostate cell lines. Our results show that mitochondrial pathways are upregulated in PCa and that splitting metabolic pathways into mitochondrial and non-mitochondrial counterparts using FunHoP adds to the interpretation of the metabolic properties of PCa cells.

The genes controlling normal function of citrate and spermine secretion are lost in aggressive prostate cancer and prostate model systems.

High secretion of the metabolites citrate and spermine is a unique hallmark for normal prostate epithelial cells, and is reduced in aggressive prostate cancer. However, the identity of the genes controlling this biological process is mostly unknown. In this study, we have created a gene signature of 150 genes connected to citrate and spermine secretion in the prostate. We have computationally integrated metabolic measurements with multiple transcriptomics datasets from the public domain, including 3826 tissue samples from prostate and prostate cancer. The accuracy of the signature is validated by its unique enrichment in prostate samples and prostate epithelial tissue compartments. The signature highlights genes AZGP1, ANPEP and metallothioneins with zinc-binding properties not previously studied in the prostate, and the expression of these genes are reduced in more aggressive cancer lesions. However, the absence of signature enrichment in common prostate model systems can make it challenging to study these genes mechanistically.

DNA methylation changes in response to neoadjuvant chemotherapy are associated with breast cancer survival.

BACKGROUND: Locally advanced breast cancer is a heterogeneous disease with respect to response to neoadjuvant chemotherapy (NACT) and survival. It is currently not possible to accurately predict who will benefit from the specific types of NACT. DNA methylation is an epigenetic mechanism known to play an important role in regulating gene expression and may serve as a biomarker for treatment response and survival. We investigated the potential role of DNA methylation as a prognostic marker for long-term survival (> 5 years) after NACT in breast cancer. METHODS: DNA methylation profiles of pre-treatment (n = 55) and post-treatment (n = 75) biopsies from 83 women with locally advanced breast cancer were investigated using the Illumina HumanMethylation450 BeadChip. The patients received neoadjuvant treatment with epirubicin and/or paclitaxel. Linear mixed models were used to associate DNA methylation to treatment response and survival based on clinical response to NACT (partial response or stable disease) and 5-year survival, respectively. LASSO regression was performed to identify a risk score based on the statistically significant methylation sites and Kaplan-Meier curve analysis was used to estimate survival probabilities using ten years of survival follow-up data. The risk score developed in our discovery cohort was validated in an independent validation cohort consisting of paired pre-treatment and post-treatment biopsies from 85 women with locally advanced breast cancer. Patients included in the validation cohort were treated with either doxorubicin or 5-FU and mitomycin NACT. RESULTS: DNA methylation patterns changed from before to after NACT in 5-year survivors, while no significant changes were observed in non-survivors or related to treatment response. DNA methylation changes included an overall loss of methylation at CpG islands and gain of methylation in non-CpG islands, and these changes affected genes linked to transcription factor activity, cell adhesion and immune functions. A risk score was developed based on four methylation sites which successfully predicted long-term survival in our cohort (p = 0.0034) and in an independent validation cohort (p = 0.049). CONCLUSION: Our results demonstrate that DNA methylation patterns in breast tumors change in response to NACT. These changes in DNA methylation show potential as prognostic biomarkers for breast cancer survival.

Clonal evolution after treatment pressure in multiple myeloma: heterogenous genomic aberrations and transcriptomic convergence.

We investigated genomic and transcriptomic changes in paired tumor samples of 29 in-house multiple myeloma (MM) patients and 28 patients from the MMRF CoMMpass study before and after treatment. A change in clonal composition was found in 46/57 (82%) of patients, and single-nucleotide variants (SNVs) increased from median 67 to 86. The highest increase in prevalence of genetic aberrations was found in RAS genes (60% to 72%), amp1q21 (18% to 35%), and TP53 (9% to 18%). The SBS-MM1 mutation signature was detected both in patients receiving high and low dose melphalan. A total of 2589 genes were differentially expressed between early and late samples (FDR < 0.05). Gene set enrichment analysis (GSEA) showed increased expression of E2F, MYC, and glycolysis pathways and a decreased expression in TNF-NFkB and TGFbeta pathways in late compared to early stage. Single sample GSEA (ssGSEA) scores of differentially expressed pathways revealed that these changes were most evident in end-stage disease. Increased expression of several potentially targetable genes was found at late disease stages, including cancer-testis antigens, XPO1 and ABC transporters. Our study demonstrates a transcriptomic convergence of pathways supporting increased proliferation and metabolism during disease progression in MM.

PRL-3 induces a positive signaling circuit between glycolysis and activation of STAT1/2.

Multiple myeloma (MM) is an incurable hematologic malignancy resulting from the clonal expansion of plasma cells. MM cells are interacting with components of the bone marrow microenvironment such as cytokines to survive and proliferate. Phosphatase of regenerating liver (PRL)-3, a cytokine-induced oncogenic phosphatase, is highly expressed in myeloma patients and is a mediator of metabolic reprogramming of cancer cells. To find novel pathways and genes regulated by PRL-3, we characterized the global transcriptional response to PRL-3 overexpression in two MM cell lines. We used pathway enrichment analysis to identify pathways regulated by PRL-3. We further confirmed the hits from the enrichment analysis with in vitro experiments and investigated their function. We found that PRL-3 induced expression of genes belonging to the type 1 interferon (IFN-I) signaling pathway due to activation of signal transducer and activator of transcription (STAT) 1 and STAT2. This activation was independent of autocrine IFN-I secretion. The increase in STAT1 and STAT2 did not result in any of the common consequences of increased IFN-I or STAT1 signaling in cancer. Knockdown of STAT1/2 did not affect the viability of the cells, but decreased PRL-3-induced glycolysis. Interestingly, glucose metabolism contributed to the activation of STAT1 and STAT2 and expression of IFN-I-stimulated genes in PRL-3-overexpressing cells. In summary, we describe a novel signaling circuit where the key IFN-I-activated transcription factors STAT1 and STAT2 are important drivers of the increase in glycolysis induced by PRL-3. Subsequently, increased glycolysis regulates the IFN-I-stimulated genes by augmenting the activation of STAT1/2.

FunHoP: Enhanced Visualization and Analysis of Functionally Homologous Proteins in Complex Metabolic Networks.

Cytoscape is often used for visualization and analysis of metabolic pathways. For example, based on KEGG data, a reader for KEGG Markup Language (KGML) is used to load files into Cytoscape. However, although multiple genes can be responsible for the same reaction, the KGML-reader KEGGScape only presents the first listed gene in a network node for a given reaction. This can lead to incorrect interpretations of the pathways. Our new method, FunHoP, shows all possible genes in each node, making the pathways more complete. FunHoP collapses all genes in a node into one measurement using read counts from RNA-seq. Assuming that activity for an enzymatic reaction mainly depends upon the gene with the highest number of reads, and weighting the reads on gene length and ratio, a new expression value is calculated for the node as a whole. Differential expression at node level is then applied to the networks. Using prostate cancer as model, we integrate RNA-seq data from two patient cohorts with metabolism data from literature. Here we show that FunHoP gives more consistent pathways that are easier to interpret biologically. Code and documentation for running FunHoP can be found at https://github.com/kjerstirise/FunHoP.

Spatial differentiation of metabolism in prostate cancer tissue by MALDI-TOF MSI.

BACKGROUND: Prostate cancer tissues are inherently heterogeneous, which presents a challenge for metabolic profiling using traditional bulk analysis methods that produce an averaged profile. The aim of this study was therefore to spatially detect metabolites and lipids on prostate tissue sections by using mass spectrometry imaging (MSI), a method that facilitates molecular imaging of heterogeneous tissue sections, which can subsequently be related to the histology of the same section. METHODS: Here, we simultaneously obtained metabolic and lipidomic profiles in different prostate tissue types using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MSI. Both positive and negative ion mode were applied to analyze consecutive sections from 45 fresh-frozen human prostate tissue samples (N = 15 patients). Mass identification was performed with tandem MS. RESULTS: Pairwise comparisons of cancer, non-cancer epithelium, and stroma revealed several metabolic differences between the tissue types. We detected increased levels of metabolites crucial for lipid metabolism in cancer, including metabolites involved in the carnitine shuttle, which facilitates fatty acid oxidation, and building blocks needed for lipid synthesis. Metabolites associated with healthy prostate functions, including citrate, aspartate, zinc, and spermine had lower levels in cancer compared to non-cancer epithelium. Profiling of stroma revealed higher levels of important energy metabolites, such as ADP, ATP, and glucose, and higher levels of the antioxidant taurine compared to cancer and non-cancer epithelium. CONCLUSIONS: This study shows that specific tissue compartments within prostate cancer samples have distinct metabolic profiles and pinpoint the advantage of methodology providing spatial information compared to bulk analysis. We identified several differential metabolites and lipids that have potential to be developed further as diagnostic and prognostic biomarkers for prostate cancer. Spatial and rapid detection of cancer-related analytes showcases MALDI-TOF MSI as a promising and innovative diagnostic tool for the clinic.

Genomic selection for white spot syndrome virus resistance in whiteleg shrimp boosts survival under an experimental challenge test.

White spot syndrome virus (WSSV) causes major worldwide losses in shrimp aquaculture. The development of resistant shrimp populations is an attractive option for management of the disease. However, heritability for WSSV resistance is generally low and genetic improvement by conventional selection has been slow. This study was designed to determine the power and accuracy of genomic selection to improve WSSV resistance in Litopenaeus vannamei. Shrimp were experimentally challenged with WSSV and resistance was evaluated as dead or alive (DOA) 23 days after infestation. All shrimp in the challenge test were genotyped for 18,643 single nucleotide polymorphisms. Breeding candidates (G0) were ranked on genomic breeding values for WSSV resistance. Two G1 populations were produced, one from G0 breeders with high and the other with low estimated breeding values. A third population was produced from "random" mating of parent stock. The average survival was 25% in the low, 38% in the random and 51% in the high-genomic breeding value groups. Genomic heritability for DOA (0.41 in G1) was high for this type of trait. The realised genetic gain and high heritability clearly demonstrates large potential for further genetic improvement of WSSV resistance in the evaluated L. vannamei population using genomic selection.

LSD1 represses a neonatal/reparative gene program in adult intestinal epithelium.

Intestinal epithelial homeostasis is maintained by adult intestinal stem cells, which, alongside Paneth cells, appear after birth in the neonatal period. We aimed to identify regulators of neonatal intestinal epithelial development by testing a small library of epigenetic modifier inhibitors in Paneth cell-skewed organoid cultures. We found that lysine-specific demethylase 1A (Kdm1a/Lsd1) is absolutely required for Paneth cell differentiation. Lsd1-deficient crypts, devoid of Paneth cells, are still able to form organoids without a requirement of exogenous or endogenous Wnt. Mechanistically, we find that LSD1 enzymatically represses genes that are normally expressed only in fetal and neonatal epithelium. This gene profile is similar to what is seen in repairing epithelium, and we find that Lsd1-deficient epithelium has superior regenerative capacities after irradiation injury. In summary, we found an important regulator of neonatal intestinal development and identified a druggable target to reprogram intestinal epithelium toward a reparative state.

Differential Effects of Dietary Supplementation of Krill Meal, Soybean Meal, Butyrate, and Bactocell® on the Gene Expression of Atlantic Salmon Head Kidney.

The head kidney is a key organ that plays a fundamental role in the regulation of the fish immune response and in the maintenance of endocrine homeostasis. Previous studies indicate that the supplementation of exogenous dietary components, such as krill meal (KM), soybean meal (SM), Bactocell® (BA), and butyrate (BU), can have a significant effect on the immune function of the head kidney. The aim of this study was to investigate the differential effect of these four dietary ingredients on the transcriptional profiles of the head kidney of the Atlantic salmon. This study revealed that just a small number of genes were responsive to the feeding regime after a long-term (12 weeks) treatment, and evidenced that the most significant alterations, both in terms of the number of affected genes and magnitude of changes in gene expression, were detectable in the BU- and KM-fed groups compared with controls, while the SM diet had a nearly negligible effect, and BA had no significant effects at all. Most of the differentially expressed genes were involved in the immune response and, in line with data previously obtained from pyloric caeca, major components of the complement system were significantly affected. These alterations were accompanied by an increase in the density of melanomacrophage centers in the KM- and SM-fed group and their reduction in the BU-fed group. While three types of dietary supplements (BU, KM, and SM) were able to produce a significant modulation of some molecular players of the immune system, the butyrate-rich diet was revealed as the one with the most relevant immune-stimulating properties in the head kidney. These preliminary results suggest that further investigations should be aimed towards the elucidation of the potential beneficial effects of butyrate and krill meal supplementation on farmed salmon health and growth performance.

DNA hypermethylation associated with upregulated gene expression in prostate cancer demonstrates the diversity of epigenetic regulation.

BACKGROUND: Prostate cancer (PCa) has the highest incidence rates of cancers in men in western countries. Unlike several other types of cancer, PCa has few genetic drivers, which has led researchers to look for additional epigenetic and transcriptomic contributors to PCa development and progression. Especially datasets on DNA methylation, the most commonly studied epigenetic marker, have recently been measured and analysed in several PCa patient cohorts. DNA methylation is most commonly associated with downregulation of gene expression. However, positive associations of DNA methylation to gene expression have also been reported, suggesting a more diverse mechanism of epigenetic regulation. Such additional complexity could have important implications for understanding prostate cancer development but has not been studied at a genome-wide scale. RESULTS: In this study, we have compared three sets of genome-wide single-site DNA methylation data from 870 PCa and normal tissue samples with multi-cohort gene expression data from 1117 samples, including 532 samples where DNA methylation and gene expression have been measured on the exact same samples. Genes were classified according to their corresponding methylation and expression profiles. A large group of hypermethylated genes was robustly associated with increased gene expression (UPUP group) in all three methylation datasets. These genes demonstrated distinct patterns of correlation between DNA methylation and gene expression compared to the genes showing the canonical negative association between methylation and expression (UPDOWN group). This indicates a more diversified role of DNA methylation in regulating gene expression than previously appreciated. Moreover, UPUP and UPDOWN genes were associated with different compartments - UPUP genes were related to the structures in nucleus, while UPDOWN genes were linked to extracellular features. CONCLUSION: We identified a robust association between hypermethylation and upregulation of gene expression when comparing samples from prostate cancer and normal tissue. These results challenge the classical view where DNA methylation is always associated with suppression of gene expression, which underlines the importance of considering corresponding expression data when assessing the downstream regulatory effect of DNA methylation.

MACPET: model-based analysis for ChIA-PET.

We present model-based analysis for ChIA-PET (MACPET), which analyzes paired-end read sequences provided by ChIA-PET for finding binding sites of a protein of interest. MACPET uses information from both tags of each PET and searches for binding sites in a two-dimensional space, while taking into account different noise levels in different genomic regions. MACPET shows favorable results compared with MACS in terms of motif occurrence and spatial resolution. Furthermore, significant binding sites discovered by MACPET are involved in a higher number of significant three-dimensional interactions than those discovered by MACS. MACPET is freely available on Bioconductor. ChIA-PET; MACPET; Model-based clustering; Paired-end tags; Peak-calling algorithm.

DNA methylation data by sequencing: experimental approaches and recommendations for tools and pipelines for data analysis.

Sequencing technologies have changed not only our approaches to classical genetics, but also the field of epigenetics. Specific methods allow scientists to identify novel genome-wide epigenetic patterns of DNA methylation down to single-nucleotide resolution. DNA methylation is the most researched epigenetic mark involved in various processes in the human cell, including gene regulation and development of diseases, such as cancer. Increasing numbers of DNA methylation sequencing datasets from human genome are produced using various platforms-from methylated DNA precipitation to the whole genome bisulfite sequencing. Many of those datasets are fully accessible for repeated analyses. Sequencing experiments have become routine in laboratories around the world, while analysis of outcoming data is still a challenge among the majority of scientists, since in many cases it requires advanced computational skills. Even though various tools are being created and published, guidelines for their selection are often not clear, especially to non-bioinformaticians with limited experience in computational analyses. Separate tools are often used for individual steps in the analysis, and these can be challenging to manage and integrate. However, in some instances, tools are combined into pipelines that are capable to complete all the essential steps to achieve the result. In the case of DNA methylation sequencing analysis, the goal of such pipeline is to map sequencing reads, calculate methylation levels, and distinguish differentially methylated positions and/or regions. The objective of this review is to describe basic principles and steps in the analysis of DNA methylation sequencing data that in particular have been used for mammalian genomes, and more importantly to present and discuss the most pronounced computational pipelines that can be used to analyze such data. We aim to provide a good starting point for scientists with limited experience in computational analyses of DNA methylation and hydroxymethylation data, and recommend a few tools that are powerful, but still easy enough to use for their own data analysis.

Selection response for Streptococcus agalactiae resistance in Nile tilapia Oreochromis niloticus.

The potential of selection to improve resistance to streptococcosis was evaluated in a commercial population of Nile tilapia in Thailand. The base generation (G0) consisted of offspring from 98 sires and 149 dams using a partly nested design. At 60 days post-hatch, 30 fish from each family were injected intraperitoneally with a Streptococcosis agalactiae solution (1 × 109  CFU/ml) and evaluated for 14 days. Disease resistance was recorded as the number of days from challenge until death (DD) and as a binary (BIN) trait (dead/alive) on day 14. Three models were used for genetic analyses: Cox frailty model for DD; animal model for DD; and animal model for BIN. Age at challenge was fitted as a covariate and contemporary group as fixed or random effect, depending on the model. Fish from the 18 most resistant families were selected to produce the first generation (G1). Heritability estimates for G0 were 0.22, 0.14 ± 0.02 and 0.11 ± 0.02 for the Cox, linear DD and linear BIN models, respectively. Selection response indicated that the risk of death decreased to 54%, survival time increased to 3.4 days and survival rate increased to 21%. These results suggest that genetic improvement is possible for this population.

Glutamine to proline conversion is associated with response to glutaminase inhibition in breast cancer.

INTRODUCTION: Glutaminase inhibitors target cancer cells by blocking the conversion of glutamine to glutamate, thereby potentially interfering with anaplerosis and synthesis of amino acids and glutathione. The drug CB-839 has shown promising effects in preclinical experiments and is currently undergoing clinical trials in several human malignancies, including triple-negative breast cancer (TNBC). However, response to glutaminase inhibitors is variable and there is a need for identification of predictive response biomarkers. The aim of this study was to determine how glutamine is utilized in two patient-derived xenograft (PDX) models of breast cancer representing luminal-like/ER+ (MAS98.06) and basal-like/triple-negative (MAS98.12) breast cancer and to explore the metabolic effects of CB-839 treatment. EXPERIMENTAL: MAS98.06 and MAS98.12 PDX mice received CB-839 (200 mg/kg) or drug vehicle two times daily p.o. for up to 28 days (n = 5 per group), and the effect on tumor growth was evaluated. Expression of 60 genes and seven glutaminolysis key enzymes were determined using gene expression microarray analysis and immunohistochemistry (IHC), respectively, in untreated tumors. Uptake and conversion of glutamine were determined in the PDX models using HR MAS MRS after i.v. infusion of [5-13C] glutamine when the models had received CB-839 (200 mg/kg) or vehicle for 2 days (n = 5 per group). RESULTS: Tumor growth measurements showed that CB-839 significantly inhibited tumor growth in MAS98.06 tumors, but not in MAS98.12 tumors. Gene expression and IHC analysis indicated a higher proline synthesis from glutamine in untreated MAS98.06 tumors. This was confirmed by HR MAS MRS of untreated tumors demonstrating that MAS98.06 used glutamine to produce proline, glutamate, and alanine, and MAS98.12 to produce glutamate and lactate. In both models, treatment with CB-839 resulted in accumulation of glutamine. In addition, CB-839 caused depletion of alanine, proline, and glutamate ([1-13C] glutamate) in the MAS98.06 model. CONCLUSION: Our findings indicate that TNBCs may not be universally sensitive to glutaminase inhibitors. The major difference in the metabolic fate of glutamine between responding MAS98.06 xenografts and non-responding MAS98.12 xenografts is the utilization of glutamine for production of proline. We therefore suggest that addiction to proline synthesis from glutamine is associated with response to CB-839 in breast cancer. The effect of glutaminase inhibition in two breast cancer patient-derived xenograft (PDX) models. 13C HR MAS MRS analysis of tumor tissue from CB-839-treated and untreated models receiving 13C-labeled glutamine ([5-13C] Gln) shows that the glutaminase inhibitor CB-839 is causing an accumulation of glutamine (arrow up) in two PDX models representing luminal-like breast cancer (MAS98.06) and basal-like breast cancer (MAS98.12). In MAS98.06 tumors, CB-839 is in addition causing depletion of proline ([5-13C] Pro), alanine ([1-13C] Ala), and glutamate ([1-13C] Glu), which could explain why CB-839 causes tumor growth inhibition in MAS98.06 tumors, but not in MAS98.12 tumors.

Norwegian e-Infrastructure for Life Sciences (NeLS).

The Norwegian e-Infrastructure for Life Sciences (NeLS) has been developed by ELIXIR Norway to provide its users with a system enabling data storage, sharing, and analysis in a project-oriented fashion. The system is available through easy-to-use web interfaces, including the Galaxy workbench for data analysis and workflow execution. Users confident with a command-line interface and programming may also access it through Secure Shell (SSH) and application programming interfaces (APIs).  NeLS has been in production since 2015, with training and support provided by the help desk of ELIXIR Norway. Through collaboration with NorSeq, the national consortium for high-throughput sequencing, an integrated service is offered so that sequencing data generated in a research project is provided to the involved researchers through NeLS. Sensitive data, such as individual genomic sequencing data, are handled using the TSD (Services for Sensitive Data) platform provided by Sigma2 and the University of Oslo. NeLS integrates national e-infrastructure storage and computing resources, and is also integrated with the SEEK platform in order to store large data files produced by experiments described in SEEK.   In this article, we outline the architecture of NeLS and discuss possible directions for further development.