Transcriptional slippage in bacteria: distribution in sequenced genomes and utilization in IS element gene expression

Journal ArticleABSTRACT: Background: Transcription slippage occurs on certain patterns of repeat mononucleotides, resulting in synthesis of a heterogeneous population of mRNAs. Individual mRNA molecules within this population differ in the number of nucleotides they contain that are not specified by the template. When transcriptional slippage occurs in a coding sequence, translation of the resulting mRNAs yields more than one protein product. Except where the products of the resulting mRNAs have distinct functions, transcription slippage occurring in a coding region is expected to be disadvantageous. This probably leads to selection against most slippage-prone sequences in coding regions. Results: To find a length at which such selection is evident, we analyzed the distribution of repetitive runs of A and T of different lengths in 108 bacterial genomes. This length varies significantly among different bacteria, but in a large proportion of available genomes corresponds to nine nucleotides. Comparative sequence analysis of these genomes was used to identify occurrences of 9A and 9T transcriptional slippage-prone sequences used for gene expression. Conclusions: IS element genes are the largest group found to exploit this phenomenon. A number of genes with disrupted open reading frames (ORFs) have slippage-prone sequences at which transcriptional slippage would result in uninterrupted ORF restoration at the mRNA level. The ability of such genes to encode functional full-length protein products brings into question their annotation as pseudogenes and in these cases is pertinent to the significance of the term 'authentic frameshift' frequently assigned to such genes

Federated Prompt-based Decision Transformer for Customized VR Services in Mobile Edge Computing System

This paper investigates resource allocation to provide heterogeneous users with customized virtual reality (VR) services in a mobile edge computing (MEC) system. We first introduce a quality of experience (QoE) metric to measure user experience, which considers the MEC system's latency, user attention levels, and preferred resolutions. Then, a QoE maximization problem is formulated for resource allocation to ensure the highest possible user experience,which is cast as a reinforcement learning problem, aiming to learn a generalized policy applicable across diverse user environments for all MEC servers. To learn the generalized policy, we propose a framework that employs federated learning (FL) and prompt-based sequence modeling to pre-train a common decision model across MEC servers, which is named FedPromptDT. Using FL solves the problem of insufficient local MEC data while protecting user privacy during offline training. The design of prompts integrating user-environment cues and user-preferred allocation improves the model's adaptability to various user environments during online execution

Machine learning-guided synthesis of advanced inorganic materials

Synthesis of advanced inorganic materials with minimum number of trials is of paramount importance towards the acceleration of inorganic materials development. The enormous complexity involved in existing multi-variable synthesis methods leads to high uncertainty, numerous trials and exorbitant cost. Recently, machine learning (ML) has demonstrated tremendous potential for material research. Here, we report the application of ML to optimize and accelerate material synthesis process in two representative multi-variable systems. A classification ML model on chemical vapor deposition-grown MoS2 is established, capable of optimizing the synthesis conditions to achieve higher success rate. While a regression model is constructed on the hydrothermal-synthesized carbon quantum dots, to enhance the process-related properties such as the photoluminescence quantum yield. Progressive adaptive model is further developed, aiming to involve ML at the beginning stage of new material synthesis. Optimization of the experimental outcome with minimized number of trials can be achieved with the effective feedback loops. This work serves as proof of concept revealing the feasibility and remarkable capability of ML to facilitate the synthesis of inorganic materials, and opens up a new window for accelerating material development

In-plane anomalous Hall effect in PT-symmetric antiferromagnetic materials

Anomalous Hall effect (AHE), a protocol of various low-power dissipation quantum phenomena and a fundamental precursor of intriguing topological phases of matter, is usually observed in ferromagnetic materials with orthogonal configuration between the electric field, magnetization and the Hall current. Here, based on the symmetry analysis, we find an unconventional AHE induced by the in-plane magnetic field (IPAHE) via spin-canting effect in $\mathcal{PT}$ symmetric antiferromagnetic (AFM) systems, featuring a linear dependence of magnetic field and 2$\pi$ angle periodicity with a comparable magnitude as conventional AHE. We demonstrate the key findings in the known AFM Dirac semimetal CuMnAs and a new kind of AFM heterodimensional VS$_2$-VS superlattice with a nodal-line Fermi surface and also briefly discuss the experimental detection. Our work provides an efficient pathway to search and/or design realistic materials for novel IPAHE that could greatly facilitate their application in AFM spintronic devices.Comment: 6 pages, 4 figures, 1 tabl

Transcriptional slippage in bacteria: distribution in sequenced genomes and utilization in IS element gene expression

BACKGROUND: Transcription slippage occurs on certain patterns of repeat mononucleotides, resulting in synthesis of a heterogeneous population of mRNAs. Individual mRNA molecules within this population differ in the number of nucleotides they contain that are not specified by the template. When transcriptional slippage occurs in a coding sequence, translation of the resulting mRNAs yields more than one protein product. Except where the products of the resulting mRNAs have distinct functions, transcription slippage occurring in a coding region is expected to be disadvantageous. This probably leads to selection against most slippage-prone sequences in coding regions. RESULTS: To find a length at which such selection is evident, we analyzed the distribution of repetitive runs of A and T of different lengths in 108 bacterial genomes. This length varies significantly among different bacteria, but in a large proportion of available genomes corresponds to nine nucleotides. Comparative sequence analysis of these genomes was used to identify occurrences of 9A and 9T transcriptional slippage-prone sequences used for gene expression. CONCLUSIONS: IS element genes are the largest group found to exploit this phenomenon. A number of genes with disrupted open reading frames (ORFs) have slippage-prone sequences at which transcriptional slippage would result in uninterrupted ORF restoration at the mRNA level. The ability of such genes to encode functional full-length protein products brings into question their annotation as pseudogenes and in these cases is pertinent to the significance of the term 'authentic frameshift' frequently assigned to such genes

Correcting Subverted Random Oracles

The random oracle methodology has proven to be a powerful tool for designing and reasoning about cryptographic schemes. In this paper, we focus on the basic problem of correcting faulty—or adversarially corrupted—random oracles, so that they can be confidently applied for such cryptographic purposes. We prove that a simple construction can transform a “subverted” random oracle—which disagrees with the original one at a small fraction of inputs—into an object that is indifferentiable from a random function, even if the adversary is made aware of all randomness used in the transformation. Our results permit future designers of cryptographic primitives in typical kleptographic settings (i.e., those permitting adversaries that subvert or replace basic cryptographic algorithms) to use random oracles as a trusted black box

Controlled Synthesis of Organic/Inorganic van der Waals Solid for Tunable Light-matter Interactions

Van der Waals (vdW) solids, as a new type of artificial materials that consist of alternating layers bonded by weak interactions, have shed light on fascinating optoelectronic device concepts. As a result, a large variety of vdW devices have been engineered via layer-by-layer stacking of two-dimensional materials, although shadowed by the difficulties of fabrication. Alternatively, direct growth of vdW solids has proven as a scalable and swift way, highlighted by the successful synthesis of graphene/h-BN and transition metal dichalcogenides (TMDs) vertical heterostructures from controlled vapor deposition. Here, we realize high-quality organic and inorganic vdW solids, using methylammonium lead halide (CH3NH3PbI3) as the organic part (organic perovskite) and 2D inorganic monolayers as counterparts. By stacking on various 2D monolayers, the vdW solids behave dramatically different in light emission. Our studies demonstrate that h-BN monolayer is a great complement to organic perovskite for preserving its original optical properties. As a result, organic/h-BN vdW solid arrays are patterned for red light emitting. This work paves the way for designing unprecedented vdW solids with great potential for a wide spectrum of applications in optoelectronics