Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation

Altitude-dependent agro-ecologies impact the microbiome diversity of scavenging indigenous chicken in Ethiopia

BACKGROUND

Scavenging indigenous village chickens play a vital role in sub-Saharan Africa, sustaining the livelihood of millions of farmers. These chickens are exposed to vastly different environments and feeds compared to commercial chickens. In this study, we analysed the caecal microbiota of 243 Ethiopian village chickens living in different altitude-dependent agro-ecologies.

RESULTS

Differences in bacterial diversity were significantly correlated with differences in specific climate factors, topsoil characteristics, and supplemental diets provided by farmers. Microbiota clustered into three enterotypes, with one particularly enriched at high altitudes. We assembled 9977 taxonomically and functionally diverse metagenome-assembled genomes. The vast majority of these were not found in a dataset of previously published chicken microbes or in the Genome Taxonomy Database.

CONCLUSIONS

The wide functional and taxonomic diversity of these microbes highlights their importance in the local adaptation of indigenous poultry, and the significant impacts of environmental factors on the microbiota argue for further discoveries in other agro-ecologies. Video Abstract.

zDB: bacterial comparative genomics made easy

The analysis and comparison of genomes rely on different tools for tasks such as annotation, orthology prediction, and phylogenetic inference. Most tools are specialized for a single task, and additional efforts are necessary to integrate and visualize the results. To fill this gap, we developed zDB, an application integrating a Nextflow analysis pipeline and a Python visualization platform built on the Django framework. The application is available on GitHub (https://github.com/metagenlab/zDB) and from the bioconda channel. Starting from annotated Genbank files, zDB identifies orthologs and infers a phylogeny for each orthogroup. A species phylogeny is also constructed from shared single-copy orthologs. The results can be enriched with Pfam protein domain prediction, Cluster of Orthologs Genes and Kyoto Encyclopedia of Genes and Genomes annotations, and Swissprot homologs. The web application allows searching for specific genes or annotations, running Blast queries, and comparing genomic regions and whole genomes. The metabolic capacities of organisms can be compared at either the module or pathway levels. Finally, users can run queries to examine the conservation of specific genes or annotations across a chosen subset of genomes and display the results as a list of genes, Venn diagram, or heatmaps. Those features make zDB useful for both bioinformaticians and researchers more accustomed to laboratory research.IMPORTANCEGenome comparison and analysis rely on many independent tools, leaving to scientists the burden to integrate and visualize their results for interpretation. To alleviate this burden, we have built zDB, a comparative genomics tool that includes both an analysis pipeline and a visualization platform. The analysis pipeline automates gene annotation, orthology prediction, and phylogenetic inference, while the visualization platform allows scientists to easily explore the results in a web browser. Among other features, the interface allows users to visually compare whole genomes and targeted regions, assess the conservation of genes or metabolic pathways, perform Blast searches, or look for specific annotations. Altogether, this tool will be useful for a broad range of applications in comparative studies between two and hundred genomes. Furthermore, it is designed to allow sharing of data sets easily at a local or international scale, thereby supporting exploratory analyses for non-bioinformaticians on the genome of their favorite organisms.

Fast and space-efficient taxonomic classification of long reads with hierarchical interleaved XOR filters

Metagenomic long-read sequencing is gaining popularity for various applications, including pathogen detection and microbiome studies. To analyze the large data created in those studies, software tools need to taxonomically classify the sequenced molecules and estimate the relative abundances of organisms in the sequenced sample. Because of the exponential growth of reference genome databases, the current taxonomic classification methods have large computational requirements. This issue motivated us to develop a new data structure for fast and memory-efficient querying of long reads. Here, we present Taxor as a new tool for long-read metagenomic classification using a hierarchical interleaved XOR filter data structure for indexing and querying large reference genome sets. Taxor implements several k-mer-based approaches, such as syncmers, for pseudoalignment to classify reads and an expectation-maximization algorithm for metagenomic profiling. Our results show that Taxor outperforms state-of-the-art tools regarding precision while having a similar recall for long-read taxonomic classification. Most notably, Taxor reduces the memory requirements and index size by >50% and is among the fastest tools regarding query times. This enables real-time metagenomics analysis with large reference databases on a small laptop in the field.

Non-invasive determination of gene expression in placental tissue using maternal plasma cell-free DNA fragmentation characters

BACKGROUND

The expression profiles of placental genes are crucial for understanding the pathogenesis of fetal development and placental-origin pregnancy syndromes. However, owing to ethical limitations and the risks of puncture sampling, it is difficult to obtain placental tissue samples repeatedly, continuously, multiple times, or in real time. Establishing a non-invasive method for predicting placental gene expression profiles through maternal plasma cell-free DNA (cfDNA) sequencing, which carries information about the source tissue and gene expression, can potentially solve this problem.

METHODS

Peripheral blood and placental samples were collected simultaneously from pregnant women who underwent cesarean section. Deep sequencing was performed on the separated plasma cfDNA and single-cell sequencing was performed on peripheral blood mononuclear cells (PBMC), chorioamniotic membranes (CAM), placental villi (PV), and decidua basalis (DB). The aggregation of corresponding information for each gene was combined with the transcriptome of PBMCs and a differential resolution transcriptome of the placenta. This combined information was then utilized for the construction of gene expression prediction models. After training, all models evaluated the correlation between the predicted and actual gene expression levels using external test set data.

RESULTS

From five women, more than 20 million reads were obtained using deep sequencing for plasma cfDNA; PBMCs obtained 32,401 single-cell expression profiles; and placental tissue obtained 156,546 single-cell expression profiles (59,069, 44,921, and 52,556 for CAM, PV, and DB, respectively). The cells in the PBMC and placenta were clustered and annotated into five and eight cell types, respectively. A "DEPICT" gene expression prediction model was successfully constructed using deep neural networks. The predicted correlation coefficients were 0.75 in PBMCs, 0.84 in the placenta, and 0.78, 0.80, and 0.77 in CAM, BP, and PV respectively, and greater than 0.68 in different cell lines in the placenta.

CONCLUSION

The DEPICT model, which can noninvasively predict placental gene expression profiles based on maternal plasma cfDNA fragmentation characteristics, was constructed to overcome the limitation of the inability to obtain real-time placental gene expression profiles and to improve research on noninvasive prediction of placental origin pregnancy syndrome.

Comparative analysis of RNA 3D structure prediction methods: towards enhanced modeling of RNA-ligand interactions

Accurate RNA structure models are crucial for designing small molecule ligands that modulate their functions. This study assesses six standalone RNA 3D structure prediction methods-DeepFoldRNA, RhoFold, BRiQ, FARFAR2, SimRNA and Vfold2, excluding web-based tools due to intellectual property concerns. We focus on reproducing the RNA structure existing in RNA-small molecule complexes, particularly on the ability to model ligand binding sites. Using a comprehensive set of RNA structures from the PDB, which includes diverse structural elements, we found that machine learning (ML)-based methods effectively predict global RNA folds but are less accurate with local interactions. Conversely, non-ML-based methods demonstrate higher precision in modeling intramolecular interactions, particularly with secondary structure restraints. Importantly, ligand-binding site accuracy can remain sufficiently high for practical use, even if the overall model quality is not optimal. With the recent release of AlphaFold 3, we included this advanced method in our tests. Benchmark subsets containing new structures, not used in the training of the tested ML methods, show that AlphaFold 3's performance was comparable to other ML-based methods, albeit with some challenges in accurately modeling ligand binding sites. This study underscores the importance of enhancing binding site prediction accuracy and the challenges in modeling RNA-ligand interactions accurately.

Chromosome-level genome assembly and annotation of xerophyte secretohalophyte Reaumuria soongarica

Reaumuria soongarica is a xerophytic shrub belonging to the Tamaricaceae family. The species is widely distributed in the deserts of Central Asia and is characterized by its remarkable adaptability to saline and barren desert environments. Using PacBio long-read sequencing and Hi-C technologies, we assembled a chromosome-level genome of R. soongarica. The genome assembly has a size of 1.28 Gb with a scaffold N50 of 116.15 Mb, and approximately 1.25 Gb sequences were anchored in 11 pseudo-chromosomes. A completeness assessment of the assembled genome revealed a BUSCO score of 97.5% and an LTR Assembly Index of 12.37. R. soongarica genome had approximately 60.07% repeat sequences. In total, 21,791 protein-coding genes were predicted, of which 95.64% were functionally annotated. This high-quality genome will serve as a foundation for studying the genomic evolution and adaptive mechanisms to arid-saline environments in R. soongarica, facilitating the exploration and utilization of its unique genetic resources.

Discovery of a Ni2+-dependent heterohexameric metformin hydrolase

The biguanide drug metformin is a first-line blood glucose-lowering medication for type 2 diabetes, leading to its presence in the global environment. However, little is known about the fate of metformin by microbial catabolism. Here, we characterize a Ni2+-dependent heterohexameric enzyme (MetCaCb) from the ureohydrolase superfamily, catalyzing the hydrolysis of metformin into guanylurea and dimethylamine. Either subunit alone is catalytically inactive, but together they work as an active enzyme highly specific for metformin. The crystal structure of the MetCaCb complex shows the coordination of the binuclear metal cluster only in MetCa, with MetCb as a protein binder of its active cognate. An in-silico search and functional assay discover a group of MetCaCb-like protein pairs exhibiting metformin hydrolase activity in the environment. Our findings not only establish the genetic and biochemical foundation for metformin catabolism but also provide additional insights into the adaption of the ancient enzymes toward newly occurred substrate.

Time-series metagenomics reveals changing protistan ecology of a temperate dimictic lake

BACKGROUND

Protists, single-celled eukaryotic organisms, are critical to food web ecology, contributing to primary productivity and connecting small bacteria and archaea to higher trophic levels. Lake Mendota is a large, eutrophic natural lake that is a Long-Term Ecological Research site and among the world's best-studied freshwater systems. Metagenomic samples have been collected and shotgun sequenced from Lake Mendota for the last 20 years. Here, we analyze this comprehensive time series to infer changes to the structure and function of the protistan community and to hypothesize about their interactions with bacteria.

RESULTS

Based on small subunit rRNA genes extracted from the metagenomes and metagenome-assembled genomes of microeukaryotes, we identify shifts in the eukaryotic phytoplankton community over time, which we predict to be a consequence of reduced zooplankton grazing pressures after the invasion of a invasive predator (the spiny water flea) to the lake. The metagenomic data also reveal the presence of the spiny water flea and the zebra mussel, a second invasive species to Lake Mendota, prior to their visual identification during routine monitoring. Furthermore, we use species co-occurrence and co-abundance analysis to connect the protistan community with bacterial taxa. Correlation analysis suggests that protists and bacteria may interact or respond similarly to environmental conditions. Cryptophytes declined in the second decade of the timeseries, while many alveolate groups (e.g., ciliates and dinoflagellates) and diatoms increased in abundance, changes that have implications for food web efficiency in Lake Mendota.

CONCLUSIONS

We demonstrate that metagenomic sequence-based community analysis can complement existing efforts to monitor protists in Lake Mendota based on microscopy-based count surveys. We observed patterns of seasonal abundance in microeukaryotes in Lake Mendota that corroborated expectations from other systems, including high abundance of cryptophytes in winter and diatoms in fall and spring, but with much higher resolution than previous surveys. Our study identified long-term changes in the abundance of eukaryotic microbes and provided context for the known establishment of an invasive species that catalyzes a trophic cascade involving protists. Our findings are important for decoding potential long-term consequences of human interventions, including invasive species introduction. Video Abstract.

Whole genome sequencing identifies elusive variants in genetically unsolved Italian inherited retinal disease patients

Inherited retinal diseases (IRDs) are a group of rare monogenic diseases with high genetic heterogeneity (pathogenic variants identified in over 280 causative genes). The genetic diagnostic rate for IRDs is around 60%, mainly thanks to the routine application of next-generation sequencing (NGS) approaches such as extensive gene panels or whole exome analyses. Whole-genome sequencing (WGS) has been reported to improve this diagnostic rate by revealing elusive variants, such as structural variants (SVs) and deep intronic variants (DIVs). We performed WGS on 33 unsolved cases with suspected autosomal recessive IRD, aiming to identify causative genetic variants in non-coding regions or to detect SVs that were unexplored in the initial screening. Most of the selected cases (30 of 33, 90.9%) carried monoallelic pathogenic variants in genes associated with their clinical presentation, hence we first analyzed the non-coding regions of these candidate genes. Whenever additional pathogenic variants were not identified with this approach, we extended the search for SVs and DIVs to all IRD-associated genes. Overall, we identified the missing causative variants in 11 patients (11 of 33, 33.3%). These included three DIVs in ABCA4, CEP290 and RPGRIP1; one non-canonical splice site (NCSS) variant in PROM1 and three SVs (large deletions) in EYS, PCDH15 and USH2A. For the previously unreported DIV in CEP290 and for the NCCS variant in PROM1, we confirmed the effect on splicing by reverse transcription (RT)-PCR on patient-derived RNA. This study demonstrates the power and clinical utility of WGS as an all-in-one test to identify disease-causing variants missed by standard NGS diagnostic methodologies.

Chromosome-Scale Genome Assembly of the Sheep-Biting Louse Bovicola ovis Using Nanopore Sequencing Data and Pore-C Analysis

Bovicola ovis, commonly known as the sheep-biting louse, is an ectoparasite that adversely affects the sheep industry. Sheep louse infestation lowers the quality of products, including wool and leather, causing a loss of approximately AUD 123M per annum in Australia alone. The lack of a high-quality genome assembly for the sheep-biting louse, as well as any closely related livestock lice, has hindered the development of louse research and management control tools. In this study, we present the assembly of B. ovis with a genome size of ~123 Mbp based on a nanopore long-read sequencing library and Illumina RNA sequencing, complemented with a chromosome-level scaffolding using the Pore-C multiway chromatin contact dataset. Combining multiple alignment and gene prediction tools, a comprehensive annotation on the assembled B. ovis genome was conducted and recalled 11,810 genes as well as other genomic features including orf, ssr, rRNA and tRNA. A manual curation using alignment with the available closely related louse species, Pediculus humanus, increased the number of annotated genes to 16,024. Overall, this study reported critical genetic resources and biological insights for the advancement of sheep louse research and the development of sustainable control strategies in the sheep industry.

Prophage-DB: A comprehensive database to explore diversity, distribution, and ecology of prophages

Background

Viruses that infect prokaryotes (phages) constitute the most abundant group of biological agents, playing pivotal roles in microbial systems. They are known to impact microbial community dynamics, microbial ecology, and evolution. Efforts to document the diversity, host range, infection dynamics, and effects of bacteriophage infection on host cell metabolism are extremely underexplored. Phages are classified as virulent or temperate based on their life cycles. Temperate phages adopt the lysogenic mode of infection, where the genome integrates into the host cell genome forming a prophage. Prophages enable viral genome replication without host cell lysis, and often contribute novel and beneficial traits to the host genome. Current phage research predominantly focuses on lytic phages, leaving a significant gap in knowledge regarding prophages, including their biology, diversity, and ecological roles.

Results

Here we develop and describe Prophage-DB, a database of prophages, their proteins, and associated metadata that will serve as a resource for viral genomics and microbial ecology. To create the database, we identified and characterized prophages from genomes in three of the largest publicly available databases. We applied several state-of-the-art tools in our pipeline to annotate these viruses, cluster and taxonomically classify them, and detect their respective auxiliary metabolic genes. In total, we identify and characterize over 350,000 prophages and 35,000 auxiliary metabolic genes. Our prophage database is highly representative based on statistical results and contains prophages from a diverse set of archaeal and bacterial hosts which show a wide environmental distribution.

Conclusion

Prophages are particularly overlooked in viral ecology and merit increased attention due to their vital implications for microbiomes and their hosts. Here, we created Prophage-DB to advance our comprehension of prophages in microbiomes through a comprehensive characterization of prophages in publicly available genomes. We propose that Prophage-DB will serve as a valuable resource for advancing phage research, offering insights into viral taxonomy, host relationships, auxiliary metabolic genes, and environmental distribution.

Two different types of hydrolases co-degrade ochratoxin A in a highly efficient degradation strain Lysobacter sp. CW239

Ochratoxin A (OTA) is a toxic secondary metabolite that widely contaminates agro-products and poses a significant dietary risk to human health. Previously, a carboxypeptidase CP4 was characterized for OTA degradation in Lysobacter sp. CW239, but the degradation activity was much lower than its host strain CW239. In this study, an amidohydrolase ADH2 was screened for OTA hydrolysis in this strain. The result showed that 50 μg/L OTA was completely degraded by 1.0 μg/mL rADH2 within 5 min, indicating ultra-efficient activity. Meanwhile, the two hydrolases (i.e., CP4 and ADH2) in the strain CW239 showed the same degradation manner, which transformed the OTA to ochratoxin α (OTα) and l-β-phenylalanine. Gene mutants (Δcp4, Δadh2 and Δcp4-adh2) testing result showed that OTA was co-degraded by carboxypeptidase CP4 and amidohydrolase ADH2, and the two hydrolases are sole agents in strain CW239 for OTA degradation. Hereinto, the ADH2 was the overwhelming efficient hydrolase, and the two types of hydrolases co-degraded OTA in CW239 by synergistic effect. The results of this study are highly significant to ochratoxin A contamination control during agro-products production and postharvest.

Genomic representativeness and chimerism in large collections of SAGs and MAGs of marine prokaryoplankton

BACKGROUND

Single amplified genomes (SAGs) and metagenome-assembled genomes (MAGs) are the predominant sources of information about the coding potential of uncultured microbial lineages, but their strengths and limitations remain poorly understood. Here, we performed a direct comparison of two previously published collections of thousands of SAGs and MAGs obtained from the same, global environment.

RESULTS

We found that SAGs were less prone to chimerism and more accurately reflected the relative abundance and the pangenome content of microbial lineages inhabiting the epipelagic of the tropical and subtropical ocean, as compared to MAGs. SAGs were also better suited to link genome information with taxa discovered through 16S rRNA amplicon analyses. Meanwhile, MAGs had the advantage of more readily recovering genomes of rare lineages.

CONCLUSIONS

Our analyses revealed the relative strengths and weaknesses of the two most commonly used genome recovery approaches in environmental microbiology. These considerations, as well as the need for better tools for genome quality assessment, should be taken into account when designing studies and interpreting data that involve SAGs or MAGs. Video Abstract.

Exploring Plant-Based Compounds as Alternatives for Targeting Enterococcus faecalis in Endodontic Therapy: A Molecular Docking Approach

Endodontic infections pose significant challenges in dental practice due to their persistence and potential complications. Among the causative agents, Enterococcus faecalis stands out for its ability to form biofilms and develop resistance to conventional antibiotics, leading to treatment failures and recurrent infections. The urgent need for alternative treatments arises from the growing concern over antibiotic resistance and the limitations of current therapeutic options in combating E. faecalis-associated endodontic infections. Plant-based natural compounds offer a promising avenue for exploration, given their diverse bioactive properties and potential as sources of novel antimicrobial agents. In this study, molecular docking and dynamics simulations are employed to explore the interactions between SrtA, a key enzyme in E. faecalis, and plant-based natural compounds. Analysis of phytocompounds through molecular docking unveiled several candidates with binding energies surpassing that of the control drug, ampicillin, with pinocembrin emerging as the lead compound due to its strong interactions with key residues of SrtA. Comparative analysis with ampicillin underscored varying degrees of structural similarity among the study compounds. Molecular dynamics simulations provided deeper insights into the dynamic behavior and stability of protein-ligand complexes, with pinocembrin demonstrating minimal conformational changes and effective stabilization of the N-terminal region. Free energy landscape analysis supported pinocembrin's stabilizing effects, further corroborated by hydrogen bond analysis. Additionally, physicochemical properties analysis highlighted the drug-likeness of pinocembrin and glabridin. Overall, this study elucidates the potential anti-bacterial properties of selected phytocompounds against E. faecalis infections, with pinocembrin emerging as a promising lead compound for further drug development efforts, offering new avenues for combating bacterial infections and advancing therapeutic interventions in endodontic practice.

Exploring non-coding genetic variability in ACE2: Functional annotation and in vitro validation of regulatory variants

The surge in human whole-genome sequencing data has facilitated the study of non-coding region variations, yet understanding their biological significance remains a challenge. We used a computational workflow to assess the regulatory potential of non-coding variants, with a particular focus on the Angiotensin Converting Enzyme 2 (ACE2) gene. This gene is crucial in physiological processes and serves as the entry point for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing coronavirus disease 19 (COVID-19). In our analysis, using data from the gnomAD population database and functional annotation, we identified 17 significant Single Nucleotide Variants (SNVs) in ACE2, particularly in its enhancers, promoters, and 3' untranslated regions (UTRs). We found preliminary evidence supporting the regulatory impact of some of these variants on ACE2 expression. Our detailed examination of two SNVs, rs147718775 and rs140394675, in the ACE2 promoter revealed that these co-occurring SNVs, when mutated, significantly enhance promoter activity, suggesting a possible increase in specific ACE2 isoform expression. This method proves effective in identifying and interpreting impactful non-coding variants, aiding in further studies and enhancing understanding of molecular bases of monogenic and complex traits.

Structural basis for transcription activation through cooperative recruitment of MntR

The manganese transport regulator (MntR) from B. subtilis is a dual regulatory protein that responds to heightened Mn2+ availability in the cell by both repressing the expression of uptake transporters and activating the expression of efflux proteins. Recent work indicates that, in its role as an activator, MntR binds several sites upstream of the genes encoding Mn2+ exporters, leading to a cooperative response to manganese. Here, we use cryo-EM to explore the molecular basis of gene activation by MntR and report a structure of four MntR dimers bound to four 18-base pair sites across an 84-base pair regulatory region of the mneP promoter. Our structures, along with solution studies including mass photometry and in vivo transcription assays, reveal that MntR dimers employ polar and non-polar contacts to bind cooperatively to an array of low-affinity DNA-binding sites. These results reveal the molecular basis for cooperativity in the activation of manganese efflux.

Replicon-Based Typing About IncG Plasmids and Molecular Characterization of Five IncG Plasmids Carrying Carbapenem Resistance Gene bla KPC-2

Purpose

To investigate the genetic diversity of IncG plasmids, we have proposed a typing scheme based on replicon repA and performed comparative genomic analysis of five IncG plasmids from China.

Methods

p30860-KPC, p116965-KPC, pA1705-KPC, pA1706-KPC and pNY5520-KPC total in five IncG plasmids from clinical isolates of Pseudomonas and Enterobacteriaceae, respectively, were fully sequenced and were compared with the previously collected reference plasmid p10265-KPC.

Results

Based on phylogeny, IncG-type plasmids are divided into IncG-I to IncG-VIII, the five plasmids belong to IncG-VIII. A detailed sequence comparison was then presented that the IncG plasmid involved accessory region I (Tn5563a/b/c/d/e), accessory region II (ISpa19), and accessory region III (bla KPC-2-region). Expect for the pNY5520-KPC, the rest of the plasmids had the same backbone structure as the reference one. Within the plasmids, insertion sequences Tn5563d and Tn5563e were identified, a novel unknown insertion region was found in Tn5563b/c/d/e. In addition, Tn6376b and Tn6376c were newly designated in the study.

Conclusion

The data presented here including a typing scheme and detailed genetic comparison which provide an insight into the diversification and evolution history of IncG plasmids.

Three-dimensional genome architecture persists in a 52,000-year-old woolly mammoth skin sample

Analyses of ancient DNA typically involve sequencing the surviving short oligonucleotides and aligning to genome assemblies from related, modern species. Here, we report that skin from a female woolly mammoth (†Mammuthus primigenius) that died 52,000 years ago retained its ancient genome architecture. We use PaleoHi-C to map chromatin contacts and assemble its genome, yielding 28 chromosome-length scaffolds. Chromosome territories, compartments, loops, Barr bodies, and inactive X chromosome (Xi) superdomains persist. The active and inactive genome compartments in mammoth skin more closely resemble Asian elephant skin than other elephant tissues. Our analyses uncover new biology. Differences in compartmentalization reveal genes whose transcription was potentially altered in mammoths vs. elephants. Mammoth Xi has a tetradic architecture, not bipartite like human and mouse. We hypothesize that, shortly after this mammoth's death, the sample spontaneously freeze-dried in the Siberian cold, leading to a glass transition that preserved subfossils of ancient chromosomes at nanometer scale.

Direct testing of natural twister ribozymes from over a thousand organisms reveals a broad tolerance for structural imperfections

Twister ribozymes are an extensively studied class of nucleolytic RNAs. Thousands of natural twisters have been proposed using sequence homology and structural descriptors. Yet, most of these candidates have not been validated experimentally. To address this gap, we developed CHiTA (Cleavage High-Throughput Assay), a high-throughput pipeline utilizing massively parallel oligonucleotide synthesis and next-generation sequencing to test putative ribozymes en masse in a scarless fashion. As proof of principle, we applied CHiTA to a small set of known active and mutant ribozymes. We then used CHiTA to test two large sets of naturally occurring twister ribozymes: over 1, 600 previously reported putative twisters and ∼1, 000 new candidate twisters. The new candidates were identified computationally in ∼1, 000 organisms, representing a massive increase in the number of ribozyme-harboring organisms. Approximately 94% of the twisters we tested were active and cleaved site-specifically. Analysis of their structural features revealed that many substitutions and helical imperfections can be tolerated. We repeated our computational search with structural descriptors updated from this analysis, whereupon we identified and confirmed the first intrinsically active twister ribozyme in mammals. CHiTA broadly expands the number of active twister ribozymes found in nature and provides a powerful method for functional analyses of other RNAs.

GRAPHICAL ABSTRACT

Iron Chelation in Soil: Scalable Biotechnology for Accelerating Carbon Dioxide Removal by Enhanced Rock Weathering

Enhanced rock weathering (EW) is an emerging atmospheric carbon dioxide removal (CDR) strategy being scaled up by the commercial sector. Here, we combine multiomics analyses of belowground microbiomes, laboratory-based dissolution studies, and incubation investigations of soils from field EW trials to build the case for manipulating iron chelators in soil to increase EW efficiency and lower costs. Microbial siderophores are high-affinity, highly selective iron (Fe) chelators that enhance the uptake of Fe from soil minerals into cells. Applying RNA-seq metatranscriptomics and shotgun metagenomics to soils and basalt grains from EW field trials revealed that microbial communities on basalt grains significantly upregulate siderophore biosynthesis gene expression relative to microbiomes of the surrounding soil. Separate in vitro laboratory incubation studies showed that micromolar solutions of siderophores and high-affinity synthetic chelator (ethylenediamine-N,N'-bis-2-hydroxyphenylacetic acid, EDDHA) accelerate EW to increase CDR rates. Building on these findings, we develop a potential biotechnology pathway for accelerating EW using the synthetic Fe-chelator EDDHA that is commonly used in agronomy to alleviate the Fe deficiency in high pH soils. Incubation of EW field trial soils with potassium-EDDHA solutions increased potential CDR rates by up to 2.5-fold by promoting the abiotic dissolution of basalt and upregulating microbial siderophore production to further accelerate weathering reactions. Moreover, EDDHA may alleviate potential Fe limitation of crops due to rising soil pH with EW over time. Initial cost-benefit analysis suggests potassium-EDDHA could lower EW-CDR costs by up to U.S. $77 t CO2 ha-1 to improve EW's competitiveness relative to other CDR strategies.

Demographic, clinical and molecular epidemiology of extended-spectrum beta-lactamase-producing Escherichia coli bloodstream infections in Central Australia

We describe the demographics, clinical and molecular epidemiology of extended-spectrum β-lactamase (ESBL) Escherichia coli bloodstream infections (BSI) in Central Australia. All ESBL-producing E. coli bloodstream isolates from January 2018 to December 2020 were retrospectively identified. Demographic and clinical information was extracted by chart review. Whole-genome sequencing was performed for multi-locus sequence typing, antibiotic-resistance genes, and phylogenetic relationships. We identified 41 non-duplicate episodes of ESBL E. coli BSI. Median age was 55 years (IQR 47-63), 78% were female, 93% were Aboriginal, and half came from a remote community. Infections were predominantly urinary (68%, 28/41). In the 12 months prior, 70% (26/37) of identified patients had been hospitalised and 81% (30/37) prescribed antibiotics. Meropenem and piperacillin-tazobactam susceptibility was maintained in 100% and 95% of isolates, respectively. Co-resistance to non-β-lactam antibiotics was 32% to gentamicin, 61% to trimethoprim/sulfamethoxazole, and 68% to ciprofloxacin. For sequenced isolates, 41% (16/35) were sequence type 131 (ST131). Mean acquired antibiotic-resistance genes for each isolate was 12.3 (SD 3.1). Four isolates carried an OXA-1 gene. Only non-ST131 isolates carried AmpC and acquired quinolone-resistance genes. There was some evidence of clustering of closely related strains, but no evidence of community or healthcare admission overlap. ESBL rates are rapidly rising in Central Australia, which is a conducive environment for antibiotic resistance development (e.g., overcrowding, socioeconomic disadvantages, high healthcare exposure and high antibiotic use). Future research is required to explore resistance-transmission dynamics in this unique setting.

Pathogen dynamics and discovery of novel viruses and enzymes by deep nucleic acid sequencing of wastewater

Wastewater contains an extensive reservoir of genetic information, yet largely unexplored. Here, we analyzed by high-throughput sequencing total nucleic acids extracted from wastewater samples collected during a 17 month-period in Berlin, Germany. By integrating global wastewater datasets and applying a novel computational approach to accurately identify viral strains within sewage RNA-sequencing data, we demonstrated the emergence and global dissemination of a specific astrovirus strain. Astrovirus abundance and sequence variation mirrored temporal and spatial patterns of infection, potentially serving as footprints of specific timeframes and geographical locations. Additionally, we revealed more than 100,000 sequence contigs likely originating from novel viral species, exhibiting distinct profiles in total RNA and DNA datasets and including undescribed bunyaviruses and parvoviruses. Finally, we identified thousands of new CRISPR-associated protein sequences, including Transposase B (TnpB), a class of compact, RNA-guided DNA editing enzymes. Collectively, our findings underscore the potential of high-throughput sequencing of total nucleic acids derived from wastewater for a broad range of applications.

Multi-scale signaling and tumor evolution in high-grade gliomas

Although genomic anomalies in glioblastoma (GBM) have been well studied for over a decade, its 5-year survival rate remains lower than 5%. We seek to expand the molecular landscape of high-grade glioma, composed of IDH-wildtype GBM and IDH-mutant grade 4 astrocytoma, by integrating proteomic, metabolomic, lipidomic, and post-translational modifications (PTMs) with genomic and transcriptomic measurements to uncover multi-scale regulatory interactions governing tumor development and evolution. Applying 14 proteogenomic and metabolomic platforms to 228 tumors (212 GBM and 16 grade 4 IDH-mutant astrocytoma), including 28 at recurrence, plus 18 normal brain samples and 14 brain metastases as comparators, reveals heterogeneous upstream alterations converging on common downstream events at the proteomic and metabolomic levels and changes in protein-protein interactions and glycosylation site occupancy at recurrence. Recurrent genetic alterations and phosphorylation events on PTPN11 map to important regulatory domains in three dimensions, suggesting a central role for PTPN11 signaling across high-grade gliomas.

Unraveling genomic features and phylogenomics through the analysis of three Mexican endemic Myotis genomes

Background

Genomic resource development for non-model organisms is rapidly progressing, seeking to uncover molecular mechanisms and evolutionary adaptations enabling thriving in diverse environments. Limited genomic data for bat species hinder insights into their evolutionary processes, particularly within the diverse Myotis genus of the Vespertilionidae family. In Mexico, 15 Myotis species exist, with three-M. vivesi, M. findleyi, and M. planiceps-being endemic and of conservation concern.

Methods

We obtained samples of Myotis vivesi, M. findleyi, and M. planiceps for genomic analysis. Each of three genomic DNA was extracted, sequenced, and assembled. The scaffolding was carried out utilizing the M. yumanensis genome via a genome-referenced approach within the ntJoin program. GapCloser was employed to fill gaps. Repeat elements were characterized, and gene prediction was done via ab initio and homology methods with MAKER pipeline. Functional annotation involved InterproScan, BLASTp, and KEGG. Non-coding RNAs were annotated with INFERNAL, and tRNAscan-SE. Orthologous genes were clustered using Orthofinder, and a phylogenomic tree was reconstructed using IQ-TREE.

Results

We present genome assemblies of these endemic species using Illumina NovaSeq 6000, each exceeding 2.0 Gb, with over 90% representing single-copy genes according to BUSCO analyses. Transposable elements, including LINEs and SINEs, constitute over 30% of each genome. Helitrons, consistent with Vespertilionids, were identified. Values around 20,000 genes from each of the three assemblies were derived from gene annotation and their correlation with specific functions. Comparative analysis of orthologs among eight Myotis species revealed 20,820 groups, with 4,789 being single copy orthogroups. Non-coding RNA elements were annotated. Phylogenomic tree analysis supported evolutionary chiropterans' relationships. These resources contribute significantly to understanding gene evolution, diversification patterns, and aiding conservation efforts for these endangered bat species.

ProtVar: mapping and contextualizing human missense variation

Genomic variation can impact normal biological function in complex ways and so understanding variant effects requires a broad range of data to be coherently assimilated. Whilst the volume of human variant data and relevant annotations has increased, the corresponding increase in the breadth of participating fields, standards and versioning mean that moving between genomic, coding, protein and structure positions is increasingly complex. In turn this makes investigating variants in diverse formats and assimilating annotations from different resources challenging. ProtVar addresses these issues to facilitate the contextualization and interpretation of human missense variation with unparalleled flexibility and ease of accessibility for use by the broadest range of researchers. By precalculating all possible variants in the human proteome it offers near instantaneous mapping between all relevant data types. It also combines data and analyses from a plethora of resources to bring together genomic, protein sequence and function annotations as well as structural insights and predictions to better understand the likely effect of missense variation in humans. It is offered as an intuitive web server https://www.ebi.ac.uk/protvar where data can be explored and downloaded, and can be accessed programmatically via an API.

Identification of intracellular bacteria from multiple single-cell RNA-seq platforms using CSI-Microbes

The study of the tumor microbiome has been garnering increased attention. We developed a computational pipeline (CSI-Microbes) for identifying microbial reads from single-cell RNA sequencing (scRNA-seq) data and for analyzing differential abundance of taxa. Using a series of controlled experiments and analyses, we performed the first systematic evaluation of the efficacy of recovering microbial unique molecular identifiers by multiple scRNA-seq technologies, which identified the newer 10x chemistries (3' v3 and 5') as the best suited approach. We analyzed patient esophageal and colorectal carcinomas and found that reads from distinct genera tend to co-occur in the same host cells, testifying to possible intracellular polymicrobial interactions. Microbial reads are disproportionately abundant within myeloid cells that up-regulate proinflammatory cytokines like IL1Β and CXCL8, while infected tumor cells up-regulate antigen processing and presentation pathways. These results show that myeloid cells with bacteria engulfed are a major source of bacterial RNA within the tumor microenvironment (TME) and may inflame the TME and influence immunotherapy response.

SynDesign: web-based prime editing guide RNA design and evaluation tool for saturation genome editing

Saturation genome editing (SGE) enables in-depth functional evaluation of disease-associated genes and variants by generating all possible single nucleotide variants (SNVs) within a given coding region. Although prime editing can be employed for inducing these SNVs, designing efficient prime editing guide RNAs (pegRNAs) can be challenging and time-consuming. Here, we present SynDesign, an easy-to-use webtool for the design, evaluation, and construction precision pegRNA libraries for SGE with synonymous mutation markers. SynDesign offers a simple yet powerful interface that automates the generation of all feasible pegRNA designs for a target gene or variant of interest. The pegRNAs are selected using the state-of-the-art models to predict prime editing efficiencies for various prime editors and cell types. Top-scoring pegRNA designs are further enhanced using synonymous mutation markers which improve pegRNA efficiency by diffusing the cellular mismatch repair mechanism and serve as sequence markers for improved identification of intended edits following deep sequencing. SynDesign is expected to facilitate future research using SGE to investigate genes or variants of interest associated with human diseases. SynDesign is freely available at https://deepcrispr.info/SynDesign without a login process.

Exploring and retrieving sequence and metadata for species across the tree of life with NCBI Datasets

To explore complex biological questions, it is often necessary to access various data types from public data repositories. As the volume and complexity of biological sequence data grow, public repositories face significant challenges in ensuring that the data is easily discoverable and usable by the biological research community. To address these challenges, the National Center for Biotechnology Information (NCBI) has created NCBI Datasets. This resource provides straightforward, comprehensive, and scalable access to biological sequences, annotations, and metadata for a wide range of taxa. Following the FAIR (Findable, Accessible, Interoperable, and Reusable) data management principles, NCBI Datasets offers user-friendly web interfaces, command-line tools, and documented APIs, empowering researchers to access NCBI data seamlessly. The data is delivered as packages of sequences and metadata, thus facilitating improved data retrieval, sharing, and usability in research. Moreover, this data delivery method fosters effective data attribution and promotes its further reuse. This paper outlines the current scope of data accessible through NCBI Datasets and explains various options for exploring and downloading the data.

Adaptive adjustment of significance thresholds produces large gains in microbial gene annotations and metabolic insights

Gene function annotations enable microbial ecologists to make inferences about metabolic potential from genomes and metagenomes. However, even tools that use the same database and general approach can differ markedly in the annotations they recover. We compare three popular methods for identifying KEGG Orthologs, applying them to genomes drawn from a range of bacterial families that occupy different host-associated and free-living biomes. Our results show that by adaptively tuning sequence similarity thresholds, sensitivity can be substantially improved while maintaining accuracy. We observe the largest improvements when few reference sequences exist for a given protein family, and when annotating genomes from non-model organisms (such as gut-dwelling Lachnospiraceae). Our results suggest that straightforward heuristic adjustments can broadly improve microbial metabolic predictions.

Gene Set Summarization Using Large Language Models

Molecular biologists frequently interpret gene lists derived from high-throughput experiments and computational analysis. This is typically done as a statistical enrichment analysis that measures the over- or under-representation of biological function terms associated with genes or their properties, based on curated assertions from a knowledge base (KB) such as the Gene Ontology (GO). Interpreting gene lists can also be framed as a textual summarization task, enabling Large Language Models (LLMs) to use scientific texts directly and avoid reliance on a KB. TALISMAN (Terminological ArtificiaL Intelligence SuMmarization of Annotation and Narratives) uses generative AI to perform gene set function summarization as a complement to standard enrichment analysis. This method can use different sources of gene functional information: (1) structured text derived from curated ontological KB annotations, (2) ontology-free narrative gene summaries, or (3) direct retrieval from the model. We demonstrate that these methods are able to generate plausible and biologically valid summary GO term lists for an input gene set. However, LLM-based approaches are unable to deliver reliable scores or p-values and often return terms that are not statistically significant. Crucially, in our experiments these methods were rarely able to recapitulate the most precise and informative term from standard enrichment analysis. We also observe minor differences depending on prompt input information, with GO term descriptions leading to higher recall but lower precision. However, newer LLM models perform statistically significantly better than the oldest model across all performance metrics, suggesting that future models may lead to further improvements. Overall, the results are nondeterministic, with minor variations in prompt resulting in radically different term lists, true to the stochastic nature of LLMs. Our results show that at this point, LLM-based methods are unsuitable as a replacement for standard term enrichment analysis, however they may provide summarization benefits for implicit knowledge integration across extant but unstandardized knowledge, for large sets of features, and where the amount of information is difficult for humans to process.

Structural basis for transcription activation through cooperative recruitment of MntR

The manganese transport regulator (MntR) from B. subtilis is a dual regulatory protein that responds to heightened Mn 2+ availability in the cell by both repressing the expression of uptake transporters and activating the expression of efflux proteins. Recent work indicates that, in its role as an activator, MntR binds several sites upstream of the genes encoding Mn 2+ exporters, leading to a cooperative response to manganese. Here, we use cryo-EM to explore the molecular basis of gene activation by MntR and report a structure of four MntR dimers bound to four 18-base pair sites across an 84-base pair regulatory region of the mneP promoter. Our structures, along with solution studies including mass photometry and in vivo transcription assays, reveal that MntR dimers employ polar and non-polar contacts to bind cooperatively to an array of low-affinity DNA-binding sites. These results reveal the molecular basis for cooperativity in the activation of manganese efflux.

Following the Evolutionary Paths of Dscam1 Proteins toward Highly Specific Homophilic Interactions

Many adhesion proteins, evolutionarily related through gene duplication, exhibit distinct and precise interaction preferences and affinities crucial for cell patterning. Yet, the evolutionary paths by which these proteins acquire new specificities and prevent cross-interactions within their family members remain unknown. To bridge this gap, this study focuses on Drosophila Down syndrome cell adhesion molecule-1 (Dscam1) proteins, which are cell adhesion proteins that have undergone extensive gene duplication. Dscam1 evolved under strong selective pressure to achieve strict homophilic recognition, essential for neuronal self-avoidance and patterning. Through a combination of phylogenetic analyses, ancestral sequence reconstruction, and cell aggregation assays, we studied the evolutionary trajectory of Dscam1 exon 4 across various insect lineages. We demonstrated that recent Dscam1 duplications in the mosquito lineage bind with strict homophilic specificities without any cross-interactions. We found that ancestral and intermediate Dscam1 isoforms maintained their homophilic binding capabilities, with some intermediate isoforms also engaging in promiscuous interactions with other paralogs. Our results highlight the robust selective pressure for homophilic specificity integral to the Dscam1 function within the process of neuronal self-avoidance. Importantly, our study suggests that the path to achieving such selective specificity does not introduce disruptive mutations that prevent self-binding but includes evolutionary intermediates that demonstrate promiscuous heterophilic interactions. Overall, these results offer insights into evolutionary strategies that underlie adhesion protein interaction specificities.

Key co-expressed genes correlated with blood serum parameters of pigs fed with different fatty acid profile diets

This study investigated how gene expression is affected by dietary fatty acids (FA) by using pigs as a reliable model for studying human diseases that involve lipid metabolism. This includes changes in FA composition in the liver, blood serum parameters and overall metabolic pathways. RNA-Seq data from 32 pigs were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA). Our aim was to identify changes in blood serum parameters and gene expression between diets containing 3% soybean oil (SOY3.0) and a standard pig production diet containing 1.5% soybean oil (SOY1.5). Significantly, both the SOY1.5 and SOY3.0 groups showed significant modules, with a higher number of co-expressed modules identified in the SOY3.0 group. Correlated modules and specific features were identified, including enriched terms and pathways such as the histone acetyltransferase complex, type I diabetes mellitus pathway, cholesterol metabolism, and metabolic pathways in SOY1.5, and pathways related to neurodegeneration and Alzheimer's disease in SOY3.0. The variation in co-expression observed for HDL in the groups analyzed suggests different regulatory patterns in response to the higher concentration of soybean oil. Key genes co-expressed with metabolic processes indicative of diseases such as Alzheimer's was also identified, as well as genes related to lipid transport and energy metabolism, including CCL5, PNISR, DEGS1. These findings are important for understanding the genetic and metabolic responses to dietary variation and contribute to the development of more precise nutritional strategies.

Draft genome sequences of Weissella cibaria GM93m3, a promising probiotic strain from raw goat milk

The draft genome of a previously documented potential probiotic Weissella cibaria strain GM93m3 from raw goat milk in Nigeria is reported. The total genome size was 2,447,229 with 46 contigs and G+C content of 44.86%.

Sirenian genomes illuminate the evolution of fully aquatic species within the mammalian superorder afrotheria

Sirenians of the superorder Afrotheria were the first mammals to transition from land to water and are the only herbivorous marine mammals. Here, we generated a chromosome-level dugong (Dugong dugon) genome. A comparison of our assembly with other afrotherian genomes reveals possible molecular adaptations to aquatic life by sirenians, including a shift in daily activity patterns (circadian clock) and tolerance to a high-iodine plant diet mediated through changes in the iodide transporter NIS (SLC5A5) and its co-transporters. Functional in vitro assays confirm that sirenian amino acid substitutions alter the properties of the circadian clock protein PER2 and NIS. Sirenians show evidence of convergent regression of integumentary system (skin and its appendages) genes with cetaceans. Our analysis also uncovers gene losses that may be maladaptive in a modern environment, including a candidate gene (KCNK18) for sirenian cold stress syndrome likely lost during their evolutionary shift in daily activity patterns. Genomes from nine Australian locations and the functionally extinct Okinawan population confirm and date a genetic break ~10.7 thousand years ago on the Australian east coast and provide evidence of an associated ecotype, and highlight the need for whole-genome resequencing data from dugong populations worldwide for conservation and genetic management.

Survival strategies of aerobic methanotrophs under hypoxia in methanogenic lake sediments

BACKGROUND

Microbial methane oxidation, methanotrophy, plays a crucial role in mitigating the release of the potent greenhouse gas methane from aquatic systems. While aerobic methanotrophy is a well-established process in oxygen-rich environments, emerging evidence suggests their activity in hypoxic conditions. However, the adaptability of these methanotrophs to such environments has remained poorly understood. Here, we explored the genetic adaptability of aerobic methanotrophs to hypoxia in the methanogenic sediments of Lake Kinneret (LK). These LK methanogenic sediments, situated below the oxidic and sulfidic zones, were previously characterized by methane oxidation coupled with iron reduction via the involvement of aerobic methanotrophs.

RESULTS

In order to explore the adaptation of the methanotrophs to hypoxia, we conducted two experiments using LK sediments as inoculum: (i) an aerobic "classical" methanotrophic enrichment with ambient air employing DNA stable isotope probing (DNA-SIP) and (ii) hypoxic methanotrophic enrichment with repeated spiking of 1% oxygen. Analysis of 16S rRNA gene amplicons revealed the enrichment of Methylococcales methanotrophs, being up to a third of the enriched community. Methylobacter, Methylogaea, and Methylomonas were prominent in the aerobic experiment, while hypoxic conditions enriched primarily Methylomonas. Using metagenomics sequencing of DNA extracted from these experiments, we curated five Methylococcales metagenome-assembled genomes (MAGs) and evaluated the genetic basis for their survival in hypoxic environments. A comparative analysis with an additional 62 Methylococcales genomes from various environments highlighted several core genetic adaptations to hypoxia found in most examined Methylococcales genomes, including high-affinity cytochrome oxidases, oxygen-binding proteins, fermentation-based methane oxidation, motility, and glycogen use. We also found that some Methylococcales, including LK Methylococcales, may denitrify, while metals and humic substances may also serve as electron acceptors alternative to oxygen. Outer membrane multi-heme cytochromes and riboflavin were identified as potential mediators for the utilization of metals and humic material. These diverse mechanisms suggest the ability of methanotrophs to thrive in ecological niches previously thought inhospitable for their growth.

CONCLUSIONS

Our study sheds light on the ability of enriched Methylococcales methanotrophs from methanogenic LK sediments to survive under hypoxia. Genomic analysis revealed a spectrum of genetic capabilities, potentially enabling these methanotrophs to function. The identified mechanisms, such as those enabling the use of alternative electron acceptors, expand our understanding of methanotroph resilience in diverse ecological settings. These findings contribute to the broader knowledge of microbial methane oxidation and have implications for understanding and potential contribution methanotrophs may have in mitigating methane emissions in various environmental conditions.

Emergence of a clinical Klebsiella pneumoniae harboring an acrAB-tolC in chromosome and carrying the two repetitive tandem core structures for bla KPC-2 and bla CTX-M-65 in a plasmid

Objective

The emergence of clinical Klebsiella pneumoniae strains harboring acrAB-tolC genes in the chromosome, along with the presence of two repetitive tandem core structures for bla KPC-2 and bla CTX-M-65 genes on a plasmid, has presented a significant clinical challenge.

Methods

In order to study the detailed genetic features of K. pneumoniae strain SC35, both the bacterial chromosome and plasmids were sequenced using Illumina and nanopore platforms. Furthermore, bioinformatics methods were employed to analyze the mobile genetic elements associated with antibiotic resistance genes.

Results

K. pneumoniae strain SC35 was found to possess a class A beta-lactamase and demonstrated resistance to all tested antibiotics. This resistance was attributed to the presence of efflux pump genes, specifically acrAB-tolC, on the SC35 chromosome. Additionally, the SC35 plasmid p1 carried the two repetitive tandem core structures for bla KPC-2 and bla CTX-M-65, as well as bla TEM-1 with rmtB, which shared overlapping structures with mobile genetic elements as In413, Tn3, and TnAs3. Through plasmid transfer assays, it was determined that the SC35 plasmid p1 could be successfully transferred with an average conjugation frequency of 6.85 × 10-4.

Conclusion

The structure of the SC35 plasmid p1 appears to have evolved in correlation with other plasmids such as pKPC2_130119, pDD01754-2, and F4_plasmid pA. The infectious strain SC35 exhibits no susceptibility to tested antibioticst, thus effective measures should be taken to prevent the spread and epidemic of this strain.

Pathogens of the oak processionary moth Thaumetopoea processionea: Developing a user-friendly bioassay system and metagenome analyses for microorganisms

The oak processionary moth (OPM) Thaumetopoea processionea is a pest of oak trees and poses health risks to humans due to the urticating setae of later instar larvae. For this reason, it is difficult to rear OPM under laboratory conditions, carry out bioassays or examine larvae for pathogens. Biological control targets the early larval instars and is based primarily on commercial preparations of Bacillus thuringiensis ssp. kurstaki (Btk). To test the entomopathogenic potential of other spore-forming bacteria, a user-friendly bioassay system was developed that (i) applies bacterial spore suspensions by oak bud dipping, (ii) targets first instar larvae through feeding exposure and (iii) takes into account their group-feeding behavior. A negligible mortality in the untreated control proved the functionality of the newly established bioassay system. Whereas the commercial Btk HD-1 strain was used as a bioassay standard and confirmed as being highly efficient, a Bacillus wiedmannii strain was ineffective in killing OPM larvae. Larvae, which died during the infection experiment, were further subjected to Nanopore sequencing for a metagenomic approach for entomopathogen detection. It further corroborated that B.wiedmannii was not able to infect and establish in OPM, but identified potential insect pathogenic species from the genera Serratia and Pseudomonas.

ABCB1-mediated docetaxel resistance reversed by erastin in prostate cancer

Docetaxel (Doc) currently serves as the primary first-line treatment for patients with castrate-resistant prostate cancer (CRPC). Erastin, a small molecule compound, can trigger inhibition of the cystine-glutamate reverse transport system and other pathways, leading to iron-dependent cell death (ferroptosis). Beyond its role in inducing cancer cell death, erastin demonstrates potential when combined with chemotherapy drugs to heighten cancer cell drug susceptibility. However, the augmentation by erastin of the effects of Doc treatment on prostate cancer, and the underlying mechanisms involved, remain unclear. In the present study, we determined the role and the underlying molecular mechanism of erastin against CRPC. The results showed that CRPC cell lines were resistant to Doc, and the expression of ferroptosis-related factors in drug-resistant cell lines was downregulated. Erastin, in synergy with Doc, exerts a pro-apoptotic effect. Erastin significantly inhibited the activity of ATP-binding cassette subfamily B member 1 (ABCB1) but did not change its protein expression and localization. Finally, in mice, erastin treatment dramatically reduced tumor growth in vivo. Taken together, our findings demonstrate that erastin enhances Doc-induced apoptosis to a certain extent and reverses Doc resistance in prostate cancer by inhibiting the activity of multidrug-resistant protein ABCB1.

Deep-time phylogenetic inference by paleoproteomic analysis of dental enamel

In temperate and subtropical regions, ancient proteins are reported to survive up to about 2 million years, far beyond the known limits of ancient DNA preservation in the same areas. Accordingly, their amino acid sequences currently represent the only source of genetic information available to pursue phylogenetic inference involving species that went extinct too long ago to be amenable for ancient DNA analysis. Here we present a complete workflow, including sample preparation, mass spectrometric data acquisition and computational analysis, to recover and interpret million-year-old dental enamel protein sequences. During sample preparation, the proteolytic digestion step, usually an integral part of conventional bottom-up proteomics, is omitted to increase the recovery of the randomly degraded peptides spontaneously generated by extensive diagenetic hydrolysis of ancient proteins over geological time. Similarly, we describe other solutions we have adopted to (1) authenticate the endogenous origin of the protein traces we identify, (2) detect and validate amino acid variation in the ancient protein sequences and (3) attempt phylogenetic inference. Sample preparation and data acquisition can be completed in 3-4 working days, while subsequent data analysis usually takes 2-5 days. The workflow described requires basic expertise in ancient biomolecules analysis, mass spectrometry-based proteomics and molecular phylogeny. Finally, we describe the limits of this approach and its potential for the reconstruction of evolutionary relationships in paleontology and paleoanthropology.

Understanding bacterial pathogen diversity: A proteogenomic analysis and use of an array of genome assemblies to identify novel virulence factors of the honey bee bacterial pathogen Paenibacillus larvae

Mass spectrometry proteomics data are typically evaluated against publicly available annotated sequences, but the proteogenomics approach is a useful alternative. A single genome is commonly utilized in custom proteomic and proteogenomic data analysis. We pose the question of whether utilizing numerous different genome assemblies in a search database would be beneficial. We reanalyzed raw data from the exoprotein fraction of four reference Enterobacterial Repetitive Intergenic Consensus (ERIC) I-IV genotypes of the honey bee bacterial pathogen Paenibacillus larvae and evaluated them against three reference databases (from NCBI-protein, RefSeq, and UniProt) together with an array of protein sequences generated by six-frame direct translation of 15 genome assemblies from GenBank. The wide search yielded 453 protein hits/groups, which UpSet analysis categorized into 50 groups based on the success of protein identification by the 18 database components. Nine hits that were not identified by a unique peptide were not considered for marker selection, which discarded the only protein that was not identified by the reference databases. We propose that the variability in successful identifications between genome assemblies is useful for marker mining. The results suggest that various strains of P. larvae can exhibit specific traits that set them apart from the established genotypes ERIC I-V.

Virus ecology and 7-year temporal dynamics across a permafrost thaw gradient

Soil microorganisms are pivotal in the global carbon cycle, but the viruses that affect them and their impact on ecosystems are less understood. In this study, we explored the diversity, dynamics, and ecology of soil viruses through 379 metagenomes collected annually from 2010 to 2017. These samples spanned the seasonally thawed active layer of a permafrost thaw gradient, which included palsa, bog, and fen habitats. We identified 5051 virus operational taxonomic units (vOTUs), doubling the known viruses for this site. These vOTUs were largely ephemeral within habitats, suggesting a turnover at the vOTU level from year to year. While the diversity varied by thaw stage and depth-related patterns were specific to each habitat, the virus communities did not significantly change over time. The abundance ratios of virus to host at the phylum level did not show consistent trends across the thaw gradient, depth, or time. To assess potential ecosystem impacts, we predicted hosts in silico and found viruses linked to microbial lineages involved in the carbon cycle, such as methanotrophy and methanogenesis. This included the identification of viruses of Candidatus Methanoflorens, a significant global methane contributor. We also detected a variety of potential auxiliary metabolic genes, including 24 carbon-degrading glycoside hydrolases, six of which are uniquely terrestrial. In conclusion, these long-term observations enhance our understanding of soil viruses in the context of climate-relevant processes and provide opportunities to explore their role in terrestrial carbon cycling.

The endometrial transcriptome of infertile women with and without implantation failure

INTRODUCTION

Implantation failure after transferring morphologically "good-quality" embryos in in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) may be explained by impaired endometrial receptivity. Analyzing the endometrial transcriptome analysis may reveal the underlying processes and could help in guiding prognosis and using targeted interventions for infertility. This exploratory study investigated whether the endometrial transcriptome profile was associated with short-term or long-term implantation outcomes (ie success or failure).

MATERIAL AND METHODS

Mid-luteal phase endometrial biopsies of 107 infertile women with one full failed IVF/ICSI cycle, obtained within an endometrial scratching trial, were subjected to RNA-sequencing and differentially expressed genes analysis with covariate adjustment (age, body mass index, luteinizing hormone [LH]-day). Endometrial transcriptomes were compared between implantation failure and success groups in the short term (after the second fresh IVF/ICSI cycle) and long term (including all fresh and frozen cycles within 12 months). The short-term analysis included 85/107 women (33 ongoing pregnancy vs 52 no pregnancy), excluding 22/107 women. The long-term analysis included 46/107 women (23 'fertile' group, ie infertile women with a live birth after ≤3 embryos transferred vs 23 recurrent implantation failure group, ie no live birth after ≥3 good quality embryos transferred), excluding 61/107 women not fitting these categories. As both analyses drew from the same pool of 107 samples, there was some sample overlap. Additionally, cell type enrichment scores and endometrial receptivity were analyzed, and an endometrial development pseudo-timeline was constructed to estimate transcriptomic deviations from the optimum receptivity day (LH + 7), denoted as ΔWOI (window of implantation).

RESULTS

There were no significantly differentially expressed genes between implantation failure and success groups in either the short-term or long-term analyses. Principal component analysis initially showed two clusters in the long-term analysis, unrelated to clinical phenotype and no longer distinct following covariate adjustment. Cell type enrichment scores did not differ significantly between groups in both analyses. However, endometrial receptivity analysis demonstrated a potentially significant displacement of the WOI in the non-pregnant group compared with the ongoing pregnant group in the short-term analysis.

CONCLUSIONS

No distinct endometrial transcriptome profile was associated with either implantation failure or success in infertile women. However, there may be differences in the extent to which the WOI is displaced.

Genetic Risk Loci and Familial Associations in Migraine: A Genome-Wide Association Study in the Han Chinese Population of Taiwan

BACKGROUND AND PURPOSE

Migraine is a condition that is often observed to run in families, but its complex genetic background remains unclear. This study aimed to identify the genetic factors influencing migraines and their potential association with the family medical history.

METHODS

We performed a comprehensive genome-wide association study of a cohort of 1,561 outpatients with migraine and 473 individuals without migraine in Taiwan, including Han Chinese individuals with or without a family history of migraine. By analyzing the detailed headache history of the patients and their relatives we aimed to isolate potential genetic markers associated with migraine while considering factors such as sex, episodic vs. chronic migraine, and the presence of aura.

RESULTS

We revealed novel genetic risk loci, including rs2287637 in DEAD-Box helicase 1 and long intergenic non-protein coding RNA 1804 and rs12055943 in engulfment and cell motility 1, that were correlated with the family history of migraine. We also found a genetic location downstream of mesoderm posterior BHLH transcription factor 2 associated with episodic migraine, whereas loci within the ubiquitin-specific peptidase 26 exonic region, dual specificity phosphatase 9 and pregnancy-upregulated non-ubiquitous CaM kinase intergenic regions, and poly (ADP-ribose) polymerase 1 and STUM were linked to chronic migraine. We additionally identified genetic regionsassociated with the presence or absence of aura. A locus between LINC02561 and urocortin 3 was predominantly observed in female patients. Moreover, three different single-nucleotide polymorphisms were associated with the family history of migraine in the control group.

CONCLUSIONS

This study has identified new genetic locations associated with migraine and its family history in a Han Chinese population, reinforcing the genetic background of migraine. The findings point to potential candidate genes that should be investigated further.

Korean urobiome platform (KUROM) study for acute uncomplicated sporadic versus recurrent cystitis in women: Clinical significance

PURPOSE

To investigate urine microbiome differences among healthy women, women with recurrent uncomplicated cystitis (rUC), and those with sporadic/single uncomplicated cystitis (sUC) to challenge traditional beliefs about origins of these infections.

MATERIALS AND METHODS

Patients who underwent both conventional urine culture and next-generation sequencing (NGS) of urine were retrospectively reviewed. Symptom-free women with normal urinalysis results as a control group were also studied. Samples were collected via transurethral catheterization.

RESULTS

In the control group, urine microbiome was detected on NGS in 83.3%, with Lactobacillus and Prevotella being the most abundant genera. The sensitivity of urine NGS was significantly higher than that of conventional urine culture in both the sUC group (91.2% vs. 32.4%) and the rUC group (82.4% vs. 16.4%). In urine NGS results, Enterobacterales, Prevotella, and Escherichia/Shigella were additionally found in the sUC group, while the recurrent urinary tract infection (rUTI)/rUC group exhibited the presence of Lactobacillus, Prevotella, Enterobacterales, Escherichia/Shigella, and Propionibacterium. Moreover, distinct patterns of urine NGS were observed based on menopausal status and ingestion of antibiotics or probiotics prior to NGS test sampling.

CONCLUSIONS

Urine microbiomes in control, sUC, and rUTI/rUC groups exhibited distinct characteristics. Notably, sUC and rUC might represent entirely separate pathological processes, given their distinct urine microbiomes. Consequently, the use of urine NGS might be essential to enhancing sensitivity compared to conventional urine culture in both sUC and rUTI/rUC groups.

Splice variants of CK1α and CK1α-like: Comparative analysis of subcellular localization, kinase activity, and function in the Wnt signaling pathway

Members of the casein kinase 1 (CK1) family are important regulators of multiple signaling pathways. CK1α is a well-known negative regulator of the Wnt/β-catenin pathway, which promotes the degradation of β-catenin via its phosphorylation of Ser45. In contrast, the closest paralog of CK1α, CK1α-like, is a poorly characterized kinase of unknown function. In this study, we show that the deletion of CK1α, but not CK1α-like, resulted in a strong activation of the Wnt/β-catenin pathway. Wnt-3a treatment further enhanced the activation, which suggests there are at least two modes, a CK1α-dependent and Wnt-dependent, of β-catenin regulation. Rescue experiments showed that only two out of ten naturally occurring splice CK1α/α-like variants were able to rescue the augmented Wnt/β-catenin signaling caused by CK1α deficiency in cells. Importantly, the ability to phosphorylate β-catenin on Ser45 in the in vitro kinase assay was required but not sufficient for such rescue. Our compound CK1α and GSK3α/β KO models suggest that the additional nonredundant function of CK1α in the Wnt pathway beyond Ser45-β-catenin phosphorylation includes Axin phosphorylation. Finally, we established NanoBRET assays for the three most common CK1α splice variants as well as CK1α-like. Target engagement data revealed comparable potency of known CK1α inhibitors for all CK1α variants but not for CK1α-like. In summary, our work brings important novel insights into the biology of CK1α, including evidence for the lack of redundancy with other CK1 kinases in the negative regulation of the Wnt/β-catenin pathway at the level of β-catenin and Axin.

Integrative analysis of ultra-deep RNA-seq reveals alternative promoter usage as a mechanism of activating oncogenic programmes during prostate cancer progression

Transcription factor (TF) proteins regulate gene activity by binding to regulatory regions, most importantly at gene promoters. Many genes have alternative promoters (APs) bound by distinct TFs. The role of differential TF activity at APs during tumour development is poorly understood. Here we show, using deep RNA sequencing in 274 biopsies of benign prostate tissue, localized prostate tumours and metastatic castration-resistant prostate cancer, that AP usage increases as tumours progress and APs are responsible for a disproportionate amount of tumour transcriptional activity. Expression of the androgen receptor (AR), the key driver of prostate tumour activity, is correlated with elevated AP usage. We identified AR, FOXA1 and MYC as potential drivers of AP activation. DNA methylation is a likely mechanism for AP activation during tumour progression and lineage plasticity. Our data suggest that prostate tumours activate APs to magnify the transcriptional impact of tumour drivers, including AR and MYC.

Characterization of the transcriptional effects of the plastic additive dibutyl phthalate alone and in combination with microplastic on the green-lipped mussel Perna canaliculus

The presence and persistence of microplastics (MPs) in diverse aquatic environments are of global concern. Microplastics can impact marine organisms via direct physical interaction and the release of potentially harmful chemical additives incorporated into the plastic. These chemicals are physically bound to the plastic matrix and can leach out. The hazards associated with chemical additives to exposed organisms is not well characterized. We investigated the hazards of plastic additives leaching from plastic. We used the common plasticizer dibutyl phthalate (DBP) as a chemical additive proxy and the New Zealand green-lipped mussel (Perna canaliculus) as a model. We used early-adult P. canaliculus exposed to combinations of virgin and DBP-spiked polyvinyl chloride (PVC), MPs, and DBP alone for 7 days. Whole transcriptome sequencing (RNA-seq) was conducted to assess whether leaching of DBP from MPs poses a hazard. The differences between groups were evaluated using pairwise permutational multivariate analysis of variance (PERMANOVA), and all treatments were significantly different from controls. In addition, a significant difference was seen between DBP and PVC MP treatment. Transcriptome analysis revealed that mussels exposed to DBP alone had the most differentially expressed genes (914), followed by PVC MP + DBP (448), and PVC MP (250). Gene ontology functional analysis revealed that the most enriched pathway types were in cellular metabolism, immune response, and endocrine disruption. Microplastic treatments enriched numerous pathways related to cellular metabolism and immune response. The combined exposure of PVC MP + DBP appears to cause combined effects, suggesting that DBP is bioavailable to the exposed mussels in the PVC MP + DBP treatment. Our results support the hypothesis that chemical additives are potentially an important driver of MP toxicity. Environ Toxicol Chem 2024;43:1604-1614. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Toll-like receptor 7: A novel neuroimmune target to reduce excessive alcohol consumption

Toll-like receptors (TLRs) are a family of innate immune receptors that recognize molecular patterns in foreign pathogens and intrinsic danger/damage signals from cells. TLR7 is a nucleic acid sensing endosomal TLR that is activated by single-stranded RNAs from microbes or by small noncoding RNAs that act as endogenous ligands. TLR7 signals through the MyD88 adaptor protein and activates the transcription factor interferon regulatory factor 7 (IRF7). TLR7 is found throughout the brain and is highly expressed in microglia, the main immune cells of the brain that have also been implicated in alcohol drinking in mice. Upregulation of TLR7 mRNA and protein has been identified in postmortem hippocampus and cortex from AUD subjects that correlated positively with lifetime consumption of alcohol. Similarly, Tlr7 and downstream signaling genes were upregulated in rat hippocampal and cortical slice cultures after chronic alcohol exposure and in these regions after chronic binge-like alcohol treatment in mice. In addition, repeated administration of the synthetic TLR7 agonists imiquimod (R837) or resiquimod (R848) increased voluntary alcohol drinking in different rodent models and produced sustained upregulation of IRF7 in the brain. These findings suggest that chronic TLR7 activation may drive excessive alcohol drinking. In the brain, this could occur through increased levels of endogenous TLR7 activators, like microRNAs and Y RNAs. This review explores chronic TLR7 activation as a pathway of dysregulated neuroimmune signaling in AUD and the endogenous small RNA ligands in the brain that could perpetuate innate immune responses and escalate alcohol drinking.