Expansion of the global RNA virome reveals diverse clades of bacteriophages.

High-throughput RNA sequencing offers broad opportunities to explore the Earth RNA virome. Mining 5,150 diverse metatranscriptomes uncovered >2.5 million RNA virus contigs. Analysis of >330,000 RNA-dependent RNA polymerases (RdRPs) shows that this expansion corresponds to a 5-fold increase of the known RNA virus diversity. Gene content analysis revealed multiple protein domains previously not found in RNA viruses and implicated in virus-host interactions. Extended RdRP phylogeny supports the monophyly of the five established phyla and reveals two putative additional bacteriophage phyla and numerous putative additional classes and orders. The dramatically expanded phylum Lenarviricota, consisting of bacterial and related eukaryotic viruses, now accounts for a third of the RNA virome. Identification of CRISPR spacer matches and bacteriolytic proteins suggests that subsets of picobirnaviruses and partitiviruses, previously associated with eukaryotes, infect prokaryotic hosts.

Climate velocities and species tracking in global mountain regions.

Mountain ranges contain high concentrations of endemic species and are indispensable refugia for lowland species that are facing anthropogenic climate change1,2. Forecasting biodiversity redistribution hinges on assessing whether species can track shifting isotherms as the climate warms3,4. However, a global analysis of the velocities of isotherm shifts along elevation gradients is hindered by the scarcity of weather stations in mountainous regions5. Here we address this issue by mapping the lapse rate of temperature (LRT) across mountain regions globally, both by using satellite data (SLRT) and by using the laws of thermodynamics to account for water vapour6 (that is, the moist adiabatic lapse rate (MALRT)). By dividing the rate of surface warming from 1971 to 2020 by either the SLRT or the MALRT, we provide maps of vertical isotherm shift velocities. We identify 17 mountain regions with exceptionally high vertical isotherm shift velocities (greater than 11.67 m per year for the SLRT; greater than 8.25 m per year for the MALRT), predominantly in dry areas but also in wet regions with shallow lapse rates; for example, northern Sumatra, the Brazilian highlands and southern Africa. By linking these velocities to the velocities of species range shifts, we report instances of close tracking in mountains with lower climate velocities. However, many species lag behind, suggesting that range shift dynamics would persist even if we managed to curb climate-change trajectories. Our findings are key for devising global conservation strategies, particularly in the 17 high-velocity mountain regions that we have identified.

Unraveling the functional dark matter through global metagenomics.

Metagenomes encode an enormous diversity of proteins, reflecting a multiplicity of functions and activities1,2. Exploration of this vast sequence space has been limited to a comparative analysis against reference microbial genomes and protein families derived from those genomes. Here, to examine the scale of yet untapped functional diversity beyond what is currently possible through the lens of reference genomes, we develop a computational approach to generate reference-free protein families from the sequence space in metagenomes. We analyse 26,931 metagenomes and identify 1.17 billion protein sequences longer than 35 amino acids with no similarity to any sequences from 102,491 reference genomes or the Pfam database3. Using massively parallel graph-based clustering, we group these proteins into 106,198 novel sequence clusters with more than 100 members, doubling the number of protein families obtained from the reference genomes clustered using the same approach. We annotate these families on the basis of their taxonomic, habitat, geographical and gene neighbourhood distributions and, where sufficient sequence diversity is available, predict protein three-dimensional models, revealing novel structures. Overall, our results uncover an enormously diverse functional space, highlighting the importance of further exploring the microbial functional dark matter.

NMPFamsDB: a database of novel protein families from microbial metagenomes and metatranscriptomes.

The Novel Metagenome Protein Families Database (NMPFamsDB) is a database of metagenome- and metatranscriptome-derived protein families, whose members have no hits to proteins of reference genomes or Pfam domains. Each protein family is accompanied by multiple sequence alignments, Hidden Markov Models, taxonomic information, ecosystem and geolocation metadata, sequence and structure predictions, as well as 3D structure models predicted with AlphaFold2. In its current version, NMPFamsDB hosts over 100 000 protein families, each with at least 100 members. The reported protein families significantly expand (more than double) the number of known protein sequence clusters from reference genomes and reveal new insights into their habitat distribution, origins, functions and taxonomy. We expect NMPFamsDB to be a valuable resource for microbial proteome-wide analyses and for further discovery and characterization of novel functions. NMPFamsDB is publicly available in http://www.nmpfamsdb.org/ or https://bib.fleming.gr/NMPFamsDB.

LipidSig 2.0: integrating lipid characteristic insights into advanced lipidomics data analysis.

In the field of lipidomics, where the complexity of lipid structures and functions presents significant analytical challenges, LipidSig stands out as the first web-based platform providing integrated, comprehensive analysis for efficient data mining of lipidomic datasets. The upgraded LipidSig 2.0 (https://lipidsig.bioinfomics.org/) simplifies the process and empowers researchers to decipher the complex nature of lipids and link lipidomic data to specific characteristics and biological contexts. This tool markedly enhances the efficiency and depth of lipidomic research by autonomously identifying lipid species and assigning 29 comprehensive characteristics upon data entry. LipidSig 2.0 accommodates 24 data processing methods, streamlining diverse lipidomic datasets. The tool's expertise in automating intricate analytical processes, including data preprocessing, lipid ID annotation, differential expression, enrichment analysis, and network analysis, allows researchers to profoundly investigate lipid properties and their biological implications. Additional innovative features, such as the 'Network' function, offer a system biology perspective on lipid interactions, and the 'Multiple Group' analysis aids in examining complex experimental designs. With its comprehensive suite of features for analyzing and visualizing lipid properties, LipidSig 2.0 positions itself as an indispensable tool for advanced lipidomics research, paving the way for new insights into the role of lipids in cellular processes and disease development.

IMG/PR: a database of plasmids from genomes and metagenomes with rich annotations and metadata.

Plasmids are mobile genetic elements found in many clades of Archaea and Bacteria. They drive horizontal gene transfer, impacting ecological and evolutionary processes within microbial communities, and hold substantial importance in human health and biotechnology. To support plasmid research and provide scientists with data of an unprecedented diversity of plasmid sequences, we introduce the IMG/PR database, a new resource encompassing 699 973 plasmid sequences derived from genomes, metagenomes and metatranscriptomes. IMG/PR is the first database to provide data of plasmid that were systematically identified from diverse microbiome samples. IMG/PR plasmids are associated with rich metadata that includes geographical and ecosystem information, host taxonomy, similarity to other plasmids, functional annotation, presence of genes involved in conjugation and antibiotic resistance. The database offers diverse methods for exploring its extensive plasmid collection, enabling users to navigate plasmids through metadata-centric queries, plasmid comparisons and BLAST searches. The web interface for IMG/PR is accessible at https://img.jgi.doe.gov/pr. Plasmid metadata and sequences can be downloaded from https://genome.jgi.doe.gov/portal/IMG_PR.

Structural determinants of the direct inhibition of GIRK channels by Sigma-1 receptor antagonist.

G-protein-gated inward rectifier K+ (GIRK) channels play a critical role in the regulation of the excitability of cardiomyocytes and neurons and include GIRK1, GIRK2, GIRK3 and GIRK4 subfamily members. BD1047 dihydrobromide (BD1047) is one of the representative antagonists of the multifunctional Sigma-1 receptor (S1R). In the analysis of the effect of BD1047 on the regulation of Gi-coupled receptors by S1R using GIRK channel as an effector, we observed that BD1047, as well as BD1063, directly inhibited GIRK currents even in the absence of S1R and in a voltage-independent manner. Thus, we aimed to clarify the effect of BD1047 on GIRK channels and identify the structural determinants. By electrophysiological recordings in Xenopus oocytes, we observed that BD1047 directly inhibited GIRK channel currents, producing a much stronger inhibition of GIRK4 compared to GIRK2. It also inhibited ACh-induced native GIRK current in isolated rat atrial myocytes. Chimeric and mutagenesis studies of GIRK2 and GIRK4 combined with molecular docking analysis demonstrated the importance of Leu77 and Leu84 within the cytoplasmic, proximal N-terminal region and Glu147 within the pore-forming region of GIRK4 for inhibition by BD1047. The activator of GIRK channels, ivermectin, competed with BD1047 at Leu77 on GIRK4. This study provides us with a novel inhibitor of GIRK channels and information for developing pharmacological treatments for GIRK4-associated diseases.

Polygenic risk score predicting susceptibility and outcome of benign prostatic hyperplasia in the Han Chinese.

BACKGROUND: Given the high prevalence of BPH among elderly men, pinpointing those at elevated risk can aid in early intervention and effective management. This study aimed to explore that polygenic risk score (PRS) is effective in predicting benign prostatic hyperplasia (BPH) incidence, prognosis and risk of operation in Han Chinese. METHODS: A retrospective cohort study included 12,474 male participants (6,237 with BPH and 6,237 non-BPH controls) from the Taiwan Precision Medicine Initiative (TPMI). Genotyping was performed using the Affymetrix Genome-Wide TWB 2.0 SNP Array. PRS was calculated using PGS001865, comprising 1,712 single nucleotide polymorphisms. Logistic regression models assessed the association between PRS and BPH incidence, adjusting for age and prostate-specific antigen (PSA) levels. The study also examined the relationship between PSA, prostate volume, and response to 5-α-reductase inhibitor (5ARI) treatment, as well as the association between PRS and the risk of TURP. RESULTS: Individuals in the highest PRS quartile (Q4) had a significantly higher risk of BPH compared to the lowest quartile (Q1) (OR = 1.51, 95% CI = 1.274-1.783, p < 0.0001), after adjusting for PSA level. The Q4 group exhibited larger prostate volumes and a smaller volume reduction after 5ARI treatment. The Q1 group had a lower cumulative TURP probability at 3, 5, and 10 years compared to the Q4 group. PRS Q4 was an independent risk factor for TURP. CONCLUSIONS: In this Han Chinese cohort, higher PRS was associated with an increased susceptibility to BPH, larger prostate volumes, poorer response to 5ARI treatment, and a higher risk of TURP. Larger prospective studies with longer follow-up are warranted to further validate these findings.

Multiomics in the central Arctic Ocean for benchmarking biodiversity change.

Multiomics approaches need to be applied in the central Arctic Ocean to benchmark biodiversity change and to identify novel species and their genes. As part of MOSAiC, EcoOmics will therefore be essential for conservation and sustainable bioprospecting in one of the least explored ecosystems on Earth.

Twenty-five years of Genomes OnLine Database (GOLD): data updates and new features in v.9.

The Genomes OnLine Database (GOLD) (https://gold.jgi.doe.gov/) at the Department of Energy Joint Genome Institute (DOE-JGI) continues to maintain its role as one of the flagship genomic metadata repositories of the world. The ever-increasing number of projects and metadata are freely available to the user community world-wide. GOLD's metadata is consumed by scientists and remains an important source for large-scale comparative genomics analysis initiatives. Encouraged by this active user engagement and growth, GOLD has continued to add new components and capabilities. The new features such as a public Application Programming Interface (API) and Ecosystem landing page as well as the growth of different entities in this current GOLD v.9 edition are described in detail in this manuscript.

The IMG/M data management and analysis system v.7: content updates and new features.

The Integrated Microbial Genomes & Microbiomes system (IMG/M: https://img.jgi.doe.gov/m/) at the Department of Energy (DOE) Joint Genome Institute (JGI) continues to provide support for users to perform comparative analysis of isolate and single cell genomes, metagenomes, and metatranscriptomes. In addition to datasets produced by the JGI, IMG v.7 also includes datasets imported from public sources such as NCBI Genbank, SRA, and the DOE National Microbiome Data Collaborative (NMDC), or submitted by external users. In the past couple years, we have continued our effort to help the user community by improving the annotation pipeline, upgrading the contents with new reference database versions, and adding new analysis functionalities such as advanced scaffold search, Average Nucleotide Identity (ANI) for high-quality metagenome bins, new cassette search, improved gene neighborhood display, and improvements to metatranscriptome data display and analysis. We also extended the collaboration and integration efforts with other DOE-funded projects such as NMDC and DOE Biology Knowledgebase (KBase).

IMG/VR v4: an expanded database of uncultivated virus genomes within a framework of extensive functional, taxonomic, and ecological metadata.

Viruses are widely recognized as critical members of all microbiomes. Metagenomics enables large-scale exploration of the global virosphere, progressively revealing the extensive genomic diversity of viruses on Earth and highlighting the myriad of ways by which viruses impact biological processes. IMG/VR provides access to the largest collection of viral sequences obtained from (meta)genomes, along with functional annotation and rich metadata. A web interface enables users to efficiently browse and search viruses based on genome features and/or sequence similarity. Here, we present the fourth version of IMG/VR, composed of >15 million virus genomes and genome fragments, a ≈6-fold increase in size compared to the previous version. These clustered into 8.7 million viral operational taxonomic units, including 231 408 with at least one high-quality representative. Viral sequences in IMG/VR are now systematically identified from genomes, metagenomes, and metatranscriptomes using a new detection approach (geNomad), and IMG standard annotation are complemented with genome quality estimation using CheckV, taxonomic classification reflecting the latest taxonomic standards, and microbial host taxonomy prediction. IMG/VR v4 is available at https://img.jgi.doe.gov/vr, and the underlying data are available to download at https://genome.jgi.doe.gov/portal/IMG_VR.

Anelasticity in thin-shell nanolattices.

In this work, we investigate the anelastic deformation behavior of periodic three-dimensional (3D) nanolattices with extremely thin shell thicknesses using nanoindentation. The results show that the nanolattice continues to deform with time under a constant load. In the case of 30-nm-thick aluminum oxide nanolattices, the anelastic deformation accounts for up to 18.1% of the elastic deformation for a constant load of 500 µN. The nanolattices also exhibit up to 15.7% recovery after unloading. Finite element analysis (FEA) coupled with diffusion of point defects is conducted, which is in qualitative agreement with the experimental results. The anelastic behavior can be attributed to the diffusion of point defects in the presence of a stress gradient and is reversible when the deformation is removed. The FEA model quantifies the evolution of the stress gradient and defect concentration and demonstrates the important role of a wavy tube profile in the diffusion of point defects. The reported anelastic deformation behavior can shed light on time-dependent response of nanolattice materials with implication for energy dissipation applications.

Shadowed versus Etched Superconductor-Semiconductor Junctions in Al/InAs Nanowires.

Hybrid semiconductor-superconductor nanowires have emerged as a cornerstone in modern quantum devices. Integrating such nanowires into hybrid devices typically requires extensive postgrowth processing which may affect device performance unfavorably. Here, we present a technique for in situ shadowing superconductors on nanowires and compare the structural and electronic properties of Al junctions formed by shadowing versus etching. Based on transmission electron microscopy, we find that typical etching procedures lead to atomic-scale surface roughening. This surface perturbation may cause a reduction of the electron mobility as demonstrated in transport measurements. Further, we display advanced shadowing geometries aiding in the pursuit of bringing fabrication of hybrid devices in situ. Finally, we give examples of shadowed junctions exploited in various device geometries that exhibit high-quality quantum transport signatures.

Characterization of unique pattern of immune cell profile in patients with nasopharyngeal carcinoma through flow cytometry and machine learning.

In patients with nasopharyngeal carcinoma (NPC), the alteration of immune responses in peripheral blood remains unclear. In this study, we established an immune cell profile for patients with NPC and used flow cytometry and machine learning (ML) to identify the characteristics of this profile. After isolation of circulating leukocytes, the proportions of 104 immune cell subsets were compared between NPC group and the healthy control group (HC). Data obtained from the immune cell profile were subjected to ML training to differentiate between the immune cell profiles of the NPC and HC groups. We observed that subjects in the NPC group presented higher proportions of T cells, memory B cells, short-lived plasma cells, IgG-positive B cells, regulatory T cells, MHC II+ T cells, CTLA4+ T cells and PD-1+ T cells than subjects in the HC group, indicating weaker and compromised cellular and humoral immune responses. ML revealed that monocytes, PD-1+ CD4 T cells, memory B cells, CTLA4+ CD4 Treg cells and PD-1+ CD8 T cells were strongly contributed to the difference in immune cell profiles between the NPC and HC groups. This alteration can be fundamental in developing novel immunotherapies for NPC.

Anticonvulsant effect of equilibrative nucleoside transporters 1 inhibitor in a mouse model of Dravet syndrome.

There are limited therapeutic options for patients with Dravet syndrome (DS). The equilibrative nucleoside transporters 1 (ENT1) mediate both the influx and efflux of adenosine across the cell membrane exerted beneficial effects in the treatment of epilepsy. This study aimed to evaluate the anticonvulsant effect of the ENT1 inhibitor in an animal model of DS (Scn1aE1099X/+ mice). J7 (5 mg/kg) treatment was efficacious in elevating seizure threshold in Scn1aE1099X/+ mice after hyperthermia exposure. Moreover, the J7 treatment significantly reduced the frequency of spontaneous excitatory post-synaptic currents (sEPSCs, ~35% reduction) without affecting the amplitude in dentate gyrus (DG) granule cells. Pretreatment with the adenosine A1 receptor (A1R) antagonist, DPCPX, abolished the J7 effects on sEPSCs. These observations suggest that the J7 shows an anticonvulsant effect in hyperthermia-induced seizures in Scn1aE1099X/+ mice. This effect possibly acts on presynaptic A1R-mediated signaling modulation in granule cells.

The phosphorylation of the movement protein TGBp1 regulates the accumulation of the Bamboo mosaic virus.

Phosphorylation and dephosphorylation of viral movement proteins plays a crucial role in regulating virus movement. Our study focused on investigating the movement protein TGBp1 of Bamboo mosaic virus (BaMV), which is a single-stranded positive-sense RNA virus. Specifically, we examined four potential phosphorylation sites (S15, S18, T58, and S247) within the TGBp1 protein. To study the impact of phosphorylation, we introduced amino acid substitutions at the selected sites. Alanine substitutions were used to prevent phosphorylation, while aspartate substitutions were employed to mimic phosphorylation. Our findings suggest that mimicking phosphorylation at S15, S18 and T58 of TGBp1 might be linked to silencing suppressor activities. The phosphorylated form at these sites exhibits a loss of silencing suppressor activity, leading to reduced viral accumulation in the inoculated leaves. Furthermore, mimicking phosphorylation at residues S15 and S18 could diminish viral accumulation at the single-cell level, while doing so at residue T58 could influence virus movement. However, mimicking phosphorylation at residue S247 does not appear to be relevant to both functions of TGBp1. Overall, our study provides insights into the functional significance of specific phosphorylation sites in BaMV TGBp1, illuminating the regulatory mechanisms involved in virus movement and silencing suppression.

CD204-positive M2-like tumor-associated macrophages increase migration of gastric cancer cells by upregulating miR-210 to reduce NTN4 expression.

BACKGROUND: Tumor-associated macrophages (TAMs) are the predominant immune cells in the tumor microenvironment and portend poor prognosis. However, the molecular mechanisms underlying the tumor promotion of TAMs have not been fully elucidated. METHODS: Coculture of gastric cancer cells with U937 cells was performed to investigate the impact of TAMs on cancer cell behavior. MicroRNA (miRNA) microarray and bioinformatics were applied to identify the involved miRNAs and the functional target genes. The regulation of the miRNA on its target gene was studied using anti-miRNA and miRNA mimic. RESULTS: Coculture with CD204+ M2-like TAMs increased proliferation, migration, and epithelial-mesenchymal transition of gastric cancer cells. MiR-210 was the most upregulated miRNA in cancer cells identified by miRNA microarray after coculture. In gastric cancer tissues, miR-210 expression was positively correlated with CD204+ M2-like TAM infiltration. Inactivation of miR-210 by antimir attenuated CD204+ M2-like TAMs-induced cancer cell migration. Using pharmacological inhibitors and neutralizing antibodies, CD204+ M2-like TAMs-secreted TNFα was found to upregulate miR-210 through NF-κB/HIF-1α signaling. Bioinformatics analysis showed netrin-4 (NTN4) as a potential target of miR-210 to suppress gastric cancer cell migration. We also found an inverse expression between miR-210 and NTN4 in cancer cells after coculture or in tumor xenografts. Anti-miR-210 increased NTN4 expression, while miR-210 mimics downregulated NTN4 in cancer cells. Reporter luciferase assays showed that MiR-210 mimics suppressed NTN4 3' untranslated region-driven luciferase activity in cancer cells, but this effect was blocked after mutating miR-210 binding site. CONCLUSIONS: CD204+ M2-like TAMs can utilize the TNF-α/NF-κB/HIF-1α/miR-210/NTN4 pathway to facilitate gastric cancer progression.

Interaction of base excision repair gene polymorphism and estrogen-DNA adducts in breast cancer risk among East Asian women.

PURPOSE: In East Asia, the incidence of breast cancer has been increasing rapidly, particularly among premenopausal women. An elevated ratio of estrogen-DNA adducts was linked to a higher risk of breast cancer. The present study explored the influence of the interaction between base excision repair (BER) gene polymorphisms and estrogen-DNA adducts on breast cancer risk. METHODS: We conducted a case-control study comprising healthy volunteers and individuals with benign breast disease (control arm, n = 176) and patients with invasive carcinoma or carcinoma in situ (case arm, n = 177). Genotyping for BER-related genes, including SMUG1, OGG1, ERCC5, and APEX1, was performed. A logistic regression model, incorporating interactions between gene polymorphisms, estrogen-DNA adduct ratio, and clinical variables, was used to identify the risk factors for breast cancer. RESULTS: Univariate analysis indicated marginal associations between breast cancer risk and APEX1 rs1130409 T > G (P = 0.057) and APEX1 rs1760944 T > G (P = 0.065). Multivariate regression analysis revealed significant associations with increased breast cancer risk for APEX1_rs1130409 (GT/GG versus TT) combined with a natural logarithmic value of the estrogen-DNA adduct ratio (estimated OR 1.164, P = 0.023) and premenopausal status with an estrogen-DNA adduct ratio > 2.93 (estimated OR 2.433, P = 0.001). CONCLUSION: APEX1_rs1130409 (GT/GG versus TT) polymorphisms, which are related to decreased BER activity, combined with an increased ratio of estrogen-DNA adducts, increase the risk of breast cancer in East Asian women.

Bringing traits back into the equation: A roadmap to understand species redistribution.

Ecological and evolutionary theories have proposed that species traits should be important in mediating species responses to contemporary climate change; yet, empirical evidence has so far provided mixed evidence for the role of behavioral, life history, or ecological characteristics in facilitating or hindering species range shifts. As such, the utility of trait-based approaches to predict species redistribution under climate change has been called into question. We develop the perspective, supported by evidence, that trait variation, if used carefully can have high potential utility, but that past analyses have in many cases failed to identify an explanatory value for traits by not fully embracing the complexity of species range shifts. First, we discuss the relevant theory linking species traits to range shift processes at the leading (expansion) and trailing (contraction) edges of species distributions and highlight the need to clarify the mechanistic basis of trait-based approaches. Second, we provide a brief overview of range shift-trait studies and identify new opportunities for trait integration that consider range-specific processes and intraspecific variability. Third, we explore the circumstances under which environmental and biotic context dependencies are likely to affect our ability to identify the contribution of species traits to range shift processes. Finally, we propose that revealing the role of traits in shaping species redistribution may likely require accounting for methodological variation arising from the range shift estimation process as well as addressing existing functional, geographical, and phylogenetic biases. We provide a series of considerations for more effectively integrating traits as well as extrinsic and methodological factors into species redistribution research. Together, these analytical approaches promise stronger mechanistic and predictive understanding that can help society mitigate and adapt to the effects of climate change on biodiversity.