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Journal articlePowell HR, Islam SA, David A, et al., 2025,
Phyre2.2: a community resource for template-based protein structure prediction
, Journal of Molecular Biology, Vol: 437, ISSN: 0022-2836Template-based modelling, also known as homology modelling, is a powerful approach to predict the structure of a protein from its amino acid sequence. The approach requires one to identify a sequence similarity between the query sequence and that of a known structure as they will adopt a similar conformation, and the known structure can be used as the template for modelling the query sequence. Recently several approaches, most notably AlphaFold, have employed enhanced machine learning and have yielded accurate models irrespective of whether there is an identifiable template. Here we report Phyre2.2 which incorporates several enhancements to our widely-used template modelling portal Phyre2. The main development is facilitating a user to submit their sequence and then Phyre2.2 identifies the most suitable AlphaFold model to be used as a template. In Phyre2.2 the user searches a template library of known structures. We have now included in our library a representative structure for every protein sequence in the protein databank (PDB). In addition, there are representatives for an apo and a holo structure if they are in the PDB. The ranking of hits has been modified to highlight to the user if there are different domains spanning the sequence. Phyre2.2 continues to support batch processing where a user can submit up to 100 sequences facilitating processing of proteomes. Phyre2.2 is freely available to all users, including commercial users, at https://www.sbg.bio.ic.ac.uk/phyre2/.
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Journal articleNikov GI, Pretorius D, Murray JW, 2025,
SOLeNNoID: a deep learning pipeline for solenoid residue detection in protein structures
, Bioinformatics, Vol: 41, ISSN: 1367-4811Motivation: Solenoid proteins, a subset of tandem repeat proteins, have structurally distinct, modular, and elongated architectures that differentiate them from globular proteins. These proteins play essential roles in diverse biological processes, including protein binding, enzymatic catalysis, ice binding, and nucleic acid interactions. Despite their biological significance and increasing commercial applications–such as in therapeutic engineered variants like DARPins and designed PPR proteins–accurate identification and annotation of solenoid structures remain challenging. Given that solenoid structures are more conserved than their sequences, recent advances in protein structure prediction suggest that structure-based solenoid detection methods are preferable to sequence-based ones.Results: We introduce SOLeNNoID, a deep-learning-based pipeline for predicting solenoid residues in protein structures. Our method employs a convolutional neural network architecture to analyse protein distance matrices, enabling accurate identification of solenoid-containing regions. SOLeNNoID covers all three solenoid subclasses: α-, α/β-, and β-solenoids. Comparative evaluation against existing structure-based methods demonstrates the superior performance of our approach. Applying SOLeNNoID to the entire Protein Data Bank led to a 71% increase in detected solenoid-containing entries compared to the gold-standard RepeatsDB database, significantly expanding the known solenoid protein repertoire.Availability and implementation: SOLeNNoID is implemented in Python and available on github at https://github.com/gnik2018/SOLeNNoID. The source code and pre-trained models are accessible under a free-software license. Training data are available on Zenodo at https://zenodo. org/records/14927497
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Journal articleDrobnic T, Cohen EJ, Calcraft T, et al., 2025,
In situ structure of a bacterial flagellar motor at subnanometre resolution reveals adaptations for increased torque (vol 10, pg 1723, 2025)
, NATURE MICROBIOLOGY, Vol: 10, Pages: 2092-2092, ISSN: 2058-5276 -
Journal articleFoster JC, Pham B, Pham R, et al., 2025,
Barrel expansion of outer membrane protein G nanopore through β-hairpin duplication
, PROTEIN SCIENCE, Vol: 34, ISSN: 0961-8368 -
Journal articleAllen ME, Sun Y, Chan CL, et al., 2025,
Thermally Driven Dynamic Behaviors in Polymeric Vesicles.
, Small, Vol: 21Stimuli-responsive polymeric vesicles offer a versatile platform for mimicking dynamic cell-like behaviors for synthetic cell applications. In this study, thermally responsive polymeric droplets derived from poly(ethylene oxide)-poly(butylene oxide) (PEO-PBO) polymersomes, aiming to create synthetic cell models that mimic key biological functions are developed. Upon heating, the nanoscale vesicles undergo fusion, transforming into sponge-like microscale droplets enriched with membrane features. By modulating the temperature, these droplets display dynamic properties such as contractility, temperature-induced fusion, and cargo trapping, including small molecules and bacteria, thereby demonstrating their ability to dynamically interface with biological entities. The findings demonstrate the potential of our sponge-like droplets in synthetic cell applications, contributing to the understanding of PEO-PBO polymersomes' unique characteristics, expanding the capabilities of synthetic cell structures, and representing an exciting possibility for advancing soft matter engineering to cell-like behaviors.
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Journal articlede Campos GY, Guimaraes JG, Machado MP, et al., 2025,
Mannan-targeting chimeric antigen receptor redirected antifungal activity of NK-92 cells against<i> Candida</i><i> albicans</i>
, CYTOTHERAPY, Vol: 27, Pages: 917-932, ISSN: 1465-3249 -
Journal articleGao F, Ye F, Jovanovic M, et al., 2025,
Subunit specialization in AAA+ proteins and substrate unfolding during transcription complex remodeling (vol 122, e2425868122, 2025)
, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 122, ISSN: 0027-8424 -
Journal articleContini C, 2025,
From light to life-like protocells
, Nature Synthesis, ISSN: 2731-0582 -
Journal articleSant DG, Smith TP, Wong ELY, et al., 2025,
Eco-evolutionary robustness of wild bacterial communities to experimental perturbation
, The ISME Journal, ISSN: 1751-7362Most knowledge about bacterial evolution and ecological interactions comes from laboratory studies. One difference between the wild and most laboratory experiments is the diversity of bacterial taxa present. Understanding how wild bacteria respond to perturbation therefore requires consideration of how ecological sorting, colonization, and genetic changes of constituent species interact. Ecological sorting of species might reduce evolutionary rates and make communities robust to disturbance, or it could amplify selection pressures and lead to unstable co-evolutionary cascades. Even estimates of basic rates of ecological sorting, dispersal, and genetic change are rare. Here, we addressed these knowledge gaps by liming wild decomposer communities living in beech tree holes and tracking ecological and evolutionary responses for 12 weeks. Overall, tree hole communities were extremely robust to liming involving short-term pulses up to 4 pH units and long-term increases up to 2 pH units. Species diversity and composition displayed significant but small changes in treatment tree holes compared to control ones. New bacterial taxa colonized at a low rate that did not vary with liming. Genetic changes in the frequency of single nucleotide polymorphisms in metagenome assembled genomes occurred at rates that were both comparable to and correlated with ecological changes in the same metagenome assembled genomes, but the rate of genetic changes did not vary between limed and control tree holes. Analysis of rates of genetic change estimated low effective population size (~104) and generation times of roughly 1 day. Our study provides estimates of rates of ecological and evolutionary processes in wild bacterial communities, which displayed remarkable robustness to our experimental perturbation.
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Journal articleCheong B, Laurenson I, Claxton P, et al., 2025,
Performance of direct detection of Mycobacterium tuberculosis within Mycobacterium tuberculosis complex by routine MALDI-ToF for the diagnosis using species-specific lipid fingerprint
, Microbiology Spectrum, ISSN: 2165-0497Objectives:Managing tuberculosis cases require species and drug susceptibility identification, which are limited by the time taken by testing procedures due to slow bacterial growth. Lipid-based matrix assisted laser desorption time-of-flight mass spectrometry (MALDI-TOF MS) is a promising tool for identifying pathogenic mycobacteria species. This study aims to define and use species-specific lipid profiles of members of the Mycobacterium tuberculosis complex (MTBC) obtained by MALDI-TOF MS, to directly discriminate M. tuberculosis from other members of the MTBC such as M. africanum, M. bovis, M. bovis BCG. Methods:Reference strains (M. tuberculosis H37Rv, M. africanum, M. bovis, M. bovis BCG) were grown in Middlebrook 7H11 media (supplemented with 10% OADC growth supplement) and incubated for up to six weeks at 37°C, to generate large biomass (~109 bacteria) required for optimization and assess reproducibility of the assay and used to set the reference lipid database. In clinical use standard shorter culture periods would be sufficient.A blinded study was then performed using a collection of 46 mycobacterial clinical isolates strains composed of 30 M. tuberculosis, 2 M. africanum, 9 M. bovis BCG, and 5 M. bovis and grown under the same conditions. Cultured mycobacteria were heat-inactivated and loaded onto the MALDI target followed by addition of the matrix. Acquisition of the data was done using the negative ion mode. Results:Using the species-specific glycolipid, sulfolipids, , M. tuberculosis was discriminated within MTBC using the MALDI-ToF process with a sensitivity and specificity of 86.7% (95% CI 69.3- 96.2) and 93.7% (95% CI 69.8- 99.8), respectively. Conclusions :Direct detection of M. tuberculosis within the MTB complex based on mycobacterial lipid profiling provides asafe and accurate method, based on the detection of the sulfolipids, as a species-specific lipid biomarker of M. tuberculosis.
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Journal articleOdom KJ, Araya-Salas M, Benedict L, et al., 2025,
Global incidence of female birdsong is predicted by territoriality and biparental care in songbirds
, Nature Communications, Vol: 16, ISSN: 2041-1723Pronounced sexual dimorphism is generally assumed to evolve through sexual selection for elaborate male traits. However, there is increasing evidence that sexual dimorphism in traits such as birdsong may also evolve through loss of elaboration in females, but the evolutionary drivers underlying this process are obscure. Here we analyse ecological and natural history traits for over 1300 songbird species and show that increased female song incidence and elaboration are most directly associated with year-round territoriality, biparental care, and large body size. Phylogenetic path analysis indicates that mating system and breeding latitude primarily have indirect effects on female song evolution. Stable, tropical life histories and mating systems with biparental care promote female song, whereas evolutionary transitions to migration, reduced territoriality, and loss of male care led to losses or reductions of female song incidence. Our analyses provide a comprehensive framework for studying the drivers of sex differences and similarities in birdsong and reveal novel interactions among natural history and sexual selection pressures that have been hypothesized to independently shape elaborate traits.
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Journal articleCrilly A, Malivert A, Jørgensen ACS, et al., 2025,
Ten simple rules for navigating AI in science
, PLoS Computational Biology, Vol: 21, ISSN: 1553-734X -
Journal articleCantwell-Jones A, Everson J, Bates OK, et al., 2025,
Phenological turnover matters when making trait-based predictions of plant-pollinator interactions
, Functional Ecology, ISSN: 0269-8463 -
Journal articleGallagher K, Sousa RS, Gatenbee C, et al., 2025,
Controlling treatment toxicity in ovarian cancer to prime the patient for tumor extinction therapy.
, bioRxivHigh-grade serous ovarian cancer (HGSOC) remains a major clinical challenge. In particular among those patients with homologous recombination (HR)-proficient tumors (>50%), most eventually succumb to their disease due to high recurrence rates, acquired resistance, and cumulative toxicity. This report summarizes work from the 12th IMO Workshop in which we explored an alternative "extinction therapy" strategy for frontline treatment of HGSOC. Inspired by ecological principles, this multi-strike approach aims to eradicate tumors not through a singular "magic bullet" but through a series of therapies after standard frontline treatment when the tumor is still, and perhaps most, vulnerable. We present a framework leveraging mathematical modeling (MM) to develop personalized multi-strike protocols for HGSOC. Key contributions include: 1) An "IMOme" score using liquid biopsy data to assess patient-specific hematopoietic toxicity risk, guiding the timing and selection of subsequent therapies, 2) MM strategies to design effective low-dose combinations of targeted agents to achieve synthetic lethality while managing toxicity, and 3) A MM framework to analyze the interplay between chemotherapy, gut microbiome toxicity, and immunotherapy, demonstrating how mitigating microbiome damage could enhance immune response. Overall, the computational approaches presented herein aim to support the design of personalized, multi-strike regimens in the frontline setting that proactively target tumor extinction while managing toxicity, ultimately seeking to deliver cures for patients with HGSOC.
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Journal articleLeither S, Strobl MAR, Scott JG, et al., 2025,
Using spatial statistics to infer game-theoretic interactions in an agent-based model of cancer cells.
, bioRxivDrug resistance in cancer is shaped not only by evolutionary processes but also by eco-evolutionary interactions between tumor subpopulations. These interactions can support the persistence of resistant cells even in the absence of treatment, undermining standard aggressive therapies and motivating drug holiday-based approaches that leverage ecological dynamics. A key challenge in implementing such strategies is efficiently identifying interaction between drug-sensitive and drug-resistant subpopulations. Evolutionary game theory provides a framework for characterizing these interactions. We investigate whether spatial patterns in single time-point images of cell populations can reveal the underlying game theoretic interactions between sensitive and resistant cells. To achieve this goal, we develop an agent-based model in which cell reproduction is governed by local game-theoretic interactions. We compute a suite of spatial statistics on single time-point images from the agent-based model under a range of games being played between cells. We quantify the informativeness of each spatial statistic and demonstrate that a simple machine learning model can classify the type of game being played. Our findings suggest that spatial structure contains sufficient information to infer ecological interactions. This work represents a step toward clinically viable tools for identifying cell-cell interactions in tumors, supporting the development of ecologically informed cancer therapies.
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Journal articleAumann RA, Gouvi G, Gregoriou M-E, et al., 2025,
Decoding and engineering temperature-sensitive lethality in<i> Ceratitis</i><i> capitata</i> for pest control
, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 122, ISSN: 0027-8424 -
Journal articleShmool TA, Martin LK, Jirkas A, et al., 2025,
Design principles for engineering ionic liquid-gold nanoparticles for therapeutic delivery to the brain
, ACS Nano, Vol: 19, Pages: 24806-24816, ISSN: 1936-0851Ionic liquid (IL) nanotechnology holds significant promise for designing nanoscale materials with tunable viscosity, polarity, and thermal stability for advanced therapeutic applications. However, the field currently lacks comprehensive guidelines for integrating ILs into complex therapeutic formulations. Herein, we propose the key design considerations for engineering immunoglobulin G (IgG) conjugated to gold nanoparticles (AuNPs) in the presence of choline-based ILs. By judicious IL cation and anion selection, we fine-tune the supramolecular assemblies and leverage the unique physicochemical properties of ILs to impart AuNPs with advantageous characteristics including enhanced structural, thermal, and thermodynamic stabilities, highly tunable morphologies, and markedly reduced aggregation propensities. Through systematic circular dichroism measurements, the thermodynamic parameters of the complex formulations were determined, offering insight into the IgG conformational changes and design parameters for systems of enhanced IgG conjugation to AuNP surfaces. In demonstrating the power of our design approach, the complex formulation of IgG-choline chloride-AuNPs, also including trehalose, histidine, and arginine, was delivered via focused ultrasound and microbubbles across the blood–brain barrier and showed a 7.6-fold increase in delivery in vivo compared to the traditional formulation. We demonstrate that IgG-IL-AuNPs can be easily and precisely manipulated at the nanometer scale, enabling the formation of versatile structural configurations. Holistically, we believe the rational design approach developed will advance the engineering of tailored IL-nanocarriers for targeted therapeutic delivery and broaden the scope of IL applications in biomedicine.
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Journal articleOToole N, Allen ME, Contini C, et al., 2025,
Microfluidic generation of bacterial biohybrids for magnetic guidance and content release
, Chemical Communications, ISSN: 1359-7345Bacterial biohybrids use bacterial and synthetic components for biotechnological applications. Here, we outline an adaptable and high-throughput microfluidic platform to create microscale biocontained bacterial biohybrids enclosed in a hydrogel with magnetotactic and biosensing properties. The biohybrids are capable of magnetically driven motility, biochemical sensing and controlled cargo release. This approach enables the scalable fabrication of biocontained multifunctional biohybrids for potential industrial and biomedical applications.
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Journal articleKing OG, Yip AYG, Horrocks V, et al., 2025,
Vancomycin-resistant enterococci utilise antibiotic-enriched nutrients for intestinal colonisation
, Nature Communications, Vol: 16, ISSN: 2041-1723Antibiotic treatment significantly disrupts the gut microbiome and promotes vancomycin- resistant enterococci (VRE) intestinal colonisation. These disruptions cause the intestine to act as a reservoir for VRE that seed difficult-to-treat infections. Here we show that antibiotics that promote VRE intestinal colonisation increase the concentration of a wide range of nutrients and decrease the concentration of a wide range of microbial metabolites. We show significant but incomplete suppression of VRE growth by individual short chain fatty acids that were decreased in antibiotic-treated faecal microbiomes. However, mixtures of short chain fatty acids provide complete or near complete suppression of VRE growth. We show that VRE use most nutrients increased in antibiotic-treated faecal microbiomes as carbon or nitrogen sources to support their growth, where Enterococcus faecium and Enterococcus faecalis have some common and some distinct preferences for the use of these specific nutrients. Finally, we show that E. faecium and E. faecalis occupy overlapping but distinct nutrient-defined intestinal niches that promote high growth when cultured with each other and when cultured with carbapenem-resistant Enterobacteriaceae. Our results demonstrate that VRE occupy distinct intestinal niches in the antibiotic-treated intestine, defined by their abilities to utilise specific enriched nutrients and their abilities to grow with reduced concentrations of inhibitory microbial metabolites.
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Journal articleKariuki R, Penman R, Newbold AD, et al., 2025,
Gold nanoparticle adsorption and uptake are directed by particle capping agent
, Small Science, Vol: 5, ISSN: 2688-4046Nanomaterials are revolutionizing the development of novel therapies, with applications ranging from drug delivery and diagnostics to controlling specific biological processes. However, the specific interactions that govern nanomaterial behavior in biological systems remain difficult to elucidate due to the complex dynamic nature of the lipid bilayer environment. Here, a combination of atomic force microscopy and molecular dynamics simulations is used to discover the precise mechanisms by which various ligand‐capped 5 nm gold nanoparticles (AuNPs) interact with supported lipid bilayers of pure fluid phospholipids (1,2‐di(9Z‐octadecenoyl)‐sn‐glycero‐3‐phosphocholine (DOPC)). When the ligand capping agent is altered, differences in adsorption and bilayer disruption as a function of capping agent size and charge are observed. Weakly physiosorbed ligands enable the absorption of the AuNP into the bilayer's hydrophobic core, whereas more strongly adsorbed ligands inhibit the complete insertion of the AuNP. However, ligand‐dependent headgroup interactions can lead to interfacial adhesion or inhibition of adsorption. These results reveal that the interaction of AuNPs with biological membranes varies depending on the specific capping agent. Notably, the mechanisms may involve cooperative (or synergistic) effects with membrane components, highlighting the importance of understanding these interactions at molecular resolution.
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Journal articlePradhan D, Tanwar A, Wong J, et al., 2025,
Toroidal displacement of <i>Klebsiella pneumoniae</i> by <i>Pseudomonas aeruginosa</i> is a unique mechanism to avoid competition for iron
, mBio, Vol: 16, ISSN: 2150-7511Competition for resources is one of the major drivers for evolution and retention of new traits in microbial communities. Quorum sensing-dependent traits of the opportunistic human pathogen Pseudomonas aeruginosa allow it to survive and thrive in the presence of other microbes. Here, we report a unique mechanism that P. aeruginosa employs specifically against Klebsiella pneumoniae to displace it on solid surfaces. Interestingly, P. aeruginosa employs neither proteases nor toxic secondary metabolites against K. pneumoniae. Rhamnolipid biosurfactant under the control of the RhlR quorum sensing system appears to be the primary factor required to displace Klebsiella effectively. Under conditions of iron limitation, both bacteria produce iron-scavenging molecules, while P. aeruginosa also produces rhamnolipid biosurfactant, allowing it to push Klebsiella cells away from the substratum. Our study describes a unique quorum and iron-responsive mechanism in P. aeruginosa to support its own growth during resource competition on a solid surface.
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Journal articleZhang-Zheng H, Malhi Y, Ziemińska K, et al., 2025,
A test of ecophysiological theories on tropical forest functional traits along a VPD gradient
, Communications Biology, Vol: 8, ISSN: 2399-3642Forest primary production is a crucial process for both ecosystem functioning and global carbon cycling. Primary production responds to both temperature and vapour pressure deficit (VPD) through separate mechanisms. Vegetation models need to quantify both responses. However, due to their often high correlations, most observational data sets used to test models or theories hardly distinguish them. Here we evaluate ecophysiological theories on the effect of VPD using tree trait data collected along a VPD gradient in West Africa. Study sites spanned an annual rainfall range of 1200–2050 mm, with varying seasonality but minimal temperature variation. Most photosynthetic traits show trends consistent with predictions from optimality theory, including higher net CO2 assimilation rates and greater photosynthetic capacity at drier sites. These patterns were associated with greater deciduousness, increased respiration rates and enhanced water transport at drier sites. In contrast, hydraulic traits showed weaker consistency with theoretical predictions or global trends, particularly those based on the xylem efficiency-safety tradeoff. Our findings suggest that vegetation models should account for higher photosynthetic capacity in drier regions, but that further research is needed to incorporate hydraulic traits into models.
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Journal articleOno M, 2025,
GatingTree: pathfinding analysis of group-specific effects in cytometry data
, Cytometry Part A, ISSN: 1552-4922Advancements in cytometry technologies have led to a remarkable increase in the number of markers thatcan be analyzed simultaneously, presenting significant challenges in data analysis. Traditional approaches,such as dimensional reduction techniques and computational clustering, although popular, often face reproducibility challenges due to their heavy reliance on inherent data structures. This reliance prevents thedirect translation of their outputs into gating strategies for downstream experiments. Here, we propose thenovel Gating Tree methodology, a pathfinding approach that investigates the multidimensional data landscape to unravel group-specific features without the use of dimensional reduction. This method employsnovel measures, including enrichment scores and gating entropy, to effectively identify group-specific featureswithin high-dimensional cytometric datasets. Our analysis, applied to both simulated and real cytometricdatasets, demonstrates that the Gating Tree not only identifies group-specific features comprehensively butalso produces outputs that are immediately usable as gating strategies for pinpointing key cell populations.Furthermore, by integrating machine learning methods, including Random Forest, we have benchmarkedGating Tree against existing methods, demonstrating its superior performance. A range of supervised andunsupervised methods implemented in Gating Tree thus provides effective visualization and output data,which can be immediately used as successive gating strategies for downstream study.
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Journal articleOllivier R, Robin S, Galland M, et al., 2025,
Transcriptomic analysis reveals candidate molecular pathways involved in pea (<i>Pisum sativum</i> L.) resistance to pea aphid (<i>Acyrthosiphon pisum</i> Harris) biotypes
, BMC GENOMICS, Vol: 26, ISSN: 1471-2164 -
Journal articleWaring BG, Lancastle L, Bell T, et al., 2025,
Windthrow disturbance impacts soil biogeochemistry and bacterial communities in a temperate forest
, Plant and Soil: international journal on plant-soil relationships, Vol: 512, Pages: 395-408, ISSN: 0032-079XAimsForests across the world are subject to disturbance via wind, wildfire, and pest and disease outbreaks. Yet we still have an incomplete understanding of how these stressors impact forest biota—particularly the soil microbes, which govern forest carbon and nutrient cycling.MethodsHere, we investigated the impact of a severe windstorm on soil bacterial communities in Kielder Forest, a temperate coniferous forest in the north of England. Within ten individual sites, defined by common stand composition and topography, we established 50 m2 plots in undisturbed stands, and in nearby stands that were moderately and/or severely disturbed by windthrow. Soils were sampled within each of the 22 study plots, and analysed for changes in carbon and nitrogen content, pH, root biomass, and bacterial community structure. We separately sequenced bacteria from bulk soils, rhizosphere soils, and root tissues to assess whether disturbance impacts varied based on the proximity of microbiota to tree roots.ResultsLess than a year after the storm, we found that the most severely disturbed stands had lower canopy cover, lower soil carbon content, higher soil pH, and a smaller fine root biomass than the undisturbed stands. Disturbance also impacted bacterial community beta-diversity, but the effects were subtle and did not vary among assemblages in bulk vs. rhizosphere soils.ConclusionsImpacts of aboveground disturbance on soil biogeochemistry can be significant, but soil bacterial communities are relatively well-buffered against these changes. However, altered patterns of root growth and carbon cycling may have longer-term implications for forest recovery after windthrow disturbances.
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Journal articleBrown CM, Westendorp MSS, Zarmiento-Garcia R, et al., 2025,
An integrative modelling approach to the mitochondrial cristae
, COMMUNICATIONS BIOLOGY, Vol: 8- Cite
- Citations: 2
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Journal articleLüdke D, Sakai T, Kourelis J, et al., 2025,
A root-specific NLR network mediates immune signaling of resistance genes against plant parasitic nematodes
, The Plant Cell, Vol: 37, ISSN: 1040-4651Plant nucleotide-binding domain and leucine-rich repeat immune receptors (NLRs) confer disease resistance to many foliar and root parasites. However, the extent to which NLR-mediated immunity is differentially regulated between plant organs is poorly known. Here, we show that a large cluster of tomato (Solanum lycopersicum) genes, encoding the cyst and root-knot nematode disease resistance proteins Hero and MeR1 as well as the NLR helper NLR required for cell death 6 (NRC6), is nearly exclusively expressed in the roots. This root-specific gene cluster emerged in Solanum species about 21 million years ago through gene duplication of the ancient asterid NRC network. NLR sensors in this gene cluster function exclusively through NRC6 helpers to trigger hypersensitive cell death. These findings indicate that the NRC6 gene cluster has sub-functionalized from the larger NRC network to specialize in mediating resistance against root pathogens, including cyst and root-knot nematodes. We propose that some NLR gene clusters and networks may have evolved organ-specific gene expression as an adaptation to particular parasites and to reduce the risk of autoimmunity.
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Journal articleBickel JK, Ahmed AIS, Pidd AB, et al., 2025,
Macrocyclic peptide probes for immunomodulatory protein CD59: potent modulators of bacterial toxin activity and antibody‐dependent cytotoxicity
, Angewandte Chemie International Edition, Vol: 64, ISSN: 1433-7851CD59 is an immunomodulatory cell surface receptor associated with human disease. Despite its importance in complement regulation and bacterial pathogenesis, CD59 remains a challenging therapeutic target. Research to date has focused on antibody or protein-based strategies. Here we present a new approach to target CD59 using macrocyclic peptides with low nanomolar affinity for CD59. Through X-ray crystallographic studies and structure-activity relationship (SAR) studies, we identify key interactions that are essential for binding and activity. We find that the macrocyclic peptide CP-06 adopts a beta-hairpin structure and binds CD59 through an intermolecular beta-sheet, mimicking protein–protein interactions of biologically relevant CD59 interaction partners. We create dimeric and lipidated macrocyclic peptide conjugates as enhanced cell-active CD59 inhibitors and show that these probes can be used to modulate both complement-mediated killing of human cells and lytic activity of bacterial virulence factors. Together, our data provide a starting point for future development of macrocyclic peptides to target CD59 activity in diverse cellular contexts.
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Journal articleVijayrajratnam S, Patkowski JB, Khorsandi J, et al., 2025,
Optimized <i>Legionella</i> expression strain for affinity purification of His-tagged membrane proteins eliminates major multimeric contaminant
, Microbiology Spectrum, Vol: 13, ISSN: 2165-0497Polyhistidine tags are frequently used for isolating proteins through nickel-nitrilotriacetic acid (Ni-NTA) affinity purification. However, proteins rich in histidine can also bind to the Ni-NTA resin, leading to contamination of the purification with undesired proteins. While attempting to purify the Legionella pneumophila Dot/Icm type IVB secretion system complex for single particle analysis, we encountered an unknown contaminant protein that bound to the Ni-NTA resin and formed uniform particles visible in negative stain electron microscopy (EM). Mass spectrometry identified this protein, which is encoded by the Legionella gene lpg1596 as a homolog of enoyl-CoA hydratase. Modeling of Lpg1596 revealed surface-exposed histidine clusters, which likely explains its ability to bind to the Ni-NTA resin. Moreover, since enoyl-CoA hydratase homologs are known to multimerize, multimers of Lpg1596 would be large enough to be visible by negative stain EM. To address the problematic issue of Lpg1596 binding to the Ni-NTA resin, we constructed and analyzed a L. pneumophila ∆lpg1596 mutant strain. Notably, Ni-NTA affinity purification of lysates from the ∆lpg1596 strain did not contain the contaminant protein or generate observable particles. Since the ∆lpg1596 mutant strain exhibited replication capabilities similar to the wild-type L. pneumophila in macrophages, its deletion will likely not affect pathogenesis studies. To facilitate the deletion of lpg1596 in other Legionella strains, we developed a set of natural transformation vectors with various antibiotic resistance markers. In summary, we present a strategy for removing a common Ni-NTA resin binding protein contaminant in L. pneumophila, which improves single particle analysis outcomes.
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Journal articleIrie N, Takeda N, Satou Y, et al., 2025,
Machine learning-assisted decoding of temporal transcriptional dynamics via fluorescent timer
, Nature Communications, Vol: 16, ISSN: 2041-1723Investigating the temporal dynamics of gene expression is crucial for understanding gene regulation across various biological processes. Using the Fluorescent Timer protein, the Timer-of-cell-kinetics-and-activity system enables analysis of transcriptional dynamics at the single-cell level. However, the complexity of Timer fluorescence data has limited its broader application. Here, we introduce an integrative approach combining molecular biology and machine learning to elucidate Foxp3 transcriptional dynamics through flow cytometric Timer analysis. We have developed a convolutional neural network-based method that incorporates image conversion and class-specific feature visualisation for class-specific feature identification at the single-cell level. Biologically, we developed a novel CRISPR mutant of Foxp3 fluorescent Timer reporter mice lacking the enhancer Conserved Non-coding Sequence 2, which revealed new roles of this enhancer in regulating Foxp3 transcription frequency under specific conditions. Furthermore, analysis of wild-type Foxp3 fluorescent Timer reporter mice at different ages uncovered distinct patterns of Foxp3 expression from neonatal to aged mice, highlighting prominent thymus-like features of neonatal splenic Foxp3+ T cells. In conclusion, our study uncovers previously unrecognised Foxp3 transcriptional dynamics, establishing a proof-of-concept for integrating CRISPR, single-cell dynamics analysis, and machine learning methods as advanced techniques to understand transcriptional dynamics in vivo.
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