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Since the discovery of the first “giant virus,” particular attention has been paid toward isolating and culturing these large DNA viruses throughAcanthamoebaspp. bait systems. While this method has allowed for the discovery of plenty novel viruses in theNucleocytoviricota, environmental -omics-based analyses have shown that there is a wealth of diversity among this phylum, particularly in marine datasets. The prevalence of these viruses in metatranscriptomes points toward their ecological importance in nutrient turnover in our oceans and as such, in depth study into non-amoebalNucleocytoviricotashould be considered a focal point in viral ecology. In this review, we report onKratosvirus quantuckense(née Aureococcus anophagefferens Virus), an algae-infecting virus of theImitervirales. Current systems for study in theNucleocytoviricotadiffer significantly from this virus and its relatives, and a litany of trade-offs within physiology, coding potential, and ecology compared to these other viruses reveal the importance ofK. quantuckense. Herein, we review the research that has been performed on this virus as well as its potential as a model system for algal-virus interactions. 

Metallic nanostructures supporting surface plasmon modes can concentrate optical fields, and enhance luminescence processes from the metal surface at plasmonic hotspots. Such nanoplasmonic metal luminescence contributes to the spectral background in surface-enhanced Raman spectroscopy (SERS) measurements and is helpful in bioimaging, nano-thermometry, and chemical reaction monitoring applications. Despite increasing interest in nanoplasmonic metal luminescence, little attention has been paid to investigating its dependence on voltage modulation. Also, the hyphenated electrochemical surface-enhanced Raman spectroscopy (EC-SERS) technique typically ignores voltage-dependent spectral background information associated with nanoplasmonic metal luminescence due to limited mechanistic understanding and poor measurement reproducibility. Here, we report a combined experiment and theory study on dynamic voltage-modulated nanoplasmonic metal luminescence from hotspots at the electrode-electrolyte interface using multiresonant nanolaminate nano-optoelectrode arrays. Our EC-SERS measurements under 785 nm laser excitation demonstrate that short-wavenumber nanoplasmonic metal luminescence associated with plasmon-enhanced electronic Raman scattering (PE-ERS) exhibits a negative voltage modulation slope (up to ≈30 % V-1) in physiological ionic solutions. Furthermore, we have developed a phenomenological model to intuitively capture plasmonic, electronic, and ionic characteristics at the metal-electrolyte interface to understand the observed dependence of the PE-ERS voltage modulation slope on voltage polarization and ionic strength. The current work represents a critical step toward the general application of nanoplasmonic metal luminescence signals in optical voltage biosensing, hybrid optical-electrical signal transduction, and interfacial electrochemical monitoring. 

Abstract Motivation Oxford Nanopore sequencing has great potential and advantages in population-scale studies. Due to the cost of sequencing, the depth of whole-genome sequencing for per individual sample must be small. However, the existing single nucleotide polymorphism (SNP) callers are aimed at high-coverage Nanopore sequencing reads. Detecting the SNP variants on low-coverage Nanopore sequencing data is still a challenging problem. Results We developed a novel deep learning-based SNP calling method, NanoSNP, to identify the SNP sites (excluding short indels) based on low-coverage Nanopore sequencing reads. In this method, we design a multi-step, multi-scale and haplotype-aware SNP detection pipeline. First, the pileup model in NanoSNP utilizes the naive pileup feature to predict a subset of SNP sites with a Bi-long short-term memory (LSTM) network. These SNP sites are phased and used to divide the low-coverage Nanopore reads into different haplotypes. Finally, the long-range haplotype feature and short-range pileup feature are extracted from each haplotype. The haplotype model combines two features and predicts the genotype for the candidate site using a Bi-LSTM network. To evaluate the performance of NanoSNP, we compared NanoSNP with Clair, Clair3, Pepper-DeepVariant and NanoCaller on the low-coverage (∼16×) Nanopore sequencing reads. We also performed cross-genome testing on six human genomes HG002–HG007, respectively. Comprehensive experiments demonstrate that NanoSNP outperforms Clair, Pepper-DeepVariant and NanoCaller in identifying SNPs on low-coverage Nanopore sequencing data, including the difficult-to-map regions and major histocompatibility complex regions in the human genome. NanoSNP is comparable to Clair3 when the coverage exceeds 16×. Availability and implementation https://github.com/huangnengCSU/NanoSNP.git. Supplementary information Supplementary data are available at Bioinformatics online. 

Abstract Magnetic order in most materials occurs when magnetic ions with finite moments arrange in a particular pattern below the ordering temperature. Intriguingly, if the crystal electric field (CEF) effect results in a spin-singlet ground state, a magnetic order can still occur due to the exchange interactions between neighboring ions admixing the excited CEF levels. The magnetic excitations in such a state are spin excitons generally dispersionless in reciprocal space. Here we use neutron scattering to study stoichiometric Ni 2 Mo 3 O 8 , where Ni 2+ ions form a bipartite honeycomb lattice comprised of two triangular lattices, with ions subject to the tetrahedral and octahedral crystalline environment, respectively. We find that in both types of ions, the CEF excitations have nonmagnetic singlet ground states, yet the material has magnetic order. Furthermore, CEF spin excitons from the tetrahedral sites form a dispersive diffusive pattern around the Brillouin zone boundary, likely due to spin entanglement and geometric frustrations. 

Abstract In situ monitoring of short‐lived transition states (TSs) is crucial for understanding electrochemical reaction mechanisms but remains challenging. Conventional electrochemical surface‐enhanced Raman spectroscopy (EC‐SERS) primarily provides vibrational information, with limitations in hotspot reproducibility and often overlooking electronic information associated with TSs. This study introduces a dual‐channel EC‐SERS strategy using nanolaminate nano‐optoelectrode (NLNOE) devices, integrating plasmon‐enhanced vibrational Raman scattering (PE‐VRS) and plasmon‐enhanced electronic Raman scattering (PE‐ERS) to concurrently probe TS dynamics within electrically connected plasmonic nanocavities. Using theAgCl(s) +e⁻⇌Ag(s) +Cl⁻(aq) redox system, this approach distinct PE‐VRS and PE‐ERS signatures of the (AgCl)^*TS. Notably, a significant increase in PE‐ERS signals concurrent with (AgCl)^*TS emergence, characterized by filled bonding and unoccupied antibonding orbitals with negligible energy gaps. This enhanced PE‐ERS signal correlates with increased (AgCl)^*TS polarizability, leading to amplified PE‐VRS signals due to enhanced electron cloud distortion. By modulating Cl⁻ ion concentrations via electrolyte composition (1× PBS and 1× PBS‐equivalent KH₂PO₄) while maintaining constant total ion concentration, the competition between Ag/AgCl and Ag/AgH₂PO₄ redox reactions within Ag nanolayers is influenced. These results demonstrate the capability of dual‐channel EC‐SERS to distinguish interfacial redox reactions based on distinct electronic and vibrational signatures associated with covalent and ionic bond characteristics. 

Abstract Long single-molecular sequencing technologies, such as PacBio circular consensus sequencing (CCS) and nanopore sequencing, are advantageous in detecting DNA 5-methylcytosine in CpGs (5mCpGs), especially in repetitive genomic regions. However, existing methods for detecting 5mCpGs using PacBio CCS are less accurate and robust. Here, we present ccsmeth, a deep-learning method to detect DNA 5mCpGs using CCS reads. We sequence polymerase-chain-reaction treated and M.SssI-methyltransferase treated DNA of one human sample using PacBio CCS for training ccsmeth. Using long (≥10 Kb) CCS reads, ccsmeth achieves 0.90 accuracy and 0.97 Area Under the Curve on 5mCpG detection at single-molecule resolution. At the genome-wide site level, ccsmeth achieves >0.90 correlations with bisulfite sequencing and nanopore sequencing using only 10× reads. Furthermore, we develop a Nextflow pipeline, ccsmethphase, to detect haplotype-aware methylation using CCS reads, and then sequence a Chinese family trio to validate it. ccsmeth and ccsmethphase can be robust and accurate tools for detecting DNA 5-methylcytosines.