Predicting efficiency of writing short sequences into the genome using prime editing

Any short sequence can be precisely written into a selected genomic target using prime editing. This ability facilitates protein tagging, correction of pathogenic deletions, and many other exciting applications. However, it remains unclear what types of sequences prime editors can efficiently insert, and how to choose optimal reagents for a desired outcome. To characterize features that influence insertion efficiency, we designed a library of 2,666 sequences up to 69 nt in length and measured the frequency of their insertion into four genomic sites in three human cell lines, using different prime editor systems. We discover that insertion sequence length, nucleotide composition and secondary structure all affect insertion rates, and that mismatch repair proficiency is a strong determinant for the shortest insertions. Combining the sequence and repair features into a machine learning model, we can predict insertion frequency for new sequences with R = 0.69. The tools we provide allow users to choose optimal constructs for DNA insertion using prime editing.

ROP Defense Using Trie Graph for System Security

Most Intrusion Detection Systems (IDS) / Intrusion Prevention Systems (IPS) cannot defend the attacks from a Return Oriented Program (ROP) which applies code reusing and exploiting techniques without the need for code injection. Malicious attackers chain a short sequence as a gadget and execute this gadget as an arbitrary (Turing-complete) behavior in the target program. Lots of ROP defense tools have been developed with satisfactory performance and low costs overhead, but malicious attackers can evade ROP tools. Therefore, it needs security researchers to continually improve existing ROP defense tools, because the defense ability of target devices, such as smartphones is weak, and such devices are being increasingly targeted. Our contribution in this paper is to propose an ROP defense method that has provided a better performance of defense against ROP attacks than existing ROP defense tools.

ROP Defense Using Trie Graph For System Security

Most Intrusion Detection Systems (IDS) / Intrusion Prevention Systems (IPS) cannot defend the attacks from a Return Oriented Program (ROP) which applies code reusing and exploiting techniques without the need for code injection. Malicious attackers chain a short sequence as a gadget and execute this gadget as an arbitrary (Turing-complete) behavior in the target program. Lots of ROP defense tools have been developed with satisfactory performance and low costs overhead, but malicious attackers can evade ROP tools. Therefore, it needs security researchers to continually improve existing ROP defense tools, because the defense ability of target devices, such as smartphones is weak, and such devices are being increasingly targeted. Our contribution in this paper is to propose an ROP defense method that has provided a better performance of defense against ROP attacks than existing ROP defense tools.

DWNet: Dual-Window Deep Neural Network for Time Series Prediction

Multivariate time series prediction is a very important task, which plays a huge role in climate, economy, and other fields. We usually use an Attention-based Encoder-Decoder network to deal with multivariate time series prediction because the attention mechanism makes it easier for the model to focus on the really important attributes. However, the Encoder-Decoder network has the problem that the longer the length of the sequence is, the worse the prediction accuracy is, which means that the Encoder-Decoder network cannot process long series and therefore cannot obtain detailed historical information. In this paper, we propose a dual-window deep neural network (DWNet) to predict time series. The dual-window mechanism allows the model to mine multigranularity dependencies of time series, such as local information obtained from a short sequence and global information obtained from a long sequence. Our model outperforms nine baseline methods in four different datasets.

A High-Throughput Short Sequence Typing Scheme for Serratia marcescens Pure Culture and Environmental DNA

Molecular typing methods are used to characterize the relatedness between bacterial isolates involved in infections. These approaches rely mostly on discrete loci or whole genome sequences (WGS) analyses of pure cultures. On the other hand, their application to environmental DNA profiling to evaluate epidemiological relatedness amongst patients and environments has received less attention. We developed a specific, high-throughput short sequence typing (HiSST) method for the opportunistic human pathogen Serratia marcescens . Genes displaying the highest polymorphism were retrieved from the core genome of 60 S. marcescens strains. Bioinformatics analyses showed that use of only three loci (within bssA , gabR and dhaM ) distinguished strains with a high level of efficiency. This HiSST scheme was applied to an epidemiological survey of S. marcescens in a neonatal intensive care unit (NICU). In a first case study, a strain responsible for an outbreak in the NICU was found in a sink drain of this unit, by using HiSST scheme and confirmed by WGS. The HiSST scheme was also applied to environmental DNA extracted from sink-environment samples. Diversity of S. marcescens was modest, with 11, 6 and 4 different sequence types (ST) of gabR , bssA and dhaM loci amongst 19 sink drains, respectively. Epidemiological relationships amongst sinks were inferred on the basis of pairwise comparisons of ST profiles. Further research aimed at relating ST distribution patterns to environmental features encompassing sink location, utilization and microbial diversity is needed to improve the surveillance and management of opportunistic pathogens. Importance Serratia marcescens is an important opportunistic human pathogen, multidrug resistant and often involved in outbreaks of nosocomial infections in neonatal intensive care unit. Here, we propose a quick and user-friendly method to select the best typing scheme for nosocomial outbreaks in relating environmental and clinical sources. This method, named high-throughput short sequence typing (HiSST), allows to distinguish strains and to explore the diversity profile of non-culturable S. marcescens . The application of HiSST profile analysis for environmental DNA offers new possibilities to track opportunistic pathogens, identify their origin and relate their distribution pattern with environmental features encompassing sink location, utilization and microbial diversity. Adaptation of the method to other opportunistic pathogens is expected to improve knowledge regarding their ecology, which of significant interest for epidemiological risk assessment and elaborate outbreak mitigation strategies.

ICSTrace: A Malicious IP Traceback Model for Attacking Data of the Industrial Control System

Considering that the attacks against the industrial control system are mostly organized and premeditated actions, IP traceback is significant for the security of the industrial control system. Based on the infrastructure of the internet, we have developed a novel malicious IP traceback model, ICSTrace, without deploying any new services. The model extracts the function codes and their parameters from the attack data according to the format of the industrial control protocol and employs a short sequence probability method to transform the function codes and their parameters into a vector, which characterizes the attack pattern of malicious IP addresses. Furthermore, a partial seeded K-means algorithm is proposed for the pattern’s clustering, which helps in tracing the attacks back to an organization. ICSTrace is evaluated based on the attack data captured by the large-scale deployed honeypots for the industrial control system, and the results demonstrate that ICSTrace is effective on malicious IP traceback in the industrial control system.

REPINs are facultative genomic symbionts of bacterial genomes

Relationships among organisms, in which one lives inside of another, with benefits accruing to both partners, are referred to as endosymbiotic. Such relationships are common in the biological world, yet descriptions are confined to organismal life. Here we argue that short sequence repeats known as REPINs - whose replication is dependent on a non-jumping RAYT transposase - form a similar facultative symbiotic relationship with the bacterial chromosome. Evidence stems from distribution patterns across the eubacteria: persistence times of many millions of years, exceedingly rare duplication rates, vertical transmission, and population biology typical of living organisms, including population size fluctuations that correlate with available genome space. Additional analysis of patterns of REPIN evolution conform with theoretical predictions of conflict (and resolution) arising from the effects of selection operating simultaneously on REPINs and host cells. A search for similar kinds of genomic symbionts suggests that the REPIN-RAYT system is not unique.

Development and Validation of a High-throughput Short Sequence Typing Scheme for Serratia marcescens Pure Culture and Environmental DNA

Molecular typing methods are used to characterize the relatedness between bacterial isolates involved in infections. These approaches rely mostly on discrete loci or whole genome sequences (WGS) analyses of pure cultures. On the other hand, their application to environmental DNA profiling to evaluate epidemiological relatedness amongst patients and environments has received less attention. We developed a specific, high-throughput short sequence typing (HiSST) method for the opportunistic human pathogen Serratia marcescens. Genes displaying the highest polymorphism were retrieved from the core genome of 60 S. marcescens strains. Bioinformatics analyses showed that use of only three loci (within bssA, gabR and dhaM) distinguished strains with the same level of efficiency than average nucleotide identity scores of whole genomes. This HiSST scheme was applied to an epidemiological survey of S. marcescens in a neonatal intensive care unit (NICU). In a first case study, a strain responsible for an outbreak in the NICU was found in a sink drain of this unit, by using HiSST scheme and confirmed by WGS. The HiSST scheme was also applied to environmental DNA extracted from sink-environment samples. Diversity of S. marcescens was modest, with 11, 6 and 4 different sequence types (ST) of gabR, bssA and dhaM loci amongst 19 sink drains, respectively. Epidemiological relationships amongst sinks were inferred on the basis of pairwise comparisons of ST profiles. Further research aimed at relating ST distribution patterns to environmental features encompassing sink location, utilization and microbial diversity is needed to improve the surveillance and management of opportunistic pathogens.