RESUMO
Developing molecular strategies to manipulate gene expression in trypanosomatids is challenging, particularly with respect to the unique gene expression mechanisms adopted by these unicellular parasites, such as polycistronic mRNA transcription and multi-gene families. In the case of Trypanosoma cruzi (T. cruzi), the causative agent of Chagas Disease, the lack of RNA interference machinery further complicated functional genetic studies important for understanding parasitic biology and developing biomarkers and potential therapeutic targets. Therefore, alternative methods of performing knockout and/or endogenous labelling experiments were developed to identify and understand the function of proteins for survival and interaction with the host. In this review, we present the main tools for the genetic manipulation of T. cruzi, focusing on the Clustered Regularly Interspaced Short Palindromic Repeats Cas9-associated system technique widely used in this organism. Moreover, we highlight the importance of using these tools to elucidate the function of uncharacterized and glycosylated proteins. Further developments of these technologies will allow the identification of new biomarkers, therapeutic targets and potential vaccines against Chagas disease with greater efficiency and speed.
Assuntos
Regulação da Expressão Gênica , Trypanosoma cruzi , Trypanosoma cruzi/genética , Trypanosoma cruzi/metabolismo , Humanos , Doença de Chagas , Sistemas CRISPR-Cas , Animais , Proteínas de Protozoários/genética , Proteínas de Protozoários/metabolismoRESUMO
A key challenge for domesticating alternative cultivable microorganisms with biotechnological potential lies in the development of innovative technologies. Within this framework, a myriad of genetic tools has flourished, allowing the design and manipulation of complex synthetic circuits and genomes to become the general rule in many laboratories rather than the exception. More recently, with the development of novel technologies such as DNA automated synthesis/sequencing and powerful computational tools, molecular biology has entered the synthetic biology era. In the beginning, most of these technologies were established in traditional microbial models (known as chassis in the synthetic biology framework) such as Escherichia coli and Saccharomyces cerevisiae, enabling fast advances in the field and the validation of fundamental proofs of concept. However, it soon became clear that these organisms, although extremely useful for prototyping many genetic tools, were not ideal for a wide range of biotechnological tasks due to intrinsic limitations in their molecular/physiological properties. Over the last decade, researchers have been facing the great challenge of shifting from these model systems to non-conventional chassis with endogenous capacities for dealing with specific tasks. The key to address these issues includes the generation of narrow and broad host plasmid-based molecular tools and the development of novel methods for engineering genomes through homologous recombination systems, CRISPR/Cas9 and other alternative methods. Here, we address the most recent advances in plasmid-based tools for the construction of novel cell factories, including a guide for helping with "build-your-own" microbial host.
Assuntos
Biotecnologia , Escherichia coli , Plasmídeos , Saccharomyces cerevisiae , Biologia SintéticaRESUMO
The realization of a sustainable bioeconomy requires our ability to understand and engineer complex design principles for the development of platform organisms capable of efficient conversion of cheap and sustainable feedstocks (e.g., sunlight, CO2 , and nonfood biomass) into biofuels and bioproducts at sufficient titers and costs. For model microbes, such as Escherichia coli, advances in DNA reading and writing technologies are driving the adoption of new paradigms for engineering biological systems. Unfortunately, microbes with properties of interest for the utilization of cheap and renewable feedstocks, such as photosynthesis, autotrophic growth, and cellulose degradation, have very few, if any, genetic tools for metabolic engineering. Therefore, it is important to develop "design rules" for building a genetic toolbox for novel microbes. Here, we present an overview of our current understanding of these rules for the genetic manipulation of prokaryotic microbes and the available genetic tools to expand our ability to genetically engineer nonmodel systems.
Assuntos
Archaea/genética , Archaea/metabolismo , Bactérias/genética , Bactérias/metabolismo , Edição de Genes/métodos , Engenharia Metabólica/métodosRESUMO
Genetic studies have a central role in the study of multiple myeloma (MM), as they become a critical component in the risk-based stratification of the disease. Significant efforts have been made to identify genetic changes and signatures that can predict clinical outcome and include them in the routine clinical care. Fluorescence in situ hybridization (FISH) still remains the most used genetic technique in clinical practice, mostly due to its very straightforward implementation and the simplicity of data analysis. The advent of high-resolution genomics (i.e. array CGH, exome and whole genome sequencing) and transcriptomics tests (i.e. gene expression profiling - GEP, and mRNA sequencing) provide a comprehensive analysis of the already defined genetic prognostic factors and are helpful tools for the identification of potential novel disease markers on the MM tumor clone. Indeed, GEP has been successfully implemented in MM as a risk-stratification tool, holding the greatest power in outcome discrimination. Nevertheless, some technical and logistic intricacies (need of a highly purified tumor clone, cost of the assay and complexity of data analysis) need to be considered before the definitive incorporation of high-throughput technologies in routine clinical tests. Until then, FISH remains the standard tool for genomic abnormality detection and disease prognostication.
Assuntos
Mieloma Múltiplo/genética , Medição de Risco/métodos , Perfilação da Expressão Gênica/métodos , Humanos , Hibridização in Situ Fluorescente/métodos , Mieloma Múltiplo/diagnóstico , Prognóstico , Translocação GenéticaRESUMO
Los estudios genéticos han alcanzado un papel central en el estudio del mieloma múltiple (MM), al convertirse en un componente crítico en la estratificación basada en el riesgo de la enfermedad. Se han hecho grandes esfuerzos para identificar cambios genéticos que puedan predecir el resultado clínico e incluirlos en la práctica clínica diaria. La hibridización in situ fluorescente (FISH) es todavía la técnica genética más utilizada en la práctica clínica, mayormente debido a su sencilla implementación y su simplicidad para el análisis de datos. El advenimiento de la genómica (hibridización genómica comparativa, secuenciación exónica o genómica completa) y del transcriptoma de alta resolución (perfiles de expresión de genes - GEP y secuenciación de ARNm) proveen un análisis exhaustivo de los ya definidos factores pronósticos genéticos y son herramientas útiles para la identificación de potenciales nuevos marcadores pronósticos de enfermedad en el clon tumoral de MM. Más aún, GEP ha sido exitosamente implementado en MM como una herramienta de estratificación de riesgo, siendo la de mayor poder de discriminación de resultados. De todas maneras, algunos aspectos técnicos y logísticos complejos (necesidad de una elevada purificación del clon tumoral, costo de los ensayos y complejidad en los análisis de los datos) deben ser considerados antes de la incorporación definitiva de estas tecnologías de alto rendimiento dentro de los ensayos clínicos de rutina. Hasta entonces, FISH continúa siendo la herramienta estándar para la detección de anormalidades genéticas y de valoración pronóstico de enfermedad.(AU)
Genetic studies have a central role in the study of multiple myeloma (MM), as they become a critical component in the risk-based stratification of the disease. Significant efforts have been made to identify genetic changes and signatures that can predict clinical outcome and include them in the routine clinical care. Fluorescence in situ hybridization (FISH) still remains the most used genetic technique in clinical practice, mostly due to its very straightforward implementation and the simplicity of data analysis. The advent of high-resolution genomics (i.e. array CGH, exome and whole genome sequencing) and transcriptomics tests (i.e. gene expression profiling - GEP, and mRNA sequencing) provide a comprehensive analysis of the already defined genetic prognostic factors and are helpful tools for the identification of potential novel disease markers on the MM tumor clone. Indeed, GEP has been successfully implemented in MM as a risk-stratification tool, holding the greatest power in outcome discrimination. Nevertheless, some technical and logistic intricacies (need of a highly purified tumor clone, cost of the assay and complexity of data analysis) need to be considered before the definitive incorporation of high-throughput technologies in routine clinical tests. Until then, FISH remains the standard tool for genomic abnormality detection and disease prognostication.(AU)
Assuntos
Humanos , Mieloma Múltiplo/genética , Medição de Risco/métodos , Perfilação da Expressão Gênica/métodos , Hibridização in Situ Fluorescente/métodos , Mieloma Múltiplo/diagnóstico , Prognóstico , Translocação GenéticaRESUMO
Los estudios genéticos han alcanzado un papel central en el estudio del mieloma múltiple (MM), al convertirse en un componente crítico en la estratificación basada en el riesgo de la enfermedad. Se han hecho grandes esfuerzos para identificar cambios genéticos que puedan predecir el resultado clínico e incluirlos en la práctica clínica diaria. La hibridización in situ fluorescente (FISH) es todavía la técnica genética más utilizada en la práctica clínica, mayormente debido a su sencilla implementación y su simplicidad para el análisis de datos. El advenimiento de la genómica (hibridización genómica comparativa, secuenciación exónica o genómica completa) y del transcriptoma de alta resolución (perfiles de expresión de genes - GEP y secuenciación de ARNm) proveen un análisis exhaustivo de los ya definidos factores pronósticos genéticos y son herramientas útiles para la identificación de potenciales nuevos marcadores pronósticos de enfermedad en el clon tumoral de MM. Más aún, GEP ha sido exitosamente implementado en MM como una herramienta de estratificación de riesgo, siendo la de mayor poder de discriminación de resultados. De todas maneras, algunos aspectos técnicos y logísticos complejos (necesidad de una elevada purificación del clon tumoral, costo de los ensayos y complejidad en los análisis de los datos) deben ser considerados antes de la incorporación definitiva de estas tecnologías de alto rendimiento dentro de los ensayos clínicos de rutina. Hasta entonces, FISH continúa siendo la herramienta estándar para la detección de anormalidades genéticas y de valoración pronóstico de enfermedad.
Genetic studies have a central role in the study of multiple myeloma (MM), as they become a critical component in the risk-based stratification of the disease. Significant efforts have been made to identify genetic changes and signatures that can predict clinical outcome and include them in the routine clinical care. Fluorescence in situ hybridization (FISH) still remains the most used genetic technique in clinical practice, mostly due to its very straightforward implementation and the simplicity of data analysis. The advent of high-resolution genomics (i.e. array CGH, exome and whole genome sequencing) and transcriptomics tests (i.e. gene expression profiling - GEP, and mRNA sequencing) provide a comprehensive analysis of the already defined genetic prognostic factors and are helpful tools for the identification of potential novel disease markers on the MM tumor clone. Indeed, GEP has been successfully implemented in MM as a risk-stratification tool, holding the greatest power in outcome discrimination. Nevertheless, some technical and logistic intricacies (need of a highly purified tumor clone, cost of the assay and complexity of data analysis) need to be considered before the definitive incorporation of high-throughput technologies in routine clinical tests. Until then, FISH remains the standard tool for genomic abnormality detection and disease prognostication.