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At least 55 records · Page 3

Genetically modified yeast species, and fermentation processes using genetically modified yeast

Yeast cells are transformed with an exogenous xylose isomerase gene. Additional genetic modifications enhance the ability of the transformed cells to ferment xylose to ethanol or other desired fermentation products. Those modifications include deletion of non-specific aldose reductase gene(s), deletion of xylitol dehydrogenase gene(s) and/or overexpression of xylulokinase.

60 APPLIED LIFE SCIENCES↗

Genetically modified yeast species, and fermentation processes using genetically modified yeast

Yeast cells are transformed with an exogenous xylose isomerase gene. Additional genetic modifications enhance the ability of the transformed cells to ferment xylose to ethanol or other desired fermentation products. Those modifications include deletion of non-specific or specific aldose reductase gene(s), deletion of xylitol dehydrogenase gene(s) and/or overexpression of xylulokinase.

09 BIOMASS FUELS↗

Genetically modified yeast species, and fermentation processes using genetically modified yeast

Yeast cells are transformed with an exogenous xylose isomerase gene. Additional genetic modifications enhance the ability of the transformed cells to ferment xylose to ethanol or other desired fermentation products. Those modifications include deletion of non-specific or specific aldose reductase gene(s), deletion of xylitol dehydrogenase gene(s) and/or overexpression of xylulokinase.

59 BASIC BIOLOGICAL SCIENCES↗

Data for Spatial Analysis of Cell Patterning to Aid Genetic and Phenotypic Understanding of Grass Stomatal Density: A Case Study in Maize

Biological processes involve complex hierarchies where composite traits result from multiple component traits. However, holistically understanding of how sets of component traits interact to underpin genotype-to-phenotype relationships is generally lacking. Stomatal density (SD) is a tractable model system for exploring how high-throughput phenotyping (HTP) data could be exploited by a new spatial analysis approach to better understand a developmentally and functionally important trait. SD is a composite trait, resulting from various components related to cell identity and size, which are themselves governed by a series of spatio-developmental processes. Data from 192 recombinant inbred lines of maize [Zea mays (L.)] were analyzed by a new stomatal patterning phenotype (SPP) to (1) describe the average spatial probability distribution of the nearest neighboring stomata; (2) derive a core set of component traits related to cell size, cell packing, and positional probabilities; (3) build a structural equation model of component traits underlying SD; and (4) identify stomatal patterning quantitative trait loci (QTL). The core set of SPP-derived traits explained 74% of the variation in SD. Analyzing SPP component traits allowed some loci previously identified as generic SD QTL to be recognized as specific to lateral versus longitudinal elements of stomatal patterning. Therefore, this study highlights how novel insights can be gained by decomposing a composite trait (e.g., SD) into a set of component traits that were present in HTP data but not previously exploited.

AI/ML↗

Systematic discovery of pseudomonad genetic factors involved in sensitivity to tailocins

Tailocins are bactericidal protein complexes produced by a wide variety of bacteria that kill closely related strains and may play a role in microbial community structure. Thanks to their high specificity, tailocins have been proposed as precision antibacterial agents for therapeutic applications. Compared to tailed phages, with whom they share an evolutionary and morphological relationship, bacterially produced tailocins kill their host upon production but producing strains display resistance to self-intoxication. Though lipopolysaccharide (LPS) has been shown to act as a receptor for tailocins, the breadth of factors involved in tailocin sensitivity, and the mechanisms behind resistance to self-intoxication, remain unclear. Here, we employed genome-wide screens in four non-model pseudomonads to identify mutants with altered fitness in the presence of tailocins produced by closely related pseudomonads. Our mutant screens identified O-antigen composition and display as most important in defining sensitivity to our tailocins. In addition, the screens suggest LPS thinning as a mechanism by which resistant strains can become more sensitive to tailocins. Furthermore, we validate many of these novel findings, and extend these observations of tailocin sensitivity to 130 genome-sequenced pseudomonads. This work offers insights into tailocin–bacteria interactions, informing the potential use of tailocins in microbiome manipulation and antibacterial therapy.

59 BASIC BIOLOGICAL SCIENCES↗