LowTempGAL: a highly responsive low temperature-inducible GAL system in Saccharomyces cerevisiae.

Temperature is an important control factor for biologics biomanufacturing in precision fermentation. Here, we explored a highly responsive low temperature-inducible genetic system (LowTempGAL) in the model yeast Saccharomyces cerevisiae. Two temperature biosensors, a heat-inducible degron and a heat-inducible protein aggregation domain, were used to regulate the GAL activator Gal4p, rendering the leaky LowTempGAL systems. Boolean-type induction was achieved by implementing a second-layer control through low-temperature-mediated repression on GAL repressor gene GAL80, but suffered delayed response to low-temperature triggers and a weak response at 30°C. Application potentials were validated for protein and small molecule production. Proteomics analysis suggested that residual Gal80p and Gal4p insufficiency caused suboptimal induction. 'Turbo' mechanisms were engineered through incorporating a basal Gal4p expression and a galactose-independent Gal80p-supressing Gal3p mutant (Gal3Cp). Varying Gal3Cp configurations, we deployed the LowTempGAL systems capable for a rapid stringent high-level induction upon the shift from a high temperature (37-33°C) to a low temperature (≤30°C). Overall, we present a synthetic biology procedure that leverages 'leaky' biosensors to deploy highly responsive Boolean-type genetic circuits. The key lies in optimisation of the intricate layout of the multi-factor system. The LowTempGAL systems may be applicable in non-conventional yeast platforms for precision biomanufacturing.

Multiplexed Assays of Variant Effect and Automated Patch-clamping Improve KCNH2-LQTS Variant Classification and Cardiac Event Risk Stratification.

Background: Long QT syndrome (LQTS) is a lethal arrhythmia syndrome, frequently caused by rare loss-of-function variants in the potassium channel encoded by KCNH2. Variant classification is difficult, often owing to lack of functional data. Moreover, variant-based risk stratification is also complicated by heterogenous clinical data and incomplete penetrance. Here, we sought to test whether variant-specific information, primarily from high-throughput functional assays, could improve both classification and cardiac event risk stratification in a large, harmonized cohort of KCNH2 missense variant heterozygotes. Methods: We quantified cell-surface trafficking of 18,796 variants in KCNH2 using a Multiplexed Assay of Variant Effect (MAVE). We recorded KCNH2 current density for 533 variants by automated patch clamping (APC). We calibrated the strength of evidence of MAVE data according to ClinGen guidelines. We deeply phenotyped 1,458 patients with KCNH2 missense variants, including QTc, cardiac event history, and mortality. We correlated variant functional data and Bayesian LQTS penetrance estimates with cohort phenotypes and assessed hazard ratios for cardiac events. Results: Variant MAVE trafficking scores and APC peak tail currents were highly correlated (Spearman Rank-order ρ = 0.69). The MAVE data were found to provide up to pathogenic very strong evidence for severe loss-of-function variants. In the cohort, both functional assays and Bayesian LQTS penetrance estimates were significantly predictive of cardiac events when independently modeled with patient sex and adjusted QT interval (QTc); however, MAVE data became non-significant when peak-tail current and penetrance estimates were also available. The area under the ROC for 20-year event outcomes based on patient-specific sex and QTc (AUC 0.80 [0.76-0.83]) was improved with prospectively available penetrance scores conditioned on MAVE (AUC 0.86 [0.83-0.89]) or attainable APC peak tail current data (AUC 0.84 [0.81-0.88]). Conclusion: High throughput KCNH2 variant MAVE data meaningfully contribute to variant classification at scale while LQTS penetrance estimates and APC peak tail current measurements meaningfully contribute to risk stratification of cardiac events in patients with heterozygous KCNH2 missense variants.

Biomechanical Analysis of Adjacent Segments after Spinal Fusion Surgery Using a Geometrically Parametric Patient-Specific Finite Element Model.

This study aimed to perform a mechanical analysis of adjacent segments after spinal fusion surgery using a geometrically parametric patient-specific finite element model to elucidate the mechanism of adjacent segment degeneration (ASD), thereby providing theoretical evidence for early disease prevention. Fourteen parameters based on patient-specific spinal geometry were extracted from a patient's preoperative computed tomography (CT) scan, and the relative positions of each spinal segment were determined using the image match method. A preoperative patient-specific model of the spine was established through the above method. The postoperative model after L4-L5 posterior lumbar interbody fusion (PLIF) surgery was constructed using the same method except that the lamina and intervertebral disc were removed, and a cage, 4 pedicle screws, and 2 connecting rods were inserted. Range of motion (ROM) and stress changes were determined by comparing the values of each anatomical structure between the preoperative and postoperative models. The overall ROM of the lumbar spine decreased after fusion, while the ROM, stress in the facet joints, and stress in the intervertebral disc of adjacent segments all increased. An analysis of the stress distribution in the annulus fibrosus, nucleus pulposus, and facet joints also showed that not only was the maximum stress in these tissues elevated, but the areas of moderate-to-high stress were also expanded. During torsion, the stress in the facet joints and annulus fibrosus of the proximal adjacent segment (L3-L4) increased to a larger extent than that in the distal adjacent segment (L5-S1). While fusion surgery causes an overall restriction of motion in the lumbar spine, it also causes more load sharing by the adjacent segments to compensate for the fused segment, thus increasing the risk of ASD. The proximal adjacent segment is more prone to degeneration than the distal adjacent segment after spinal fusion due to the significant increase in stress.

Integration of Yeast Episomal/Integrative Plasmid Causes Genotypic and Phenotypic Diversity and Improved Sesquiterpene Production in Metabolically Engineered Saccharomyces cerevisiae.

The variability in phenotypic outcomes among biological replicates in engineered microbial factories presents a captivating mystery. Establishing the association between phenotypic variability and genetic drivers is important to solve this intricate puzzle. We applied a previously developed auxin-inducible depletion of hexokinase 2 as a metabolic engineering strategy for improved nerolidol production in Saccharomyces cerevisiae, and biological replicates exhibit a dichotomy in nerolidol production of either 3.5 or 2.5 g L-1 nerolidol. Harnessing Oxford Nanopore's long-read genomic sequencing, we reveal a potential genetic cause─the chromosome integration of a 2µ sequence-based yeast episomal plasmid, encoding the expression cassettes for nerolidol synthetic enzymes. This finding was reinforced through chromosome integration revalidation, engineering nerolidol and valencene production strains, and generating a diverse pool of yeast clones, each uniquely fingerprinted by gene copy numbers, plasmid integrations, other genomic rearrangements, protein expression levels, growth rate, and target product productivities. Τhe best clone in two strains produced 3.5 g L-1 nerolidol and ∼0.96 g L-1 valencene. Comparable genotypic and phenotypic variations were also generated through the integration of a yeast integrative plasmid lacking 2µ sequences. Our work shows that multiple factors, including plasmid integration status, subchromosomal location, gene copy number, sesquiterpene synthase expression level, and genome rearrangement, together play a complicated determinant role on the productivities of sesquiterpene product. Integration of yeast episomal/integrative plasmids may be used as a versatile method for increasing the diversity and optimizing the efficiency of yeast cell factories, thereby uncovering metabolic control mechanisms.

An in vivo gene amplification system for high level expression in Saccharomyces cerevisiae.

Bottlenecks in metabolic pathways due to insufficient gene expression levels remain a significant problem for industrial bioproduction using microbial cell factories. Increasing gene dosage can overcome these bottlenecks, but current approaches suffer from numerous drawbacks. Here, we describe HapAmp, a method that uses haploinsufficiency as evolutionary force to drive in vivo gene amplification. HapAmp enables efficient, titratable, and stable integration of heterologous gene copies, delivering up to 47 copies onto the yeast genome. The method is exemplified in metabolic engineering to significantly improve production of the sesquiterpene nerolidol, the monoterpene limonene, and the tetraterpene lycopene. Limonene titre is improved by 20-fold in a single engineering step, delivering ∼1 g L-1 in the flask cultivation. We also show a significant increase in heterologous protein production in yeast. HapAmp is an efficient approach to unlock metabolic bottlenecks rapidly for development of microbial cell factories.

Microglia-derived TNF-α mediates Müller cell activation by activating the TNFR1-NF-κB pathway.

Microglia and its interaction with Müller cells are responsible to retinal surveillance during retinal neurodegeneration, however, the role and mechanism of microglia-derived tumor necrosis factor (TNF)-α in the activation of retinal Müller cells have not been fully elucidated. In the present study, primary microglia and Müller cells were isolated from newborn Sprague-Dawley (SD) rats with purities of 88.2 ± 6.2% and 92.2 ± 2.2%, respectively. By performing immunofluorescence and Western blot analysis, we found that TNF receptor (TNFR)-1 and TNFR2 were expressed in Müller cells. After co-cultured with microglia-conditioned medium (MCM), the elevated mRNA levels of glial fibrillary acidic protein (GFAP), proinflammatory factors (TNF-α, IL-1ß, CXCL-1, CSF-1, NOS2, COX2) and decreased CNTF mRNA levels were found in Müller cells. However, pretreatment with R-7050 (a TNF-α receptor inhibitor) or anti-TNFR1 significantly abrogated the changes. Simultaneously, pretreatment with anti-TNFR2 slightly inhibited the expression of GFAP in MCM-incubated Müller cells. Meanwhile, anti-TNFR1 treatment reversed the increased expression of CSF-1 and IL-1ß induced by TNF-α. Compared to the control groups, the phosphorylation of NF-κB P65, MAPK P38 and ERK1/2 in TNF-α-treated Müller cells was significantly increased. Nevertheless, pretreatment with anti-TNFR1 inhibited the phosphorylation of NF-κB P65 and MAPK p38, especially NF-κB P65. Additionally, pretreatment with Bay117082 (an NF-κB inhibitor) also significantly inhibited NF-κB P65 phosphorylation and GFAP expression. Moreover, anti-TNFR1 and Bay117082 treatment reduced NF-κB P65 phosphorylation of Müller cells induced by MCM. These results suggested that microglia-derived TNF-α served as a vital role in regulating Müller cells activation during retinal neurodegeneration.