Targeted, programmable, and precise tandem duplication in the mammalian genome.

Tandem duplications are frequent structural variations of the genome and play important roles in genetic disease and cancer. However, interpreting the phenotypic consequences of tandem duplications remains challenging, in part owing to the lack of genetic tools to model such variations. Here, we developed a strategy, tandem duplication via prime editing (TD-PE), to create targeted, programmable, and precise tandem duplication in the mammalian genome. In this strategy, we design a pair of in trans prime editing guide RNAs (pegRNAs) for each targeted tandem duplication, which encode the same edits but prime the single-stranded DNA (ssDNA) extension in opposite directions. The reverse transcriptase (RT) template of each extension is designed homologous to the target region of the other single guide RNA (sgRNA) to promote the reannealing of the edited DNA strands and the duplication of the fragment in between. We showed that TD-PE produced robust and precise in situ tandem duplications of genomic fragments ranging from ∼50 bp to ∼10 kb, with a maximal efficiency up to 28.33%. By fine-tuning the pegRNAs, we achieved simultaneous targeted duplication and fragment insertion. Finally, we successfully produced multiple disease-relevant tandem duplications, showing the general utility of TD-PE in genetic research.

Bi-PE: bi-directional priming improves CRISPR/Cas9 prime editing in mammalian cells.

Prime editors consisting of Cas9-nickase and reverse transcriptase enable targeted precise editing of small DNA pieces, including all 12 kinds of base substitutions, insertions and deletions, while without requiring double-strand breaks or donor templates. Current optimized prime editing strategy (PE3) uses two guide RNAs to guide the performance of prime editor. One guide RNA carrying both spacer and templating sequences (pegRNA) guides prime editor to produce ssDNA break and subsequent extension, and the other one produces a nick in the complementary strand. Here, we demonstrated that positioning the nick sgRNA nearby the templating sequences of the pegRNA facilitated targeted large fragment deletion and that engineering both guide RNAs to be pegRNAs to achieve bi-direction prime editing (Bi-PE) further increase the efficiency by up to 16 times and improved the accuracy of editing products by 60 times. In addition, we showed that Bi-PE strategy also increased the efficiency of simultaneous conversion of multiple bases but not single base conversion over PE3. In conclusion, Bi-PE strategy expanded the editing scope and improved the efficiency and the accuracy of prime editing system, which might have a wide range of potential applications.

Mattress-Based Non-Influencing Sleep Apnea Monitoring System.

A mattress-type non-influencing sleep apnea monitoring system was designed to detect sleep apnea-hypopnea syndrome (SAHS). The pressure signals generated during sleep on the mattress were collected, and ballistocardiogram (BCG) and respiratory signals were extracted from the original signals. In the experiment, wavelet transform (WT) was used to reduce noise and decompose and reconstruct the signal to eliminate the influence of interference noise, which can directly and accurately separate the BCG signal and respiratory signal. In feature extraction, based on the five features commonly used in SAHS, an innovative respiratory waveform similarity feature was proposed in this work for the first time. In the SAHS detection, the binomial logistic regression was used to determine the sleep apnea symptoms in the signal segment. Simulation and experimental results showed that the device, algorithm, and system designed in this work were effective methods to detect, diagnose, and assist the diagnosis of SAHS.

A split cytosine deaminase architecture enables robust inducible base editing.

Directed base substitution with base editing technology enables efficient and programmable conversion of C:G or A:T base pairs to T:A or G:C in the genome. Although this technology has shown great potentials in a variety of basic research, off-target editing is among one of the biggest challenges toward its way to clinical application. Base editing tools, especially the tools converting C to T, caused unpredictable off-target editing throughout the genome, which raise the concern that long-term application of these tools would induce genomic instability or even tumorigenesis. To overcome this challenge, we designed an inducible base editing tool that was active only in the presence of a clinically safe chemical, rapamycin. In the guidance of structural information, we designed four split-human APOBEC3A (A3A) -BE3 base editors in which these A3A deaminase enzymes were split at sites that were opposite to the protein-nucleotide interface. We showed that by inducible deaminase reconstruction with a rapamycin responsible interaction system (FRB and FKBP); three out of four split-A3A-derived base editors showed robust inducible base editing. However, in the absence of rapamycin, their editing ability was dramatically inhibited. Among these split editors, splicing at Aa85 of A3A generated the most efficient inducible editing. In addition, compared to the full-length base editor, the splitting did not obviously alter the editing window and motif preference, but slightly increased the product purity. We also expanded this strategy to another frequently used cytosine deaminase, rat APOBEC1 (rA1), and observed a similar induction response. In summary, these results demonstrated the concept that splitting deaminases is a practicable method for timely controlling of base editing tools.

A New Node Deployment and Location Dispatch Algorithm for Underwater Sensor Networks.

Considering that deployment strategies for underwater sensor networks should contribute to fully connecting the networks, a Guaranteed Full Connectivity Node Deployment (GFCND) algorithm is proposed in this study. The GFCND algorithm attempts to deploy the coverage nodes according to the greedy iterative strategy, after which the connectivity nodes are used to improve network connectivity and fully connect the whole network. Furthermore, a Location Dispatch Based on Command Nodes (LDBCN) algorithm is proposed, which accomplishes the location adjustment of the common nodes with the help of the SINK node and the command nodes. The command nodes then dispatch the common nodes. Simulation results show that the GFCND algorithm achieves a comparatively large coverage percentage and a fully connected network; furthermore, the LDBCN algorithm helps the common nodes preserve more total energy when they reach their destination locations.

Node Deployment Algorithm Based on Connected Tree for Underwater Sensor Networks.

Designing an efficient deployment method to guarantee optimal monitoring quality is one of the key topics in underwater sensor networks. At present, a realistic approach of deployment involves adjusting the depths of nodes in water. One of the typical algorithms used in such process is the self-deployment depth adjustment algorithm (SDDA). This algorithm mainly focuses on maximizing network coverage by constantly adjusting node depths to reduce coverage overlaps between two neighboring nodes, and thus, achieves good performance. However, the connectivity performance of SDDA is irresolute. In this paper, we propose a depth adjustment algorithm based on connected tree (CTDA). In CTDA, the sink node is used as the first root node to start building a connected tree. Finally, the network can be organized as a forest to maintain network connectivity. Coverage overlaps between the parent node and the child node are then reduced within each sub-tree to optimize coverage. The hierarchical strategy is used to adjust the distance between the parent node and the child node to reduce node movement. Furthermore, the silent mode is adopted to reduce communication cost. Simulations show that compared with SDDA, CTDA can achieve high connectivity with various communication ranges and different numbers of nodes. Moreover, it can realize coverage as high as that of SDDA with various sensing ranges and numbers of nodes but with less energy consumption. Simulations under sparse environments show that the connectivity and energy consumption performances of CTDA are considerably better than those of SDDA. Meanwhile, the connectivity and coverage performances of CTDA are close to those depth adjustment algorithms base on connected dominating set (CDA), which is an algorithm similar to CTDA. However, the energy consumption of CTDA is less than that of CDA, particularly in sparse underwater environments.

An improved BECT spike detection method with functional brain network features based on PLV.

Background: Children with benign childhood epilepsy with centro-temporal spikes (BECT) have spikes, sharps, and composite waves on their electroencephalogram (EEG). It is necessary to detect spikes to diagnose BECT clinically. The template matching method can identify spikes effectively. However, due to the individual specificity, finding representative templates to detect spikes in actual applications is often challenging. Purpose: This paper proposes a spike detection method using functional brain networks based on phase locking value (FBN-PLV) and deep learning. Methods: To obtain high detection effect, this method uses a specific template matching method and the 'peak-to-peak' phenomenon of montages to obtain a set of candidate spikes. With the set of candidate spikes, functional brain networks (FBN) are constructed based on phase locking value (PLV) to extract the features of the network structure during spike discharge with phase synchronization. Finally, the time domain features of the candidate spikes and the structural features of the FBN-PLV are input into the artificial neural network (ANN) to identify the spikes. Results: Based on FBN-PLV and ANN, the EEG data sets of four BECT cases from the Children's Hospital, Zhejiang University School of Medicine are tested with the AC of 97.6%, SE of 98.3%, and SP 96.8%.

Internally inlaid SaCas9 base editors enable window specific base editing.

Rationale: Base editors composed of catalytic defective Cas9 and cytosine or adenosine deaminase are powerful tools to convert bases in a genome. However, the fixed and narrow editing window of current base editors has impeded their utility. To increase the scope and diversify the editing patterns is quite necessary. Methods and Results: We designed a subset of base editors derived from SaCas9 in which deaminase was inlaid into various locations of the SaCas9 protein. The resulting base editors were characterized with multiple genomic sites and were found to have distinct editing features to the N-terminal SaCas9 CBE (Sa-CBE-N). Among them, Sa-CBE-693, in which a cytosine deaminase was inserted between amino acids 693 and 694, showed an increased editing efficiency and a significantly expanded editing window ranging from bases 2-18. This feature enhanced the editing efficiency of BCL11A enhancer that contains multiple consensus bases in a 15-bp fragment. Another variant, Sa-CBE-125, displayed backward-shifted editing window, which we showed was particularly powerful in editing cytosines that were accompanied with unintended bystander cytosines at their 5' side. Additionally, these editors showed reduced Cas9 independent DNA off-target editing compared with Sa-CBE-N. Conclusion: Our inlaid base editors improved the targeting scope and diversified the editing pattern.

Expanding PAM recognition and enhancing base editing activity of Cas9 variants with non-PI domain mutations derived from xCas9.

The recognition of protospacer adjacent motif (PAM) is a key factor for the CRISPR (i.e. clustered regularly interspaced short palindromic repeats)/CRISPR-associated 9 (Cas9) system to distinguish foreign DNAs from the host genome, and also significantly restricts the targeting scope of the system during genome-editing applications. Structurally, the PAM interacting (PI) domain, which usually is located in the C-terminus of Cas9 proteins, directly binds to PAM and plays a key role in determining the recognition specificity. However, several lines of evidence showed that other regions of Cas9 protein beyond the PI domain might also play roles in PAM interaction. Here, we constructed a mosaic SpCas9 protein (xCas9-NG) by fusing the PI domain of SpCas9 PAM variant, Cas9-NG with the non-PI fragment of xCas9 protein that contains multiple amino acid substitutions. We found that non-PI fragment of xCas9 expanded PAM recognition of the Cas9-NG PI domain. In addition, xCas9-NG showed an improved editing efficiency in the majority of targets harboring xCas9 and Cas9-NG PAMs. Importantly, this finding was also successfully extended to other Cas9 variants, including SpRY and the non-G SpCas9 series. Together, our work expands the target scope of SpCas9 editing system and demonstrates the notion that the non-PI domain fragment plays an important role in PAM restriction.

Flexible, anti-damage, and non-contact sensing electronic skin implanted with MWCNT to block public pathogens contact infection.

If a person comes into contact with pathogens on public facilities, there is a threat of contact (skin/wound) infections. More urgently, there are also reports about COVID-19 coronavirus contact infection, which once again reminds that contact infection is a very easily overlooked disease exposure route. Herein, we propose an innovative implantation strategy to fabricate a multi-walled carbon nanotube/polyvinyl alcohol (MWCNT/PVA, MCP) interpenetrating interface to achieve flexibility, anti-damage, and non-contact sensing electronic skin (E-skin). Interestingly, the MCP E-skin had a fascinating non-contact sensing function, which can respond to the finger approaching 0-20 mm through the spatial weak field. This non-contact sensing can be applied urgently to human-machine interactions in public facilities to block pathogen. The scratches of the fruit knife did not damage the MCP E-skin, and can resist chemical corrosion after hydrophobic treatment. In addition, the MCP E-skin was developed to real-time monitor the respiratory and cough for exercise detection and disease diagnosis. Notably, the MCP E-skin has great potential for emergency applications in times of infectious disease pandemics. Electronic Supplementary Material: Supplementary material (fabrication of MCP E-skin, laser confocal tomography, parameter optimization, mechanical property characterization, finite element simulation, sensing mechanism, signal processing) is available in the online version of this article at 10.1007/s12274-021-3831-z.

WT-PE: Prime editing with nuclease wild-type Cas9 enables versatile large-scale genome editing.

Large scale genomic aberrations including duplication, deletion, translocation, and other structural changes are the cause of a subtype of hereditary genetic disorders and contribute to onset or progress of cancer. The current prime editor, PE2, consisting of Cas9-nickase and reverse transcriptase enables efficient editing of genomic deletion and insertion, however, at small scale. Here, we designed a novel prime editor by fusing reverse transcriptase (RT) to nuclease wild-type Cas9 (WT-PE) to edit large genomic fragment. WT-PE system simultaneously introduced a double strand break (DSB) and a single 3' extended flap in the target site. Coupled with paired prime editing guide RNAs (pegRNAs) that have complementary sequences in their 3' terminus while target different genomic regions, WT-PE produced bi-directional prime editing, which enabled efficient and versatile large-scale genome editing, including large fragment deletion up to 16.8 megabase (Mb) pairs and chromosomal translocation. Therefore, our WT-PE system has great potential to model or treat diseases related to large-fragment aberrations.

A universal strategy for AAV delivery of base editors to correct genetic point mutations in neonatal PKU mice.

Base editing tools enabled efficient conversion of C:G or A:T base pairs to T:A or G:C, which are especially powerful for targeting monogenic lesions. However, in vivo correction of disease-causing mutations is still less efficient because of the large size of base editors. Here, we designed a dual adeno-associated virus (AAV) strategy for in vivo delivery of base editors, in which deaminases were linked to Cas9 through the interaction of GCN4 peptide and its single chain variable fragment (scFv) antibody. We found that one or two copies of GCN4 peptide were enough for the assembly of base editors and produced robust targeted editing. By optimization of single-guide RNAs (sgRNAs) that target phenylketonuria (PKU) mutation, we were able to achieve up to 27.7% correction in vitro. In vivo delivery of this dual AAV base editing system resulted in efficient correction of PKU-related mutation in neonatal mice and subsequent rescue of hyperphenylalaninemia-associated syndromes. Considering the similarity between Cas9 proteins from different organisms, our delivery strategy will be compatible with other Cas9-derived base editors.

Random-PE: an efficient integration of random sequences into mammalian genome by prime editing.

Prime editing (PE) enables efficiently targeted introduction of multiple types of small-sized genetic change without requiring double-strand breaks or donor templates. Here we designed a simple strategy to introduce random DNA sequences into targeted genomic loci by prime editing, which we named random prime editing (Random-PE). In our strategy, the prime editing guide RNA (pegRNA) was engineered to harbor random sequences between the primer binding sequence (PBS) and homologous arm (HA) of the reverse transcriptase templates. With these pegRNAs, we achieved efficient targeted insertion or substitution of random sequences with different lengths, ranging from 5 to 10, in mammalian cells. Importantly, the diversity of inserted sequences is well preserved. By fine-tuning the design of random sequences, we were able to make simultaneously insertions or substitutions of random sequences in multiple sites, allowing in situ evolution of multiple positions in a given protein. Therefore, these results provide a framework for targeted integration of random sequences into genomes, which can be redirected for manifold applications, such as in situ protospacer adjacent motif (PAM) library construction, enhancer screening, and DNA barcoding.

A Noise-Filtering Method for Link Prediction in Complex Networks.

Link prediction plays an important role in both finding missing links in networked systems and complementing our understanding of the evolution of networks. Much attention from the network science community are paid to figure out how to efficiently predict the missing/future links based on the observed topology. Real-world information always contain noise, which is also the case in an observed network. This problem is rarely considered in existing methods. In this paper, we treat the existence of observed links as known information. By filtering out noises in this information, the underlying regularity of the connection information is retrieved and then used to predict missing or future links. Experiments on various empirical networks show that our method performs noticeably better than baseline algorithms.