Gene family-free genome comparison

Dörr D. Gene family-free genome comparison. Bielefeld: Universität Bielefeld; 2016.Computational comparative genomics offers valuable insights into the shared and individual evolutionary histories of living and extinct species and expands our understanding of cellular processes in living cells. Comparing genomes means identifying differences that originated from mutational modifications in their evolutionary past. In studying genome evolution, one differentiates between point mutations, genome rearrangements, and content modifications. Point mutations affect one or few consecutive nucleotide bases in the DNA sequence, whereas genome rearrangements operate on larger genomic regions, thereby altering the order and composition of genes in chromosomal sequences. Lastly, content modifications are a result of gene family evolution that causes gene duplications and losses. Genome rearrangement studies commonly assume that evolutionary relationships between all pairs of genes are resolved. Based on the biological concept of homology, the set of genes can be partitioned into gene families. All genes in a gene family are homologous, i.e., they evolved from the same ancestral sequence. Homology information is generally not given, hence gene families are commonly predicted computationally on the basis of sequence similarity or higher order features of their gene products. These predictions are often unreliable, leading to errors in subsequent genome rearrangement studies. In an attempt to avoid errors resulting from incorrect or incomplete gene family assignments, we develop new methods for genome rearrangement studies that do not require prior knowledge of gene family assignments of genes. Our approach, called gene family-free genome comparison, is innovative in that we account for differences between genes caused by point mutations while studying their order and composition in chromosomes. In lieu of gene family assignments, our proposed methods rely on pairwise similarities between genes. In practice, we obtain gene similarities from the conservation of their protein sequences. Two genes that are located next to each other on a chromosome are said to be adjacent, their adjoining extremities form an adjacency. The number of conserved adjacencies, i.e., those adjacencies that are common to two genomes, gives rise to a measure for gene~order-based genome similarity. If the gene content of both genomes is identical, the number of conserved adjacencies is the dual measure of the well-known breakpoint distance. We study the problem of computing the number of conserved adjacencies in a family-free setting, which relies on pairwise similarities between genes. We analyze its computational complexity and develop exact and heuristic algorithms for its solution in pairwise comparisons. We then advance to the problem of reconstructing ancestral sequences. Given three genomes, we study the problem of constructing a fourth genome, called the median, which maximizes a family-free, pairwise measure of conserved adjacencies between the median and each of the three given genomes. Our model is a family-free generalization of the well-studied mixed multichromosomal breakpoint median. We show that this problem is NP-hard and devise an exact algorithm for its solution. Gene orders become increasingly scrambled over longer evolutionary periods of time. In distant genomes, gene order analyses based on identifying pairs of conserved adjacencies might no longer be informative. Yet, relaxed constraints of gene order conservation are still able to capture weaker, but nonetheless existing remnants of common ancestral gene order, which leads to the problem of identifying syntenic blocks in two or more genomes. Knowing the evolutionary relationships between genes, one can assign a unique character to each gene family and represent a chromosome by a string drawn from the alphabet of gene family characters. Two intervals from two strings are called common intervals if the sets of characters within these intervals are identical. We extend this concept to indeterminate strings, which are a class of strings that have at every position a non-empty set of characters. We propose several models of common intervals in indeterminate strings and devise efficient algorithms for their corresponding discovery problems. Subsequently, we use the concept of common intervals in indeterminate strings to identify syntenic regions in a gene family-free setting. We evaluate all our proposed models and algorithms on simulated or biological datasets and assess their performance and applicability in gene family-free genome analyses

Common Co-activation of AXL and CDCP1 in EGFR-mutation-positive Non-smallcell Lung Cancer Associated With Poor Prognosis.

Epidermal growth factor receptor (EGFR)-mutation-positive non-smallcell lung cancer (NSCLC) is incurable, despite high rates of response to EGFR tyrosine kinase inhibitors (TKIs). We investigated receptor tyrosine kinases (RTKs), Src family kinases and focal adhesion kinase (FAK) as genetic modifiers of innate resistance in EGFR-mutation-positive NSCLC. We performed gene expression analysis in two cohorts (Cohort 1 and Cohort 2) of EGFR-mutation-positive NSCLC patients treated with EGFR TKI. We evaluated the efficacy of gefitinib or osimertinib with the Src/FAK/Janus kinase 2 (JAK2) inhibitor, TPX0005 in vitro and in vivo. In Cohort 1, CUB domain-containing protein-1 (CDCP1) was an independent negative prognostic factor for progression-free survival (hazard ratio of 1.79, p=0.0407) and overall survival (hazard ratio of 2.23, p=0.0192). A two-gene model based on AXL and CDCP1 expression was strongly associated with the clinical outcome to EGFR TKIs, in both cohorts of patients. Our preclinical experiments revealed that several RTKs and non-RTKs, were up-regulated at baseline or after treatment with gefitinib or osimertinib. TPX-0005 plus EGFR TKI suppressed expression and activation of RTKs and downstream signaling intermediates. Co-expression of CDCP1 and AXL is often observed in EGFR-mutation-positive tumors, limiting the efficacy of EGFR TKIs. Co-treatment with EGFR TKI and TPX-0005 warrants testing

Boosting the concordance index for survival data - a unified framework to derive and evaluate biomarker combinations

The development of molecular signatures for the prediction of time-to-event outcomes is a methodologically challenging task in bioinformatics and biostatistics. Although there are numerous approaches for the derivation of marker combinations and their evaluation, the underlying methodology often suffers from the problem that different optimization criteria are mixed during the feature selection, estimation and evaluation steps. This might result in marker combinations that are only suboptimal regarding the evaluation criterion of interest. To address this issue, we propose a unified framework to derive and evaluate biomarker combinations. Our approach is based on the concordance index for time-to-event data, which is a non-parametric measure to quantify the discrimatory power of a prediction rule. Specifically, we propose a component-wise boosting algorithm that results in linear biomarker combinations that are optimal with respect to a smoothed version of the concordance index. We investigate the performance of our algorithm in a large-scale simulation study and in two molecular data sets for the prediction of survival in breast cancer patients. Our numerical results show that the new approach is not only methodologically sound but can also lead to a higher discriminatory power than traditional approaches for the derivation of gene signatures.Comment: revised manuscript - added simulation study, additional result

IGHV mutational status of nodal marginal zone lymphoma by NGS reveals distinct pathogenic pathways with different prognostic implications

The precise B cell of origin and molecular pathogenesis of nodal marginal zone lymphoma (NMZL) remain poorly defined. To date, due to the rarity of NMZL, the vast majority of already-published studies have been conducted on a limited number of samples and the technical approach to analyze the immunoglobulin genes was of amplifying rearranged variable region genes with the classical direct sequencing of the PCR products followed by cloning. Here, we studied the B cell Ig heavy-chain repertoires by next-generation sequencing (NGS) in 30 NMZL cases. Most of the cases were mutated (20/28; 71.5%) with homologies to the respective germ line genes ranging from 85 to 97, 83%, whereas 8/28 (28.5%) were unmutated. In addition, our results show that NMZL cases have a biased usage of specific immunoglobulin heavy-chain variable (IGHV) region genes. Moreover, we documented intraclonal diversity in all (100%) of the mutated cases and ongoing somatic hypermutations (SHM) have been confirmed by hundreds of reads. We analyzed the mutational pattern to detect and quantify antigen selection pressure and we found a positive selection in 4 cases, whereas in the remaining cases there was an unspecific stimulation. Finally, the disease-specific survival and the progression-free survival were significantly different between cases with mutated and unmutated IGHV genes, pointing out mutational status as a possible new biomarker in NMZL

The histone deacetylase inhibiting drug Entinostat induces lipid accumulation in differentiated HepaRG cells

Dietary overload of toxic, free metabolic intermediates leads to disrupted insulin signalling and fatty liver disease. However, it was recently reported that this pathway might not be universal: depletion of histone deacetylase (HDAC) enhances insulin sensitivity alongside hepatic lipid accumulation in mice, but the mechanistic role of microscopic lipid structure in this effect remains unclear. Here we study the effect of Entinostat, a synthetic HDAC inhibitor undergoing clinical trials, on hepatic lipid metabolism in the paradigmatic HepaRG liver cell line. Specifically, we statistically quantify lipid droplet morphology at single cell level utilizing label-free microscopy, coherent anti-Stokes Raman scattering, supported by gene expression. We observe Entinostat efficiently rerouting carbohydrates and free-fatty acids into lipid droplets, upregulating lipid coat protein gene Plin4, and relocating droplets nearer to the nucleus. Our results demonstrate the power of Entinostat to promote lipid synthesis and storage, allowing reduced systemic sugar levels and sequestration of toxic metabolites within protected protein-coated droplets, suggesting a potential therapeutic strategy for diseases such as diabetes and metabolic syndrome

Clinical and functional characterisation of a novel TNFRSF1A c.605T > A/V173D cleavage site mutation associated with tumour necrosis factor receptor-associated periodic fever syndrome (TRAPS), cardiovascular complications and excellent response to etanercept treatment.

Objectives: To study the clinical outcome, treatment response, T-cell subsets and functional consequences of a novel tumour necrosis factor (TNF) receptor type 1 (TNFRSF1A) mutation affecting the receptor cleavage site. Methods: Patients with symptoms suggestive of tumour necrosis factor receptor-associated periodic syndrome (TRAPS) and 22 healthy controls (HC) were screened for mutations in the TNFRSF1A gene. Soluble TNFRSF1A and inflammatory cytokines were measured by ELISAs. TNFRSF1A shedding was examined by stimulation of peripheral blood mononuclear cells (PBMCs) with phorbol 12-myristate 13-acetate followed by flow cytometric analysis (FACS). Apoptosis of PBMCs was studied by stimulation with TNFa in the presence of cycloheximide and annexin V staining. T cell phenotypes were monitored by FACS. Results: TNFRSF1A sequencing disclosed a novel V173D/ p.Val202Asp substitution encoded by exon 6 in one family, the c.194–14G.A splice variant in another and the R92Q/p.Arg121Gln substitution in two families. Cardiovascular complications (lethal heart attack and peripheral arterial thrombosis) developed in two V173D patients. Subsequent etanercept treatment of the V173D carriers was highly effective over an 18-month follow-up period. Serum TNFRSF1A levels did not differ between TRAPS patients and HC, while TNFRSF1A cleavage from monocytes was significantly reduced in V173D and R92Q patients. TNFa-induced apoptosis of PBMCs and T-cell senescence were comparable between V173D patients and HC. Conclusions: The TNFRSF1A V173D cleavage site mutation may be associated with an increased risk for cardiovascular complications and shows a strong response to etanercept. T-cell senescence does not seem to have a pathogenetic role in affected patients

Differential effects of RGS proteins on Gαq and Gα11 activity

Heterotrimeric G proteins play a pivotal role in GPCR signalling; they link receptors to intracellular effectors and their inactivation by RGS proteins is a key factor in resetting the pathway following stimulation. The precise GPCR:G protein:RGS combination determines the nature and duration of the response. Investigating the activity of particular combinations is difficult in cells which contain multiples of each component. We have therefore utilised a previously characterised yeast system to express mammalian proteins in isolation. Human Gαq and Gα11 spontaneously activated the yeast pheromone-response pathway by a mechanism which required the formation of Gα-GTP. This provided an assay for the specific activity of human RGS proteins. RGS1, RGS2, RGS3 and RGS4 inhibited the spontaneous activity of both Gαq and Gα11 but, in contrast, RGS5 and RGS16 were much less effective against Gα11 than Gαq. Interestingly, RGS2 and RGS3 were able to inhibit signalling from the constitutively active Gαq QL/Gα11 QL mutants, confirming the GAP-independent activity of these RGS proteins. To determine if the RGS-Gα specificity was maintained under conditions of GPCR stimulation, minor modifications to the C-terminus of Gαq/Gα11 enabled coupling to an endogenous receptor. RGS2 and RGS3 were effective inhibitors of both Gα subunits even at high levels of receptor stimulation, emphasising their GAP-independent activity. At low levels of stimulation RGS5 and RGS16 retained their differential Gα activity, further highlighting that RGS proteins can discriminate between two very closely related Gα subunits

Gene Expression Profiling of Bronchoalveolar Lavage Cells Preceding a Clinical Diagnosis of Chronic Lung Allograft Dysfunction.

BackgroundChronic Lung Allograft Dysfunction (CLAD) is the main limitation to long-term survival after lung transplantation. Although CLAD is usually not responsive to treatment, earlier identification may improve treatment prospects.MethodsIn a nested case control study, 1-year post transplant surveillance bronchoalveolar lavage (BAL) fluid samples were obtained from incipient CLAD (n = 9) and CLAD free (n = 8) lung transplant recipients. Incipient CLAD cases were diagnosed with CLAD within 2 years, while controls were free from CLAD for at least 4 years following bronchoscopy. Transcription profiles in the BAL cell pellets were assayed with the HG-U133 Plus 2.0 microarray (Affymetrix). Differential gene expression analysis, based on an absolute fold change (incipient CLAD vs no CLAD) >2.0 and an unadjusted p-value ≤0.05, generated a candidate list containing 55 differentially expressed probe sets (51 up-regulated, 4 down-regulated).ResultsThe cell pellets in incipient CLAD cases were skewed toward immune response pathways, dominated by genes related to recruitment, retention, activation and proliferation of cytotoxic lymphocytes (CD8+ T-cells and natural killer cells). Both hierarchical clustering and a supervised machine learning tool were able to correctly categorize most samples (82.3% and 94.1% respectively) into incipient CLAD and CLAD-free categories.ConclusionsThese findings suggest that a pathobiology, similar to AR, precedes a clinical diagnosis of CLAD. A larger prospective investigation of the BAL cell pellet transcriptome as a biomarker for CLAD risk stratification is warranted