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Berry, P.

Publications and source records attributed to Berry, P..

4 recordsLinked to original sources

Insulin resistance modifies longitudinal multi-omics responses to habitual diet

How habitual diet influences the gut microbiome and plasma metabolome across insulin resistance states remains unclear. We conducted year-long multi-omics profiling of 71 deeply phenotyped adults, integrating repeated assessments of diet, metabolome, gut microbiome, clinical laboratory measures, and inflammatory markers. Using gold-standard insulin suppression tests and machine learning-derived dietary patterns, we examined how dietary patterns relate to metabolic and microbial landscapes by insulin resistance status. Insulin-sensitive individuals exhibited stronger and more numerous diet-omics associations than insulin-resistant individuals, identifying metabolic flexibility as a central determinant of dietary responsiveness. Parabacteroides emerged as a candidate microbial mediator between refined carbohydrate-rich dietary patterns and host metabolic signatures. Integrated into a cardiovascular risk prediction model, diet, metabolites, microbial taxa, and immune markers each contributed to 10-year atherosclerotic cardiovascular disease risk. These findings show that inter-individual variation in cardiometabolic risk partly reflects differences in molecular responsiveness to habitual diet, informing precision nutrition and cardiovascular prevention.

molecular biology↗

Pathologic polyglutamine aggregation begins with a self-poisoning polymer crystal

A long-standing goal of amyloid research has been to characterize the structural basis of the rate-determining nucleating event. However, the ephemeral nature of nucleation has made this goal unachievable with existing biochemistry, structural biology, and computational approaches. Here, we addressed that limitation for polyglutamine (polyQ), a polypeptide sequence that causes Huntingtons and other amyloid-associated neurodegenerative diseases when its length exceeds a characteristic threshold. To identify essential features of the polyQ amyloid nucleus, we used a direct intracellular reporter of self-association to quantify frequencies of amyloid appearance as a function of concentration, conformational templates, and rational polyQ sequence permutations. We found that nucleation of pathologically expanded polyQ involves segments of three glutamine (Q) residues at every other position. We demonstrate using molecular simulations that this pattern encodes a four-stranded steric zipper with interdigitated Q side chains. Once formed, the zipper poisoned its own growth by engaging naive polypeptides on orthogonal faces, in a fashion characteristic of polymer crystals with intramolecular nuclei. We further show that self-poisoning can be exploited to block amyloid formation, by genetically oligomerizing polyQ prior to nucleation. By uncovering the physical nature of the rate-limiting event for polyQ aggregation in cells, our findings elucidate the molecular etiology of polyQ diseases.

biophysics↗

The polyglutamine amyloid nucleus in living cells is monomeric and has competing dimensions of order

A long-standing goal of the study of amyloids has been to characterize the structural basis of the rate-determining nucleating event. However, the ephemeral nature of that event has made it inaccessible to classical biochemistry, structural biology, and computational approaches. Here, we addressed that limitation by measuring the dependence of amyloid formation on concentration and conformational templates in living cells, whose volumes are sufficiently small to resolve the outcomes of independent nucleation events. We characterized numerous rationally designed sequence variants of polyglutamine (polyQ), a polypeptide that precipitates Huntingtons and other amyloid-associated neurodegenerative diseases when its length exceeds a characteristic threshold. This effort uncovered a pattern of approximately twelve Qs, only for polypeptides exceeding the clinical length threshold, that allow for amyloid nucleation to occur spontaneously within single polypeptides. Nucleation was inhibited by intermolecular phase separation. Using atomistic molecular dynamics simulations, we found that the pattern encodes a minimal steric zipper of interdigitated side chains. Lateral growth of the steric zipper competed with axial growth to produce "pre-amyloid" oligomers. By illuminating the structural mechanism of polyQ amyloid formation in cells, our findings reveal a potential molecular etiology for polyQ diseases, and may provide a roadmap for the design of new therapies.

biophysics↗

Development of a pest threshold decision support system for minimising damage to winter wheat from wheat bulb fly, Delia coarctata

Graphical AbstractIn this article we describe two predictive models that can be used for the integrated management of wheat bulb fly. Our first model is a pest level prediction model and our second model predicts the number of shoots a winter wheat crop will achieve by the terminal spikelet developmental stage. We revise and update current wheat bulb fly damage thresholds and combine this with our two models to devise a tolerance-based decision support system that can be used to minimise the risk of crop damage by wheat bulb fly. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=152 SRC="FIGDIR/small/435242v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@ee5b9aorg.highwire.dtl.DTLVardef@c0197corg.highwire.dtl.DTLVardef@1c9519eorg.highwire.dtl.DTLVardef@d6a52_HPS_FORMAT_FIGEXP M_FIG C_FIG SummaryWheat bulb fly, Delia coarctata, is an important pest of winter wheat in the UK, causing significant damage of up to 4 t ha-1. Accepted population thresholds for D. coarctata are 250 eggs m-2 for crops sown up to the end of October and 100 eggs m-2 for crops sown from November. Fields with populations of D. coarctata that exceed the thresholds are at higher risk of experiencing economically damaging pest infestations. In the UK, recent withdrawal of insecticides means that only a seed treatment is available for chemical control of D. coarctata, however this is only effective for late-sown crops (November onwards) and accurate estimations of annual population levels are required to ensure a seed treatment is applied if needed. As a result of the lack of post-drilling control strategies, the management of D. coarctata is becoming increasingly reliant on non-chemical methods of control. Control strategies that are effective in managing similar stem-boring pests of wheat include sowing earlier and using higher seed rates to produce crops with more shoots and greater tolerance to shoot damage. In this study we develop two predictive models that can be used for integrated D. coarctata management. The first is an updated pest level prediction model that predicts D. coarctata populations from meteorological parameters with a predictive accuracy of 70%, which represents a significant improvement on the previous D. coarctata population prediction model. Our second model predicts the maximum number of shoots for a winter wheat crop that would be expected at the terminal spikelet development stage. This shoot number model uses information about the thermal time from plant emergence to terminal spikelet, leaf phyllochron length, plant population, and sowing date to predict the degree of tolerance a crop will have against D. coarctata. The shoot number model was calibrated against data collected from five field experiments and tested against data from four experiments. Model testing demonstrated that the shoot number model has a predictive accuracy of 70%. A decision support system using these two models for the sustainable management of D. coarcata risk is described.

plant biology↗