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1.
Bioinformatics ; 40(5)2024 05 02.
Artigo em Inglês | MEDLINE | ID: mdl-38656970

RESUMO

MOTIVATION: Many diseases, such as cancer, are characterized by an alteration of cellular metabolism allowing cells to adapt to changes in the microenvironment. Stable isotope-resolved metabolomics (SIRM) and downstream data analyses are widely used techniques for unraveling cells' metabolic activity to understand the altered functioning of metabolic pathways in the diseased state. While a number of bioinformatic solutions exist for the differential analysis of SIRM data, there is currently no available resource providing a comprehensive toolbox. RESULTS: In this work, we present DIMet, a one-stop comprehensive tool for differential analysis of targeted tracer data. DIMet accepts metabolite total abundances, isotopologue contributions, and isotopic mean enrichment, and supports differential comparison (pairwise and multi-group), time-series analyses, and labeling profile comparison. Moreover, it integrates transcriptomics and targeted metabolomics data through network-based metabolograms. We illustrate the use of DIMet in real SIRM datasets obtained from Glioblastoma P3 cell-line samples. DIMet is open-source, and is readily available for routine downstream analysis of isotope-labeled targeted metabolomics data, as it can be used both in the command line interface or as a complete toolkit in the public Galaxy Europe and Workfow4Metabolomics web platforms. AVAILABILITY AND IMPLEMENTATION: DIMet is freely available at https://github.com/cbib/DIMet, and through https://usegalaxy.eu and https://workflow4metabolomics.usegalaxy.fr. All the datasets are available at Zenodo https://zenodo.org/records/10925786.


Assuntos
Marcação por Isótopo , Metabolômica , Software , Metabolômica/métodos , Humanos , Marcação por Isótopo/métodos , Glioblastoma/metabolismo , Linhagem Celular Tumoral
2.
Hepatology ; 66(6): 2016-2028, 2017 12.
Artigo em Inglês | MEDLINE | ID: mdl-28646562

RESUMO

Hepatocellular adenomas (HCAs) are rare benign tumors divided into three main subgroups defined by pathomolecular features, HNF1A (H-HCA), mutated ß-catenin (b-HCA), and inflammatory (IHCA). In the case of unclassified HCAs (UHCAs), which are currently identified by default, a high risk of bleeding remains a clinical issue. The objective of this study was to explore UHCA proteome with the aim to identify specific biomarkers. Following dissection of the tumoral (T) and nontumoral (NT) tissue on formalin-fixed, paraffin-embedded HCA tissue sections using laser capture methodology, we performed mass spectrometry analysis to compare T and NT protein expression levels in H-HCA, IHCA, b-HCA, UHCA, and focal nodular hyperplasia. Using this methodology, we searched for proteins which are specifically deregulated in UHCA. We demonstrate that proteomic profiles allow for discriminating known HCA subtypes through identification of classical biomarkers in each HCA subgroup. We observed specific up-regulation of the arginine synthesis pathway associated with overexpression of argininosuccinate synthase (ASS1) and arginosuccinate lyase in UHCA. ASS1 immunohistochemistry identified all the UHCA, of which 64.7% presented clinical bleeding manifestations. Interestingly, we demonstrated that the significance of ASS1 was not restricted to UHCA, but also encompassed certain hemorrhagic cases in other HCA subtypes, particularly IHCA. CONCLUSION: ASS1 + HCA combined with a typical hematoxylin and eosin stain aspect defined a new HCA subgroup at a high risk of bleeding. (Hepatology 2017;66:2016-2028).


Assuntos
Adenoma de Células Hepáticas/metabolismo , Argininossuccinato Sintase/metabolismo , Neoplasias Hepáticas/metabolismo , Adenoma de Células Hepáticas/complicações , Adenoma de Células Hepáticas/patologia , Adulto , Arginina/biossíntese , Biomarcadores Tumorais/metabolismo , Estudos de Coortes , Feminino , Hemorragia/etiologia , Humanos , Microdissecção e Captura a Laser , Fígado/patologia , Neoplasias Hepáticas/complicações , Neoplasias Hepáticas/patologia , Espectrometria de Massas , Pessoa de Meia-Idade , Proteoma
3.
Genome Res ; 22(12): 2385-98, 2012 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-22835905

RESUMO

KLF1 (formerly known as EKLF) regulates the development of erythroid cells from bi-potent progenitor cells via the transcriptional activation of a diverse set of genes. Mice lacking Klf1 die in utero prior to E15 from severe anemia due to the inadequate expression of genes controlling hemoglobin production, cell membrane and cytoskeletal integrity, and the cell cycle. We have recently described the full repertoire of KLF1 binding sites in vivo by performing KLF1 ChIP-seq in primary erythroid tissue (E14.5 fetal liver). Here we describe the KLF1-dependent erythroid transcriptome by comparing mRNA-seq from Klf1(+/+) and Klf1(-/-) erythroid tissue. This has revealed novel target genes not previously obtainable by traditional microarray technology, and provided novel insights into the function of KLF1 as a transcriptional activator. We define a cis-regulatory module bound by KLF1, GATA1, TAL1, and EP300 that coordinates a core set of erythroid genes. We also describe a novel set of erythroid-specific promoters that drive high-level expression of otherwise ubiquitously expressed genes in erythroid cells. Our study has identified two novel lncRNAs that are dynamically expressed during erythroid differentiation, and discovered a role for KLF1 in directing apoptotic gene expression to drive the terminal stages of erythroid maturation.


Assuntos
Eritropoese/genética , Regulação da Expressão Gênica no Desenvolvimento , Fatores de Transcrição Kruppel-Like/genética , RNA Mensageiro/genética , Transcriptoma , Animais , Apoptose , Fatores de Transcrição Hélice-Alça-Hélice Básicos/genética , Fatores de Transcrição Hélice-Alça-Hélice Básicos/metabolismo , Western Blotting , Diferenciação Celular , Mapeamento Cromossômico , Proteína p300 Associada a E1A/genética , Proteína p300 Associada a E1A/metabolismo , Células Eritroides/citologia , Células Eritroides/metabolismo , Fator de Transcrição GATA1/genética , Fator de Transcrição GATA1/metabolismo , Perfilação da Expressão Gênica , Marcação In Situ das Extremidades Cortadas , Fatores de Transcrição Kruppel-Like/metabolismo , Fígado/metabolismo , Camundongos , Camundongos Endogâmicos BALB C , Regiões Promotoras Genéticas , Proteínas Proto-Oncogênicas/genética , Proteínas Proto-Oncogênicas/metabolismo , RNA Mensageiro/metabolismo , Análise de Sequência de RNA/métodos , Proteína 1 de Leucemia Linfocítica Aguda de Células T
4.
Biol Imaging ; 2: e4, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-38510431

RESUMO

Detection of RNA spots in single-molecule fluorescence in-situ hybridization microscopy images remains a difficult task, especially when applied to large volumes of data. The variable intensity of RNA spots combined with the high noise level of the images often requires manual adjustment of the spot detection thresholds for each image. In this work, we introduce DeepSpot, a Deep Learning-based tool specifically designed for RNA spot enhancement that enables spot detection without the need to resort to image per image parameter tuning. We show how our method can enable downstream accurate spot detection. DeepSpot's architecture is inspired by small object detection approaches. It incorporates dilated convolutions into a module specifically designed for context aggregation for small object and uses Residual Convolutions to propagate this information along the network. This enables DeepSpot to enhance all RNA spots to the same intensity, and thus circumvents the need for parameter tuning. We evaluated how easily spots can be detected in images enhanced with our method by testing DeepSpot on 20 simulated and 3 experimental datasets, and showed that accuracy of more than 97% is achieved. Moreover, comparison with alternative deep learning approaches for mRNA spot detection (deepBlink) indicated that DeepSpot provides more precise mRNA detection. In addition, we generated single-molecule fluorescence in-situ hybridization images of mouse fibroblasts in a wound healing assay to evaluate whether DeepSpot enhancement can enable seamless mRNA spot detection and thus streamline studies of localized mRNA expression in cells.

5.
EMBO Mol Med ; 14(12): e15343, 2022 12 07.
Artigo em Inglês | MEDLINE | ID: mdl-36278433

RESUMO

Lactate is a central metabolite in brain physiology but also contributes to tumor development. Glioblastoma (GB) is the most common and malignant primary brain tumor in adults, recognized by angiogenic and invasive growth, in addition to its altered metabolism. We show herein that lactate fuels GB anaplerosis by replenishing the tricarboxylic acid (TCA) cycle in absence of glucose. Lactate dehydrogenases (LDHA and LDHB), which we found spatially expressed in GB tissues, catalyze the interconversion of pyruvate and lactate. However, ablation of both LDH isoforms, but not only one, led to a reduction in tumor growth and an increase in mouse survival. Comparative transcriptomics and metabolomics revealed metabolic rewiring involving high oxidative phosphorylation (OXPHOS) in the LDHA/B KO group which sensitized tumors to cranial irradiation, thus improving mouse survival. When mice were treated with the antiepileptic drug stiripentol, which targets LDH activity, tumor growth decreased. Our findings unveil the complex metabolic network in which both LDHA and LDHB are integrated and show that the combined inhibition of LDHA and LDHB strongly sensitizes GB to therapy.


Assuntos
Neoplasias Encefálicas , Glioblastoma , Lactato Desidrogenases , Animais , Camundongos , Ácido Láctico , Metabolômica , Glioblastoma/enzimologia , Glioblastoma/patologia , Neoplasias Encefálicas/enzimologia , Neoplasias Encefálicas/patologia
6.
Cell Rep Methods ; 1(5): 100068, 2021 09 27.
Artigo em Inglês | MEDLINE | ID: mdl-35474672

RESUMO

Advances in single-cell RNA sequencing have allowed for the identification of cellular subtypes on the basis of quantification of the number of transcripts in each cell. However, cells might also differ in the spatial distribution of molecules, including RNAs. Here, we present DypFISH, an approach to quantitatively investigate the subcellular localization of RNA and protein. We introduce a range of analytical techniques to interrogate single-molecule RNA fluorescence in situ hybridization (smFISH) data in combination with protein immunolabeling. DypFISH is suited to study patterns of clustering of molecules, the association of mRNA-protein subcellular localization with microtubule organizing center orientation, and interdependence of mRNA-protein spatial distributions. We showcase how our analytical tools can achieve biological insights by utilizing cell micropatterning to constrain cellular architecture, which leads to reduction in subcellular mRNA distribution variation, allowing for the characterization of their localization patterns. Furthermore, we show that our method can be applied to physiological systems such as skeletal muscle fibers.


Assuntos
Fibras Musculares Esqueléticas , RNA , RNA/genética , Hibridização in Situ Fluorescente/métodos , RNA Mensageiro/genética , Fibras Musculares Esqueléticas/metabolismo , Transporte Proteico
7.
Neurooncol Adv ; 1(1): vdz029, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-32642662

RESUMO

BACKGROUND: Glioblastomas are heterogeneous tumors composed of a necrotic and tumor core and an invasive periphery. METHODS: Here, we performed a proteomics analysis of laser-capture micro-dissected glioblastoma core and invasive areas of patient-derived xenografts. RESULTS: Bioinformatics analysis identified enriched proteins in central and invasive tumor areas. Novel markers of invasion were identified, the genes proteolipid protein 1 (PLP1) and Dynamin-1 (DNM1), which were subsequently validated in tumors and by functional assays. CONCLUSIONS: In summary, our results identify new networks and molecules that may play an important role in glioblastoma development and may constitute potential novel therapeutic targets.

8.
Nat Commun ; 10(1): 4521, 2019 10 04.
Artigo em Inglês | MEDLINE | ID: mdl-31586061

RESUMO

Designing highly specific modulators of protein-protein interactions (PPIs) is especially challenging in the context of multiple paralogs and conserved interaction surfaces. In this case, direct generation of selective and competitive inhibitors is hindered by high similarity within the evolutionary-related protein interfaces. We report here a strategy that uses a semi-rational approach to separate the modulator design into two functional parts. We first achieve specificity toward a region outside of the interface by using phage display selection coupled with molecular and cellular validation. Highly selective competition is then generated by appending the more degenerate interaction peptide to contact the target interface. We apply this approach to specifically bind a single PDZ domain within the postsynaptic protein PSD-95 over highly similar PDZ domains in PSD-93, SAP-97 and SAP-102. Our work provides a paralog-selective and domain specific inhibitor of PSD-95, and describes a method to efficiently target other conserved PPI modules.


Assuntos
Anticorpos/química , Domínios PDZ , Peptídeos/química , Engenharia de Proteínas , Mapas de Interação de Proteínas/efeitos dos fármacos , Animais , Anticorpos/farmacologia , Células COS , Chlorocebus aethiops , Proteína 4 Homóloga a Disks-Large/antagonistas & inibidores , Proteína 4 Homóloga a Disks-Large/metabolismo , Desenho de Fármacos , Mapeamento de Epitopos , Modelos Moleculares , Biblioteca de Peptídeos , Peptídeos/farmacologia , Ligação Proteica , Proteínas Recombinantes/metabolismo
9.
Metabolomics ; 11(6): 1587-1597, 2015.
Artigo em Inglês | MEDLINE | ID: mdl-26491418

RESUMO

Metabolomics has become a crucial phenotyping technique in a range of research fields including medicine, the life sciences, biotechnology and the environmental sciences. This necessitates the transfer of experimental information between research groups, as well as potentially to publishers and funders. After the initial efforts of the metabolomics standards initiative, minimum reporting standards were proposed which included the concepts for metabolomics databases. Built by the community, standards and infrastructure for metabolomics are still needed to allow storage, exchange, comparison and re-utilization of metabolomics data. The Framework Programme 7 EU Initiative 'coordination of standards in metabolomics' (COSMOS) is developing a robust data infrastructure and exchange standards for metabolomics data and metadata. This is to support workflows for a broad range of metabolomics applications within the European metabolomics community and the wider metabolomics and biomedical communities' participation. Here we announce our concepts and efforts asking for re-engagement of the metabolomics community, academics and industry, journal publishers, software and hardware vendors, as well as those interested in standardisation worldwide (addressing missing metabolomics ontologies, complex-metadata capturing and XML based open source data exchange format), to join and work towards updating and implementing metabolomics standards.

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