Distinct regulatory mechanisms balance DegP proteolysis to maintain cellular fitness during heat stress

Intracellular proteases combat proteotoxic stress by degrading damaged proteins, but their activity must be carefully controlled to maintain cellular fitness. The activity of Escherichia coli DegP, a highly conserved periplasmic protease, is regulated by substrate-dependent allosteric transformations between inactive and active trimer conformations and by the formation of polyhedral cages that confine the active sites within a proteolytic chamber. Here, we investigate how these distinct control mechanisms contribute to bacterial fitness under heat stress. We found that mutations that increase or decrease the equilibrium population of active DegP trimers reduce high-temperature fitness, that a mutation that blocks cage formation causes a mild fitness decrease, and that combining mutations that stabilize active DegP and block cage formation generates a lethal rogue protease. This lethality is suppressed by an extragenic mutation that prevents covalent attachment of an abundant outer-membrane lipoprotein to peptidoglycan and makes this protein an inhibitor of the rogue protease. Lethality is also suppressed by intragenic mutations that stabilize inactive DegP trimers. In combination, our results suggest that allosteric control of active and inactive conformations is the primary mechanism that regulates DegP proteolysis and fitness, with cage formation providing an additional layer of cellular protection against excessive protease activity.National Institutes of Health (U.S.) (grant AI-16892)Charles A. King Trust (Postdoctoral Fellowship

KoSBi: A Dataset for Mitigating Social Bias Risks Towards Safer Large Language Model Application

Large language models (LLMs) learn not only natural text generation abilities but also social biases against different demographic groups from real-world data. This poses a critical risk when deploying LLM-based applications. Existing research and resources are not readily applicable in South Korea due to the differences in language and culture, both of which significantly affect the biases and targeted demographic groups. This limitation requires localized social bias datasets to ensure the safe and effective deployment of LLMs. To this end, we present KO SB I, a new social bias dataset of 34k pairs of contexts and sentences in Korean covering 72 demographic groups in 15 categories. We find that through filtering-based moderation, social biases in generated content can be reduced by 16.47%p on average for HyperCLOVA (30B and 82B), and GPT-3.Comment: 17 pages, 8 figures, 12 tables, ACL 202

Who Wrote this Code? Watermarking for Code Generation

Large language models for code have recently shown remarkable performance in generating executable code. However, this rapid advancement has been accompanied by many legal and ethical concerns, such as code licensing issues, code plagiarism, and malware generation, making watermarking machine-generated code a very timely problem. Despite such imminent needs, we discover that existing watermarking and machine-generated text detection methods for LLMs fail to function with code generation tasks properly. Hence, in this work, we propose a new watermarking method, SWEET, that significantly improves upon previous approaches when watermarking machine-generated code. Our proposed method selectively applies watermarking to the tokens with high enough entropy, surpassing a defined threshold. The experiments on code generation benchmarks show that our watermarked code has superior quality compared to code produced by the previous state-of-the-art LLM watermarking method. Furthermore, our watermark method also outperforms DetectGPT for the task of machine-generated code detection

SQuARe: A Large-Scale Dataset of Sensitive Questions and Acceptable Responses Created Through Human-Machine Collaboration

The potential social harms that large language models pose, such as generating offensive content and reinforcing biases, are steeply rising. Existing works focus on coping with this concern while interacting with ill-intentioned users, such as those who explicitly make hate speech or elicit harmful responses. However, discussions on sensitive issues can become toxic even if the users are well-intentioned. For safer models in such scenarios, we present the Sensitive Questions and Acceptable Response (SQuARe) dataset, a large-scale Korean dataset of 49k sensitive questions with 42k acceptable and 46k non-acceptable responses. The dataset was constructed leveraging HyperCLOVA in a human-in-the-loop manner based on real news headlines. Experiments show that acceptable response generation significantly improves for HyperCLOVA and GPT-3, demonstrating the efficacy of this dataset.Comment: 19 pages, 10 figures, ACL 202

Identification of Nucleophilic Probes for Protease-Mediated Transpeptidation

Proteases have evolved to mediate the hydrolysis of peptide bonds but may perform transpeptidation in the presence of a proper nucleophilic molecule that can effectively compete with water to react with the acyl-enzyme intermediate. There have been several examples of protease-mediated transpeptidation, but they are generally inefficient, and little effort has been made to systematically control the transpeptidation activity of other proteases with good nucleophiles. Here, we developed an on-bead screening approach to find a probe that functions efficiently as a nucleophile in the protease-mediated transpeptidation reaction, and we identified good probes for a model protease DegP. These probes were covalently linked to the C-termini of the cleaved peptides in a mild condition and made the selective enrichment of ligated peptides possible. We suggest that good nucleophilic probes can be found for many other proteases that act via acyl-enzyme intermediates, and these probes will help characterize their substrates

Cage assembly of DegP protease is not required for substrate-dependent regulation of proteolytic activity or high-temperature cell survival

DegP, a member of the highly conserved HtrA family, performs quality-control degradation of misfolded proteins in the periplasm of Gram-negative bacteria and is required for high-temperature survival of Escherichia coli. Substrate binding transforms DegP from an inactive oligomer containing two trimers into active polyhedral cages, typically containing four or eight trimers. Although these observations suggest a causal connection, we show that cage assembly and proteolytic activation can be uncoupled. Indeed, DegP variants that remain trimeric, hexameric, or dodecameric in the presence or absence of substrate still display robust and positively cooperative substrate degradation in vitro and, most importantly, sustain high-temperature bacterial growth as well as the wild-type enzyme. Our results support a model in which substrate binding converts inactive trimers into proteolytically active trimers, and simultaneously leads to cage assembly by enhancing binding of PDZ1 domains in one trimer to PDZ2′ domains in neighboring trimers. Thus, both processes depend on substrate binding, but they can be uncoupled without loss of biological function. We discuss potential coupling mechanisms and why cage formation may have evolved if it is not required for DegP proteolysis.National Institutes of Health (U.S.) (Grant AI-16892

Viewpoint Usability for Desktop Augmented Reality

International audienceIn this paper, we have investigated the comparative usability among three different viewing configurations of augmented reality (AR) system that uses a desktop monitor instead of a head mounted display. In many cases, due to operational or cost reasons, the use of head mounted displays may not be viable. Such a configuration is bound to cause usability problems because of the mismatch in the user’s proprioception, scale, hand eye coordination, and the reduced 3D depth perception. We asked a pool of subjects to carry out an object manipulation task in three different desktop AR set ups. We measured the subject’s task performance and surveyed for the perceived usability and preference. Our results indicated that placing a fixed camera in the back of the user was the best option for convenience and attaching a camera on the user’s head for task performance. The results should provide a valuable guide for designing desktop augmented reality systems without head mounted display

Enzyme-Triggered Depolymerization of Polymeric Micelles for Targeted Anticancer Therapy

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How Does an Inquiry-Based Instructional Approach Predict the STEM Creative Productivity of Specialized Science High School Students?

Creative productivity has not been studied much as an outcome of specialized science high schools. Rather, STEM career choices, acquisition of a STEM degree, and taking advanced STEM courses were taken as outcomes. This study examined whether the inquiry-based instructional approaches experienced by students predict their creative productivity and whether its effects are mediated through co-cognitive factors, school engagement, and school GPA. This study is part of a national longitudinal study about students from Science Academies, a type of specialized science high school in South Korea. A total of 599 students at Science Academies were surveyed on experiences of inquiry-based instructional approaches, co-cognitive factors, school engagement, and school GPA in math and science in their second year, and on creative productivity in their last year at Science Academies. Creative productivity was measured by the number of awards received from STEM competitions for research, problem solving, or projects. Confirmatory factor analyses confirmed the convergent validity of the measurement model. Structural equation modeling analysis and bootstrapping analysis revealed the direct, indirect, and total effects of inquiry-based instructional approaches on creative productivity. Inquiry-based instructional approaches experienced by students at Science Academies had a sequentially positive impact on co-cognitive factors, school engagement, and school GPA, ultimately contributing to creative productivity