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  • Journal article
    Endres R, Matas-Gil A, 2024,

    Unraveling biochemical spatial patterns: machine learning approaches to the inverse problem of stationary Turing patterns

    , iScience, Vol: 27, ISSN: 2589-0042

    The diffusion-driven Turing instability is a potential mechanism for spatial pattern formation in numerous biological and chemical systems. However, engineering these patterns and demonstrating that they are produced by this mechanism is challenging. To address this, we aim to solve the inverse problem in artificial and experimental Turing patterns. This task is challenging since patterns are often corrupted by noise and slight changes in initial conditions can lead to different patterns. We used both least squares to explore the problem and physics-informed neural networks to build a noise-robust method. We elucidate the functionality of our network in scenarios mimicking biological noise levels and showcase its application using an experimentally obtained chemical pattern. The findings reveal the significant promise of machine learning in steering the creation of synthetic patterns in bioengineering, thereby advancing our grasp of morphological intricacies within biological systems while acknowledging existing limitations.
  • Journal article
    Collins ASP, Kurt H, Duggan C, Cotur Y, Coatsworth P, Naik A, Kaisti M, Bozkurt T, Güder Fet al., 2024,

    Parallel, continuous monitoring and quantification of programmed cell death in plant tissue

    , Advanced Science, Vol: 11, ISSN: 2198-3844

    Accurate quantification of hypersensitive response (HR) programmed cell death is imperative for understanding plant defense mechanisms and developing disease-resistant crop varieties. Here, a phenotyping platform for rapid, continuous-time, and quantitative assessment of HR is demonstrated: Parallel Automated Spectroscopy Tool for Electrolyte Leakage (PASTEL). Compared to traditional HR assays, PASTEL significantly improves temporal resolution and has high sensitivity, facilitating detection of microscopic levels of cell death. Validation is performed by transiently expressing the effector protein AVRblb2 in transgenic Nicotiana benthamiana (expressing the corresponding resistance protein Rpi-blb2) to reliably induce HR. Detection of cell death is achieved at microscopic intensities, where leaf tissue appears healthy to the naked eye one week after infiltration. PASTEL produces large amounts of frequency domain impedance data captured continuously. This data is used to develop supervised machine-learning (ML) models for classification of HR. Input data (inclusive of the entire tested concentration range) is classified as HR-positive or negative with 84.1% mean accuracy (F1 score = 0.75) at 1 h and with 87.8% mean accuracy (F1 score = 0.81) at 22 h. With PASTEL and the ML models produced in this work, it is possible to phenotype disease resistance in plants in hours instead of days to weeks.
  • Journal article
    Manser CL, Perez-Carrasco R, 2024,

    A mathematical framework for measuring and tuning tempo in developmental gene regulatory networks.

    , Development, Vol: 151

    Embryo development is a dynamic process governed by the regulation of timing and sequences of gene expression, which control the proper growth of the organism. Although many genetic programmes coordinating these sequences are common across species, the timescales of gene expression can vary significantly among different organisms. Currently, substantial experimental efforts are focused on identifying molecular mechanisms that control these temporal aspects. In contrast, the capacity of established mathematical models to incorporate tempo control while maintaining the same dynamical landscape remains less understood. Here, we address this gap by developing a mathematical framework that links the functionality of developmental programmes to the corresponding gene expression orbits (or landscapes). This unlocks the ability to find tempo differences as perturbations in the dynamical system that preserve its orbits. We demonstrate that this framework allows for the prediction of molecular mechanisms governing tempo, through both numerical and analytical methods. Our exploration includes two case studies: a generic network featuring coupled production and degradation, with a particular application to neural progenitor differentiation; and the repressilator. In the latter, we illustrate how altering the dimerisation rates of transcription factors can decouple the tempo from the shape of the resulting orbits. We conclude by highlighting how the identification of orthogonal molecular mechanisms for tempo control can inform the design of circuits with specific orbits and tempos.
  • Journal article
    Joyce M, Falconio FA, Blackhurst L, Prieto-Godino L, French AS, Gilestro GFet al., 2024,

    Divergent evolution of sleep in Drosophila species

    , Nature Communications, Vol: 15, ISSN: 2041-1723

    Living organisms synchronize their biological activities with the earth’s rotation through the circadian clock, a molecular mechanism that regulates biology and behavior daily. This synchronization factually maximizes positive activities (e.g., social interactions, feeding) during safe periods, and minimizes exposure to dangers (e.g., predation, darkness) typically at night. Beyond basic circadian regulation, some behaviors like sleep have an additional layer of homeostatic control, ensuring those essential activities are fulfilled. While sleep is predominantly governed by the circadian clock, a secondary homeostatic regulator, though not well-understood, ensures adherence to necessary sleep amounts and hints at a fundamental biological function of sleep beyond simple energy conservation and safety. Here we explore sleep regulation across seven Drosophila species with diverse ecological niches, revealing that while circadian-driven sleep aspects are consistent, homeostatic regulation varies significantly. The findings suggest that in Drosophilids, sleep evolved primarily for circadian purposes. The more complex, homeostatically regulated functions of sleep appear to have evolved independently in a species-specific manner, and are not universally conserved. This laboratory model may reproduce and recapitulate primordial sleep evolution.
  • Journal article
    Miao A, Luo T, Hsieh B, Edge CJ, Gridley M, Wong RTC, Constandinou TG, Wisden W, Franks NPet al., 2024,

    Brain clearance is reduced during sleep and anesthesia (vol 27, pg 1046, 2024)

    , NATURE NEUROSCIENCE, ISSN: 1097-6256
  • Journal article
    Nkumama IN, Ogwang R, Odera D, Musasia F, Mwai K, Nyamako L, Murungi L, Tuju J, Fürle K, Rosenkranz M, Kimathi R, Njuguna P, Hamaluba M, Kapulu MC, Frank R, CHMI-SIKA study team, Osier FHAet al., 2024,

    Breadth of Fc-mediated effector function correlates with clinical immunity following human malaria challenge.

    , Immunity, Vol: 57, Pages: 1215-1224.e6

    Malaria is a life-threatening disease of global health importance, particularly in sub-Saharan Africa. The growth inhibition assay (GIA) is routinely used to evaluate, prioritize, and quantify the efficacy of malaria blood-stage vaccine candidates but does not reliably predict either naturally acquired or vaccine-induced protection. Controlled human malaria challenge studies in semi-immune volunteers provide an unparalleled opportunity to robustly identify mechanistic correlates of protection. We leveraged this platform to undertake a head-to-head comparison of seven functional antibody assays that are relevant to immunity against the erythrocytic merozoite stage of Plasmodium falciparum. Fc-mediated effector functions were strongly associated with protection from clinical symptoms of malaria and exponential parasite multiplication, while the gold standard GIA was not. The breadth of Fc-mediated effector function discriminated clinical immunity following the challenge. These findings present a shift in the understanding of the mechanisms that underpin immunity to malaria and have important implications for vaccine development.
  • Journal article
    Haber DA, Arien Y, Lamdan LB, Alcalay Y, Zecharia C, Krsticevic F, Yonah ES, Avraham RD, Krzywinska E, Krzywinski J, Marois E, Windbichler N, Papathanos PAet al., 2024,

    Targeting mosquito X-chromosomes reveals complex transmission dynamics of sex ratio distorting gene drives.

    , Nat Commun, Vol: 15

    Engineered sex ratio distorters (SRDs) have been proposed as a powerful component of genetic control strategies designed to suppress harmful insect pests. Two types of CRISPR-based SRD mechanisms have been proposed: X-shredding, which eliminates X-bearing sperm, and X-poisoning, which eliminates females inheriting disrupted X-chromosomes. These differences can have a profound impact on the population dynamics of SRDs when linked to the Y-chromosome: an X-shredder is invasive, constituting a classical meiotic Y-drive, whereas X-poisoning is self-limiting, unable to invade but also insulated from selection. Here, we establish X-poisoning strains in the malaria vector Anopheles gambiae targeting three X-linked genes during spermatogenesis, resulting in male bias. We find that sex distortion is primarily driven by a loss of X-bearing sperm, with limited evidence for postzygotic lethality of female progeny. By leveraging a Drosophila melanogaster model, we show unambiguously that engineered SRD traits can operate differently in these two insects. Unlike X-shredding, X-poisoning could theoretically operate at early stages of spermatogenesis. We therefore explore premeiotic Cas9 expression to target the mosquito X-chromosome. We find that, by pre-empting the onset of meiotic sex chromosome inactivation, this approach may enable the development of Y-linked SRDs if mutagenesis of spermatogenesis-essential genes is functionally balanced.
  • Journal article
    Smith T, Mishra S, Dorigatti I, Dixit M, Tristem M, Pearse Wet al., 2024,

    Differential responses of SARS-CoV-2 variants to environmental drivers during their selective sweeps

    , Scientific Reports, Vol: 14, ISSN: 2045-2322

    Previous work has shown that environmental variables affect SARS-CoV-2 transmission, but it is unclear whether different strains show similar environmental responses. Here we leverage genetic data on the transmission of three (Alpha, Delta and Omicron BA.1) variants of SARS-CoV-2 throughout England, to unpick the roles that climate and public-health interventions play in the circulation of this virus. We find evidence for enhanced transmission of the virus in colder conditions in the first variant selective sweep (of Alpha, in winter), but limited evidence of an impact of climate in either the second (of Delta, in the summer, when vaccines were prevalent) or third sweep (of Omicron, in the winter, during a successful booster-vaccination campaign). We argue that the results for Alpha are to be expected if the impact of climate is non-linear: we find evidence of an asymptotic impact of temperature on the alpha variant transmission rate. That is, at lower temperatures, the influence of temperature on transmission is much higher than at warmer temperatures. As with the initial spread of SARS-CoV-2, however, the overwhelming majority of variation in disease transmission is explained by the intrinsic biology of the virus and public-health mitigation measures. Specifically, when vaccination rates are high, a major driver of the spread of a new variant is it’s ability to evade immunity, and any climate effects are secondary (as evidenced for Delta and Omicron). Climate alone cannot describe the transmission dynamics of emerging SARS-CoV-2 variants.
  • Journal article
    Baxter JM, Hutchison CDM, Fadini A, Maghlaoui K, Cordon-Preciado V, Morgan RML, Agthe M, Horrell S, Tellkamp F, Mehrabi P, Pfeifer Y, Muller-Werkmeister HM, von Stetten D, Pearson AR, van Thor JJet al., 2024,

    Power Density Titration of Reversible Photoisomerization of a Fluorescent Protein Chromophore in the Presence of Thermally Driven Barrier Crossing Shown by Quantitative Millisecond Serial Synchrotron X-ray Crystallography

    , JOURNAL OF THE AMERICAN CHEMICAL SOCIETY, Vol: 146, Pages: 16394-16403, ISSN: 0002-7863
  • Journal article
    Cawood EE, Baker E, Edwards TA, Woolfson DN, Karamanos TK, Wilson AJet al., 2024,

    Understanding β-strand mediated protein-protein interactions: tuning binding behaviour of intrinsically disordered sequences by backbone modification

    , CHEMICAL SCIENCE, ISSN: 2041-6520
  • Journal article
    Fu Z, Ciais P, Wigneron J-P, Gentine P, Feldman AF, Makowski D, Viovy N, Kemanian AR, Goll DS, Stoy PC, Prentice IC, Yakir D, Liu L, Ma H, Li X, Huang Y, Yu K, Zhu P, Li X, Zhu Z, Lian J, Smith WKet al., 2024,

    Global critical soil moisture thresholds of plant water stress.

    , Nat Commun, Vol: 15

    During extensive periods without rain, known as dry-downs, decreasing soil moisture (SM) induces plant water stress at the point when it limits evapotranspiration, defining a critical SM threshold (θcrit). Better quantification of θcrit is needed for improving future projections of climate and water resources, food production, and ecosystem vulnerability. Here, we combine systematic satellite observations of the diurnal amplitude of land surface temperature (dLST) and SM during dry-downs, corroborated by in-situ data from flux towers, to generate the observation-based global map of θcrit. We find an average global θcrit of 0.19 m3/m3, varying from 0.12 m3/m3 in arid ecosystems to 0.26 m3/m3 in humid ecosystems. θcrit simulated by Earth System Models is overestimated in dry areas and underestimated in wet areas. The global observed pattern of θcrit reflects plant adaptation to soil available water and atmospheric demand. Using explainable machine learning, we show that aridity index, leaf area and soil texture are the most influential drivers. Moreover, we show that the annual fraction of days with water stress, when SM stays below θcrit, has increased in the past four decades. Our results have important implications for understanding the inception of water stress in models and identifying SM tipping points.
  • Journal article
    Lane BJ, Ma Y, Yan N, Wang B, Ackermann K, Karamanos TK, Bode BE, Pliotas Cet al., 2024,

    Monitoring the conformational ensemble and lipid environment of a mechanosensitive channel under cyclodextrin-induced membrane tension.

    , Structure, Vol: 32, Pages: 739-750.e4

    Membrane forces shift the equilibria of mechanosensitive channels enabling them to convert mechanical cues into electrical signals. Molecular tools to stabilize and methods to capture their highly dynamic states are lacking. Cyclodextrins can mimic tension through the sequestering of lipids from membranes. Here we probe the conformational ensemble of MscS by EPR spectroscopy, the lipid environment with NMR, and function with electrophysiology under cyclodextrin-induced tension. We show the extent of MscS activation depends on the cyclodextrin-to-lipid ratio, and that lipids are depleted slower when MscS is present. This has implications in MscS' activation kinetics when distinct membrane scaffolds such as nanodiscs or liposomes are used. We find MscS transits from closed to sub-conducting state(s) before it desensitizes, due to the lack of lipid availability in its vicinity required for closure. Our approach allows for monitoring tension-sensitive states in membrane proteins and screening molecules capable of inducing molecular tension in bilayers.
  • Journal article
    Oqua AI, Manchanda Y, McGlone ER, Jones B, Rouse S, Tomas Aet al., 2024,

    Lipid regulation of the glucagon receptor family

    , Journal of Endocrinology, Vol: 261, ISSN: 0022-0795

    The glucagon receptor family are typical class B1 G protein-coupled receptors (GPCRs) with important roles in metabolism, including the control of pancreas, brain, and liver function. As proteins with seven transmembrane domains, GPCRs are intimately in contact with lipid bilayers and therefore can be putatively regulated by interactions with their lipidic components, including cholesterol, sphingolipids, and other lipid species. Additionally, these receptors, as well as the agonists they bind to, can undergo lipid modifications, which can influence their binding capacity and/or elicit modified or biased signalling profiles. While the effect of lipids, and in particular cholesterol, has been widely studied for other GPCR classes, information about their role in regulating the glucagon receptor family is only beginning to emerge. Here we summarise our current knowledge on the effects of cholesterol modulation of glucagon receptor family signalling and trafficking profiles, as well as existing evidence for specific lipid-receptor binding and indirect effects of lipids via lipid modification of cognate agonists. Finally, we discuss the different methodologies that can be employed to study lipid-receptor interactions and summarise the importance of this area of investigation to increase our understanding of the biology of this family of metabolically relevant receptors.
  • Journal article
    Woubshete M, Cioccolo S, Byrne B, 2024,

    Advances in membrane mimetic systems for manipulation and analysis of membrane proteins; detergents, polymers, lipids and scaffolds

    , ChemPlusChem, Vol: 89, ISSN: 2192-6506

    Extracting membrane proteins from the hydrophobic environment of the biological membrane, in a physiologically relevant and stable state, suitable for downstream analysis remains a challenge. The traditional route to membrane protein extraction has been to use detergents and the last 15 years or so have seen a veritable explosion in the development of novel detergents with improved properties, making them more suitable for individual proteins and specific applications. There have also been significant advances in the development of encapsulation of membrane proteins in lipid based nanodiscs, either directly from the native membrane using polymers allowing effective capture of the protein and protein-associated membrane lipids, or via reconstitution of detergent extracted and purified protein into nanodiscs of defined lipid composition. All of these advances have been successfully applied to the study of membrane proteins via a range of techniques and there have been some spectacular membrane protein structures solved. In addition, the first detailed structural and biophysical analyses of membrane proteins retained within a biological membrane have been reported. Here we summarise and review the recent advances with respect to these new agents and systems for membrane protein extraction, reconstitution and analysis.
  • Journal article
    Lu Y, Duman R, Beilsten-Edmands J, Winter G, Basham M, Evans G, Kamps JJAG, Orville AM, Kwong H-S, Beis K, Armour W, Wagner Aet al., 2024,

    Ray-tracing analytical absorption correction for X-ray crystallography based on tomographic reconstructions.

    , J Appl Crystallogr, Vol: 57, Pages: 649-658, ISSN: 0021-8898

    Processing of single-crystal X-ray diffraction data from area detectors can be separated into two steps. First, raw intensities are obtained by integration of the diffraction images, and then data correction and reduction are performed to determine structure-factor amplitudes and their uncertainties. The second step considers the diffraction geometry, sample illumination, decay, absorption and other effects. While absorption is only a minor effect in standard macromolecular crystallography (MX), it can become the largest source of uncertainty for experiments performed at long wavelengths. Current software packages for MX typically employ empirical models to correct for the effects of absorption, with the corrections determined through the procedure of minimizing the differences in intensities between symmetry-equivalent reflections; these models are well suited to capturing smoothly varying experimental effects. However, for very long wavelengths, empirical methods become an unreliable approach to model strong absorption effects with high fidelity. This problem is particularly acute when data multiplicity is low. This paper presents an analytical absorption correction strategy (implemented in new software AnACor) based on a volumetric model of the sample derived from X-ray tomography. Individual path lengths through the different sample materials for all reflections are determined by a ray-tracing method. Several approaches for absorption corrections (spherical harmonics correction, analytical absorption correction and a combination of the two) are compared for two samples, the membrane protein OmpK36 GD, measured at a wavelength of λ = 3.54 Å, and chlorite dismutase, measured at λ = 4.13 Å. Data set statistics, the peak heights in the anomalous difference Fourier maps and the success of experimental phasing are used to compare the results from the different absorption correction approaches. The strategies using the new analytical absorptio
  • Journal article
    Makrydaki E, Donini R, Krueger A, Royle K, Moya Ramirez I, Kuntz DA, Rose DR, Haslam SM, Polizzi KM, Kontoravdi Cet al., 2024,

    Immobilized enzyme cascade for targeted glycosylation

    , Nature Chemical Biology, Vol: 20, Pages: 732-741, ISSN: 1552-4450

    Glycosylation is a critical post-translational protein modification that affects folding, half-life and functionality. Glycosylation is a non-templated and heterogeneous process because of the promiscuity of the enzymes involved. We describe a platform for sequential glycosylation reactions for tailored sugar structures (SUGAR-TARGET) that allows bespoke, controlled N-linked glycosylation in vitro enabled by immobilized enzymes produced with a one-step immobilization/purification method. We reconstruct a reaction cascade mimicking a glycosylation pathway where promiscuity naturally exists to humanize a range of proteins derived from different cellular systems, yielding near-homogeneous glycoforms. Immobilized β-1,4-galactosyltransferase is used to enhance the galactosylation profile of three IgGs, yielding 80.2-96.3% terminal galactosylation. Enzyme recycling is demonstrated for a reaction time greater than 80 h. The platform is easy to implement, modular and reusable and can therefore produce homogeneous glycan structures derived from various hosts for functional and clinical evaluation.
  • Journal article
    Pazuki RH, Endres RG, 2024,

    Robustness of Turing models and gene regulatory networks with a sweet spot

    , Physical review E (statistical, nonlinear, biological, and soft matter physics), Vol: 109, ISSN: 2470-0045

    Traditional linear stability analysis based on matrix diagonalization is a computationally intensive process for high-dimensional systems of differential equations, posing substantial limitations for the exploration of Turing systems of pattern formation where an additional wave-number parameter needs to be investigated. In this paper, we introduce an efficient and intuitive technique that leverages Gershgorin's theorem to determine upper limits on regions of parameter space and the wave number beyond which Turing instabilities cannot occur. This method offers a streamlined avenue for exploring the phase diagrams of other complex multi-parametric models, such as those found in gene regulatory networks in systems biology. Due to its suitability for the asymptotic limit of infinitely large systems, it predicts the existence of a sweet spot in network size for maximal Jacobian stability.
  • Journal article
    Bonnin RA, Creton E, Perrin A, Girlich D, Emeraud C, Jousset AB, Duque M, Jacquemin A, Hopkins K, Bogaerts P, Glupczynski Y, Pfennigwerth N, Gniadkowski M, Hendrickx APA, van der Zwaluw K, Apfalter P, Hartl R, Studentova V, Hrabak J, Larrouy-Maumus G, Rocha EPC, Naas T, Dortet Let al., 2024,

    Spread of carbapenemase-producing Morganella spp from 2013 to 2021: a comparative genomic study.

    , Lancet Microbe, Vol: 5, Pages: e547-e558

    BACKGROUND: Morganella spp are opportunistic pathogens involved in various infections. Intrinsic resistance to multiple antibiotics (including colistin) combined with the emergence of carbapenemase producers reduces the number of active antimicrobials. The aim of this study was to characterise genetic features related to the spread of carbapenem-resistant Morganella spp. METHODS: This comparative genomic study included extensively drug-resistant Morganella spp isolates collected between Jan 1, 2013, and March 1, 2021, by the French National Reference Center (NRC; n=68) and European antimicrobial resistance reference centres in seven European countries (n=104), as well as one isolate from Canada, two reference strains from the Pasteur Institute collection (Paris, France), and two colistin-susceptible isolates from Bicêtre Hospital (Kremlin-Bicêtre, France). The isolates were characterised by whole-genome sequencing, antimicrobial susceptibility testing, and biochemical tests. Complete genomes from GenBank (n=103) were also included for genomic analysis, including phylogeny and determination of core genomes and resistomes. Genetic distance between different species or subspecies was performed using average nucleotide identity (ANI). Intrinsic resistance mechanisms to polymyxins were investigated by combining genetic analysis with mass spectrometry on lipid A. FINDINGS: Distance analysis by ANI of 275 isolates identified three groups: Morganella psychrotolerans, Morganella morganii subspecies sibonii, and M morganii subspecies morganii, and a core genome maximum likelihood phylogenetic tree showed that the M morganii isolates can be separated into four subpopulations. On the basis of these findings and of phenotypic divergences between isolates, we propose a modified taxonomy for the Morganella genus including four species, Morganella psychrotolerans, Morganella sibonii, Morganella morganii, and a new species represented by a unique environmental isolate. W
  • Journal article
    Delhaye G, van der Linde S, Bauman D, Orme CDL, Suz LM, Bidartondo MIet al., 2024,

    Ectomycorrhizal fungi are influenced by ecoregion boundaries across Europe

    , Global Ecology and Biogeography, Vol: 33, ISSN: 1466-822X

    AimEcoregions and the distance decay in community similarity are fundamental concepts in biogeography and conservation biology that are well supported across plants and animals, but not fungi. Here we test the relevance of these concepts for ectomycorrhizal (ECM) fungi in temperate and boreal regions.LocationEurope.Time Period2008–2015.Major Taxa StudiedEctomycorrhizal fungi.MethodsWe used a large dataset of ~24,000 ectomycorrhizas, assigned to 1350 operational taxonomic units, collected from 129 forest plots via a standardized protocol. We investigated the relevance of ecoregion delimitations for ECM fungi through complementary methodological approaches based on distance decay models, multivariate analyses and indicator species analyses. We then evaluated the effects of host tree and climate on the observed biogeographical distributions.ResultsEcoregions predict large-scale ECM fungal biodiversity patterns. This is partly explained by climate differences between ecoregions but independent from host tree distribution. Basidiomycetes in the orders Russulales and Atheliales and producing epigeous fruiting bodies, with potentially short-distance dispersal, show the best agreement with ecoregion boundaries. Host tree distribution and fungal abundance (as opposed to presence/absence only) are important to uncover biogeographical patterns in mycorrhizas.Main ConclusionsEcoregions are useful units to investigate eco-evolutionary processes in mycorrhizal fungal communities and for conservation decision-making that includes fungi.
  • Journal article
    Cai JA, Christophides GK, 2024,

    Immune interactions between mosquitoes and microbes during midgut colonization

    , CURRENT OPINION IN INSECT SCIENCE, Vol: 63, ISSN: 2214-5745
  • Journal article
    Moulick D, Majumdar A, Choudhury A, Das A, Chowardhara B, Pattnaik BK, Dash GK, Murmu K, Bhutia KL, Upadhyay MK, Yadav P, Dubey PK, Nath R, Murmu S, Jana S, Sarkar S, Garai S, Ghosh D, Mondal M, Chandra Santra S, Choudhury S, Brahmachari K, Hossain Aet al., 2024,

    Emerging concern of nano-pollution in agro-ecosystem: Flip side of nanotechnology.

    , Plant Physiol Biochem, Vol: 211

    Nanomaterials (NMs) have proven to be a game-changer in agriculture, showcasing their potential to boost plant growth and safeguarding crops. The agricultural sector has widely adopted NMs, benefiting from their small size, high surface area, and optical properties to augment crop productivity and provide protection against various stressors. This is attributed to their unique characteristics, contributing to their widespread use in agriculture. Human exposure from various components of agro-environmental sectors (soil, crops) NMs residues are likely to upsurge with exposure paths may stimulates bioaccumulation in food chain. With the aim to achieve sustainability, nanotechnology (NTs) do exhibit its potentials in various domains of agriculture also have its flip side too. In this review article we have opted a fusion approach using bibliometric based analysis of global research trend followed by a holistic assessment of pros and cons i.e. toxicological aspect too. Moreover, we have also tried to analyse the current scenario of policy associated with the application of NMs in agro-environment.
  • Journal article
    Christman ME, Spears LR, Burchfield EK, Pearse WD, Strange JP, Ramirez RAet al., 2024,

    Bumble bee responses to climate and landscapes: Investigating habitat associations and species assemblages across geographic regions in the United States of America.

    , Glob Chang Biol, Vol: 30

    Bumble bees are integral pollinators of native and cultivated plant communities, but species are undergoing significant changes in range and abundance on a global scale. Climate change and land cover alteration are key drivers in pollinator declines; however, limited research has evaluated the cumulative effects of these factors on bumble bee assemblages. This study tests bumble bee assemblage (calculated as richness and abundance) responses to climate and land use by modeling species-specific habitat requirements, and assemblage-level responses across geographic regions. We integrated species richness, abundance, and distribution data for 18 bumble bee species with site-specific bioclimatic, landscape composition, and landscape configuration data to evaluate the effects of multiple environmental stressors on bumble bee assemblages throughout 433 agricultural fields in Florida, Indiana, Kansas, Kentucky, Maryland, South Carolina, Utah, Virginia, and West Virginia from 2018 to 2020. Distinct east versus west groupings emerged when evaluating species-specific habitat associations, prompting a detailed evaluation of bumble bee assemblages by geographic region. Maximum temperature of warmest month and precipitation of driest month had a positive impact on bumble bee assemblages in the Corn Belt/Appalachian/northeast, southeast, and northern plains regions, but a negative impact on the mountain region. Further, forest land cover surrounding agricultural fields was highlighted as supporting more rich and abundant bumble bee assemblages. Overall, climate and land use combine to drive bumble bee assemblages, but how those processes operate is idiosyncratic and spatially contingent across regions. From these findings, we suggested regionally specific management practices to best support rich and abundant bumble bee assemblages in agroecosystems. Results from this study contribute to a better understanding of climate and landscape factors affecting bumble bees and their habit
  • Journal article
    Riva F, Haddad N, Fahrig L, Banks-Leite Cet al., 2024,

    Principles for area-based biodiversity conservation

    , ECOLOGY LETTERS, Vol: 27, ISSN: 1461-023X
  • Journal article
    Luiselli J, Overcast I, Rominger A, Ruffley M, Morlon H, Rosindell Jet al., 2024,

    Detecting the ecological footprint of selection

    , PLoS One, Vol: 19, ISSN: 1932-6203

    The structure of communities is influenced by many ecological and evolutionary processes, but the way these manifest in classic biodiversity patterns often remains unclear. Here we aim to distinguish the ecological footprint of selection-through competition or environmental filtering-from that of neutral processes that are invariant to species identity. We build on existing Massive Eco-evolutionary Synthesis Simulations (MESS), which uses information from three biodiversity axes-species abundances, genetic diversity, and trait variation-to distinguish between mechanistic processes. To correctly detect and characterise competition, we add a new and more realistic form of competition that explicitly compares the traits of each pair of individuals. Our results are qualitatively different to those of previous work in which competition is based on the distance of each individual's trait to the community mean. We find that our new form of competition is easier to identify in empirical data compared to the alternatives. This is especially true when trait data are available and used in the inference procedure. Our findings hint that signatures in empirical data previously attributed to neutrality may in fact be the result of pairwise-acting selective forces. We conclude that gathering more different types of data, together with more advanced mechanistic models and inference as done here, could be the key to unravelling the mechanisms of community assembly and question the relative roles of neutral and selective processes.
  • Journal article
    Duncan SM, Carbajo CG, Nagar R, Zhong Q, Breen C, Ferguson MAJ, Tiengwe Cet al., 2024,

    Generation of a bloodstream form Trypanosoma brucei double glycosyltransferase null mutant competent in receptor-mediated endocytosis of transferrin.

    , PLoS Pathog, Vol: 20

    The bloodstream form of Trypanosoma brucei expresses large poly-N-acetyllactosamine (pNAL) chains on complex N-glycans of a subset of glycoproteins. It has been hypothesised that pNAL may be required for receptor-mediated endocytosis. African trypanosomes contain a unique family of glycosyltransferases, the GT67 family. Two of these, TbGT10 and TbGT8, have been shown to be involved in pNAL biosynthesis in bloodstream form Trypanosoma brucei, raising the possibility that deleting both enzymes simultaneously might abolish pNAL biosynthesis and provide clues to pNAL function and/or essentiality. In this paper, we describe the creation of a TbGT10 null mutant containing a single TbGT8 allele that can be excised upon the addition of rapamycin and, from that, a TbGT10 and TbGT8 double null mutant. These mutants were analysed by lectin blotting, glycopeptide methylation linkage analysis and flow cytometry. The data show that the mutants are defective, but not abrogated, in pNAL synthesis, suggesting that other GT67 family members can compensate to some degree for loss of TbGT10 and TbGT8. Despite there being residual pNAL synthesis in these mutants, certain glycoproteins appear to be particularly affected. These include the lysosomal CBP1B serine carboxypeptidase, cell surface ESAG2 and the ESAG6 subunit of the essential parasite transferrin receptor (TfR). The pNAL deficient TfR in the mutants continued to function normally with respect to protein stability, transferrin binding, receptor mediated endocytosis of transferrin and subcellular localisation. Further the pNAL deficient mutants were as viable as wild type parasites in vitro and in in vivo mouse infection experiments. Although we were able to reproduce the inhibition of transferrin uptake with high concentrations of pNAL structural analogues (N-acetylchito-oligosaccharides), this effect disappeared at lower concentrations that still inhibited tomato lectin uptake, i.e., at concentrations able to outcompete lectin-
  • Journal article
    Affinito F, Kordas RL, Matias MG, Pawar Set al., 2024,

    Metabolic plasticity drives mismatches in physiological traits between prey and predator

    , Communications Biology, Vol: 7, ISSN: 2399-3642

    Metabolic rate, the rate of energy use, underpins key ecological traits of organisms, from development and locomotion to interaction rates between individuals. In a warming world, the temperature-dependence of metabolic rate is anticipated to shift predator-prey dynamics. Yet, there is little real-world evidence on the effects of warming on trophic interactions. We measured the respiration rates of aquatic larvae of three insect species from populations experiencing a natural temperature gradient in a large-scale mesocosm experiment. Using a mechanistic model we predicted the effects of warming on these taxa’s predator-prey interaction rates. We found that species-specific differences in metabolic plasticity lead to mismatches in the temperature-dependence of their relative velocities, resulting in altered predator-prey interaction rates. This study underscores the role of metabolic plasticity at the species level in modifying trophic interactions and proposes a mechanistic modelling approach that allows an efficient, high-throughput estimation of climate change threats across species pairs.
  • Journal article
    Bradfer-Lawrence T, Duthie B, Abrahams C, Adam M, Barnett RJ, Beeston A, Darby J, Dell B, Gardner N, Gasc A, Heath B, Howells N, Janson M, Kyoseva M-V, Luypaert T, Metcalf OC, Nousek-McGregor AE, Poznansky F, Ross SRP-J, Sethi S, Smyth S, Waddell E, Froidevaux JSPet al., 2024,

    The Acoustic Index User's Guide: A practical manual for defining, generating and understanding current and future acoustic indices

    , METHODS IN ECOLOGY AND EVOLUTION, ISSN: 2041-210X
  • Journal article
    Rosindell J, Manson K, Gumbs R, Pearse WD, Steel Met al., 2024,

    Phylogenetic Biodiversity Metrics Should Account for Both Accumulation and Attrition of Evolutionary Heritage

    , SYSTEMATIC BIOLOGY, Vol: 73, Pages: 158-182, ISSN: 1063-5157
  • Journal article
    Sandoval Calle D, Prentice IC, Nobrega R, 2024,

    Simple process-led algorithms for simulating habitats (SPLASH v 2.0): robust calculations of water and energy fluxes

    , Geoscientific Model Development, Vol: 17, Pages: 4229-4309, ISSN: 1991-959X

    The current representation of key processes in Land Surface Models (LSM) for estimating water and energy balances still relies heavily on empirical equations that require calibration oriented to site-specific characteristics. When multiple parameters are used, different combinations of parameter values can produce equally acceptable results, leading to a risk of obtaining “right answers for wrong reasons”, compromising the reproducibility of the simulations and limiting the ecological interpretability of the results. To address this problem and reduce the need for free parameters, here we present novel formulations based on first-principles to calculate key components of water and energy balances, extending the already parsimonious SPLASHmodel v.1.0 (Davis et al. 2017, GMD). We found analytical solutions for many processes, enabling us to increase spatial resolution and include the terrain effects directly in the calculations without unreasonably inflating computational demands. This calibration-free model estimates quantities such as net radiation, evapotranspiration, condensation, soil water content,surface runoff, subsurface lateral flow and snow-water equivalent. These quantities are derived from readily meteorological data such as near-surface air temperature, precipitation and solar radiation, and soil physical properties. Whenever empirical formulations were required, e.g. pedotransfer functions and albedo-snow cover relationships, we selected and optimized thebest-performing equations through a combination of remote sensing and globally distributed terrestrial observational datasets. Simulations at global scales at different resolutions were run to evaluate spatial patterns, while simulations with point-based observations were run to evaluate seasonal patterns using data from hundreds of stations and comparisons with the VIC-3L model, demonstrating improved performance based on statistical tests and observational comparisons. In summary, our m
  • Journal article
    Connolly JB, Burt A, Christophides G, Diabate A, Habtewold T, Hancock PA, James AA, Kayondo JK, Lwetoijera DW, Manjurano A, McKemey AR, Santos MR, Windbichler N, Randazzo Fet al., 2024,

    Considerations for first field trials of low-threshold gene drive for malaria vector control

    , Malaria Journal, Vol: 23, ISSN: 1475-2875

    Sustainable reductions in African malaria transmission require innovative tools for mosquito control. One proposal involves the use of low-threshold gene drive in Anopheles vector species, where a 'causal pathway' would be initiated by (i) the release of a gene drive system in target mosquito vector species, leading to (ii) its transmission to subsequent generations, (iii) its increase in frequency and spread in target mosquito populations, (iv) its simultaneous propagation of a linked genetic trait aimed at reducing vectorial capacity for Plasmodium, and (v) reduced vectorial capacity for parasites in target mosquito populations as the gene drive system reaches fixation in target mosquito populations, causing (vi) decreased malaria incidence and prevalence. Here the scope, objectives, trial design elements, and approaches to monitoring for initial field releases of such gene dive systems are considered, informed by the successful implementation of field trials of biological control agents, as well as other vector control tools, including insecticides, Wolbachia, larvicides, and attractive-toxic sugar bait systems. Specific research questions to be addressed in initial gene drive field trials are identified, and adaptive trial design is explored as a potentially constructive and flexible approach to facilitate testing of the causal pathway. A fundamental question for decision-makers for the first field trials will be whether there should be a selective focus on earlier points of the pathway, such as genetic efficacy via measurement of the increase in frequency and spread of the gene drive system in target populations, or on wider interrogation of the entire pathway including entomological and epidemiological efficacy. How and when epidemiological efficacy will eventually be assessed will be an essential consideration before decisions on any field trial protocols are finalized and implemented, regardless of whether initial field trials focus exclusively on the measur

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