scholarly journals Optimized gene expression from bacterial chromosome by high-throughput integration and screening

2021 ◽  
Vol 7 (7) ◽  
pp. eabe1767
Author(s):  
Tatyana E. Saleski ◽  
Meng Ting Chung ◽  
David N. Carruthers ◽  
Azzaya Khasbaatar ◽  
Katsuo Kurabayashi ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Throughput ◽  
High Throughput Screening ◽  
Efficient Production ◽  
Expression Levels ◽  
Pathway Gene ◽  
Pathway Expression ◽  
Wide Range ◽  
Cell To Cell Variability ◽  
Gene Expression Levels

Chromosomal integration of recombinant genes is desirable compared with expression from plasmids due to increased stability, reduced cell-to-cell variability, and elimination of the need for antibiotics for plasmid maintenance. Here, we present a new approach for tuning pathway gene expression levels via random integration and high-throughput screening. We demonstrate multiplexed gene integration and expression-level optimization for isobutanol production in Escherichia coli. The integrated strains could, with far lower expression levels than plasmid-based expression, produce high titers (10.0 ± 0.9 g/liter isobutanol in 48 hours) and yields (69% of the theoretical maximum). Close examination of pathway expression in the top-performing, as well as other isolates, reveals the complexity of cellular metabolism and regulation, underscoring the need for precise optimization while integrating pathway genes into the chromosome. We expect this method for pathway integration and optimization can be readily extended to a wide range of pathways and chassis to create robust and efficient production strains.

scholarly journals Optimized gene expression from bacterial chromosome by high-throughput integration and screening

2020 ◽  
Author(s):  
Tatyana E Saleski ◽  
Meng Ting Chung ◽  
David N Carruthers ◽  
Azzaya Khasbaatar ◽  
Katsuo Kurabayashi ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Throughput ◽  
High Throughput Screening ◽  
Efficient Production ◽  
Expression Levels ◽  
Pathway Gene ◽  
Pathway Expression ◽  
Wide Range ◽  
Gene Integration ◽  
Cell To Cell Variability

Chromosomal integration of recombinant genes is desirable compared to expression from plasmids due to increased stability, reduced cell-to-cell variability, and the elimination of antibiotics for plasmid maintenance. Here, we present a new approach for tuning pathway gene expression levels via random integrations and high-throughput screening. We demonstrate multiplexed gene integration and expression-level optimization for isobutanol production in Escherichia coli. The integrated strains could, with significantly lower expression levels than plasmid-based expression, produce high titers (10.0 +/- 0.9 g/L isobutanol in 48 h) and yields (69 % of the theoretical maximum). Close examination of pathway expression in the top-performing, as well as other isolates, reveals the complexity of cellular metabolism and regulation, underscoring the need for precise optimization while integrating pathway genes into the chromosome. We expect this new method for multiplexed pathway gene integration and expression optimization can be readily extended to a wide range of pathways and chassis to create robust and efficient production strains.

scholarly journals High-throughput mRNA sequencing of stromal cells from endometriomas and endometrium

Reproduction ◽  
2017 ◽  
Vol 154 (1) ◽  
pp. 93-100 ◽  
Author(s):  
Kadri Rekker ◽  
Merli Saare ◽  
Elo Eriste ◽  
Tõnis Tasa ◽  
Viktorija Kukuškina ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Throughput ◽  
Complement System ◽  
Stromal Cells ◽  
Cell Types ◽  
Coagulation Cascade ◽  
Expression Levels ◽  
Mrna Sequencing ◽  
Standard Design ◽  
Gene Expression Levels

The aetiology of endometriosis is still unclear and to find mechanisms behind the disease development, it is important to study each cell type from endometrium and ectopic lesions independently. The objective of this study was to uncover complete mRNA profiles in uncultured stromal cells from paired samples of endometriomas and eutopic endometrium. High-throughput mRNA sequencing revealed over 1300 dysregulated genes in stromal cells from ectopic lesions, including several novel genes in the context of endometriosis. Functional annotation analysis of differentially expressed genes highlighted pathways related to cell adhesion, extracellular matrix–receptor interaction and complement and coagulation cascade. Most importantly, we found a simultaneous upregulation of complement system components and inhibitors, indicating major imbalances in complement regulation in ectopic stromal cells. We also performed in vitro experiments to evaluate the effect of endometriosis patients’ peritoneal fluid (PF) on complement system gene expression levels, but no significant impact of PF on C3, CD55 and CFH levels was observed. In conclusion, the use of isolated stromal cells enables to determine gene expression levels without the background interference of other cell types. In the future, a new standard design studying all cell types from endometriotic lesions separately should be applied to reveal novel mechanisms behind endometriosis pathogenesis.

scholarly journals Positive-feedback, ratiometric biosensor expression improves high-throughput metabolite-producer screening efficiency in yeast

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Thomas C. Williams ◽  
Xin Xu ◽  
Martin Ostrowski ◽  
Isak S. Pretorius ◽  
Ian T. Paulsen
Keyword(s):  
Gene Expression ◽  
Synthetic Biology ◽  
High Throughput ◽  
Positive Feedback ◽  
High Throughput Screening ◽  
Transcriptional Regulator ◽  
Gfp Expression ◽  
Dynamic Regulation ◽  
Wide Range ◽  
Screening Efficiency

Biosensors are valuable and versatile tools in synthetic biology that are used to modulate gene expression in response to a wide range of stimuli. Ligand responsive transcription factors are a class of biosensor that can be used to couple intracellular metabolite concentration with gene expression to enable dynamic regulation and high-throughput metabolite producer screening. We have established the Saccharomyces cerevisiae WAR1 transcriptional regulator and PDR12 promoter as an organic acid biosensor that can be used to detect varying levels of para-hydroxybenzoic acid (PHBA) production from the shikimate pathway and output green fluorescent protein (GFP) expression in response. The dynamic range of GFP expression in response to PHBA was dramatically increased by engineering positive-feedback expression of the WAR1 transcriptional regulator from its target PDR12 promoter. In addition, the noise in GFP expression at the population-level was controlled by normalising GFP fluorescence to constitutively expressed mCherry fluorescence within each cell. These biosensor modifications increased the high-throughput screening efficiency of yeast cells engineered to produce PHBA by 5,000-fold, enabling accurate fluorescence activated cell sorting isolation of producer cells that were mixed at a ratio of 1 in 10,000 with non-producers. Positive-feedback, ratiometric transcriptional regulator expression is likely applicable to many other transcription-factor/promoter pairs used in synthetic biology and metabolic engineering for both dynamic regulation and high-throughput screening applications.

The development of the DCIS score: Scaling and normalization in the Marin General Hospital cohort.

2012 ◽  
Vol 30 (27_suppl) ◽  
pp. 190-190 ◽  
Author(s):  
Frederick L. Baehner ◽  
Steven M Butler ◽  
Carl N. Yoshizawa ◽  
Che Prasad ◽  
Diana B. Cherbavaz ◽  
...  
Keyword(s):  
Gene Expression ◽  
General Hospital ◽  
Risk Group ◽  
Recurrence Score ◽  
Low Risk ◽  
Tumor Characteristics ◽  
Clinicopathologic Characteristics ◽  
Expression Levels ◽  
Wide Range ◽  
Gene Expression Levels

190 Background: In selected low-risk patients with DCIS treated with wide local excision without radiation, the DCIS score was validated as a predictor of 10 year risk of an ipsilateral breast event (IBE - recurrence of in situ or invasive carcinoma) (p = 0.02) (Solin; SABCS 2011). As part of the development of the DCIS score, scaling from 0 to 100 and determination of risk group cutoff values was done using 100 patient DCIS samples from Marin General Hospital (MGH) selected to have a wide range of tumor characteristics. Methods: 100 patient specimens diagnosed with DCIS were provided by MGH. The Oncotype DX assay was performed, normalized expression levels for the 16 cancer related genes were determined, the DCIS Score and Recurrence Score (RS) were calculated. Distributions of the DCIS score, RS, and individual gene expression levels were described overall and by tumor characteristics. Treatment and pt outcome data were not available. Results: Samples for 96 pts had sufficient tumor and were evaluable; 47% had high nuclear grade, 52% comedo necrosis, 32% tumor size >10 mm, and 9% were ER-negative by IHC. After scaling and risk group cutoff determination, the DCIS score was low risk (0-38) for 49%, intermediate risk (39-54) for 27%, and high risk (≥55) for 24% of pts (Table). The DCIS score was widely distributed within subgroups defined by each of the clinical and pathology characteristics. Proliferation gene expression levels were low in DCIS, on average, relative to prior studies in invasive breast cancer. 92% had a proliferation gene group score <6.5, the threshold used when the RS is calculated; no threshold is used in calculating the DCIS score. Conclusions: Optimal scaling and risk cutoff determination for a wide range of all clinicopathologic characteristics provides for a wide distribution for the DCIS Score. [Table: see text]

scholarly journals Local adaptation contributes to gene expression divergence in maize

2021 ◽  
Vol 11 (2) ◽  
Author(s):  
Jennifer Blanc ◽  
Karl A G Kremling ◽  
Edward Buckler ◽  
Emily B Josephs
Keyword(s):  
Gene Expression ◽  
Local Adaptation ◽  
Cold Response ◽  
Expression Levels ◽  
Maize Populations ◽  
Maize Genotypes ◽  
Wide Range ◽  
History Of ◽  
Insight Into ◽  
Gene Expression Levels

Abstract Gene expression links genotypes to phenotypes, so identifying genes whose expression is shaped by selection will be important for understanding the traits and processes underlying local adaptation. However, detecting local adaptation for gene expression will require distinguishing between divergence due to selection and divergence due to genetic drift. Here, we adapt a QST−FST framework to detect local adaptation for transcriptome-wide gene expression levels in a population of diverse maize genotypes. We compare the number and types of selected genes across a wide range of maize populations and tissues, as well as selection on cold-response genes, drought-response genes, and coexpression clusters. We identify a number of genes whose expression levels are consistent with local adaptation and show that genes involved in stress response show enrichment for selection. Due to its history of intense selective breeding and domestication, maize evolution has long been of interest to researchers, and our study provides insight into the genes and processes important for in local adaptation of maize.

Immunofocus-PD-L1 high throughput quantitative next generation sequencing assay.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e13521-e13521
Author(s):  
Gareth Haydn Williams ◽  
Robert Paul Thatcher ◽  
Tiffany Eira Haddow ◽  
Keeda-Marie Hardisty ◽  
Marco Loddo
Keyword(s):  
Gene Expression ◽  
Next Generation Sequencing ◽  
High Throughput ◽  
Immune Cell ◽  
Next Generation ◽  
Cut Points ◽  
Expression Levels ◽  
Sequencing Platform ◽  
Generation Sequencing ◽  
Gene Expression Levels

e13521 Background: Immunohistochemical (IHC) assays are presently used as the gold standard predictive tests for immunotherapy but are compromised due to a number of potential variables. Comparative studies have demonstrated differing levels of PD-L1 staining between assays which appears independent of the antibody binding epitope. Secondly, inter-reader reliability even between expert pathologists is problematic particularly for assessment of PD-L1 positive immune cell populations. Methods: To improve predictive testing for anti PD-L1/PD1 immunotherapies we have developed and validated a Next Generation Sequencing Platform, Immunofocus, able to perform high-throughput quantitative PD-L1 gene expression levels in routine diagnostic PWET biopsies. We applied Immunofocus to a cohort of 130 NSCLCs and compared PD-L1 gene expression levels with PD-L1 IHC scores generated using the VENTANA PD-L1 (SP142) Assay. The PD-L1 IHC assessment was carried out double blinded by an independent laboratory. PD-L1 IHC scores were calculated using an algorithm combining tumour proportion score (TPS) with a PD-L1 positive immune cell (IC) score and immune cell area. Results: An exceptionally high degree of correlation was observed between the NGS PD-L1 levels with the combined PD-L1 IHC scores (P < 0.001). Therapeutic cut points for NGS PD-L1 levels were identified corresponding to PD-L1 IHC defined clinical cut points. Notably, ~20% of patients with negative PD-L1 IHC scores showed high NGS PD-L1 expression levels. We hypothesize that these cases represent false negatives and identify a cohort of patients who have shown significant response rates to anti-PD-L1/PD-directed immunotherapies. Conclusions: The Immunofocus NGS PD-L1 assay has potential to greatly improve patient selection for immunotherapy by removing the IHC assay variables and inter-reader variability which compromise current PD-L1 IHC tests while also providing standardized high throughput in the clinical setting. Immunofocus is able to integrate gene expression with somatic mutation analysis allowing capture of networks regulating the immune-checkpoint including for example adaptive and innate resistance pathways, JAK1/2 pathways, differential MHC expression, TEFF gene signature, neoantigen surrogates such as DDR defects and TMB. The integration of NGS PD-L1 expression with other putative biomarkers of response is presently ongoing to further improve prediction of response.

Local adaptation contributes to gene expression divergence in maize

2020 ◽  
Author(s):  
Jennifer Blanc ◽  
Karl A. G. Kremling ◽  
Edward Buckler ◽  
Emily B. Josephs
Keyword(s):  
Gene Expression ◽  
Local Adaptation ◽  
Cold Response ◽  
Expression Levels ◽  
Maize Populations ◽  
Maize Genotypes ◽  
Wide Range ◽  
History Of ◽  
Insight Into ◽  
Gene Expression Levels

AbstractGene expression links genotypes to phenotypes, so identifying genes whose expression is shaped by selection will be important for understanding the traits and processes underlying local adaptation. However, detecting local adaptation for gene expression will require distinguishing between divergence due to selection and divergence due to genetic drift. Here, we adapt a QST –FST framework to detect local adaptation for transcriptome-wide gene expression levels in a population of diverse maize genotypes. We compare the number and types of selected genes across a wide range of maize populations and tissues, as well as selection on cold-response genes, drought-response genes, and coexpression clusters. We identify a number of genes whose expression levels are consistent with local adaptation and show that genes involved in stress-response show enrichment for selection. Due to its history of intense selective breeding and domestication, maize evolution has long been of interest to researchers, and our study provides insight into the genes and processes important for in local adaptation of maize.

Sign in / Sign up

Export Citation Format

Share Document