10 research outputs found
High production of fatty alcohols in Escherichia coli with fatty acid starvation
Background: Microbial biofuel synthesis attracting increasing attention. Great advances have been made in producing fatty alcohols from fatty acyl-CoAs and fatty acids in Escherichia coli. However, the low titers and limited knowledge regarding the basic characteristics of fatty alcohols, such as location and toxicity, have hampered large-scale industrialization. Further research is still needed.</p
TALENs-Assisted Multiplex Editing for Accelerated Genome Evolution To Improve Yeast Phenotypes
Genome
editing is an important tool for building novel genotypes
with a desired phenotype. However, the fundamental challenge is to
rapidly generate desired alterations on a genome-wide scale. Here,
we report TALENs (transcription activator-like effector nucleases)-assisted
multiplex editing (TAME), based on the interaction of designed TALENs
with the DNA sequences between the critical TATA and GC boxes, for
generating multiple targeted genomic modifications. Through iterative
cycles of TAME to induce abundant semirational <i>indels</i> coupled with efficient screening using a reporter, the targeted
fluorescent trait can be continuously and rapidly improved by accumulating
multiplex beneficial genetic modifications in the evolving yeast genome.
To further evaluate its efficiency, we also demonstrate the application
of TAME for significantly improving ethanol tolerance of yeast in
a short amount of time. Therefore, TAME is a broadly generalizable
platform for accelerated genome evolution to rapidly improve yeast
phenotypes
Additional file 1: of Genome shuffling of the nonconventional yeast Pichia anomala for improved sugar alcohol production
Fig. S1. The colorimetric assay of sugar alcohols. a The flow chart of the colorimetric method for sugar alcohol screening. b The correlation of the two sugar alcohol-detection methods by linear regression. H and C represent the HPLC and colorimetric methods, respectively. Fig. S2. Comparison of the DNA content among the parent and shuffled strains, as determined by flow cytometry. The DNA content is shown for a haploid control strain S. cerevisiae BY4741, haploid parent strain P. anomala HP, diploid strain P. anomala TIB-x229 and shuffled strains GS2-1, GS2-2 and GS2-3
An NGS-Independent Strategy for Proteome-Wide Identification of Single Amino Acid Polymorphisms by Mass Spectrometry
Detection
of proteins containing single amino acid polymorphisms
(SAPs) encoded by nonsynonymous SNPs (nsSNPs) can aid researchers
in studying the functional significance of protein variants. Most
proteogenomic approaches for large-scale SAPs mapping require construction
of a sample-specific database containing protein variants predicted
from the next-generation sequencing (NGS) data. Searching shotgun
proteomic data sets against these NGS-derived databases allowed for
identification of SAP peptides, thus validating the proteome-level
sequence variation. Contrary to the conventional approaches, our study
presents a novel strategy for proteome-wide SAP detection without
relying on sample-specific NGS data. By searching a deep-coverage
proteomic data set from an industrial thermotolerant yeast strain
using our strategy, we identified 337 putative SAPs compared to the
reference genome. Among the SAP peptides identified with stringent
criteria, 85.2% of SAP sites were validated using whole-genome sequencing
data obtained for this organism, which indicates high accuracy of
SAP identification with our strategy. More interestingly, for certain
SAP peptides that cannot be predicted by genomic sequencing, we used
synthetic peptide standards to verify expression of peptide variants
in the proteome. Our study has provided a unique tool for proteogenomics
to enable proteome-wide direct SAP identification and capture nongenetic
protein variants not linked to nsSNPs
Distinct Proteome Remodeling of Industrial <i>Saccharomyces cerevisiae</i> in Response to Prolonged Thermal Stress or Transient Heat Shock
To gain a deep understanding of yeast-cell
response to heat stress,
multiple laboratory strains have been intensively studied via genome-wide
expression analysis for the mechanistic dissection of classical heat-shock
response (HSR). However, robust industrial strains of <i>Saccharomyces
cerevisiae</i> have hardly been explored in global analysis for
elucidation of the mechanism of thermotolerant response (TR) during
fermentation. Herein, we employed data-independent acquisition and
sequential window acquisition of all theoretical mass spectra based
proteomic workflows to characterize proteome remodeling of an industrial
strain, ScY01, responding to prolonged thermal stress or transient
heat shock. By comparing the proteomic signatures of ScY01 in TR versus
HSR as well as the HSR of the industrial strain versus a laboratory
strain, our study revealed disparate response mechanisms of ScY01
during thermotolerant growth or under heat shock. In addition, through
proteomics data-mining for decoding transcription factor interaction
networks followed by validation experiments, we uncovered the functions
of two novel transcription factors, Mig1 and Srb2, in enhancing the
thermotolerance of the industrial strain. This study has demonstrated
that accurate and high-throughput quantitative proteomics not only
provides new insights into the molecular basis for complex microbial
phenotypes but also pinpoints upstream regulators that can be targeted
for improving the desired traits of industrial microorganisms
Distinct Proteome Remodeling of Industrial <i>Saccharomyces cerevisiae</i> in Response to Prolonged Thermal Stress or Transient Heat Shock
To gain a deep understanding of yeast-cell
response to heat stress,
multiple laboratory strains have been intensively studied via genome-wide
expression analysis for the mechanistic dissection of classical heat-shock
response (HSR). However, robust industrial strains of <i>Saccharomyces
cerevisiae</i> have hardly been explored in global analysis for
elucidation of the mechanism of thermotolerant response (TR) during
fermentation. Herein, we employed data-independent acquisition and
sequential window acquisition of all theoretical mass spectra based
proteomic workflows to characterize proteome remodeling of an industrial
strain, ScY01, responding to prolonged thermal stress or transient
heat shock. By comparing the proteomic signatures of ScY01 in TR versus
HSR as well as the HSR of the industrial strain versus a laboratory
strain, our study revealed disparate response mechanisms of ScY01
during thermotolerant growth or under heat shock. In addition, through
proteomics data-mining for decoding transcription factor interaction
networks followed by validation experiments, we uncovered the functions
of two novel transcription factors, Mig1 and Srb2, in enhancing the
thermotolerance of the industrial strain. This study has demonstrated
that accurate and high-throughput quantitative proteomics not only
provides new insights into the molecular basis for complex microbial
phenotypes but also pinpoints upstream regulators that can be targeted
for improving the desired traits of industrial microorganisms