Engineering DNA polymerases for application in DNB-based sequencing technology

DNA polymerases serve as the core engine to afford sequence information in sequencing technologies that have revolutionized modern biological research. For application in the DNB-based sequencing platform, an assemblage of DNA polymerases was engineered to catalyze the requisite biochemical reaction. In the process, naturally occurring polymerases were tapped into through deep-learning algorithms for constraints between individual protein residues to narrow down the protein sequence space and to annotate protein sequences in light of their catalytic properties. And the constraints were subsequently applied in designing potential polymerase candidates with the guidance of the sequence annotations. Additionally, ancestral protein sequences were estimated to expand the candidate repertoire. Furthermore, the candidates were subjected to in silico screening before examined by an HTS methodology based on fluorescence signal. Finally, the resulting proteins were expressed and purified for testing in the DNB-based sequencing platform. Our sequencing data suggested that these proteins behave better than their existing counterparts

SPIDER-WEB enables stable, repairable, and encryptible algorithms under arbitrary local biochemical constraints in DNA-based storage

DNA has been considered as a promising medium for storing digital information. Despite the biochemical progress in DNA synthesis and sequencing, novel coding algorithms need to be constructed under the specific constraints in DNA-based storage. Many functional operations and storage carriers were introduced in recent years, bringing in various biochemical constraints including but not confined to long single-nucleotide repeats and abnormal GC content. Existing coding algorithms are not applicable or unstable due to more local biochemical constraints and their combinations. In this paper, we design a graph-based architecture, named SPIDER-WEB, to generate corresponding graph-based algorithms under arbitrary local biochemical constraints. These generated coding algorithms could be used to encode arbitrary digital data as DNA sequences directly or served as a benchmark for the follow-up construction of coding algorithms. To further consider recovery and security issues existing in the storage field, it also provides pluggable algorithmic patches based on the generated coding algorithms: path-based correcting and mapping shuffling. They provide approaches for probabilistic error correction and symmetric encryption respectively.Comment: 30 pages; 12 figures; 2 table

A token-based dynamic scheduled MAC protocol for health monitoring

Developments of wireless body area networks (WBANs) facilitate the pervasive health monitoring with mHealth applications. WBANs can support continuous health monitoring for the human body in convenience and high efficiency without any intervention. The monitoring data in health care have the characteristics of various data flows and heterogeneous data arrival rates, the transmission of which must be in timeliness and reliability, especially the burst data. Moreover, the energy-constraint nodes should be provident in energy consumption. Designing MAC protocols with high reliability and energy efficiency for WBANs is the prime consideration. In this paper, we propose a token-based two-round reservation MAC (TTR MAC) protocol based on IEEE 802.15.6 with considering the data features of health monitoring. With analyzing the characteristics of monitoring data, one-round reservation is conducted for periodic data and two-round reservation is generated adaptively for burst data to save energy. Besides, TTR MAC protocol assigns appropriate number of allocation slots to nodes in heterogeneous data arrival rates. Furthermore, a token is introduced on the basis of user priority and health severity index to indicate the transmission order of nodes with burst data, which highly decreases the average delay. In addition, a bit sequence scheduled algorithm is proposed for m-periodic (m>1) monitoring data for network capacity expansion. The simulation results show that TTR MAC protocol achieves higher energy efficiency and longer lifetime compared with IEEE 802.15.6 and other one-round reservation MAC (OR MAC) protocols for both 1-periodic and m-periodic data.info:eu-repo/semantics/publishedVersio

Mechanical properties and fracture damage law of coal-rock composition under the action of supercritical CO2

The injection of CO2 into deep unrecoverable coal seams is one of the effective ways to achieve CO2 geological sequestration, but CO2 will be in a supercritical state under the action of high pressure and high temperature. In order to investigate the effect of supercritical CO2 action on coal reservoir structure, based on the self-developed supercritical CO2 immersion experimental system, combined with acoustic emission test system and RFPA3D numerical simulation, we studied the three coal seam thicknesses and three top and bottom lithologies of the mechanical damage characteristics and the fracture extension evolution of “Rock-Coal-Rock” (RCR) composite specimens under the action of supercritical CO2 were investigated. The results show that: ① After the action of supercritical CO2, the degradation of compressive strength and elastic modulus of the RCR composite gradually increases and decreases with the increase of coal thickness, while the degradation of compressive strength and elastic modulus are basically the same when the strength ratios of rock and coal are different and do not show large differences; ② The action of supercritical CO2 will promote the plastic damage of the coal body and intensify the transformation of the RCR composite from tensile splitting damage to shear plastic damage, and the degree of plastic damage of RCR assemblage is positively correlated with both coal thickness and rock-to-coal strength ratio; ③ The supercritical CO2 immersion promoted the RCR assemblage to enter the elastic deformation stage earlier, and the destabilization damage occurred after a more brief elastic deformation, the greater the coal thickness, the greater the influence, while the rock-to-coal strength ratio has less influence; ④ The instability potential of RCR assemblage is proportional to coal thickness and inversely proportional to rock-coal strength ratio, and the power intensity of damage is inversely proportional to coal thickness and proportional to rock-coal strength ratio; ⑤ The total energy, dissipative energy, elastic energy and surplus energy of RCR assemblage gradually decrease with the increase of coal thickness and gradually increase with the increase of rock-coal strength ratio, and the supercritical CO2 effect will cause the elastic energy ratio of RCR assemblage specimens to decrease, the dissipative energy ratio to increase and the surplus energy ratio to decreases. Combining the above research results shows that the thicker the coal seam is, the more likely it is to be destabilized, and the higher the strength of the top and bottom rock layer is, the less likely it is to be destabilized, and the dynamic strength of the seam destabilization is inversely proportional to the coal thickness and positively proportional to the rock-to-coal strength ratio. Therefore, in a certain area of stratum that meets the premise of CO2 injection and storage, the area of stratum with higher top and bottom rock strength and thinner coal seam thickness should be selected to store CO2 with higher safety. The research results can provide some theoretical reference for the safety of geological storage of CO2 injected into deep unmineable coal seams

Analysis of lncRNA-Associated ceRNA Network Reveals Potential lncRNA Biomarkers in Human Colon Adenocarcinoma

Background/Aims: Long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) play significant roles in the development of tumors, but the functions of specific lncRNAs and lncRNA-related ceRNA networks have not been fully elucidated for colon adenocarcinoma (COAD). In this study, we aimed to clarify the lncRNA-microRNA (miRNA)-mRNA ceRNA network and potential lncRNA biomarkers in COAD. Methods: We extracted data from The Cancer Genome Atlas (TCGA) and identified COAD-specific mRNAs, miRNAs, and lncRNAs. The biological processes in Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed for COAD-specific mRNAs. We then constructed a ceRNA network of COAD-specific mRNAs, miRNAs and lncRNAs and analyzed the correlation between expression patterns and clinical features of the lncRNAs involved. After identifying potential mRNA targets of 4 lncRNAs related to overall survival (OS), we conducted stepwise analysis of these targets through GO and KEGG. Using tissue samples from our own patients, we also verified certain analytical results using quantitative real-time PCR (qRT-PCR). Results: Data from 521 samples (480 tumor tissue and 41 adjacent non-tumor tissue samples) were extracted from TCGA. A total of 258 specific lncRNAs, 206 specific miRNAs, and 1467 specific mRNAs were identified (absolute log2 [fold change] > 2, false discovery rate < 0.01). Analysis of KEGG revealed that specific mRNAs were enriched in cancer-related pathways. The ceRNA network was constructed with 64 lncRNAs, 18 miRNAs, and 42 mRNAs. Among these lncRNAs involved in the network, 3 lncRNAs (LINC00355, HULC, and IGF2-AS) were confirmed to be associated with certain clinical features and 4 lncRNAs (HOTAIR, LINC00355, KCNQ1OT1, and TSSC1-IT1) were found to be negatively linked to OS (log-rank p < 0.05). KEGG showed that the potential mRNA targets of these 4 lncRNAs may be concentrated in the MAPK pathway. Certain results were validated by qRT-PCR. Conclusion: This study providing novel insights into the lncRNA-miRNA-mRNA ceRNA network and reveals potential lncRNA biomarkers in COAD

Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays.

Spatially resolved transcriptomic technologies are promising tools to study complex biological processes such as mammalian embryogenesis. However, the imbalance between resolution, gene capture, and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation embryos. Here, we combined DNA nanoball (DNB)-patterned arrays and in situ RNA capture to create spatial enhanced resolution omics-sequencing (Stereo-seq). We applied Stereo-seq to generate the mouse organogenesis spatiotemporal transcriptomic atlas (MOSTA), which maps with single-cell resolution and high sensitivity the kinetics and directionality of transcriptional variation during mouse organogenesis. We used this information to gain insight into the molecular basis of spatial cell heterogeneity and cell fate specification in developing tissues such as the dorsal midbrain. Our panoramic atlas will facilitate in-depth investigation of longstanding questions concerning normal and abnormal mammalian development.This work is part of the ‘‘SpatioTemporal Omics Consortium’’ (STOC) paper package. A list of STOC members is available at: http://sto-consortium.org. We would like to thank the MOTIC China Group, Rongqin Ke (Huaqiao University, Xiamen, China), Jiazuan Ni (Shenzhen University, Shenzhen, China), Wei Huang (Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China), and Jonathan S. Weissman (Whitehead Institute, Boston, USA) for their help. This work was supported by the grant of Top Ten Foundamental Research Institutes of Shenzhen, the Shenzhen Key Laboratory of Single-Cell Omics (ZDSYS20190902093613831), and the Guangdong Provincial Key Laboratory of Genome Read and Write (2017B030301011); Longqi Liu was supported by the National Natural Science Foundation of China (31900466) and Miguel A. Esteban’s laboratory at the Guangzhou Institutes of Biomedicine and Health by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16030502), National Natural Science Foundation of China (92068106), and the Guangdong Basic and Applied Basic Research Foundation (2021B1515120075).S

Dynamic time slot allocation and stream control for MIMO STDMA in ad hoc networks

Abstract Multiple-input multiple-output (MIMO) technologies have been shown to potentially improve the performance of network. Many traditional medium access control (MAC) protocols, such as spatial time division multiple access (STDMA), may not support MIMO technologies directly and not make full use of the feature of MIMO, which may be a limitation in the practical application in ad hoc networks. Therefore, in this paper, we propose a dynamic time slot allocation and stream control for MIMO STDMA (DTSMS) protocol to improve STDMA in performance. Utilizing stream control technology of MIMO and reservation scheme, DTSMS makes improvement on network throughput and avoids the mutual interference of neighbor links. Thus, DTSMS can support both unicast and multicast simultaneously. Moreover, we implement the dynamic time slot allocation scheme in DTSMS to guarantee the transmission efficiency of packets with high cross-layer transmission parameters, such as the packet priority, neighbor node density, or link quality. Utilizing the collected cross-layer information, the proposed scheme allocates time slots for all nodes dynamically according to the changes of network topology and nodes’ transmission parameters. Finally, the effectiveness of the protocol is demonstrated by numerical analysis and simulations. The results show that DTSMS outperforms STDMA in terms of network throughput and delay. Furthermore, compared to our previous TTS-MIMO, DTSMS can decrease the delay of packets with high transmission parameters and improve the quality of service (QoS)