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1.
Nat Chem Biol ; 16(1): 60-68, 2020 01.
Artículo en Inglés | MEDLINE | ID: mdl-31768033

RESUMEN

Genome mining has become a key technology to exploit natural product diversity. Although initially performed on a single-genome basis, the process is now being scaled up to mine entire genera, strain collections and microbiomes. However, no bioinformatic framework is currently available for effectively analyzing datasets of this size and complexity. In the present study, a streamlined computational workflow is provided, consisting of two new software tools: the 'biosynthetic gene similarity clustering and prospecting engine' (BiG-SCAPE), which facilitates fast and interactive sequence similarity network analysis of biosynthetic gene clusters and gene cluster families; and the 'core analysis of syntenic orthologues to prioritize natural product gene clusters' (CORASON), which elucidates phylogenetic relationships within and across these families. BiG-SCAPE is validated by correlating its output to metabolomic data across 363 actinobacterial strains and the discovery potential of CORASON is demonstrated by comprehensively mapping biosynthetic diversity across a range of detoxin/rimosamide-related gene cluster families, culminating in the characterization of seven detoxin analogues.


Asunto(s)
Actinobacteria/genética , Vías Biosintéticas/genética , Biología Computacional/métodos , Genoma Bacteriano , Algoritmos , Productos Biológicos , Análisis por Conglomerados , Minería de Datos/métodos , Genómica , Metabolómica , Microbiota , Familia de Multigenes , Filogenia , Reproducibilidad de los Resultados , Programas Informáticos
2.
Leukemia ; 2024 Sep 04.
Artículo en Inglés | MEDLINE | ID: mdl-39232206

RESUMEN

Pediatric acute lymphoblastic leukemia (ALL) is marked by low mutational load at initial diagnosis, which increases at relapse. To determine which processes are active in (relapsed) ALL and how they behave during disease progression before and after therapy, we performed whole genome sequencing on 97 tumor samples of 29 multiply relapsed ALL patients. Mutational load increased upon relapse in 28 patients and upon every subsequent relapse in 22 patients. In addition to two clock-like mutational processes, we identified UV-like damage, APOBEC activity, reactive oxygen species, thiopurine-associated damage and an unknown therapy component as drivers of mutagenesis. Mutational processes often affected patients over longer time periods, but could also occur in isolated events, suggesting the requirement of additional triggers. Thiopurine exposure was the most prominent source of new mutations in relapse, affecting over half of the studied patients in first and/or later relapse and causing potential relapse-driving mutations in multiple patients. Our data demonstrate that multiple mutational processes frequently act in parallel as prominent secondary drivers with dynamic activity during ALL development and progression.

3.
Assay Drug Dev Technol ; 14(8): 439-452, 2016 10.
Artículo en Inglés | MEDLINE | ID: mdl-27636821

RESUMEN

High-content screening (HCS) can generate large multidimensional datasets and when aligned with the appropriate data mining tools, it can yield valuable insights into the mechanism of action of bioactive molecules. However, easy-to-use data mining tools are not widely available, with the result that these datasets are frequently underutilized. Here, we present HC StratoMineR, a web-based tool for high-content data analysis. It is a decision-supportive platform that guides even non-expert users through a high-content data analysis workflow. HC StratoMineR is built by using My Structured Query Language for storage and querying, PHP: Hypertext Preprocessor as the main programming language, and jQuery for additional user interface functionality. R is used for statistical calculations, logic and data visualizations. Furthermore, C++ and graphical processor unit power is diffusely embedded in R by using the rcpp and rpud libraries for operations that are computationally highly intensive. We show that we can use HC StratoMineR for the analysis of multivariate data from a high-content siRNA knock-down screen and a small-molecule screen. It can be used to rapidly filter out undesirable data; to select relevant data; and to perform quality control, data reduction, data exploration, morphological hit picking, and data clustering. Our results demonstrate that HC StratoMineR can be used to functionally categorize HCS hits and, thus, provide valuable information for hit prioritization.


Asunto(s)
Minería de Datos/métodos , Bases de Datos Factuales/estadística & datos numéricos , Internet , Estadística como Asunto/métodos , Análisis por Conglomerados , Células HeLa , Humanos , Células MCF-7
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