Compositions and methods for modeling saccharomyces cerevisiae metabolism
申请人:The Regents of The University of California
公开号:EP2463654A1
公开(公告)日:2012-06-13
The invention provides an in silica model for determining a S. cerevisiae physiological function. The model includes a data structure relating a plurality of S. cerevisiae reactants to a plurality of S. cerevisiae reactions, a constraint set for the plurality of S. cerevisiae reactions, and commands for determining a distribution of flux through the reactions that is predictive of a S. cerevisiae physiological function. A model of the invention can further include a gene database containing information characterizing the associated gene or genes. The invention further provides methods for making an in silica S. cerevisiae model and methods for determining a S. cerevisiae physiological function using a model of the invention. The invention provides an in silica model for determining a S. cerevisiae physiological function. The model includes a data structure relating a plurality of S. cerevisiae reactants to a plurality of S. cerevisiae reactions, a constraint set for the plurality of S. cerevisiae reactions, and commands for determining a distribution of flux through the reactions that is predictive of a S. cerevisiae physiological function. A model of the invention can further include a gene database containing information characterizing the associated gene or genes. The invention further provides methods for making an in silica S. cerevisiae model and methods for determining a S. cerevisiae physiological function using a model of the invention.
MASSIVELY PARALLEL ON-CHIP CONSTRUCTION OF SYNTHETIC MICROBIAL COMMUNITIES
申请人:MASSACHUSETTS INSTITUTE OF TECHNOLOGY
公开号:US20220228190A1
公开(公告)日:2022-07-21
The present disclosure relates to compositions and methods for combinatorial assessment of nanoscale droplets, as specifically exemplified by massively parallel assessment of spatially-directed (while agnostic as to precise droplet content) combinations of droplets harboring distinct and independently identifiable microbial types and/or chemical compounds or mixtures. More particularly, the disclosure relates to a platform and methodologies for identifying advantageous (including synergistic, additive, etc.) microbial interactions and/or chemical compound or mixture interactions with microbes in a manner that allows for binary, trinary, etc. combinatorial assessments to be performed across a range of many discrete input types of microbes (e.g., 6-16 or more discrete input microbial types), to an extent capable of approaching comprehensive sampling and measurement of microbial community combinations from a selected panel of microbial inputs, optionally also in the presence of chemical compounds or mixtures (e.g., test compounds or mixtures for antimicrobial effect).