The impact of expression vector position on transgene transcription allows for rational expression vector design in a targeted integration system

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Population dynamics in cloned CHO cell lines

The inherent nature of cloned CHO cell lines includes the presence of genetic and phenotypic drift that leads to heterogeneous populations. The genetic heterogeneity exhibited by these cells can be exploited to understand the population dynamics of cloned cell lines. One way to track heterogeneity within populations is by utilizing genetic sequence variants (SVs) as biomarkers for distinct populations. In the experiments described here, cell lines with varying levels of sequence variants resulting from a single nucleotide change in the gene of interest were used to study population dynamics in cloned CHO cell lines. Analysis of four different monoclonal antibody-expressing cell lines with known sequence variants under varying continuous culture conditions provided insight into transcription and translation rates of SV-containing cell lines and allowed us to generate population dynamic models leading to better understanding of SVs and the genetic heterogeneity of clonal cell lines. Early time points of these cell lines were further subcloned and analyzed to gain further understanding of subpopulation dynamics in cloned cell lines and the results of these experiments will be presented. Subclones of these four clonal cell lines proved varying degrees of heterogeneity while falling into distinct population dynamics models. Additionally, mixing of subclones expressing the same mAb, with and without SVs at similar growth rates allowed us to evaluate how populations shift over time. A range of expected and unexpected outcomes was observed with these intentionally mixed populations demonstrating the complexity of clonal cell line heterogeneity. This study will further our understanding on the interplay between clonality, heterogeneity and population dynamics of “clonal” cell lines and will allow for critical assessment of overarching cell line development methods and strategies

Addressing human variability in next-generation human health risk assessments of environmental chemicals

International audienceCharacterizing variability in the extent and nature of responses to environmental exposures is a critical aspect of human health risk assessment. Our goal was to explore how next-generation human health risk assessments may better characterize variability in the context of the conceptual framework for the source-to-outcome continuum. This review was informed by a National Research Council workshop titled 'Biological Factors that Underlie Individual Susceptibility to Environmental Stressors and Their Implications for Decision-Making.' We considered current experimental and in silico approaches, and emerging data streams (such as genetically defined human cells lines, genetically diverse rodent models, human omic profiling, and genome-wide association studies) that are providing new types of information and models relevant for assessing interindividual variability for application to human health risk assessments of environmental chemicals. One challenge for characterizing variability is the wide range of sources of inherent biological variability (e.g., genetic and epigenetic variants) among individuals. A second challenge is that each particular pair of health outcomes and chemical exposures involves combinations of these sources, which may be further compounded by extrinsic factors (e.g., diet, psychosocial stressors, other exogenous chemical exposures). A third challenge is that different decision contexts present distinct needs regarding the identification-and extent of characterization-of interindividual variability in the human population. Despite these inherent challenges, opportunities exist to incorporate evidence from emerging data streams for addressing interindividual variability in a range of decision-making contexts

eHive: An Artificial Intelligence workflow system for genomic analysis

<p>Abstract</p> <p>Background</p> <p>The Ensembl project produces updates to its comparative genomics resources with each of its several releases per year. During each release cycle approximately two weeks are allocated to generate all the genomic alignments and the protein homology predictions. The number of calculations required for this task grows approximately quadratically with the number of species. We currently support 50 species in Ensembl and we expect the number to continue to grow in the future.</p> <p>Results</p> <p>We present eHive, a new fault tolerant distributed processing system initially designed to support comparative genomic analysis, based on blackboard systems, network distributed autonomous agents, dataflow graphs and block-branch diagrams. In the eHive system a MySQL database serves as the central blackboard and the autonomous agent, a Perl script, queries the system and runs jobs as required. The system allows us to define dataflow and branching rules to suit all our production pipelines. We describe the implementation of three pipelines: (1) pairwise whole genome alignments, (2) multiple whole genome alignments and (3) gene trees with protein homology inference. Finally, we show the efficiency of the system in real case scenarios.</p> <p>Conclusions</p> <p>eHive allows us to produce computationally demanding results in a reliable and efficient way with minimal supervision and high throughput. Further documentation is available at: <url>http://www.ensembl.org/info/docs/eHive/</url>.</p

Magnetic resonance spectroscopic imaging in gliomas: clinical diagnosis and radiotherapy planning

The reprogramming of cellular metabolism is a hallmark of cancer diagnosis and prognosis. Proton magnetic resonance spectroscopic imaging (MRSI) is a non-invasive diagnostic technique for investigating brain metabolism to establish cancer diagnosis and IDH gene mutation diagnosis as well as facilitate pre-operative planning and treatment response monitoring. By allowing tissue metabolism to be quantified, MRSI provides added value to conventional MRI. MRSI can generate metabolite maps from a single volume or multiple volume elements within the whole brain. Metabolites such as NAA, Cho and Cr, as well as their ratios Cho:NAA ratio and Cho:Cr ratio, have been used to provide tumor diagnosis and aid in radiation therapy planning as well as treatment assessment. In addition to these common metabolites, 2-hydroxygluterate (2HG) has also been quantified using MRSI following the recent discovery of IDH mutations in gliomas. This has opened up targeted drug development to inhibit the mutant IDH pathway. This review provides guidance on MRSI in brain gliomas, including its acquisition, analysis methods, and evolving clinical applications

Transcriptional diversity of long-term glioblastoma survivors

BACKGROUND: Glioblastoma (GBM) is a highly aggressive type of glioma with poor prognosis. However, a small number of patients live much longer than the median survival. A better understanding of these long-term survivors (LTSs) may provide important insight into the biology of GBM. METHODS: We identified 7 patients with GBM, treated at Memorial Sloan-Kettering Cancer Center (MSKCC), with survival \u3e48 months. We characterized the transcriptome of each patient and determined rates of MGMT promoter methylation and IDH1 and IDH2 mutational status. We identified LTSs in 2 independent cohorts (The Cancer Genome Atlas [TCGA] and NCI Repository for Molecular Brain Neoplasia Data [REMBRANDT]) and analyzed the transcriptomal characteristics of these LTSs. RESULTS: The median overall survival of our cohort was 62.5 months. LTSs were distributed between the proneural (n = 2), neural (n = 2), classical (n = 2), and mesenchymal (n = 1) subtypes. Similarly, LTS in the TCGA and REMBRANDT cohorts demonstrated diverse transcriptomal subclassification identities. The majority of the MSKCC LTSs (71%) were found to have methylation of the MGMT promoter. None of the patients had an IDH1 or IDH2 mutation, and IDH mutation occurred in a minority of the TCGA LTSs as well. A set of 60 genes was found to be differentially expressed in the MSKCC and TCGA LTSs. CONCLUSIONS: While IDH mutant proneural tumors impart a better prognosis in the short-term, survival beyond 4 years does not require IDH mutation and is not dictated by a single transcriptional subclass. In contrast, MGMT methylation continues to have strong prognostic value for survival beyond 4 years. These findings have substantial impact for understanding GBM biology and progression

Estimating survival in patients with gastrointestinal cancers and brain metastases: An update of the graded prognostic assessment for gastrointestinal cancers (GI-GPA).

BackgroundPatients with gastrointestinal cancers and brain metastases (BM) represent a unique and heterogeneous population. Our group previously published the Diagnosis-Specific Graded Prognostic Assessment (DS-GPA) for patients with GI cancers (GI-GPA) (1985-2007, n = 209). The purpose of this study is to update the GI-GPA based on a larger contemporary database.MethodsAn IRB-approved consortium database analysis was performed using a multi-institutional (18), multi-national (3) cohort of 792 patients with gastrointestinal (GI) cancers, with newly-diagnosed BM diagnosed between 1/1/2006 and 12/31/2017. Survival was measured from date of first treatment for BM. Multiple Cox regression was used to select and weight prognostic factors in proportion to their hazard ratios. These factors were incorporated into the updated GI-GPA.ResultsMedian survival (MS) varied widely by primary site and other prognostic factors. Four significant factors (KPS, age, extracranial metastases and number of BM) were used to formulate the updated GI-GPA. Overall MS for this cohort remains poor; 8 months. MS by GPA was 3, 7, 11 and 17 months for GPA 0-1, 1.5-2, 2.5-3.0 and 3.5-4.0, respectively. &gt;30% present in the worst prognostic group (GI-GPA of ≤1.0).ConclusionsBrain metastases are not uncommon in GI cancer patients and MS varies widely among them. This updated GI-GPA index improves our ability to estimate survival for these patients and will be useful for therapy selection, end-of-life decision-making and stratification for future clinical trials. A user-friendly, free, on-line app to calculate the GPA score and estimate survival for an individual patient is available at brainmetgpa.com

CAG expansion affects the expression of mutant huntingtin in the Huntington's disease brain

AbstractA trinucleotide repeat (CAG) expansion in the huntingtin gene causes Huntington's disease (HD). In brain tissue from HD heterozygotes with adult onset and more clinically severe juvenile onset, where the largest expansions occur, a mutant protein of equivalent intensity to wild-type huntingtin was detected in cortical synaptosomes, indicating that a mutant species is synthesized and transported with the normal protein to nerve endings. The increased size of mutant huntingtin relative to the wild type was highly correlated with CAG repeat expansion, thereby linking an altered electrophoretic mobility of the mutant protein to its abnormal function. Mutant huntingtin appeared in gray and white matter with no difference in expression in affected regions. The mutant protein was broader than the wild type and in 6 of 11 juvenile cases resolved as a complex of bands, consistent with evidence at the DNA level for somatic mosaicism. Thus, HD pathogenesis results from a gain of function by an aberrant protein that is widely expressed in brain and is harmful only to some neurons

Analysis of variation at transcription factor binding sites in Drosophila and humans

Background: Advances in sequencing technology have boosted population genomics and made it possible to map the positions of transcription factor binding sites (TFBSs) with high precision. Here we investigate TFBS variability by combining transcription factor binding maps generated by ENCODE, modENCODE, our previously published data and other sources with genomic variation data for human individuals and Drosophila isogenic lines. Results: We introduce a metric of TFBS variability that takes into account changes in motif match associated with mutation and makes it possible to investigate TFBS functional constraints instance-by-instance as well as in sets that share common biological properties. We also take advantage of the emerging per-individual transcription factor binding data to show evidence that TFBS mutations, particularly at evolutionarily conserved sites, can be efficiently buffered to ensure coherent levels of transcription factor binding. Conclusions: Our analyses provide insights into the relationship between individual and interspecies variation and show evidence for the functional buffering of TFBS mutations in both humans and flies. In a broad perspective, these results demonstrate the potential of combining functional genomics and population genetics approaches for understanding gene regulation.European Molecular Biology Laboratory (interdisciplinary fellowship (EIPOD))Deutsche Forschungsgemeinschaft (DFG FU 750/1-1

A high-resolution map of human evolutionary constraint using 29 mammals.

The comparison of related genomes has emerged as a powerful lens for genome interpretation. Here we report the sequencing and comparative analysis of 29 eutherian genomes. We confirm that at least 5.5% of the human genome has undergone purifying selection, and locate constrained elements covering ∼4.2% of the genome. We use evolutionary signatures and comparisons with experimental data sets to suggest candidate functions for ∼60% of constrained bases. These elements reveal a small number of new coding exons, candidate stop codon readthrough events and over 10,000 regions of overlapping synonymous constraint within protein-coding exons. We find 220 candidate RNA structural families, and nearly a million elements overlapping potential promoter, enhancer and insulator regions. We report specific amino acid residues that have undergone positive selection, 280,000 non-coding elements exapted from mobile elements and more than 1,000 primate- and human-accelerated elements. Overlap with disease-associated variants indicates that our findings will be relevant for studies of human biology, health and disease