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The technology of recombineering, in vivo genetic engineering, was initially developed in Escherichia coli and uses bacteriophage-encoded homologous recombination proteins to efficiently recombine DNA at short homologies (35 to 50 nt). Because the technology is homology driven, genomic DNA can be modified precisely and independently of restriction site location. Recombineering uses linear DNA substrates that are introduced into the cell by electroporation; these can be PCR products, synthetic double-strand DNA (dsDNA), or single-strand DNA (ssDNA). Here we describe the applications, challenges, and factors affecting ssDNA and dsDNA recombineering in a variety of non-model bacteria, both Gram-negative and -positive, and recent breakthroughs in the field. We list different microbes in which the widely used phage λ Red and Rac RecET recombination systems have been used for in vivo genetic engineering. New homologous ssDNA and dsDNA recombineering systems isolated from non-model bacteria are also described. The Basic Protocol outlines a method for ssDNA recombineering in the non-model species of Shewanella. The Alternate Protocol describes the use of CRISPR/Cas as a counter-selection system in conjunction with recombineering to enhance recovery of recombinants. We provide additional background information, pertinent considerations for experimental design, and parameters critical for success. The design of ssDNA oligonucleotides (oligos) and various internet-based tools for oligo selection from genome sequences are also described, as is the use of oligo-mediated recombination. This simple form of genome editing uses only ssDNA oligo(s) and does not require an exogenous recombination system. The information presented here should help researchers identify a recombineering system suitable for their microbe(s) of interest. If no system has been characterized for a specific microbe, researchers can find guidance in developing a recombineering system from scratch. We provide a flowchart of decision-making paths for strategically applying annealase-dependent or oligo-mediated recombination in non-model and undomesticated bacteria. © 2022 Wiley Periodicals LLC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA. Basic Protocol: ssDNA recombineering in Shewanella species Alternate Protocol: ssDNA recombineering coupled to CRISPR/Cas9 in Shewanella species.

Solid-state nanopore-based electrical detection of DNA nucleotides with the quantum tunneling technique has emerged as a powerful strategy to be the next-generation sequencing technology. However, experimental complexity has been a foremost obstacle in achieving a more accurate high-throughput analysis with industrial scalability. Here, with one of the nucleotide training data sets of a model monolayer gold nanopore, we have predicted the transmission function for all other nucleotides with root-mean-square error scores as low as 0.12 using the optimized eXtreme Gradient Boosting Regression (XGBR) model. Further, the SHapley Additive exPlanations (SHAP) analysis helped in exploring the interpretability of the XGBR model prediction and revealed the complex relationship between the molecular properties of nucleotides and their transmission functions by both global and local interpretable explanations. Hence, experimental integration of our proposed machine-learning-assisted transmission function prediction method can offer a new direction for the realization of cheap, accurate, and ultrafast DNA sequencing.

Malignant rhabdoid tumor (MRT) is a highly aggressive pediatric malignancy with no effective therapy. Therefore, it is necessary to identify a target for the development of novel molecule-targeting therapeutic agents. In this study, we report the importance of the runt-related transcription factor 1 (

Spätzle is a crucial ligand for Toll-like receptor (TLR) that triggers the activation of TLR signal pathway in insects. In this study, open reading frames (ORFs) of two spätzles were cloned from Portunus trituberculatus (PtSpz1 and PtSpz2). Both of PtSpzs contained the typical cystine-knot domain of spätzle. Tissue distribution analysis showed that both of PtSpzs were predominantly expressed in the gills. Transcriptional levels of the two PtSpzs in hemocytes and gill rapidly increased at 3 h and 6 h post Vibrio alginolyticus challenge, respectively. The two PtSpzs could bind to several pathogen-associated molecules including lipopolysaccharide (LPS), peptidoglycan (PGN) and envelope proteins of white spot syndrome virus (WSSV). Moreover, the two PtSpzs could directly interact with the extracellular leucine-rich repeats (LRR) domain of TLR. This study revealed that spätzle could interact with pathogen-associated molecules and TLR of host, which may be two important steps for spätzle to deliver signals into host cells.

Lysozyme is relevant to the innate immune system as a vital protein for crustaceans. In the present study, we cloned and characterized a novel c-type lysozyme gene (LvLYZ) from the Pacific white shrimp (Litopenaeus vannamei). The obtained full-length cDNA of LvLYZ was 990 bp and contained an open reading frame of 693 bp. Its deduced amino acid sequence consisted of 230 amino acids (aa) with a 17 aa signal peptide at the N-terminal and 130 aa functional domains. The multiple sequence alignment (MSA) indicated that the typical active sites in LvLYZ were similarly conserved as c-type lysozymes from other species. The transcription of LvLYZ appeared in all detected tissues and had relatively higher expression levels in hemocytes, hepatopancreas, gill and intestine. The mRNA expression profiles of LvLYZ were up-regulated in hemocyte and hepatopancreas post the stimulation of Vibrio parahaemolyticus or white spot syndrome virus (WSSV), respectively. The recombinant protein of LvLYZ (rLvLYZ) exhibited antibacterial activities against various microbes, including Escherichia coli, Vibrio splendidus, Micrococcaus luteus, Vibrio parahaemolyticus and Staphylococcus aureus. These results indicated that LvLYZ could cope with bacteria in L. vannamei and may play a significant role in immune response against invading pathogens.

HCoV-OC43 is one of the mildly pathogenic coronaviruses with high infection rates in common population. Here, 43 HCoV-OC43 related cases with pneumonia were reported, corresponding genomes of HCoV-OC43 were obtained. Phylogenetic analyses based on complete genome, orf1ab and spike genes revealed that two novel genotypes of HCoV-OC43 have emerged in China. Obvious recombinant events also can be detected in the analysis of the evolutionary dynamics of novel HCoV-OC43 genotypes. Estimated divergence time analysis indicated that the two novel genotypes had apparently independent evolutionary routes. Efforts should be conducted for further investigation of genomic diversity and evolution analysis of mildly pathogenic coronaviruses.

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RNA aptamers are oligonucleotides with high binding affinity and specificity for target molecules and are expected to be a new generation of therapeutic molecules and targeted delivery materials. The tertiary structure of RNA molecules and RNA-protein interaction sites are increasingly important as potential targets for new drugs. The pathological mechanisms of diseases must be understood in detail to guide drug design. In developing RNA aptamers as drugs, information about the interaction mechanisms and structures of RNA aptamer-target protein complexes are useful. We constructed a database, RNA aptamer 3D-structural modeling (RNAapt3D), consisting of RNA aptamer data that are potential drug candidates. The database includes RNA sequences and computationally predicted RNA tertiary structures based on secondary structures and implements methods that can be used to predict unknown structures of RNA aptamer-target molecule complexes. RNAapt3D should enable the design of RNA aptamers for target molecules and improve the efficiency and productivity of candidate drug selection. RNAapt3D can be accessed at https://rnaapt3d.medals.jp.

Mucopolysaccharidosis type II (MPS II) is an X-linked recessive lysosomal storage disorder caused by various variants in the IDS gene. It is known that genomic recombinants between IDS and its homologous pseudogene IDSP1 account for a small number of patients, for whom genetic diagnosis usually relies on restriction enzyme digestion at specific loci. Nevertheless, such approach cannot reveal the impact of rearrangements on IDS transcription, which is crucial for the interpretation of the pathogenicity of rearrangement variants.RNA sequencing (RNA-seq) was explored to analyze transcriptional alterations in four male MPS II patients who were negative for Sanger sequencing of the IDS gene. Reverse transcription-polymerase chain reaction and TA clone sequencing were used to validate RNA-seq analysis results. The IDS-IDSP1 recombinant was determined by sequencing the indicated loci in genome.Differential expression analysis showed the expression levels of IDS gene in patients were largely reduced compared to the healthy individuals. Differential splicing analysis revealed skipping of exons 8 and 9 of IDS, without any splice-junction defects at the genomic level. In addition, two types of fusion transcripts, IDS_EOLA1 and IDS_EOLA1-DT_EOLA1 were identified by gene fusion analysis. Sequencing of the known rearrangement alleles showed these four patients have the same type of IDS-IDSP1 recombinant.We establish an RNA-seq workflow to analyze transcriptional characteristics of IDS gene from multiple perspectives. Our study validates the diagnostic value of RNA-seq in MPS II, including the discovery of transcriptional alterations and the potential to suggest genome-level rearrangements in IDS.

Protein interactions with the microRNA (miRNA)-mediated gene silencing protein Argonaute 2 (AGO2) control miRNA expression. miRNA biogenesis starts with the production of precursor transcripts and culminates with the loading of mature miRNA onto AGO2 by DICER1. Here we reveal an additional component to the regulatory mechanism for miRNA biogenesis involving the adaptor protein, growth factor receptor-bound protein 2 (GRB2). The N-terminal SH3 domain of GRB2 is recruited to the PAZ domain of AGO2 forming a ternary complex containing GRB2, AGO2 and DICER1. Using small-RNA sequencing we identified two groups of miRNAs which are regulated by the binding of GRB2. First, mature and precursor transcripts of mir-17~92 and mir-221 miRNAs are enhanced. Second, mature, but not precursor, let-7 family miRNAs are diminished suggesting that GRB2 directly affects loading of these miRNAs. Notably, the resulting loss of let-7 augments expression of oncogenic targets such as RAS. Thus, a new role for GRB2 is established with implications for cancer pathogenesis through regulation of miRNA biogenesis and oncogene expression.

Some transcription factors bind DNA motifs containing direct or inverted sequence repeats. Preference for each of these DNA topologies is dictated by structural constraints. Most prokaryotic regulators form symmetric oligomers, which require operators with a dyad structure. Binding to direct repeats requires breaking the internal symmetry, a property restricted to a few regulators, most of them from the AraC family. The KorA family of transcriptional repressors, involved in plasmid propagation and stability, includes members that form symmetric dimers and recognize inverted repeats. Our structural analyses show that ArdK, a member of this family, can form a symmetric dimer similar to that observed for KorA, yet it binds direct sequence repeats as a non-symmetric dimer. This is possible by the 180° rotation of one of the helix–turn–helix domains. We then probed and confirmed that ArdK shows affinity for an inverted repeat, which, surprisingly, is also recognized by a non-symmetrical dimer. Our results indicate that structural flexibility at different positions in the dimerization interface constrains transcription factors to bind DNA sequences with one of these two alternative DNA topologies., This work was supported by the Spanish Ministry of Economy, Industry and Competitiveness [BIO2016-77883-C2-2-P and FIS2015-72574-EXP (AEI/FEDER, EU), to D.R.B., BFU2017-86378-P to F.dlC.] and by the Spanish Ministryof Science (MCI/AEI/FEDER,UE) [PGC2018-093885-BI00 and PID2021-122164NB-I00 to G.M., PID2020- 117028GB-I00 to D.R.B. and PID2019-110216GB-I00 to R. F-L.].

Tracking SARS-CoV-2 variants of concern (VOC) by genomic sequencing is time-consuming. The rapid screening of VOCs is necessary for clinical laboratories. In this study, we developed a rapid screening method based on multiplex RT-PCR by extended S-gene target failure (eSGTF), a false negative result caused by S-gene mutations.Three S-gene target (SGT) regions (SGT1, codons 65-72; SGT2, codons 152-159; and SGT3, codons 370-377) and an N-gene region (for internal control) were detected in single-tube. Four types of VOC (Alpha, Delta, Omicron BA.1, and Omicron BA.2) are classified by positive/negative patterns of 3 S-gene regions (eSGTF pattern).The eSGTF patterns of VOCs were as follows (SGT1, SGT2, SGT3; P, positive; N, negative): Alpha, NPP; Delta, PNP; Omicron BA.1, NPN pattern; and Omicron BA.2, PPN. As compared with the S-gene sequencing, eSGTF patterns were identical to the specific VOCs (concordance rate = 96.7%, N = 206/213). Seven samples with discordant results had a minor mutation in the probe binding region. The epidemics of VOCs estimated by eSGTF patterns were similar to those in Japan.Multiplex RT-PCR and eSGTF patterns enable high-throughput screening of VOCs. It will be useful for the rapid determination of VOCs in clinical laboratories.

Glutaredoxin (Grx) is a class molecule oxidoreductase, which plays a key role in maintaining redox homeostasis and regulating cell survival pathways. However, the expression pattern and function of Grx remain unknown in the mud crab (Scylla paramamosain). In the present study, a novel full-length of Grx 5 from the mud crab (designated as Sp-Grx 5) was cloned and characterized. The open reading frame of Sp-Grx 5 was 441 bp, which encoded a putative protein of 146 amino acids. The amino acid sequence of Sp-Grx 5 contained a typical C-G-F-S redox active motif and several GSH binding sites. Sp-Grx 5 widely existed in all tested tissues with a high-level expression in hepatopancreas. Subcellular localization showed that Sp-Grx 5 was located in the cytoplasm and nucleus. The expression of Sp-Grx 5 was significantly up-regulated after Vibrio parahaemolyticus infection and cadmium exposure, suggesting that Sp-Grx 5 was involved in innate immunity and detoxification. Furthermore, overexpression of Sp-Grx 5 could improve cells viability after H

Ficolins, belonging to the fibrinogen-related protein superfamily, are important pattern recognition receptors in innate immunity. Here, a ficolin gene Ptficolin was characterized from the swimming crab Portunus trituberculatus. The completed cDNA sequence of Ptficolin encoded a signal peptide, a coiled-coil region and a fibrinogen-like domain but without the typical collagen region of vertebrate ficolins. Ptficolin showed higher expression in stomach and hepatopancreas, and presented a time-dependent response after pathogen challenge and injury stimulation. The recombinant Ptficolin (rPtficolin) could bind to various PAMPs and microorganisms, and agglutinate microorganisms and rabbit erythrocytes in a Ca

Maize is a globally valuable commodity and one of the most extensively studied genetic model organisms. However, we know surprisingly little about the extent and potential utility of the genetic variation found in wild relatives of maize. Here, we characterize a high-density genomic variation map from 744 genomes encompassing maize and all wild taxa of the genus Zea, identifying over 70 million single-nucleotide polymorphisms. The variation map reveals evidence of selection within taxa displaying novel adaptations. We focus on adaptive alleles in highland teosinte and temperate maize, highlighting the key role of flowering-time-related pathways in their adaptation. To show the utility of variants in these data, we generate mutant alleles for two flowering-time candidate genes. This work provides an extensive sampling of the genetic diversity of Zea, resolving questions on evolution and identifying adaptive variants for direct use in modern breeding.

It was noticed that the mortality rate of SARS-CoV-2 infection experienced a significant declination in the early stage of the epidemic. We suspect that the sharp deterioration of virus toxicity is related to the deletion of the untranslated region (UTR) of the virus genome. It was found that the genome length of SARS-CoV-2 engaged a significant truncation due to UTR deletion after a mega-sequence analysis. Sequence similarity analysis further indicated that short UTR strains originated from its long UTR ancestors after an irreversible deletion. A good correlation was discovered between genome length and mortality, which demonstrated that the deletion of the virus UTR significantly affected the toxicity of the virus. This correlation was further confirmed in a significance analysis of the genetic influence on the clinical outcomes. The viral genome length of hospitalized patients was significantly more extensive than that of asymptomatic patients. In contrast, the viral genome length of asymptomatic was considerably longer than that of ordinary patients with symptoms. A genome-level mutation scanning was performed to systematically evaluate the influence of mutations at each position on virulence. The results indicated that UTR deletion was the primary driving force in alternating virus virulence in the early evolution. In the end, we proposed a mathematical model to explain why this UTR deletion was not continuous.

Genome sequencing (GS) outperforms other rare disease diagnostics, but standardized approaches to assessing its clinical utility are limited. This study assessed the validity of the Clinician-reported Genetic testing Utility InDEx (C-GUIDE), a novel tool for assessing the utility of genetic testing from a clinician’s perspective, for GS. C-GUIDE ratings were completed for patients who received GS results. For each patient, total C-GUIDE and single item global scores were calculated. Construct validity was assessed using linear regression to determine the association between C-GUIDE total and global item scores and measure the effects of potential explanatory variables. Ratings were completed for 67 pediatric and 36 adult patients. GS indications were neurological for 70.9% and results were diagnostic for 28.2%. When the C-GUIDE assessed primary (PV), secondary (SV), and pharmacogenomic (PGx) variants, on average, a one unit increase in the global item score was associated with an increase of 7.3 in the C-GUIDE score (p p p p

Cold shock protein D (CspD) is one of the homologous proteins of cold shock protein A (CspA), inhibiting DNA replication by binding to single-stranded DNA. We found that CspD from Vibrio cholerae (VcCspD) possesses one heme regulatory motif (HRM) sequence and specifically binds heme with a stoichiometry of 1:1. The binding of a synthetic single-stranded DNA oligomer (ssDNA) was followed by fluorescence quenching of Trp. The fluorescence quenching associated with the addition of ssDNA was suppressed in the presence of heme, indicating that heme binding to VcCspD inhibited the formation of the VcCspD-ssDNA complex. Such heme-induced inhibition was not observed for the VcCspD mutant with replacement of Cys22 in the HRM with alanine (C22A). Heme binding at Cys22 is, therefore, essential for the inhibition of ssDNA binding for VcCspD. The growth of Escherichia coli at 37 °C was slowed when VcCspD was overexpressed, indicating that VcCspD hampers the growth of E. coli. When the production of heme in cells was promoted by the addition of a heme precursor, δ-aminolevulinic acid, the growth of E. coli expressing VcCspD was decelerated, but the growth of E. coli expressing the C22A mutant was not decelerated. These observations allow us to conclude that heme specifically binds to the HRM region in VcCspD and inhibits the binding of target ssDNA, which suggests that heme functions as a regulatory molecule for DNA replication.

Selective gene regulation is mediated by recognition of specific DNA sequences by transcription factors (TFs). The extremely challenging task of searching out specific cognate DNA binding sites among several million putative sites within the eukaryotic genome is achieved by complex molecular recognition mechanisms. Elements of this recognition code include the core binding sequence, the flanking sequence context, and the shape and conformational flexibility of the composite binding site. To unravel the extent to which DNA flexibility modulates TF binding, in this study, we employed experimentally guided molecular dynamics simulations of ternary complex of closely related Hox heterodimers Exd-Ubx and Exd-Scr with DNA. Results demonstrate that flexibility signatures embedded in the flanking sequences impact TF binding at the cognate binding site. A DNA sequence has intrinsic shape and flexibility features. While shape features are localized, our analyses reveal that flexibility features of the flanking sequences percolate several basepairs and allosterically modulate TF binding at the core. We also show that lack of flexibility in the motif context can render the cognate site resistant to protein-induced shape changes and subsequently lower TF binding affinity. Overall, this study suggests that flexibility-guided DNA shape, and not merely the static shape, is a key unexplored component of the complex DNA-TF recognition code.

Inspired by the biological processes of molecular recognition and transportation across membranes, nanopore techniques have evolved in recent decades as ultrasensitive analytical tools for individual molecules. In particular, nanopore-based single-molecule DNA/RNA sequencing has advanced genomic and transcriptomic research due to the portability, lower costs and long reads of these methods. Nanopore applications, however, extend far beyond nucleic acid sequencing. In this Review, we present an overview of the broad applications of nanopores in molecular sensing and sequencing, chemical catalysis and biophysical characterization. We highlight the prospects of applying nanopores for single-protein analysis and sequencing, single-molecule covalent chemistry, clinical sensing applications for single-molecule liquid biopsy, and the use of synthetic biomimetic nanopores as experimental models for natural systems. We suggest that nanopore technologies will continue to be explored to address a number of scientific challenges as control over pore design improves.

Colletotrichum gloeosporioides ES026, isolated as an endophytic fungal strain, was found to produce the important medicinal compound HuperzineA (HupA). In a genetic context, ES026 showed potential in elucidating the biosynthetic pathway of HupA.The ES026 strain was sequenced using de-novo Illumina sequencing methods in this study. Assembling the cleaned data resulted in 58,594,804bp, consisting of 404 scaffolds. The G + C mol % content of this genome was 52.53%. The genome progressive-alignment with other 4 Colletotrichum strains revealed that ES026 showed closer relation with 030206, SMCG1#C and Nara gc5. More than 60 putative biosynthetic clusters were predicted with the fungal version antiSMASH4.0 program. More than 33 types I polyketide-related biosynthetic gene clusters were distributed, containing PKS and PKS-NRPS (polyketide-nonribosomal peptides) hybrid gene clusters. Another 8 NRPS biosynthetic gene clusters were distributed among the genome of ES026. The prenyltransferases, probably involved in aromatic prenyl-compounds and terpenoid biosynthesis, were analyzed using bioinformatics tools like MEGA.We predicted a new possible biosynthetic pathway for the HupA from the pipecolic acid, based on the published HupA biosynthesis proposed pathway, the biosynthesis and pipecolic acid-derived compounds. We hypothesize that a hybrid PKS-NRPS mega-enzyme was probably involved in the biosynthesis of HupA with the pipecolic acid, the building block of rapamycin, as a HupA precursor. The rapamycin is produced from a polyketide biosynthesis pathway, and the domain incorporating the pipecolic acid is studied.

The sequence assembly algorithms have rapidly evolved with the vigorous growth of genome sequencing technology over the past two decades. Assembly mainly uses the iterative expansion of overlap relationships between sequences to construct the target genome. The assembly algorithms can be typically classified into several categories, such as the Greedy strategy, Overlap-Layout-Consensus (OLC) strategy, and de Bruijn graph (DBG) strategy. In particular, due to the rapid development of third-generation sequencing (TGS) technology, some prevalent assembly algorithms have been proposed to generate high-quality chromosome-level assemblies. However, due to the genome complexity, the length of short reads, and the high error rate of long reads, contigs produced by assembly may contain misassemblies adversely affecting downstream data analysis. Therefore, several read-based and reference-based methods for misassembly identification have been developed to improve assembly quality. This work primarily reviewed the development of DNA sequencing technologies and summarized sequencing data simulation methods, sequencing error correction methods, various mainstream sequence assembly algorithms, and misassembly identification methods. A large amount of computation makes the sequence assembly problem more challenging, and therefore, it is necessary to develop more efficient and accurate assembly algorithms and alternative algorithms.

Motivation The volume of public nucleotide sequence data has blossomed over the past two decades and is ripe for re- and meta-analyses to enable novel discoveries. However, reproducible re-use and management of sequence datasets and associated metadata remain critical challenges. We created the open source Python package q2-fondue to enable user-friendly acquisition, re-use and management of public sequence (meta)data while adhering to open data principles. Results q2-fondue allows fully provenance-tracked programmatic access to and management of data from the NCBI Sequence Read Archive (SRA). Unlike other packages allowing download of sequence data from the SRA, q2-fondue enables full data provenance tracking from data download to final visualization, integrates with the QIIME 2 ecosystem, prevents data loss upon space exhaustion and allows download of (meta)data given a publication library. To highlight its manifold capabilities, we present executable demonstrations using publicly available amplicon, whole genome and metagenome datasets. Availability and implementation q2-fondue is available as an open-source BSD-3-licensed Python package at https://github.com/bokulich-lab/q2-fondue. Usage tutorials are available in the same repository. All Jupyter notebooks used in this article are available under https://github.com/bokulich-lab/q2-fondue-examples. Supplementary information Supplementary data are available at Bioinformatics online., Bioinformatics, 38 (22), ISSN:1367-4803, ISSN:1460-2059

In vitro transcription (IVT) using T7 RNA polymerase has become the most common method to synthesize RNAs for use in basic research and pharmaceutical applications. To solve the heterogeneity issue associated with the system, cis-acting ribozymes have been exploited to direct co-transcriptional processing to yield target RNAs with precisely defined ends. However, traditionally used ribozymes have many limitations, such as low efficiency and special sequence requirements of target RNAs. In addition, the introduction of ribozymes in IVT complicates the downstream purification of target RNAs. Here we describe a new cassette of engineered ribozymes (HHV-Kt and Twister-Kt) that can work in concert to produce RNA with defined 5' and 3' ends. The pair of ribozymes displayed reliably high activity when working with RNA of various lengths and structures. The engineered ribozymes also carry a K-turn RNA motif that enables fast post-IVT clearance of cleaved ribozymes and uncleaved precursors using K-turn affinity resins. Finally, we demonstrated the scalability of our system for the rapid production of large quantities of homogeneous RNA samples.

Sequence-dependent binding between DNA and proteins in chromatin is an essential part of gene expression. Linker histone H1 is an important protein in the regulation of chromatin compartmentalization and compaction, and its binding with the nucleosome is sensitive to the DNA sequence. Although the interactions of H1 and DNA have been widely investigated, the mechanism of nucleosome conformation changes induced by the DNA-sequence-dependent binding with gH1 (globular H1.0) remains largely unclear at the atomic level. In the present molecular dynamics simulations, both linker and dyad DNAs were mutated to investigate the conformational changes of the nucleosome induced by the sequence-dependent binding of gH1 based on the on-dyad binding mode. Our results indicate that gH1 is insensitive to the DNA sequence of the dyad DNA but presents an apparent preference to linker DNA with an AT-rich sequence. Moreover, this specific binding induces the entry/exit region of a nucleosome to a tight conformation and regulates the accessibility of core histones. Considering that the entry/exit region of the nucleosome is a crucial binding site for many functional proteins related to gene expression, the conformational change at this region could represent an important gene regulation signal.

Ficolin, a member of the fibrinogen-related proteins family (FREPs), functions as a pattern recognition receptor (PRR) in vertebrates and in invertebrates as a novel lectin. In this study, we discovered the Ficolin homolog of Chinese mitten crab (Eriocheir sinensis), which we named EsFicolin. The obtained sequence showed that it has a highly conserved C-terminal fibrinogen-related domain (FReD) and a coiled-coil structure for trimer formation. EsFicolin was up-regulated in hemocytes after being stimulated by bacteria. Recombinant EsFicolin protein binds to gram-negative and gram-positive bacteria and agglutinates bacteria through pathogen-associated molecular patterns. In-depth study found that recombinant EsFicolin could effectively remove bacteria and showed direct antibacterial activity. EsFicolin could also promote the phagocytosis of hemocytes to enhance bacterial clearance. These findings suggest that EsFicolin plays an important role in the crab antibacterial immune response.

The sea cucumber Apostichopus japonicus is one of the most dominant and economically important aquaculture species in China. Saponin, which possesses notable biological and pharmacological properties, is a key determinant of the nutritional and health value of A. japonicus. In the present study, we amplified the full-length cDNA of a phosphomevalonate kinase (PMK) gene (named AjPMK) using rapid amplification of cDNA ends (RACE). Subsequently, we engineered a recombinant AjPMK (rAjPMK) protein and assessed its enzymatic activity by enzyme-linked immunosorbent assay (ELISA). Proteins that interact with rAjPMK were screened and identified via pull-down assay combined with liquid chromatography with tandem mass spectrometry (LC-MS/MS). We found that the full-length cDNA of AjPMK contained 1354 bp and an open reading frame (ORF) of 612 bp. The AjPMK protein was predicted not to contain a signal peptide but to contain a phosphonolate kinase domain seen in higher eukaryotes and a P-loop with a relatively conserved nucleoside triphosphate hydrolase domain. The molecular weight of the AjPMK protein was estimated to be 23.81 kDa, and its isoelectric point was predicted to be 8.72. Phylogenetic analysis showed that AjPMK had a closer evolutionary relationship with genes from starfish than with those of other selected species. Besides, we found that rAjPMK synthesized mevalonate-5-diphosphate, interacted either directly or indirectly with crucial pattern recognition receptors (PRRs) and was regulated by immune-related processes, including antioxidative reactions, stress resistance responses and enzyme hydrolysis. Moreover, AjPMK also interacted with farnesyl pyrophosphate synthase, an enzyme reported to be involved in saponin biosynthesis. Together, our findings implied that AjPMK may be directly involved in saponin biosynthesis and the regulation of various innate immune processes.

Members of the E74-like factor (ELF) subfamily are involved in the immune stress process of organisms by regulating immune responses and the development of immune-related cells. PmE74 of Penaeus monodon was characterized and functionally analyzed in this study. The full length of PmE74 was 3106 bp, with a 5'-UTR of 297 bp, and a 3'-UTR of 460 bp. The ORF (Open reading frame) was 2349 bp and encoded 782 amino acids. Domain analysis showed that PmE74 contains a typical Ets domain. Multiple sequence alignment and phylogenetic tree analysis showed that PmE74 clustered with Litopenaeus vannamei E74 and displayed significant similarity (98.98%). PmE74 was expressed in all tissues tested in P. monodon, with the highest levels of expression observed in the testis, intestine, and epidermis. Different pathogen stimulation studies have revealed that PmE74 expression varies in response to different pathogen stimuli. A 96-h acute low salt stress study revealed that PmE74 in the hepatopancreas was upregulated and downregulated in the salinity 17 group and considerably downregulated in the salinity 3 group, whereas PmE74 in gill tissue was considerably downregulated in both groups. Further, by knocking down PmE74 and learning the trends of its linkage genes PmAQP1, PmNKA, PmE75, PmFtz-f1, PmEcR, and PmRXR in response to low salt stress, it was further indicated that PmE74 could have a vital role in the regulation of low salt stress. The SNP test revealed that PmE74-In1-53 was significantly associated with low salt tolerance traits in P. monodon (P 0.05). The findings of this study can aid in the advancement of molecular marker-assisted breeding in P. monodon, as well as provide fundamental data and methodologies for further investigation of its low salt tolerance strains in P. monodon.

Synthesizing DNA molecules by design has become an essential tool in molecular biology and is expected to become ubiquitous in the coming decade. Successful design of a synthetic DNA molecule often requires satisfying multiple objectives, some of which may conflict with others. One particularly important objective is the elimination of unwanted protein binding sites, which may interfere with the desired function of the synthesized molecule. While most design tools offer this fundamental capability, they do not follow a systematic approach that guarantees elimination of all unwanted sites whenever a feasible solution exists. Furthermore, the algorithms these tools use (when published) are often quite naive and inefficient. We present a formal description of the binding site elimination problem and suggest several efficient algorithms that eliminate unwanted patterns with minimum interference to the desired function of the synthesized sequence. These algorithms are simple, efficient, and flexible and, therefore, can be easily incorporated in all existing DNA design tools, enhancing their design capabilities.

The experimental and computational techniques for capturing information about protein structures and genetic variation within the human genome have advanced dramatically in the past 20 years, generating extensive new data resources. In this review, we discuss these advances, along with new approaches for determining the impact a genetic variant has on protein function. We focus on the potential of new methods that integrate human genetic variation into protein structures to discover relationships to disease, including the discovery of mutational hotspots in cancer-related proteins, the localization of protein-altering variants within protein regions for common complex diseases, and the assessment of variants of unknown significance for Mendelian traits. We expect that approaches that integratethese data sources will play increasingly important roles in disease gene discovery and variant interpretation.

Interleukin-1 receptor-associated kinase 4 (IRAK4) plays a crucial role in the Toll-like receptor/IL-1R signal pathway, which mediates the downstream signal transduction involved in innate and adaptive immunity. In the present study, an IRAK4 homologue (named as MaIRAK4) from blunt snout bream (Megalobrama amblycephala) was cloned and characterized. The open reading frame (ORF) of MaIRAK4 contains 1422 nucleotides, encoding a putative protein of 473 amino acids. Protein structural analysis revealed that MaIRAK4 has an N-terminal death domain (DD) and a central kinase domain (S_TKc), similar to those of mammals and other fishes. Multiple sequence alignment demonstrated that MaIRAK4 is highly homologous with that of grass carp (97.67%). The qRT-PCR analysis showed that MaIRAK4 expressed widely in all examined tissues, including heart, liver, spleen, kidney, head-kidney, gill, intestine and muscle, with the highest expression in the liver and spleen. After stimulation with LPS, MaIRAK4 expression upregulated significantly and reached a peak at 6 h and 12 h post LPS stimulation in the spleen and head-kidney, respectively. After challenge with Aeromonas hydrophila, MaIRAK4 expression peaked at 48 h and 72 h in spleen/head-kidney and liver, respectively. These results implied that MaIRAK4 is involved in the host defense against bacterial infection. Subcellular localization analysis indicated that MaIRAK4 distributed in the cytoplasm. Co-immunoprecipitation and subcellular co-localization assay revealed that MaIRAK4 can combine with MaMyD88 through DD domain. MaIRAK4 overexpression can induce slightly the NF-κB promoter activity in HEK 293 cells. However, the activity of NF-κB promoter was dramatically enhanced after co-transfection with MaIRAK4 and MaMyD88 plasmids. The results showed that MaIRAK4 was involved in NF-κB signal pathway mediated by maMyD88. The expression level of pro-inflammatory cytokines (IL-1β, IL-6, IL-8 and TNF-α) decreased significantly after the siRNA-mediated knockdown of MaIRAK4. Together, these results suggest that MaIRAK4 plays an important function in the innate immunity of M. amblycephala by inducing cytokines expression.

Promoters play an irreplaceable role in biological processes and genetics, which are responsible for stimulating the transcription and expression of specific genes. Promoter abnormalities have been found in some diseases, and the level of promoter-binding transcription factors can be used as a marker before a disease occurs. Hence, detecting promoters from DNA sequences has important biological significance, particular, distinguishing strong promoters can help to elucidate differences in gene expression and the mechanisms of specific diseases. With the introduction of third-generation sequencing, it is difficult to match the speed of sequencing to the speed of labeling promoters experimentally. Many computing models have been designed to fill this gap and identify unlabeled DNA. However, their feature representation methods are very singular, which cannot reflect the information contained in the original samples. With the aim of avoiding information loss, we propose a computational model based on multiple descriptors and feature selection to jointly express samples. It is worth mentioning that a new feature descriptor called K-mer word vector is defined. The promoter model of multiple feature descriptors dominated by K-mer word vector achieves similar performance to existing methods, the sensitivity of 85.72% can distinguish the promoter more effectively than other methods. Furthermore, the performance of the promoter strength has surpassed published methods, and accuracy of 77.00% greatly improves the ability to distinguish between strong and weak promoters.

Crustins are a kind of antibacterial peptides (AMP) existing in crustaceans, and their antibacterial abilities are considered to be related to the conserved WAP domain. In this study, a novel type I Crustin gene was identified in Exopalaemon carinicauda, named EcCru. The deduced amino acid sequence revealed that the conserved cysteine at position 7 in the WAP domain was replaced by aspartic acid. The gene is 405 bp in length, encoding 134 amino acids, and is mainly distributed in gills and hepatopancreas. After Vibrio parahaemolyticus and Aeromonas hydrophila stimulation, the expression of EcCru was significantly up-regulated within 12 h, and then returned to normal levels. The recombinant protein was obtained using the Pichia pastoris expression system, and the recombinant protein had neither antibacterial activity against gram-positive or gram-negative bacteria. But the antibacterial ability emerged when Asp

Motivation Several recently developed single-cell DNA sequencing technologies enable whole-genome sequencing of thousands of cells. However, the ultra-low coverage of the sequenced data (, Bioinformatics, 38 (18), ISSN:1367-4803, ISSN:1460-2059

Motivation 5-Methylcytosine (m5C) is a crucial post-transcriptional modification. With the development of technology, it is widely found in various RNAs. Numerous studies have indicated that m5C plays an essential role in various activities of organisms, such as tRNA recognition, stabilization of RNA structure, RNA metabolism and so on. Traditional identification is costly and time-consuming by wet biological experiments. Therefore, computational models are commonly used to identify the m5C sites. Due to the vast computing advantages of deep learning, it is feasible to construct the predictive model through deep learning algorithms. Results In this study, we construct a model to identify m5C based on a deep fusion approach with an improved residual network. First, sequence features are extracted from the RNA sequences using Kmer, K-tuple nucleotide frequency component (KNFC), Pseudo dinucleotide composition (PseDNC) and Physical and chemical property (PCP). Kmer and KNFC extract information from a statistical point of view. PseDNC and PCP extract information from the physicochemical properties of RNA sequences. Then, two parts of information are fused with new features using bidirectional long- and short-term memory and attention mechanisms, respectively. Immediately after, the fused features are fed into the improved residual network for classification. Finally, 10-fold cross-validation and independent set testing are used to verify the credibility of the model. The results show that the accuracy reaches 91.87%, 95.55%, 92.27% and 95.60% on the training sets and independent test sets of Arabidopsis thaliana and M.musculus, respectively. This is a considerable improvement compared to previous studies and demonstrates the robust performance of our model. Availability and implementation The data and code related to the study are available at https://github.com/alivelxj/m5c-DFRESG.

During a recent survey of leaf-mining microlepidoptera in the Cerrado biome, mines of an undescribed Porphyrosela Braun (Lepidoptera: Gracillariidae: Lithocolletinae) were found associated with the forage peanut, Arachis pintoi Krapov. & W.C. Greg. (Fabaceae). Consequently, adults, immature stages and the leaf mine of Porphyrosela arachisella sp. nov. are herein described based on light and scanning electron microscopy. A preliminary analysis of DNA barcode sequences including putative members of other lithocolletine species and all BINs (Barcode Index Numbers) available for Porphyrosela supports P. arachisella as an independent cluster, with 8 to 11% divergence. Its nearest neighbour was the cluster formed by three BINs (BOLD: ADT2137, BOLD: AAG1161 and BOLD: ADU9985) that includes specimens from Australia, Vietnam and Bangladesh. This is the first report of a lithocolletine gracillariid for Brazil, and the third species recognized for the genus in the Neotropical region.

Here, a fluorescent polymerase chain reaction (PCR) nanokit is established to detect the specific DNA sequence in a single living cell. Different from well-developed protocols to load cell-permeable probes into single cell for recognition, the DNA sequence in a cellular nucleus is sorted into a nanopipette in our strategy. The target DNA sequence is reacted with the PCR kit components in the nanopipette to complete a PCR amplification reaction. SYBR Green prefilled in the nanopipette is intercalated into double-stranded DNA to induce fluorescence emission for real-time detection down to a single copy. An obvious increase in the fluorescence is observed that validates the detection of the target DNA sequence in single living cells. The established real-time fluorescent PCR nanokit could adapt the PCR kit for single cell analysis and thus offers an alternatively general and highly sensitive strategy for the detection of specific DNA sequences in single living cells.

Leaves from the ornamental plant Chaenostoma cordatum (Thunb.) Benth. expressing virus-like symptoms were collected for pathogen testing. A virus with features consistent with those of members of the genus Potexvirus was identified by high-throughput sequencing. The genome sequence was confirmed and completed using RT-PCR, cloning, rapid amplification of cDNA ends kits, and Sanger sequencing, revealing a complete viral genome of 6,071 nucleotides, excluding the poly-A tail. Phylogenetic analysis of the RNA-dependent RNA polymerase sequence from the viral genome indicated that its closest relative is Plantago asiatica mosaic virus. Further analysis of the nucleotide and amino acid sequences revealed that it had diverged enough from other potexviruses to be considered a member of a new species.

DNA is naturally dynamic and can self-assemble into alternative secondary structures including the intercalated motif (i-motif), a four-stranded structure formed in cytosine-rich DNA sequences. Until recently, i-motifs were thought to be unstable in physiological cellular environments. Studies demonstrating their existence in the human genome and role in gene regulation are now shining light on their biological relevance. Herein, we review the effects of epigenetic modifications on i-motif structure and stability, and biological factors that affect i-motif formation within cells. Furthermore, we highlight recent progress in targeting i-motifs with structure-specific ligands for biotechnology and therapeutic purposes.

Thanks to the tremendous advancement of deep sequencing and large-scale profiling, epitranscriptomics has become a rapidly growing field. As one of the most important parts of epitranscriptomics, ribonucleic acid (RNA) methylation has been focused on for years for its fundamental role in regulating the many aspects of RNA function. Thanks to the big data generated in sequencing, machine learning methods have been developed for efficiently identifying methylation sites. In this review, we comprehensively explore machine learning based approaches for predicting 10 types of methylation of RNA, which include m6A, m5C, m7G, 5hmC, m1A, m5U, m6Am, and so on. Firstly, we reviewed three main aspects of machine learning which are data, features and learning algorithms. Then, we summarized all the methods that have been used to predict the 10 types of methylation. Furthermore, the emergent methods which were designed to predict multiple types of methylation were also reviewed. Finally, we discussed the future perspectives for RNA methylation sites prediction.

Transcriptional regulation underlies most developmental programs and physiological responses to environmental changes in plants. Transcription factors (TFs) play a key role in the regulation of gene expression by binding specifically to short DNA sequences in the regulatory regions of genes: the TF binding sites (TFBSs). In recent years, several bioinformatic tools have been developed to detect TFBSs in candidate genes, either by de novo prediction or by directly mapping experimentally known TFBSs. However, most of these tools contain information for only a few species or require multi-step procedures, and are not always intuitive for non-experienced researchers. Here we present TFBS-Discovery Tool Hub (TDTHub), a web server for quick and intuitive studies of transcriptional regulation in plants. TDTHub uses pre-computed TFBSs in 40 plant species and allows the choice of two mapping algorithms, providing a higher versatility. Besides the main TFBS enrichment tool, TDTHub includes additional tools to assist in the analysis and visualization of data. In order to demonstrate the effectiveness of TDTHub, we analyzed the transcriptional regulation of the anthocyanin biosynthesis pathway. We also analyzed the transcriptional cascades in response to jasmonate and wounding in Arabidopsis and tomato (Solanum lycopersicum), respectively. In these studies, TDTHub helped to verify the most relevant TF nodes and to propose new ones with a prominent role in these pathways. TDTHub is available at http://acrab.cnb.csic.es/TDTHub/, and it will be periodically upgraded and expanded for new species and gene annotations.

The self-assembly of block copolymers is often rationalized by structure and microphase separation; pathways that diverge from this parameter space may provide new mechanisms of polymer self-assembly. Here, we show that the sequence and length of single-stranded DNA directly influence the self-assembly of sequence-defined DNA block copolymers. While increasing the length of DNA led to predictable changes in self-assembly, changing only the sequence of DNA produced three distinct structures: spherical micelles (spherical nucleic acids, SNAs) from flexible poly(thymine) DNA, fibers from semi-rigid mixed-sequence DNA, and networked superstructures from rigid poly(adenine) DNA. The secondary structure of poly(adenine) DNA strands drives a temperature-dependent polymerization and assembly mechanism: copolymers stored in an SNA reservoir form fibers after thermal activation, which then aggregate upon cooling to form interwoven networks. DNA is often used as a programming code that aids in nanostructure addressability and function; Here, we show that the inherent physical and chemical properties of single-stranded DNA sequences also make them an ideal material to direct self-assembled morphologies and select for new methods of supramolecular polymerization.

It is widely known that an optimal nucleotide sequence context immediately upstream of the AUG start codon greatly improves the efficiency of translation initiation of mRNA in mammalian and plant somatic cells, which in turn increases protein levels. However, it is still unclear whether a similar regulatory mechanism is also present in highly differentiated cells. Here, we surveyed this issue in Arabidopsis thaliana sperm cells and found that the sequence context-mediated regulation of translation initiation in sperm cells is generally similar to that in somatic cells. A simple motif of four adenine nucleotides at positions - 1 to - 4 greatly improved the efficiency of translation initiation, and when the motif was present there, translation was even initiated at some non-AUG codons in sperm cells. However, unlike that in mammalian cells, a mainly effective nucleotide site to regulate the efficiency of translation initiation was not present at positions - 1 to - 4 in sperm cells. Meanwhile, different from somatic cells, sperm cells did not use eukaryotic translation initiation factor 1 to regulate the efficiency in a poor context consisting of the lowest frequency nucleotides. All these results contribute to our understanding of the cytoplasmic event of translation initiation in highly differentiated sperm cells.

Markov models have frequently been used in genetic sequence analysis. The number of parameters of a Markov model increases exponentially with model order, so it is often recommended that the order be chosen based on the size of data being modeled, lower orders for small and higher orders for large dataset sizes. Approaches based on model selection criterion have also been proposed. An important problem in microbiology and evolutionary biology is to decipher chimeric genomes of microbes, particularly, identify segments of distinct ancestries in genomes and reconstruct the plausible evolutionary scenarios that might have shaped the chimeric genomes in the microbial world. In this study, we assessed a Markov model-based segmentation method for its ability to detect compositionally disparate segments in chimeric sequence constructs as a function of model order, sequence length, and phylogenetic divergence. Our results show that the choice of Markov model order depends on both sequence size and composition. Higher order Markov models were found to be more effective in delineating sequence segments arising from closely related organisms in longer constructs; on the other hand, lower order Markov models were found to be more appropriate in delineating sequence segments arising from distantly related organisms in shorter constructs. These findings are important and timely, with broad implications in fields such as epidemiology that has to deal with the emergence of novel pathogenic chimeras that arise by foreign DNA acquisition, and ecology where chimeric structures may arise in various ecosystems, necessitating more robust approaches for their deconstruction and interpretation.

Dactylogyridae is one of the most studied families of parasitic flatworms with more than 1000 species and 166 genera described to date including ecto- and endoparasites. Dactylogyrid monogeneans were suggested as model organisms for host-parasite macroevolutionary and biogeographical studies due to the scientific and economic importance of some of their host lineages. Consequently, an array of phylogenetic research into different dactylogyrid lineages has been produced over the past years but the last family-wide study was published 16 years ago. Here, we provide a meta-analysis of the phylogenetic relationships of Dactylogyridae including representatives of all genera with available molecular data (n = 67). First, we investigate the systematic informativeness of morphological characters widely used to diagnose dactylogyrid genera through a parsimony analysis of the characters, character mapping, and phylogenetic comparative methods. Second, we provide an overview of the current state of the systematics of the family and its subfamilies, and summarise potentially poly- and paraphyletic genera. Third, we elaborate on the implications of taxonomic, citation, and confirmation bias in past studies. Fourth, we discuss host range, biogeographical, and freshwater-marine patterns. We found two well-supported macroclades which we assigned to the subfamilies Dactylogyrinae and Ancyrocephalinae. These subfamilies further include 16 well-supported clades with only a few synapomorphies that could be deduced from generic diagnoses in the literature. Furthermore, few morphological characters considered systematically informative at the genus level display a strong phylogenetic signal. However, the parsimony analysis suggests that these characters provide little information on the relationships between genera. We conclude that a strong taxonomic bias and low coverage of DNA sequences and regions limit knowledge on morphological and biogeographical evolutionary patterns that can be inferred from these results. We propose addressing potential citation and confirmation biases through a 'level playing field' multiple sequence alignment as provided by this study. This research was funded by Czech Science Foundation (GACˇ R) standard project GA19-13573S. N.K. (BOF21PD01), A.J.C.L. (BOF19OWB02) and M.P.M.V. (BOF20TT06) are financed by the Special Research Fund of Hasselt University, Belgium. Walter A. Boeger (Universidade Federal do Paraná, Brazil) is thanked for fruitful discussions on this matter

Honey bee, Apis mellifera, drones are typically haploid, developing from an unfertilized egg, inheriting only their queen’s alleles and none from the many drones she mated with. Thus the ordered combination or ‘phase’ of alleles is known, making drones a valuable haplotype resource. We collated whole-genome sequence data for 1,407 drones, including 45 newly sequenced Scottish drones, collectively representing 19 countries, 8 subspecies and various hybrids. Following alignment to Amel_HAv3.1, variant calling and quality filtering, we retained 17.4 M high quality variants across 1,328 samples with a genotyping rate of 98.7%. We demonstrate the utility of this haplotype resource, AmelHap, for genotype imputation, returning >95% concordance when up to 61% of data is missing in haploids and up to 12% of data is missing in diploids. AmelHap will serve as a useful resource for the community for imputation from low-depth sequencing or SNP chip data, accurate phasing of diploids for association studies, and as a comprehensive reference panel for population genetic and evolutionary analyses. For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission. This work was supported by a grant from the CB Dennis British Beekeepers’ Research Trust awarded to MB and DW, and through strategic investment funding to the Roslin Institute from the Biotechnology and Biological Sciences Research Council (BBS/E/D/30002276). MP was supported by a Basque Government grant (IT1233-19).

Data from omics studies have been used for prediction and classification of various diseases in biomedical and bioinformatics research. In recent years, Machine Learning (ML) algorithms have been used in many different fields related to healthcare systems, especially for disease prediction and classification tasks. Integration of molecular omics data with ML algorithms has offered a great opportunity to evaluate clinical data. RNA sequence (RNA-seq) analysis has been emerged as the gold standard for transcriptomics analysis. Currently, it is being used widely in clinical research. In our present work, RNA-seq data of extracellular vesicles (EV) from healthy and colon cancer patients are analyzed. Our aim is to develop models for prediction and classification of colon cancer stages. Five different canonical ML and Deep Learning (DL) classifiers are used to predict colon cancer of an individual with processed RNA-seq data. The classes of data are formed on the basis of both colon cancer stages and cancer presence (healthy or cancer). The canonical ML classifiers, which are k-Nearest Neighbor (kNN), Logistic Model Tree (LMT), Random Tree (RT), Random Committee (RC), and Random Forest (RF), are tested with both forms of the data. In addition, to compare the performance with canonical ML models, One-Dimensional Convolutional Neural Network (1-D CNN), Long Short-Term Memory (LSTM), and Bidirectional LSTM (BiLSTM) DL models are utilized. Hyper-parameter optimizations of DL models are constructed by using genetic meta-heuristic optimization algorithm (GA). The best accuracy in cancer prediction is obtained with RC, LMT, and RF canonical ML algorithms as 97.33%. However, RT and kNN show 95.33% performance. The best accuracy in cancer stage classification is achieved with RF as 97.33%. This result is followed by LMT, RC, kNN, and RT with 96.33%, 96%, 94.66%, and 94%, respectively. According to the results of the experiments with DL algorithms, the best accuracy in cancer prediction is obtained with 1-D CNN as 97.67%. BiLSTM and LSTM show 94.33% and 93.67% performance, respectively. In classification of the cancer stages, the best accuracy is achieved with BiLSTM as 98%. 1-D CNN and LSTM show 97% and 94.33% performance, respectively. The results reveal that both canonical ML and DL models may outperform each other for different numbers of features. publishedVersion

Background. To date (14 January 2022), the incidence and related mortality rate of COVID-19 in America, Europe, and Asia despite administrated of billions doses of many approved vaccines are still higher than in Egypt. Epigenetic alterations mediate the effects of environmental factors on the regulation of genetic material causing many diseases. Objective. We aimed to explore the methylation status of HeyL promoter, a downstream transcription factor in Notch signal, an important regulator of cell proliferation and differentiation blood, pulmonary epithelial, and nerves cells. Methods. Our objective was achieved by DNA sequencing of the product from methyl-specific PCR of HeyL promoter after bisulfite modification of DNA extracted from the blood samples of 30 COVID-19 patients and 20 control health subjects and studying its association with clinical-pathological biomarkers. Results. We found that the HeyL promoter was partial-methylated in Egyptian COVID-19 patients and control healthy subjects compared to full methylated one that was published in GenBank. We identified unmethylated CpG (TG) flanking the response elements within HeyL promoter in Egyptian COVID-19 patients and control healthy subjects vs. methylated CpG (CG) in reference sequence (GenBank). Also, we observed that the frequency of partial-methylated HeyL promoter was higher in COVID-19 patients and associated with aging, fever, severe pneumonia, ageusia/anosmia, and dry cough compared to control healthy subjects. Conclusion. We concluded that hypomethylated HeyL promoter in Egyptian population may facilitate the binding of transcription factors to their binding sites, thus enhancing its regulatory action on the blood, pulmonary epithelium, and nerves cells in contrast to full methylated one that was published in GenBank; thus, addition of demethylating agents to the treatment protocol of COVID-19 may improve the clinical outcomes. Administration of therapy must be based on determination of methylation status of HeyL, a novel prognostic marker for severe illness in COVID-19 patients.

Ionizing radiation is used in cancer radiation therapy to effectively damage the DNA of tumors. The main damage is due to generation of highly reactive secondary species such as low-energy electrons (LEEs). The accurate quantification of DNA radiation damage of well-defined DNA target sequences in terms of absolute cross sections for LEE-induced DNA strand breaks is possible by the DNA origami technique; however, to date, it is possible only for DNA single strands. In the present work DNA double strand breaks in the DNA sequence 5'-d(CAC)(4)/5'd(GTG)(4) are compared with DNA single strand breaks in the oligonucleotides 5'-d(CAC)(4) and 5'-d(GTG)(4) upon irradiation with LEEs in the energy range from 5 to 20 eV. A maximum of strand break cross section was found around 7 and 10 eV independent of the DNA sequence, indicating that dissociative electron attachment is the underlying mechanism of strand breakage and confirming previous studies using plasmid DNA.