RESUMO
Here, we present a generalized method of guide RNA "tuning" that enables Cas9 to discriminate between two target sites that differ by a single-nucleotide polymorphism. We employ our methodology to generate an in vivo mutation prevention system in which Cas9 actively restricts the occurrence of undesired gain-of-function mutations within a population of engineered organisms. We further demonstrate that the system is scalable to a multitude of targets and that the general tuning and prevention concepts are portable across engineered Cas9 variants and Cas9 orthologs. Finally, we show that the mutation prevention system maintains robust activity even when placed within the complex environment of the mouse gastrointestinal tract.
Assuntos
Sistemas CRISPR-Cas , Farmacorresistência Bacteriana/genética , Escherichia coli/genética , Genômica/métodos , Mutação , RNA Guia de Cinetoplastídeos , Animais , Antibióticos Antituberculose/farmacologia , Escherichia coli/metabolismo , Genoma Bacteriano , Camundongos , Rifampina/farmacologiaRESUMO
Polyhydroxyalkanoates (PHAs) could be used to make sustainable, biodegradable plastics. However, the precise and accurate mechanistic modeling of PHA biosynthesis, especially medium-chain-length PHA (mcl-PHA), for yield improvement remains a challenge to biology. PHA biosynthesis is typically triggered by nitrogen limitation and tends to peak at an optimal carbon-to-nitrogen (C/N) ratio. Specifically, simulation of the underlying dynamic regulation mechanisms for PHA bioprocess is a bottleneck owing to surfeit model complexity and current modeling philosophies for uncertainty. To address this issue, we proposed a quantum-like decision-making model to encode gene expression and regulation events as hidden layers by the general transformation of a density matrix, which uses the interference of probability amplitudes to provide an empirical-level description for PHA biosynthesis. We implemented our framework modeling the biosynthesis of mcl-PHA in Pseudomonas putida with respect to external C/N ratios, showing its optimization production at maximum PHA production of 13.81% cell dry mass (CDM) at the C/N ratio of 40:1. The results also suggest the degree of P. putida's preference in channeling carbon towards PHA production as part of the bacterium's adaptative behavior to nutrient stress using quantum formalism. Generic parameters (kD, kN and theta θ) obtained based on such quantum formulation, representing P. putida's PHA biosynthesis with respect to external C/N ratios, was discussed. This work offers a new perspective on the use of quantum theory for PHA production, demonstrating its application potential for other bioprocesses.
Assuntos
Nitrogênio , Poli-Hidroxialcanoatos , Pseudomonas putida , Pseudomonas putida/metabolismo , Pseudomonas putida/genética , Poli-Hidroxialcanoatos/biossíntese , Poli-Hidroxialcanoatos/metabolismo , Nitrogênio/metabolismo , Carbono/metabolismo , Teoria Quântica , Nutrientes/metabolismo , Modelos BiológicosRESUMO
The Biological Macromolecular Crystallization Database (BMCD) has been a publicly available resource since 1988, providing a curated archive of information on crystal growth for proteins and other biological macromolecules. The BMCD content has recently been expanded to include 14 372 crystal entries. The resource continues to be freely available at http://xpdb.nist.gov:8060/BMCD4. In addition, the software has been adapted to support the Java-based Lucene query language, enabling detailed searching over specific parameters, and explicit search of parameter ranges is offered for five numeric variables. Extensive tools have been developed for import and handling of data from the RCSB Protein Data Bank. The updated BMCD is called version 4.02 or BMCD4. BMCD4 entries have been expanded to include macromolecule sequence, enabling more elaborate analysis of relations among protein properties, crystal-growth conditions and the geometric and diffraction properties of the crystals. The BMCD version 4.02 contains greatly expanded content and enhanced search capabilities to facilitate scientific analysis and design of crystal-growth strategies.
Assuntos
Bases de Dados de Proteínas , Complexos Multiproteicos/química , Proteínas/química , Animais , Cristalização , Cristalografia por Raios X , Sistemas de Gerenciamento de Base de Dados , Humanos , Linguagens de ProgramaçãoRESUMO
The Personal Genome Project (PGP) is an effort to enroll many participants to create an open-access repository of genome, health and trait data for research. However, PGP participants are not enrolled for studying any specific traits and participants choose the phenotypes to disclose. To measure the extent and willingness and to encourage and guide participants to contribute phenotypes, we developed an algorithm to score and rank the phenotypes and participants of the PGP. The scoring algorithm calculates the participation index (P-index) for every participant, where 0 indicates no reported phenotypes and 100 indicate complete phenotype reporting. We calculated the P-index for all 5,015 participants in the PGP and they ranged from 0 to 96.7. We found that participants mainly have either high scores (P-index > 90, 29.5%) or low scores (P-index < 10, 57.8%). While, there are significantly more males than female participants (1,793 versus 1,271), females tend to have on average higher P-indexes (P = 0.015). We also reported the P-indexes of participants based on demographics and states like Missouri and Massachusetts have better P-indexes than states like Utah and Minnesota. The P-index can therefore be used as an unbiased way to measure and rank participant's phenotypic contribution towards the PGP.
Assuntos
Fenótipo , Algoritmos , Estudos de Coortes , Doença , Feminino , Genoma Humano , Geografia , Humanos , Masculino , Característica Quantitativa Herdável , Inquéritos e Questionários , Estados UnidosRESUMO
The Biological Macromolecule Crystallization Database (BMCD) archives crystallization data from published reports for all forms of biological macromolecules that have produced crystals suitable for X-ray diffraction studies. The information includes the crystallization conditions, crystal data, comments about the crystallization procedure and information on the biological macromolecule or biological macromolecule complex. Crystallization procedures, including fast screens and more general procedures, can be developed effectively using this web-based resource (http://wwwbmcd.nist.gov:8080/bmcd/bmcd.html).