Recovery, assessment, and molecular characterization of minor olive genotypes in Tunisia

Olive is one of the oldest cultivated species in the Mediterranean Basin, including Tunisia, where it has a wide diversity, with more than 200 cultivars, of both wild and feral forms. Many minor cultivars are still present in marginal areas of Tunisia, where they are maintained by farmers in small local groves, but they are poorly characterized and evaluated. In order to recover this neglected germplasm, surveys were conducted in different areas, and 31 genotypes were collected, molecularly characterized with 12 nuclear microsatellite (simple sequence repeat (SSR)) markers, and compared with 26 reference cultivars present in the Tunisian National Olive collection. The analysis revealed an overall high genetic diversity of this olive’s germplasm, but also discovered the presence of synonymies and homonymies among the commercialized varieties. The structure analysis showed the presence of different gene pools in the analyzed germplasm. In particular, the marginal germplasm from Ras Jbal and Azmour is characterized by gene pools not present in commercial (Nurseries) varieties, pointing out the very narrow genetic base of the commercialized olive material in Tunisia, and the need to broaden it to avoid the risk of genetic erosion of this species in this country

Interactions with Fibroblasts Are Distinct in Basal-Like and Luminal Breast Cancers

Basal-like breast cancers have several well-characterized distinguishing molecular features, but most of these are features of the cancer cells themselves. The unique stromal-epithelial interactions, and more generally, microenvironmental features of Basal-like breast cancers have not been well characterized. To identify characteristic microenvironment features of Basal-like breast cancer we performed cocultures of several Basal-like breast cancer cell lines with fibroblasts and compared these to cocultures of Luminal breast cancer cell lines with fibroblasts. Interactions between Basal-like cancer cells and fibroblasts induced expression of numerous interleukins and chemokines, including IL-6, IL-8, CXCL1, CXCL3, and TGFbeta. Under the influence of fibroblasts, Basal-like breast cancer cell lines also showed increased migration in vitro. Migration was less pronounced for Luminal lines, but these lines were more likely to have altered proliferation. These differences were relevant to tumor biology in vivo, as the gene set that distinguished Luminal and Basal-like stromal interactions in coculture also distinguishes Basal-like from Luminal tumors with 98% accuracy in 10-fold CV and 100% accuracy in an independent test set. However, comparisons between cocultures where cells were in direct contact and cocultures where interaction was solely through soluble factors suggest that there is an important impact of direct cell-to-cell contact. The phenotypes and gene expression changes invoked by cancer cell interactions with fibroblasts support the microenvironment and cell-cell interactions as intrinsic features of breast cancer subtypes

Biallelic variants in OGDH encoding oxoglutarate dehydrogenase lead to a neurodevelopmental disorder characterized by global developmental delay, movement disorder, and metabolic abnormalities

PURPOSE: This study aimed to establish the genetic cause of a novel autosomal recessive neurodevelopmental disorder characterized by global developmental delay, movement disorder, and metabolic abnormalities. METHODS: We performed a detailed clinical characterization of 4 unrelated individuals from consanguineous families with a neurodevelopmental disorder. We used exome sequencing or targeted-exome sequencing, cosegregation, in silico protein modeling, and functional analyses of variants in HEK293 cells and Drosophila melanogaster, as well as in proband-derived fibroblast cells. RESULTS: In the 4 individuals, we identified 3 novel homozygous variants in oxoglutarate dehydrogenase (OGDH) (NM_002541.3), which encodes a subunit of the tricarboxylic acid cycle enzyme α-ketoglutarate dehydrogenase. In silico homology modeling predicts that c.566C>T:p.(Pro189Leu) and c.890C>A:p.(Ser297Tyr) variants interfere with the structure and function of OGDH. Fibroblasts from individual 1 showed that the p.(Ser297Tyr) variant led to a higher degradation rate of the OGDH protein. OGDH protein with p.(Pro189Leu) or p.(Ser297Tyr) variants in HEK293 cells showed significantly lower levels than the wild-type protein. Furthermore, we showed that expression of Drosophila Ogdh (dOgdh) carrying variants homologous to p.(Pro189Leu) or p.(Ser297Tyr), failed to rescue developmental lethality caused by loss of dOgdh. SpliceAI, a variant splice predictor, predicted that the c.935G>A:p.(Arg312Lys)/p.(Phe264_Arg312del) variant impacts splicing, which was confirmed through a mini-gene assay in HEK293 cells. CONCLUSION: We established that biallelic variants in OGDH cause a neurodevelopmental disorder with metabolic and movement abnormalities

Benchmarking of cell type deconvolution pipelines for transcriptomics data

Many computational methods have been developed to infer cell type proportions from bulk transcriptomics data. However, an evaluation of the impact of data transformation, pre-processing, marker selection, cell type composition and choice of methodology on the deconvolution results is still lacking. Using five single-cell RNA-sequencing (scRNA-seq) datasets, we generate pseudo-bulk mixtures to evaluate the combined impact of these factors. Both bulk deconvolution methodologies and those that use scRNA-seq data as reference perform best when applied to data in linear scale and the choice of normalization has a dramatic impact on some, but not all methods. Overall, methods that use scRNA-seq data have comparable performance to the best performing bulk methods whereas semi-supervised approaches show higher error values. Moreover, failure to include cell types in the reference that are present in a mixture leads to substantially worse results, regardless of the previous choices. Altogether, we evaluate the combined impact of factors affecting the deconvolution task across different datasets and propose general guidelines to maximize its performance. Inferring cell type proportions from transcriptomics data is affected by data transformation, normalization, choice of method and the markers used. Here, the authors use single-cell RNAseq datasets to evaluate the impact of these factors and propose guidelines to maximise deconvolution performance

Quantitative proteome landscape of the NCI-60 cancer cell lines

Here we describe a proteomic data resource for the NCI-60 cell lines generated by pressure cycling technology and SWATH mass spectrometry. We developed the DIA-expert software to curate and visualize the SWATH data, leading to reproducible detection of over 3,100 SwissProt proteotypic proteins and systematic quantification of pathway activities. Stoichiometric relationships of interacting proteins for DNA replication, repair, the chromatin remodeling NuRD complex, β-catenin, RNA metabolism, and prefoldins are more evident than that at the mRNA level. The data are available in CellMiner (discover.nci.nih.gov/cellminercdb and discover.nci.nih.gov/cellminer), allowing casual users to test hypotheses and perform integrative, cross-database analyses of multi-omic drug response correlations for over 20,000 drugs. We demonstrate the value of proteome data in predicting drug response for over 240 clinically relevant chemotherapeutic and targeted therapies. In summary, we present a novel proteome resource for the NCI-60, together with relevant software tools, and demonstrate the benefit of proteome analyses

A biclustering algorithm based on a Bicluster Enumeration Tree: application to DNA microarray data

<p>Abstract</p> <p>Background</p> <p>In a number of domains, like in DNA microarray data analysis, we need to cluster simultaneously rows (genes) and columns (conditions) of a data matrix to identify groups of rows coherent with groups of columns. This kind of clustering is called <it>biclustering</it>. Biclustering algorithms are extensively used in DNA microarray data analysis. More effective biclustering algorithms are highly desirable and needed.</p> <p>Methods</p> <p>We introduce <it>BiMine</it>, a new enumeration algorithm for biclustering of DNA microarray data. The proposed algorithm is based on three original features. First, <it>BiMine </it>relies on a new evaluation function called <it>Average Spearman's rho </it>(ASR). Second, <it>BiMine </it>uses a new tree structure, called <it>Bicluster Enumeration Tree </it>(BET), to represent the different biclusters discovered during the enumeration process. Third, to avoid the combinatorial explosion of the search tree, <it>BiMine </it>introduces a parametric rule that allows the enumeration process to cut tree branches that cannot lead to good biclusters.</p> <p>Results</p> <p>The performance of the proposed algorithm is assessed using both synthetic and real DNA microarray data. The experimental results show that <it>BiMine </it>competes well with several other biclustering methods. Moreover, we test the biological significance using a gene annotation web-tool to show that our proposed method is able to produce biologically relevant biclusters. The software is available upon request from the authors to academic users.</p

A Cell Permeable Peptide Inhibitor of NFAT Inhibits Macrophage Cytokine Expression and Ameliorates Experimental Colitis

Nuclear factor of activated T cells (NFAT) plays a critical role in the development and function of immune and non-immune cells. Although NFAT is a central transcriptional regulator of T cell cytokines, its role in macrophage specific gene expression is less defined. Previous work from our group demonstrated that NFAT regulates Il12b gene expression in macrophages. Here, we further investigate NFAT function in murine macrophages and determined the effects of a cell permeable NFAT inhibitor peptide 11R-VIVIT on experimental colitis in mice. Treatment of bone marrow derived macrophages (BMDMs) with tacrolimus or 11R-VIVIT significantly inhibited LPS and LPS plus IFN-γ induced IL-12 p40 mRNA and protein expression. IL-12 p70 and IL-23 secretion were also decreased. NFAT nuclear translocation and binding to the IL-12 p40 promoter was reduced by NFAT inhibition. Experiments in BMDMs from IL-10 deficient (Il10−/−) mice demonstrate that inhibition of IL-12 expression by 11R-VIVIT was independent of IL-10 expression. To test its therapeutic potential, 11R-VIVIT was administered systemically to Il10−/− mice with piroxicam-induced colitis. 11R-VIVIT treated mice demonstrated significant improvement in colitis compared to mice treated with an inactive peptide. Moreover, decreased spontaneous secretion of IL-12 p40 and TNF in supernatants from colon explant cultures was demonstrated. In summary, NFAT, widely recognized for its role in T cell biology, also regulates important innate inflammatory pathways in macrophages. Selective blocking of NFAT via a cell permeable inhibitory peptide is a promising therapeutic strategy for the treatment of inflammatory bowel diseases

Biallelic variants in KARS1 are associated with neurodevelopmental disorders and hearing loss recapitulated by the knockout zebrafish

Purpose: Pathogenic variants in Lysyl-tRNA synthetase 1 (KARS1) have increasingly been recognized as a cause of early-onset complex neurological phenotypes. To advance the timely diagnosis of KARS1-related disorders, we sought to delineate its phenotype and generate a disease model to understand its function in vivo. Methods: Through international collaboration, we identified 22 affected individuals from 16 unrelated families harboring biallelic likely pathogenic or pathogenic in KARS1 variants. Sequencing approaches ranged from disease-specific panels to genome sequencing. We generated loss-of-function alleles in zebrafish. Results: We identify ten new and four known biallelic missense variants in KARS1 presenting with a moderate-to-severe developmental delay, progressive neurological and neurosensory abnormalities, and variable white matter involvement. We describe novel KARS1-associated signs such as autism, hyperactive behavior, pontine hypoplasia, and cerebellar atrophy with prevalent vermian involvement. Loss of kars1 leads to upregulation of p53, tissue-specific apoptosis, and downregulation of neurodevelopmental related genes, recapitulating key tissue-specific disease phenotypes of patients. Inhibition of p53 rescued several defects of kars1−/− knockouts. Conclusion: Our work delineates the clinical spectrum associated with KARS1 defects and provides a novel animal model for KARS1-related human diseases revealing p53 signaling components as potential therapeutic targets

From community approaches to single-cell genomics: the discovery of ubiquitous hyperhalophilic Bacteroidetes generalists

The microbiota of multi-pond solar salterns around the world has been analyzed using a variety of culture-dependent and molecular techniques. However, studies addressing the dynamic nature of these systems are very scarce. Here we have characterized the temporal variation during 1 year of the microbiota of five ponds with increasing salinity (from 18% to >40%), by means of CARD-FISH and DGGE. Microbial community structure was statistically correlated with several environmental parameters, including ionic composition and meteorological factors, indicating that the microbial community was dynamic as specific phylotypes appeared only at certain times of the year. In addition to total salinity, microbial composition was strongly influenced by temperature and specific ionic composition. Remarkably, DGGE analyses unveiled the presence of most phylotypes previously detected in hypersaline systems using metagenomics and other molecular techniques, such as the very abundant Haloquadratum and Salinibacter representatives or the recently described low GC Actinobacteria and Nanohaloarchaeota. In addition, an uncultured group of Bacteroidetes was present along the whole range of salinity. Database searches indicated a previously unrecognized widespread distribution of this phylotype. Single-cell genome analysis of five members of this group suggested a set of metabolic characteristics that could provide competitive advantages in hypersaline environments, such as polymer degradation capabilities, the presence of retinal-binding light-activated proton pumps and arsenate reduction potential. In addition, the fairly high metagenomic fragment recruitment obtained for these single cells in both the intermediate and hypersaline ponds further confirm the DGGE data and point to the generalist lifestyle of this new Bacteroidetes group.This work was supported by the projects CGL2012-39627-C03-01 and 02 of the Spanish Ministry of Economy and Competitiveness, which were also co-financed with FEDER support from the European Union. TG group research is funded in part by a grant from the Spanish Ministry of Economy and Competitiveness (BIO2012-37161), a grant from the Qatar National Research Fund grant (NPRP 5-298-3-086) and a grant from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC (grant agreement no. ERC-2012-StG-310325)

A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression data

Batch effects are the systematic non-biological differences between batches (groups) of samples in microarray experiments due to various causes such as differences in sample preparation and hybridization protocols. Previous work focused mainly on the development of methods for effective batch effects removal. However, their impact on cross-batch prediction performance, which is one of the most important goals in microarray-based applications, has not been addressed. This paper uses a broad selection of data sets from the Microarray Quality Control Phase II (MAQC-II) effort, generated on three microarray platforms with different causes of batch effects to assess the efficacy of their removal. Two data sets from cross-tissue and cross-platform experiments are also included. Of the 120 cases studied using Support vector machines (SVM) and K nearest neighbors (KNN) as classifiers and Matthews correlation coefficient (MCC) as performance metric, we find that Ratio-G, Ratio-A, EJLR, mean-centering and standardization methods perform better or equivalent to no batch effect removal in 89, 85, 83, 79 and 75% of the cases, respectively, suggesting that the application of these methods is generally advisable and ratio-based methods are preferred