The refinement of tightly regulated prokaryotic expression systems that permit functional expression of toxic recombinant proteins is a continually evolving process. Unfortunately, the current best ...promoter options are either tightly repressed and produce little protein, or produce substantial protein but lack the necessary repression to avoid mutations stimulated by leaky expression in the absence of inducer. In this report, we present three novel prokaryotic expression constructs that are tightly regulated by L-rhamnose and D-glucose. These expression vectors utilize the Escherichia coli rhaT promoter and corresponding regulatory genes to provide titratable, high-level protein yield without compromising clone integrity. Together, these components may enable the stable cloning and functional expression of otherwise toxic proteins.
Summary
The delivery of DNA to mammalian cells is of critical importance to the development of genetic vaccines, gene replacement therapies and gene silencing. For these applications, targeting, ...effective DNA transfer and vector safety are the major roadblocks in furthering development. In this report, we present a novel DNA delivery vehicle that makes use of protoplasted, achromosomal bacterial minicells. Transfer of plasmid DNA as measured by green fluorescent protein expression was found to occur in as high as 25% of cultured Cos‐7 cells when a novel chimeric protein containing the D2–D5 region of invasin was expressed and displayed on the surface of protoplasted minicells. Based on endoplasmic reticulum stress and other responses, protoplasted minicells were non‐toxic to recipient eukaryotic cells as a consequence of the transfection process. Taken together, these results suggest that bacterial minicells may represent a novel and promising gene delivery vehicle.
Toxic protein expression in Giacalone, Matthew J; Gentile, Angela M; Lovitt, Brian T ...
BioTechniques,
2006-March-01, Letnik:
40, Številka:
3
Journal Article
Recenzirano
The refinement of tightly regulated prokaryotic expression systems that permit functional expression of toxic recombinant proteins is a continually evolving process. Unfortunately, the current best ...promoter options are either tightly repressed and produce little protein, or produce substantial protein but lack the necessary repression to avoid mutations stimulated by leaky expression in the absence ofinducer. In this report, we present three novel prokaryotic expression constructs that are tightly regulated by L-rhamnose and D-glucose. These expression vectors utilize the Escherichia coli rhaT promoter and corresponding regulatory genes to provide titratable, high-level protein yield without compromising clone integrity. Together, these components may enable the stable cloning and functional expression of otherwise toxic proteins.
Lichen is an important food source for caribou in Canada. Lichen mapping using remote sensing (RS) images could be a challenging task, however, as lichens generally appear in unevenly distributed, ...small patches, and could resemble surficial features. Moreover, collecting lichen labeled data (reference data) is expensive, which restricts the application of many robust supervised classification models that generally demand a large quantity of labeled data. The goal of this study was to investigate the potential of using a very-high-spatial resolution (1-cm) lichen map of a small sample site (e.g., generated based on a single UAV scene and using field data) to train a subsequent classifier to map caribou lichen over a much larger area (~0.04 km2 vs. ~195 km2) and a lower spatial resolution image (in this case, a 50-cm WorldView-2 image). The limited labeled data from the sample site were also partially noisy due to spatial and temporal mismatching issues. For this, we deployed a recently proposed Teacher-Student semi-supervised learning (SSL) approach (based on U-Net and U-Net++ networks) involving unlabeled data to assist with improving the model performance. Our experiments showed that it was possible to scale-up the UAV-derived lichen map to the WorldView-2 scale with reasonable accuracy (overall accuracy of 85.28% and F1-socre of 84.38%) without collecting any samples directly in the WorldView-2 scene. We also found that our noisy labels were partially beneficial to the SSL robustness because they improved the false positive rate compared to the use of a cleaner training set directly collected within the same area in the WorldView-2 image. As a result, this research opens new insights into how current very high-resolution, small-scale caribou lichen maps can be used for generating more accurate large-scale caribou lichen maps from high-resolution satellite imagery.
Illumination variations in non-atmospherically corrected high-resolution satellite (HRS) images acquired at different dates/times/locations pose a major challenge for large-area environmental mapping ...and monitoring. This problem is exacerbated in cases where a classification model is trained only on one image (and often limited training data) but applied to other scenes without collecting additional samples from these new images. In this research, by focusing on caribou lichen mapping, we evaluated the potential of using conditional Generative Adversarial Networks (cGANs) for the normalization of WorldView-2 (WV2) images of one area to a source WV2 image of another area on which a lichen detector model was trained. In this regard, we considered an extreme case where the classifier was not fine-tuned on the normalized images. We tested two main scenarios to normalize four target WV2 images to a source 50 cm pansharpened WV2 image: (1) normalizing based only on the WV2 panchromatic band, and (2) normalizing based on the WV2 panchromatic band and Sentinel-2 surface reflectance (SR) imagery. Our experiments showed that normalizing even based only on the WV2 panchromatic band led to a significant lichen-detection accuracy improvement compared to the use of original pansharpened target images. However, we found that conditioning the cGAN on both the WV2 panchromatic band and auxiliary information (in this case, Sentinel-2 SR imagery) further improved normalization and the subsequent classification results due to adding a more invariant source of information. Our experiments showed that, using only the panchromatic band, F1-score values ranged from 54% to 88%, while using the fused panchromatic and SR, F1-score values ranged from 75% to 91%.
The activation of inert C─H bonds by transition metals is of considerable industrial and academic interest, but important gaps remain in our understanding of this reaction. We report the first ...experimental determination of the structure of the simplest hydrocarbon, methane, when bound as a ligand to a homogenous transition metal species. We find that methane binds to the metal center in this system through a single M···H-C bridge; changes in the
coupling constants indicate clearly that the structure of the methane ligand is significantly perturbed relative to the free molecule. These results are relevant to the development of better C─H functionalization catalysts.
Various mutations in leucine-rich repeat kinase 2 (LRRK2) have been linked to susceptibility for both familial and idiopathic late-onset Parkinson’s disease (PD). In this study, we have demonstrated ...that phosphorylation of MBP and LRRKtide by the LRRK2 G2019S mutant was activated by Mn2+ in vitro. This enhanced G2019S kinase activity was due to the combination of an increase in kinase and a decrease in ATPase activity by Mn2+. Compared to 10 mM Mg2+, 1 mM Mn2+ reduced ATP K m for G2019S from 103 to 1.8 μM and only modestly reduced k cat (2.5-fold); as a result, the Mn2+ increased its k cat/K m by 22-fold. This change in ATP K m was due in large part to an increase in nucleotide affinity. While Mn2+ also increased ATP affinity and had similar effects on k cat/K m for LRRK2 WT and R1441C enzymes, it reduced their k cat values significantly by 13−17-fold. Consequently, the difference in the kinase activity between G2019S and other LRRK2 variants was enhanced from about 2-fold in Mg2+ to 10-fold in Mn2+ at saturating ATP concentrations relative to its K m. Furthermore, while Mg2+ yielded optimal V max values at Mg2+ concentration greater than 5 mM, the optimal Mn2+ concentration for activating LRRK2 catalysis was in the micromolar range with increasing Mn2+ above 1 mM causing a decrease in enzyme activity. Finally, despite the large but expected differences in IC50 tested at 100 μM ATP, the apparent K i values of a small set of LRRK2 ATP-competitive inhibitors were within 5-fold between Mg2+- and Mn2+-mediated reactions except AMP-CPP, an ATP analogue.
As language models (LMs) scale, they develop many novel behaviors, good and bad, exacerbating the need to evaluate how they behave. Prior work creates evaluations with crowdwork (which is ...time-consuming and expensive) or existing data sources (which are not always available). Here, we automatically generate evaluations with LMs. We explore approaches with varying amounts of human effort, from instructing LMs to write yes/no questions to making complex Winogender schemas with multiple stages of LM-based generation and filtering. Crowdworkers rate the examples as highly relevant and agree with 90-100% of labels, sometimes more so than corresponding human-written datasets. We generate 154 datasets and discover new cases of inverse scaling where LMs get worse with size. Larger LMs repeat back a dialog user's preferred answer ("sycophancy") and express greater desire to pursue concerning goals like resource acquisition and goal preservation. We also find some of the first examples of inverse scaling in RL from Human Feedback (RLHF), where more RLHF makes LMs worse. For example, RLHF makes LMs express stronger political views (on gun rights and immigration) and a greater desire to avoid shut down. Overall, LM-written evaluations are high-quality and let us quickly discover many novel LM behaviors.
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