CRISPR-Cas systems depend on the Cas1-Cas2 integrase to capture and integrate short foreign DNA fragments into the CRISPR locus, enabling adaptation to new viruses. We present crystal structures of Cas1-Cas2 bound to both donor and target DNA in intermediate and product integration complexes, as well as a cryo-electron microscopy structure of the full CRISPR locus integration complex, including the accessory protein IHF (integration host factor). The structures show unexpectedly that indirect sequence recognition dictates integration site selection by favoring deformation of the repeat and the flanking sequences. IHF binding bends the DNA sharply, bringing an upstream recognition motif into contact with Cas1 to increase both the specificity and efficiency of integration. These results explain how the Cas1-Cas2 CRISPR integrase recognizes a sequence-dependent DNA structure to ensure site-selective CRISPR array expansion during the initial step of bacterial adaptive immunity.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5748385 | PMC |
http://dx.doi.org/10.1126/science.aao0679 | DOI Listing |
Sci Rep
December 2024
College of Economics and Management, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
In light of the Chinese government's dual carbon goals, achieving cleaner production activities has become a central focus, with regional environmental collaborative governance, including the management of agricultural carbon reduction, emerging as a mainstream approach. This study examines 268 prefecture-level cities in China, measuring the carbon emission efficiency of city agriculture from 2001 to 2022. By integrating social network analysis and a modified gravity model, the study reveals the characteristics of the spatial association network of city agricultural carbon emission efficiency in China.
View Article and Find Full Text PDFSci Rep
December 2024
Merchant Marine College, Shanghai Maritime University, Shanghai, 201306, China.
The intelligent identification of wear particles in ferrography is a critical bottleneck that hampers the development and widespread adoption of ferrography technology. To address challenges such as false detection, missed detection of small wear particles, difficulty in distinguishing overlapping and similar abrasions, and handling complex image backgrounds, this paper proposes an algorithm called TCBGY-Net for detecting wear particles in ferrography images. The proposed TCBGY-Net uses YOLOv5s as the backbone network, which is enhanced with several advanced modules to improve detection performance.
View Article and Find Full Text PDFSci Rep
December 2024
School of Electrical Engineering, Vellore Institute of Technology, Chennai, 600127, India.
Spherical tanks have been predominantly used in process industries due to their large storage capability. The fundamental challenges in process industries require a very efficient controller to control the various process parameters owing to their nonlinear behavior. The current research work in this paper aims to propose the Approximate Generalized Time Moments (AGTM) optimization technique for designing Fractional-Order PI (FOPI) and Fractional-Order PID (FOPID) controllers for the nonlinear Single Spherical Tank Liquid Level System (SSTLLS).
View Article and Find Full Text PDFSci Rep
December 2024
Shaanxi Key Laboratory of Complex System Control and Intelligent Informantion Processing, Xi'an University of Technology, Xi'an 710048, China.
In the integrated radar and communication system (IRCS), the design of signal that can simultaneously satisfy the radar detection and communication transmission is very important and difficult. Recently, some new properties of a class of solvable chaotic system have been studied for wireless applications, such as low bit error rate (BER) wireless communications and low cost target detection. In this paper, a novel IRCS based on the chaotic signal is proposed, and the performance of proposed scheme is analyzed.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Computer Science, Birzeit University, P.O. Box 14, Birzeit, West Bank, Palestine.
Accurate classification of logos is a challenging task in image recognition due to variations in logo size, orientation, and background complexity. Deep learning models, such as VGG16, have demonstrated promising results in handling such tasks. However, their performance is highly dependent on optimal hyperparameter settings, whose fine-tuning is both labor-intensive and time-consuming.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!