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Abstract Background New treatments are needed for people with treatment-resistant depression (TRD), who do not benefit from anti-depressants and many of whom do not recover fully with psychological treatments. The Community Navigator programme was co-produced with service users and practitioners. It is a novel social intervention which aims to reduce loneliness and thus improve health outcomes for people with TRD. Participants receive up to 10 individual meetings with a Community Navigator, who helps them to map their social world and set and enact goals to enhance their social connections and reduce loneliness. Participants may also access group meet-ups with others in the programme every 2 months, and may be offered modest financial support to enable activities to support social connections. Methods A researcher-blind, multi-site, 1:1 randomised controlled trial with N = 306 participants will test the effectiveness of the Community Navigator programme for people with TRD in secondary community mental health teams (CMHTs). Our primary hypothesis is that people who are offered the Community Navigator programme as an addition to usual CMHT care will be less depressed, assessed using the PHQ-9 self-report measure, at 8-month, end-of-treatment follow-up, compared to a control group receiving usual CMHT care and a booklet with information about local social groups and activities. We will follow participants up at end-of-treatment and at 14 months, 6 months after end-of-treatment follow-up. Secondary outcomes include the following: loneliness, anxiety, personal recovery, self-efficacy, social network, social identities. We will collect data about health-related quality of life and service use to investigate the cost-effectiveness of the Community Navigator programme. Discussion This trial will provide definitive evidence about the effectiveness and cost-effectiveness of the Community Navigator programme and whether it can be recommended for use in practice. The trial is due to finish in August 2025. Trial registration Prospectively registered on 8th July 2022 at: ISRCTN13205972.

ABSTRACTAnalyzing microbial genomes has become an essential part of microbiology research, giving valuable insights into the functions and evolution of microbial species. Identifying genes of interest and assigning putative annotations to those genes is a central task in genome analysis, and a plethora of tools and approaches have been developed for this task. The ProkFunFind tool was developed to bridge the gap between these various annotation approaches, providing a flexible and customizable search approach to annotate microbial functions. ProkFunFind is designed around hierarchical definitions of biological functions, where individual genes can be identified using heterogeneous search terms consisting of sequences, profile hidden Markov models, protein domains, and orthology groups. This flexible and customizable search approach allows for searches to be tailored to specific biological functions, and the search results are output in multiple formats to facilitate downstream analyses. The utility of the ProkFunFind search tool was demonstrated through its application in searching for bacterial flagella, which are complex organelles composed of multiple genes. Overall, ProkFunFind provides an accessible and flexible way to integrate multiple types of annotation and sequence data while annotating biological functions in microbial genomes.IMPORTANCEGenome sequencing and analysis are increasingly important parts of microbiology, providing a way to predict metabolic functions, identify virulence factors, and understand the evolution of microbes. The expanded use of genome sequencing has also brought an abundance of search and annotation methods, but integrating the information from these different methods can be challenging and is often done through ad hoc approaches. To bridge the gap between different types of annotations, we developed ProkFunFind, a flexible and customizable search tool incorporating multiple search approaches and annotation types to annotate microbial functions. We demonstrated the utility of ProkFunFind by searching for gene clusters encoding flagellar genes using a combination of different annotation types and searches. Overall, ProkFunFind provides a reproducible and flexible way to identify gene clusters of interest, facilitating the meaningful analysis of new and existing microbial genomes.

Abstract Background Equol, an isoflavonoid metabolite with possible health benefits in humans, is known to be produced by some human gut bacteria. While the genes encoding the equol production pathway have been characterized in a few bacterial strains, a systematic analysis of the equol production pathway is currently lacking. Results This study presents an analysis of the taxonomic distribution and evolutionary history of the gene cluster encoding the equol production pathway. A survey for equol gene clusters within the Genome Taxonomy Database bacterial genomes and human gut metagenomes resulted in the identification of a highly conserved gene cluster found in nine bacterial species from the Eggerthellaceae family. The identified gene clusters from human gut metagenomes revealed potential variations in the equol gene cluster organization and gene content within the equol-producing Eggerthellaceae clades. Subsequent analysis showed that in addition to the four genes directly involved in equol production, multiple other genes were consistently found in the equol gene clusters. These genes were predicted to encode a putative electron transport complex and hydrogenase maturase system, suggesting potential roles for them in the equol production pathway. Analysis of the gene clusters and a phylogenetic reconstruction of a putative NAD kinase gene provided evidence of the recent transfer of the equol gene cluster from a basal Eggerthellaceae species to Slackia_A equolifaciens, Enteroscipio sp000270285, and Lactococcus garvieae 20–92. Conclusions This analysis demonstrates that the highly conserved equol gene cluster is taxonomically restricted to the Eggerthellaceae family of bacteria and provides evidence of the role of horizontal gene transfer in the evolutionary history of these genes. These results provide a foundation for future studies of equol production in the human gut and future efforts related to bioengineering and the use of equol-producing bacteria as probiotics.

ABSTRACT Microbial acclimation to different temperature conditions can involve broad changes in cell composition and metabolic efficiency. A systems-level view of these metabolic responses in nonmesophilic organisms, however, is currently missing. In this study, thermodynamically constrained genome-scale models were applied to simulate the metabolic responses of a deep-sea psychrophilic bacterium, Shewanella psychrophila WP2, under suboptimal (4°C), optimal (15°C), and supraoptimal (20°C) growth temperatures. The models were calibrated with experimentally determined growth rates of WP2. Gibbs free energy change of reactions (ΔrG′), metabolic fluxes, and metabolite concentrations were predicted using random simulations to characterize temperature-dependent changes in the metabolism. The modeling revealed the highest metabolic efficiency at the optimal temperature, and it suggested distinct patterns of ATP production and consumption that could lead to lower metabolic efficiency under suboptimal or supraoptimal temperatures. The modeling also predicted rearrangement of fluxes through multiple metabolic pathways, including the glycolysis pathway, Entner-Doudoroff pathway, tricarboxylic acid (TCA) cycle, and electron transport system, and these predictions were corroborated through comparisons to WP2 transcriptomes. Furthermore, predictions of metabolite concentrations revealed the potential conservation of reducing equivalents and ATP in the suboptimal temperature, consistent with experimental observations from other psychrophiles. Taken together, the WP2 models provided mechanistic insights into the metabolism of a psychrophile in response to different temperatures. IMPORTANCE Metabolic flexibility is a central component of any organism’s ability to survive and adapt to changes in environmental conditions. This study represents the first application of thermodynamically constrained genome-scale models in simulating the metabolic responses of a deep-sea psychrophilic bacterium to various temperatures. The models predicted differences in metabolic efficiency that were attributed to changes in metabolic pathway utilization and metabolite concentration during growth under optimal and nonoptimal temperatures. Experimental growth measurements were used for model calibration, and temperature-dependent transcriptomic changes corroborated the model-predicted rearrangement of metabolic fluxes. Overall, this study highlights the utility of modeling approaches in studying the temperature-driven metabolic responses of an extremophilic organism.

ABSTRACT Insertions in the SARS-CoV-2 genome have the potential to drive viral evolution, but the source of the insertions is often unknown. Recent proposals have suggested that human RNAs could be a source of some insertions, but the small size of many insertions makes this difficult to confirm. Through an analysis of available direct RNA sequencing data from SARS-CoV-2-infected cells, we show that viral-host chimeric RNAs are formed through what are likely stochastic RNA-dependent RNA polymerase template-switching events. Through an analysis of the publicly available GISAID SARS-CoV-2 genome collection, we identified two genomic insertions in circulating SARS-CoV-2 variants that are identical to regions of the human 18S and 28S rRNAs. These results provide direct evidence of the formation of viral-host chimeric sequences and the integration of host genetic material into the SARS-CoV-2 genome, highlighting the potential importance of host-derived insertions in viral evolution. IMPORTANCE Throughout the COVID-19 pandemic, the sequencing of SARS-CoV-2 genomes has revealed the presence of insertions in multiple globally circulating lineages of SARS-CoV-2, including the Omicron variant. The human genome has been suggested to be the source of some of the larger insertions, but evidence for this kind of event occurring is still lacking. Here, we leverage direct RNA sequencing data and SARS-CoV-2 genomes to show that host-viral chimeric RNAs are generated in infected cells and two large genomic insertions have likely been formed through the incorporation of host rRNA fragments into the SARS-CoV-2 genome. These host-derived insertions may increase the genetic diversity of SARS-CoV-2 and expand its strategies to acquire genetic material, potentially enhancing its adaptability, virulence, and spread.

Abstract Background Although native to North America, the invasion of the aphid-like grape phylloxera Daktulosphaira vitifoliae across the globe altered the course of grape cultivation. For the past 150 years, viticulture relied on grafting-resistant North American Vitis species as rootstocks, thereby limiting genetic stocks tolerant to other stressors such as pathogens and climate change. Limited understanding of the insect genetics resulted in successive outbreaks across the globe when rootstocks failed. Here we report the 294-Mb genome of D. vitifoliae as a basic tool to understand host plant manipulation, nutritional endosymbiosis, and enhance global viticulture. Results Using a combination of genome, RNA, and population resequencing, we found grape phylloxera showed high duplication rates since its common ancestor with aphids, but similarity in most metabolic genes, despite lacking obligate nutritional symbioses and feeding from parenchyma. Similarly, no enrichment occurred in development genes in relation to viviparity. However, phylloxera evolved > 2700 unique genes that resemble putative effectors and are active during feeding. Population sequencing revealed the global invasion began from the upper Mississippi River in North America, spread to Europe and from there to the rest of the world. Conclusions The grape phylloxera genome reveals genetic architecture relative to the evolution of nutritional endosymbiosis, viviparity, and herbivory. The extraordinary expansion in effector genes also suggests novel adaptations to plant feeding and how insects induce complex plant phenotypes, for instance galls. Finally, our understanding of the origin of this invasive species and its genome provide genetics resources to alleviate rootstock bottlenecks restricting the advancement of viticulture.

Abstract High‐throughput sequencing has become an increasingly central component of microbiome research. The development of de Bruijn graph‐based methods for assembling high‐throughput sequencing data has been an important part of the broader adoption of sequencing as part of biological studies. Recent advances in the construction and representation of de Bruijn graphs have led to new approaches that utilize the de Bruijn graph data structure to aid in different biological analyses. One type of application of these methods has been in alternative approaches to the assembly of sequencing data like gene‐targeted assembly, where only gene sequences are assembled out of larger metagenomes, and differential assembly, where sequences that are differentially present between two samples are assembled. de Bruijn graphs have also been applied for comparative genomics where they can be used to represent large sets of multiple genomes or metagenomes where structural features in the graphs can be used to identify variants, indels, and homologous regions in sequences. These de Bruijn graph‐based representations of sequencing data have even begun to be applied to whole sequencing databases for large‐scale searches and experiment discovery. de Bruijn graphs have played a central role in how high‐throughput sequencing data is worked with, and the rapid development of new tools that rely on these data structures suggests that they will continue to play an important role in biology in the future.

An amendment to this paper has been published and can be accessed via the original article.

Despite their biological and ecological significance, a mechanistic characterization of microbiome function is frequently missing from many nonmodel marine invertebrates. As an initial step toward filling this gap for the eastern oyster, Crassostrea virginica

The metabolism of individual organisms and biological communities can be viewed as a network of metabolites connected to each other through chemical reactions. In metabolic networks, chemical reactions transform reactants into products, thereby transferring elements between these metabolites. Knowledge of how elements are transferred through reactant/product pairs allows for the identification of primary compound connections through a metabolic network. However, such information is not readily available and is often challenging to obtain for large reaction databases or genome-scale metabolic models. In this study, a new algorithm was developed for automatically predicting the element-transferring reactant/product pairs using the limited information available in the standard representation of metabolic networks. The algorithm demonstrated high efficiency in analyzing large datasets and provided accurate predictions when benchmarked with manually curated data. Applying the algorithm to the visualization of metabolic networks highlighted pathways of primary reactant/product connections and provided an organized view of element-transferring biochemical transformations. The algorithm was implemented as a new function in the open source software package PSAMM in the release v0.30 (https://zhanglab.github.io/psamm/).

ABSTRACT Shewanella piezotolerans strain WP3 belongs to the group 1 branch of the Shewanella genus and is a piezotolerant and psychrotolerant species isolated from the deep sea. In this study, a genome-scale model was constructed for WP3 using a combination of genome annotation, ortholog mapping, and physiological verification. The metabolic reconstruction contained 806 genes, 653 metabolites, and 922 reactions, including central metabolic functions that represented nonhomologous replacements between the group 1 and group 2 Shewanella species. Metabolic simulations with the WP3 model demonstrated consistency with existing knowledge about the physiology of the organism. A comparison of model simulations with experimental measurements verified the predicted growth profiles under increasing concentrations of carbon sources. The WP3 model was applied to study mechanisms of anaerobic respiration through investigating energy conservation, redox balancing, and the generation of proton motive force. Despite being an obligate respiratory organism, WP3 was predicted to use substrate-level phosphorylation as the primary source of energy conservation under anaerobic conditions, a trait previously identified in other Shewanella species. Further investigation of the ATP synthase activity revealed a positive correlation between the availability of reducing equivalents in the cell and the directionality of the ATP synthase reaction flux. Comparison of the WP3 model with an existing model of a group 2 species, Shewanella oneidensis MR-1, revealed that the WP3 model demonstrated greater flexibility in ATP production under the anaerobic conditions. Such flexibility could be advantageous to WP3 for its adaptation to fluctuating availability of organic carbon sources in the deep sea. IMPORTANCE The well-studied nature of the metabolic diversity of Shewanella bacteria makes species from this genus a promising platform for investigating the evolution of carbon metabolism and energy conservation. The Shewanella phylogeny is diverged into two major branches, referred to as group 1 and group 2. While the genotype-phenotype connections of group 2 species have been extensively studied with metabolic modeling, a genome-scale model has been missing for the group 1 species. The metabolic reconstruction of Shewanella piezotolerans strain WP3 represented the first model for Shewanella group 1 and the first model among piezotolerant and psychrotolerant deep-sea bacteria. The model brought insights into the mechanisms of energy conservation in WP3 under anaerobic conditions and highlighted its metabolic flexibility in using diverse carbon sources. Overall, the model opens up new opportunities for investigating energy conservation and metabolic adaptation, and it provides a prototype for systems-level modeling of other deep-sea microorganisms.

There is increasing interest in the chronic lymphocytic leukemia (CLL) microenvironment and the mechanisms that may promote CLL cell survival and proliferation. A role for T helper (Th) cells has been suggested, but current evidence is only circumstantial. Here we show that CLL patients had memory Th cells that were specific for endogenous CLL antigens. These Th cells activated autologous CLL cell proliferation in vitro and in human → mouse xenograft experiments. Moreover, CLL cells were efficient antigen-presenting cells that could endocytose and process complex proteins through antigen uptake pathways, including the B cell receptor. Activation of CLL cells by Th cells was contact and CD40L dependent. The results suggest that CLL is driven by ongoing immune responses related to Th cell–CLL cell interaction. We propose that Th cells support malignant B cells and that they could be targeted in the treatment of CLL.

The genome-scale models of metabolic networks have been broadly applied in phenotype prediction, evolutionary reconstruction, community functional analysis, and metabolic engineering. Despite the development of tools that support individual steps along the modeling procedure, it is still difficult to associate mathematical simulation results with the annotation and biological interpretation of metabolic models. In order to solve this problem, here we developed a Portable System for the Analysis of Metabolic Models (PSAMM), a new open-source software package that supports the integration of heterogeneous metadata in model annotations and provides a user-friendly interface for the analysis of metabolic models. PSAMM is independent of paid software environments like MATLAB, and all its dependencies are freely available for academic users. Compared to existing tools, PSAMM significantly reduced the running time of constraint-based analysis and enabled flexible settings of simulation parameters using simple one-line commands. The integration of heterogeneous, model-specific annotation information in PSAMM is achieved with a novel format of YAML-based model representation, which has several advantages, such as providing a modular organization of model components and simulation settings, enabling model version tracking, and permitting the integration of multiple simulation problems. PSAMM also includes a number of quality checking procedures to examine stoichiometric balance and to identify blocked reactions. Applying PSAMM to 57 models collected from current literature, we demonstrated how the software can be used for managing and simulating metabolic models. We identified a number of common inconsistencies in existing models and constructed an updated model repository to document the resolution of these inconsistencies.

During the Global Ocean Data Assimilation Experiment (GODAE), numerical modeling and prediction in coastal and shelf seas benefited from development of state-of-the-art, data-assimilative, and data-validated large-scale models that can supply initial and boundary conditions to nested domains. Rather than attempting an exhaustive synthesis, this article illustrates the progress in coastal ocean modeling and prediction made possible by GODAE, either directly by providing estimates, or more subtly by rendering coastal forecasting more feasible and its applications more obvious.

The aim of this study was to determine the relative abundance and relationship of vitamin D responsive and calcium transporting transcripts (TRPV5, TRPV6, calD9k, calD28k, PMCA, NCX1, CYP27B1, CYP24A1, and VDR) in ovine, canine and, equine kidney using quantitative real-time PCR (RT-qPCR), and then perform a comparison between the three species. Renal tissue samples were harvested post-mortem from 10 horses, 10 sheep, and five dogs. Primers were designed for each gene. For each sample total RNA was extracted, cDNA synthesised, and RT-qPCR was performed. RT-qPCR data were normalised and statistical comparison was performed. Due to their consistent correlation with each other in each species, TRPV6, calD9k/calD28k, and PMCA appeared to be the main pathways involved in active transepithelial calcium transport in the kidney of sheep, dogs and horses. The results indicate that all of the studied genes were expressed in the renal tissue of studied species, although the expression levels and correlation of transcripts with each other were different from species to species. All vitamin D responsive and calcium transporting transcripts were highly correlated with VDR in equine kidney, but not in sheep and dogs. The CYP27B1 and CYP24A1 mRNAs showed a different renal expression pattern and correlation in horses compared with sheep and dogs. Given the high urinary calcium concentration and low serum 1,25(OH)2D concentration in horses, it could be expected that CYP27B1 expression would be lower than CYP24A1 in the horse, and this did not appear to be the case. The findings suggest that despite low serum vitamin D concentrations, vitamin D still plays a significant role in calcium metabolism in horses, especially given the strong correlations between VDR and vitamin D responsive transcripts in these animals.

Systemic lupus erythematosus (SLE) is marked by a T helper (Th) cell dependent B cell hyperresponsiveness, with frequent germinal center reactions, and gammaglobulinemia. A hallmark of SLE is the finding of IgG autoantibodies specific for dsDNA. The specificity of the Th cells that drive the expansion of anti-dsDNA B cells is unresolved. However, anti-microbial, anti-histone and anti-idiotype Th cell responses have been hypothesized to play a role. It has been entirely unclear if these seemingly disparate Th cell responses and hypotheses could be related or unified. Here we describe that H chain CDR3 idiotypes from IgG+ B cells of lupus mice have sequence similarities with both microbial and other self peptides, matched sequences were increased within the mutated CDR3 repertoire and when sequences were derived from lupus mice with expanded anti-dsDNA B cells. Analyses of histone sequences showed that particular histone peptides were similar to VDJ junctions. Moreover, lupus mice had Th cell responses towards histone peptides similar to anti-dsDNA CDR3 sequences. The results suggest that Th cell in lupus may have multiple cross-reactive specificities linked to the IgVH CDR3 Id-peptide sequences as well as similar DNA-associated protein motifs.

Inherited rickets of Corriedale sheep is characterized by decreased growth rate, thoracic lordosis and angular limb deformities. Previous outcross and backcross studies implicate inheritance as a simple autosomal recessive disorder. A genome wide association study was conducted using the Illumina OvineSNP50 BeadChip on 20 related sheep comprising 17 affected and 3 carriers. A homozygous region of 125 consecutive single-nucleotide polymorphism (SNP) loci was identified in all affected sheep, covering a region of 6 Mb on ovine chromosome 6. Among 35 candidate genes in this region, the dentin matrix protein 1 gene (DMP1) was sequenced to reveal a nonsense mutation 250C/T on exon 6. This mutation introduced a stop codon (R145X) and could truncate C-terminal amino acids. Genotyping by PCR-RFLP for this mutation showed all 17 affected sheep were "T T" genotypes; the 3 carriers were "C T"; 24 phenotypically normal related sheep were either "C T" or "C C"; and 46 unrelated normal control sheep from other breeds were all "C C". The other SNPs in DMP1 were not concordant with the disease and can all be ruled out as candidates. Previous research has shown that mutations in the DMP1 gene are responsible for autosomal recessive hypophosphatemic rickets in humans. Dmp1_knockout mice exhibit rickets phenotypes. We believe the R145X mutation to be responsible for the inherited rickets found in Corriedale sheep. A simple diagnostic test can be designed to identify carriers with the defective "T" allele. Affected sheep could be used as animal models for this form of human rickets, and for further investigation of the role of DMP1 in phosphate homeostasis.

Alloimmunization is a common phenomenon after transfusion, with an estimated incidence of 0.5% increasing to 20–60% in chronically transfused patients. In recently transfused patients, serological typing can be hampered by mixed field agglutination. We established RT-PCR methods for RHD, RHC/c and RHE/e typing using mRNA from reticulocytes. Molecular typing was performed soon after 51 separate mismatched transfusion events involving 30 patients. Accurate identification of the transfused patients’ phenotype was confirmed in all cases. Reticulocyte maturation studies revealed that temperature is a crucial parameter for transition into mature red blood cells.

It has been suggested that VH4-34 gene segment expression is counter-selected in multiple myeloma (MM) due to a self-tolerance mechanism. We cloned and sequenced a VH4-34 gene segment from bone marrow mononuclear cells of a stage III MM patient. We show that VH4-34 was expressed by the serum IgA myeloma (M)-protein, as demonstrated by reactivity with the VH4-34 specific 9G4 mAb and mass spectrometry (MS). The M-protein had weak reactivity with nuclei. These results demonstrate that VH4-34 may be expressed in secreted IgA M-protein with weak autoreactivity. Thus, counter-selection of VH4-34 is pronounced but not absolute in MM. Mechanisms of how VH4-34 can occasionally be expressed in MM and clinical implications are discussed.