bluuebunny/crossref_metadata_2025 huggingface dataset:
Sweeps in space: leveraging geographic data to identify beneficial alleles inAnopheles gambiae
Authors: Rehmann Clara T. , Small Scott T. , Ralph Peter L. , Kern Andrew D.
Published: February 2025

As organisms adapt to environmental changes, natural selection modifies the frequency of non-neutral alleles. For beneficial mutations, the outcome of this process may be a selective sweep, in which an allele rapidly increases in frequency and perhaps reaches fixation within a population. Selective sweeps have well-studied effects on patterns of local genetic variation in panmictic populations, but much less is known about the dynamics of sweeps in continuous space. In particular, because limited movement across a landscape leads to unique patterns of population structure, spatial dynamics may influence the trajectory of selected mutations. Here, we use forward-in-time, individual-based simulations in continuous space to study the impact of space on beneficial mutations as they sweep through a population. In particular, we show that selection changes the joint distribution of allele frequency and geographic range occupied by a focal allele and demonstrate that this signal can be used to identify selective sweeps. We then leverage this signal to identify in-progress selective sweeps within the malaria vectorAnopheles gambiae, a species under strong selection pressure from vector control measures. By considering space, we identify multiple previously undescribed variants with potential phenotypic consequences, including mutations im-pacting known IR-associated genes and altering protein structure and properties. Our results demonstrate a novel signal for detecting selection in spatial population genetic data that may have implications for genomic surveillance and understanding geographic patterns of genetic variation.
Curvature generation and engineering principles fromShewanella oneidensismulti-flagellin flagellum
Authors: Lou Qing , Fan Hongcheng , Liu Yang , Miller Jeff F. , Huang Yu , Zhou Z. Hong
Published: February 2025

Motility driven by nanoscale flagella is vital to microbial survival and spread in fluid and structured environments. Absence of native flagellum structures, however, has limited our understanding of the mechanisms of microbial motility, hindering efforts to engineer microbe-based microbots for applications. Here, by cryogenic electron tomography (cryoET) and microscopy (cryoEM), we determined the structural basis of motility driven by the single flagellum anchored to one pole ofShewanella oneidensisMR-1 (S. oneidensis), an electrogenic bacterium commonly used in biotechnology. The structures of the curved flagellum, representing the conformation during motion, are captured, allowing delineation of molecular interactions among the subunits of its three components—filament, hook, and hook-filament junction. The structures of the filament, i.e., the propeller, reveal a varying composition of the flagellin isoforms FlaA and FlaB throughout the filament. Distinct inter-subunit interactions are identified at residues 129 and 134, which are the major determinants of functional differences in motility for the two isoforms. The hook—the universal joint—has a significantly larger curvature than that of the filament, despite both containing 11 curvature-defining conformers of their subunits. Transition between the propeller and universal joint is mediated by hook-filament junction, composed of 11 subunits of FlgK and FlgL, reconciling incompatibility between the filament and hook. Correlating these compositional and structural transitions with varying levels of curvature in flagellar segments reveals molecular mechanism enabling propulsive motility. Mechanistic understandings fromS. oneidensissuggest engineering principles for nanoscale biomimetic systems.

Graphic abstract
Pneumolysin nanopores with 20 nm inner diameter to characterize the size and shape of Tau oligomers
Authors: Mukhopadhyay Anasua , Chanakul Wachara , Larpin Yu-Noel , Awasthi Saurabh , Protopopova Anna D. , Köffel René , Ianiro Alessandro , Mayer Michael
Published: February 2025

Protein nanopores are emerging as versatile tools to fingerprint biomolecules due to their capability to characterize single molecules without the requirement for labeling. A long-standing challenge with biological nanopores is, however, that large biomolecules in their native state are often too large to enter these pores. Here, we report the self-assembly of approximately 35 ± 5 pneumolysin (PLY) toxins to a stable transmembrane pore with a diameter of 20 ± 3 nm, an effective length of 9.5 nm, and excellent low noise characteristics in the context of nanopore-based resistive pulse recordings. The exceptionally large pore diameter enables the characterization of the size and shape of individual proteins and protein complexes ranging in molecular weight from 50 kDa to 0.8 MDa. Moreover, PLY pores make it possible to follow the time course of the formation of oligomers of tau protein in solution by revealing the size, monomer number, approximate shape, and abundance of these oligomers. At least four characteristics make PLY pores well suited for the characterization of heterogeneous amyloid oligomer samples: First, they are not prone to clogging. Second, they provide label-free single particle analysis. Third, their large diameters make it possible to characterize a wide range of amyloid oligomer sizes with high resolution. And fourth, resistive pulse recordings from these pores provide stable open pore current baselines with low electrical noise.
A genetically-diverse mouse model reveals a complex gene-environment regulation of cognitive resilience and susceptibility to Alzheimer’s disease
Authors: Dunn Amy R. , Kaur Harpreet , Dai Miko , Charland Kevin , Ouellette Andrew R. , Hadad Niran , Doyle Patricia H. , Acosta Glen H.G. , Litkowski Elizabeth , Hohman Timothy J. , O’Connell Kristen M.S. , Kaczorowski Catherine C.
Published: February 2025

Alzheimer’s disease (AD) has a complex etiology arising from largely unknown interactions between genetic and environmental factors. Even in populations with highly penetrant, disease-causing familial Alzheimer’s disease mutations, there is wide variation in disease onset and progression, suggesting that clinical symptoms are modified by genetics and environment. Identification of such modifiers is critical, as mechanisms that promote resilience to deleterious AD mutations, unhealthy diet, or aging represent promising therapeutic targets for AD and other causes of cognitive decline; global resilience factors that protect against multiple “hits” are among the highest priority for discovery. Both genetic and environmental protective factors in AD have been identified; however, interacting gene-environment (GxE) factors are incredibly difficult to study in human populations given complex genomes, poor self-reporting, data from underrepresented groups, and incompletely documented exposomes. Here, we used a population of mouse strains that model the polygenic nature of human AD to characterize individuals that display cognitive resilience to high-risk genetic and dietary perturbations to define and quantitate roles for genetics, sex, age, diet, and complex interactions that are nearly impossible to elucidate from humans or inbred AD mice. We found that some strains showed improved AD-related outcomes when fed a high-fat high-sugar (HFHS) diet, suggesting the need for personalized recommendations for dietary interventions in AD. We found a locus on Chr 10 that was associated with cognitive resilience to AD in females, and this association was strengthened by HFHS diet, directly pointing to an interaction between specific genetic and environmental factors in AD risk and resilience. In conclusion, this study is the first of its kind to explore characteristics of resilience and GxE interactions in a genetically diverse mouse model. We present a subset of strains that exemplify global cognitive resilience to be leveraged for deep mechanistic studies aimed toward development of resilience-based and personalized therapeutic interventions.

Highlights

Comprehensive phenotyping of genetically diverse mice (AD-BXDs) revealed cognitively resilient strains to extreme genetic and dietary risk factors

Locus on chromosome 10 harbors resilience factor/s that buffer the impact of familial AD mutations, female sex, and high-fat high-sugar diet

Human cognitive resilience genes are conserved in AD-BXDs

About 10% of female AD-BXD mouse strains showed an improved AD-related cognitive outcome on a HFHS diet.
Functional relocation of the maize chloroplastatpBgene to the nucleus restores photosynthetic competence to a gene-edited non-photosynthetic mutant
Authors: Mangu Venkata RamanaRao , Jenkins Kelsey , Pratt Anna , Boltz Kara A , Pazouki Leila , Hui Alice Y. , Staub Jeffrey M.
Published: February 2025

We present a novel approach to photosynthetic gene engineering in maize using a nuclear-encoded, chloroplast-targeted TALE-cytidine deaminase enzyme to create non-photosynthetic knockout mutants of the chloroplastrbcLgene. An off-target mutation in the adjacentatpBgene, encoding the β subunit of ATP synthase, was consistently found in all edited lines, identified as pigment-deficient in tissue culture. These double mutants, carrying mutations in both genes, were purified to homoplasmy using unique leaf-base regeneration techniques. To test mutation complementation and identify the causal gene, nuclear transgenic lines expressing chloroplast-targeted RbcL and AtpB proteins were generated. The results show that nuclear expression of AtpB restores chlorophyll accumulation and supports wild-type growth in tissue culture.
SARS-CoV-2 infection of the brain: the K18-hACE2 mouse model to illustrate the role and response of the vasculature in neurotropic viral infection
Authors: Neck Simon De , Penrice-Randal Rebekah , Hetzel Udo , Seehusen Frauke , Sharma Parul , Bentley Eleanor G. , Helminger Barbara , Kirby Adam , Balistreri Giuseppe , Stewart James P. , Kipar Anja
Published: February 2025

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) primarily affects the respiratory tract and lungs; however, the associated disease, coronavirus disease 2019 (COVID-19) can also involve the central nervous system. The pathomechanisms underlying neurological impairments in COVID-19 and post COVID-19 condition remain incompletely understood, hence experimental studies under defined conditions, in a suitable animal model, can help to clarify the effect of SARS-CoV-2 infection in the brain. The K18-hACE2 mouse represents such a model, as intranasal challenge with SARS-CoV-2 VOC generally results in widespread neuronal infection with limited tissue response in the brain, consistent with a mild non-suppurative (meningo)encephalitis, with microgliosis, astrogliosis and (peri)vascular leukocyte infiltrates but no evidence of infection of vessel structures. The present study used this model to address the hypothesis that the vascular reaction is secondary to the neuronal infection. It confirmed that in intranasally challenged K18-hACE2 mice the virus targeted the neurons without overt neuropathic effect, whilst sparing the blood vessels, and further characterised the resulting inflammatory response in the brain in situ and through bulk RNA sequencing. The former highlighted the recruitment of leukocytes (neutrophils, monocytes/macrophages, and lymphocytes) via postcapillary venules, with their accumulation in the perivascular space and occasional emigration into the neuroparenchyma, without targeting and/or damage to the vessel wall. At the transcriptome level, this was accompanied by positive enrichment of pathways and the upregulation of genes involved in both the inflammatory reaction and the recruitment (including adhesion and migration) and activity of the leukocytes. We also found morphological and molecular evidence of subtle impairment of blood-brain barrier function, i.e. increased permeability. The results obtained from the model indicate that SARS-CoV-2 infection of the neurons induces neuroinflammation, with leukocyte recruitment and activation as well as blood-brain barrier dysfunction. These data can help to understand more fully the reaction of the CNS in COVID-19 patients, and neurotropic virus infections in general.
Acetylation of histone H2B on lysine 120 regulates BRD4 binding to intergenic enhancers
Authors: Hamilton Gregory A. , Ruiz Penelope D. , Ye Kenny , Gamble Matthew J.
Published: February 2025

BRD4 is a bromodomain-containing transcriptional co-regulator that plays important roles in driving transcription by binding to histone acetyl-lysines at enhancers and promoters while recruiting additional transcriptional cofactors. While the mechanisms by which BRD4 regulates transcription have been explored, the critical acetylations primarily responsible for targeting it to chromatin remain unclear. Through a machine learning approach, we determined that distinct sets of histone acetylations dominate the prediction of chromatin accessibility and BRD4 binding in distinct chromatin contexts (e.g. intergenic enhancers, gene body enhancers and promoters). Using human fibroblasts engineered to predominantly express specific histones with lysine-to-arginine mutations, we demonstrate that one such acetylation, H2BK120ac, is required to recruit BRD4 specifically to intergenic enhancers, while not affecting chromatin accessibility. Loss of H2BK120ac did not affect BRD4 binding to either promoters or gene body enhancers, demonstrating that the rules governing BRD4 recruitment to regulatory regions depends on the specific genomic context. Highlighting the importance of H2BK120ac in directing BRD4 recruitment, we found that expression of the H2BK120R mutant significantly reduces the phenotypes driven by BRD4-NUT, an oncogenic fusion protein that drives NUT midline carcinoma. This work demonstrates the critical nature that genomic context plays in BRD4 recruitment to distinct classes of regulatory elements, and suggests that intergenic and gene body enhancers represent classes of functional distinct elements.
Powerful and accurate case-control analysis of spatial molecular data with deep learning-defined tissue microniches
Authors: Reshef Yakir , Sood Lakshay , Curtis Michelle , Rumker Laurie , Stein Daniel J. , Palshikar Mukta G. , Nayar Saba , Filer Andrew , Jonsson Anna Helena , Korsunsky Ilya , Raychaudhuri Soumya
Published: February 2025

As spatial molecular data grow in scope and resolution, there is a pressing need to identify key spatial structures associated with disease. Current approaches often rely on hand-crafted features such as local abundances of manually annotated, discrete cell types, which may overlook important signals. Here we introduce variational inference-based microniche analysis (VIMA), a method that combines deep learning with principled statistics to discover associated spatial features with greater flexibility and precision. VIMA uses a variational autoencoder to extract numerical “fingerprints” from small tissue patches that capture their biological content. It uses these fingerprints to define a large number of “microniches” – small, potentially overlapping groups of tissue patches with highly similar biology that span multiple samples. It then uses rigorous statistics to identify microniches whose abundance correlates with case-control status. We show in simulations that VIMA is well calibrated and more powerful and accurate than other approaches. We then apply VIMA to a 140-gene spatial transcriptomics dataset in Alzheimer’s dementia, a 54-marker CO-Detection by indEXing (CODEX) dataset in ulcerative colitis (UC), and a 7-marker immunohistochemistry dataset in rheumatoid arthritis (RA), in each case recapitulating known biology and identifying novel spatial features of disease.
Large scale laboratory evolution uncovers clinically relevant collateral antibiotic sensitivity
Authors: Chowdhury Farhan R. , Banari Veronica , Lesnic Vlada , Zhanel George G. , Findlay Brandon L.
Published: February 2025

The increasing prevalence of antibiotic resistance is a critical challenge, necessitating the development of strategies to mitigate the evolution of resistance. Collateral sensitivity (CS)-based sequential therapies have been proposed to mitigate resistance evolution. However, the evolutionary repeatability of CS across different experimental conditions and its clinical relevance remain underexplored, hindering its potential for translation into clinical practice. Here, we evolve 20-24 lineages ofE. coliagainst tigecycline (TIG) and piperacillin (PIP), antibiotics suggested to produce CS, through three separate laboratory adaptive evolution (ALE) platforms to test for the robustness of CS interactions and the effect of the choice of ALE on CS evolution. We generate over 130 resistant mutants and 540 resistance and collateral sensitivity measurements to identify a CS relationship between TIG and polymyxin B (POL) that is highly repeatable across all the ALEs tested, suggesting that this CS interaction is preserved across different evolution microenvironments. We determine the mechanism of this novel CS by showing that cells resistant to TIG deactivate the Lon protease and overproduce negatively charged exopolysaccharides, which in turn attracts the polycationic POL and renders cells hypersensitive to the drug. We find that this CS relationship is present in a clinical dataset of over 750 uropathogenic MDRE. coliisolates, and show that the soft agar gradient evolution (SAGE) platform best predicts collateral effects (CS, neutrality or cross resistance) in this dataset. Our study provides a framework for identifying robust CS with clinical implications that can reduce the emergence of resistance to our existing antibiotics.
CommercialSaccharomyces cerevisiaebaker’s yeasts: strain redundancy, genome plasticity, and colonization of the sourdough environment and the human body
Authors: Rácz Hanna Viktória , Imre Alexandra , Németh Bálint , Antunovics Zsuzsa , Bazenova Rizagul , Bendixsen Devin , Harmath Andrea , Herman Lilla , Fülep Ádám , Lopandic Ksenija , Máthé Endre , Póliska Szilárd , Pócsi István , Stelkens Rike , Pfliegler Walter P.
Published: February 2025

Leavening dough is one of the most widespread applications of fermentative yeast and the most common practice for the general public to come into contact with microbial cultures.Saccharomyces cerevisiaeis the typical species used for dough making, but the evolutionary origin of strains isolated from dough is mixed. Here, using 49 newly sequenced and 183 previously described isolates from the bakery environment, we show that the traditional strains used in Europe for sourdough making are more closely related to Chinese Mantou sourdough lineages than to commercially used baker yeast strains. Surprisingly, the expansion of these traditional European strains into other human-associated niches, including the human body, has been very limited. This is in stark contrast to the Mixed-origin clade commercial baking yeasts, which consists of only a few globally distributed clonal lineages that dominate the yeast market and recurrently colonize sourdoughs and human hosts. These clonal lineages consistently maintain their ploidy, unique heterozygous chromosomal rearrangements, and stable aneuploidies in addition to several diverse structural variants. In addition to the previously known diploid and tetraploid groups of commercial isolates, we describe a widely distributed stable triploid aneuploid clonal lineage. We show that company practices and global trade help the distribution of these clonal clusters and that these yeasts are characterized by their exclusively mitotic reproduction.
Temporal occupancy distributions reveal multifaceted and heterogeneous effects of climatic variation on montane butterflies
Authors: Reis Gbolahan A , Forister Matthew L , Halsch Christopher A , Dittemore Clare M , Shapiro Arthur M , Gompert Zachariah
Published: February 2025

Climate change has substantially altered the phenology of many organisms, with profound implications for biodiversity and species interactions. However, phenological studies of insects have often focused on shifts over time, without explicitly examining how climate drives these changes. In addition, the metrics used to measure changes in phenology often capture only limited information about the flight period. In this study, we analyzed multidecadal observational and climate data using a hierarchical Bayesian framework to model the annual probability of occurrence distributions for 135 butterfly species across five montane sites along an elevational gradient. Our analysis used polynomial models that account for shifts in abundance and the timing and length of flight periods to investigate the effect of climate on butterfly phenology. We found that spring maximum and minimum temperatures, as well as winter precipitation, are important predictors of butterfly phenology. High winter precipitation delayed phenology at high-elevation sites where substantial snowfall occurs, while increased spring maximum temperatures generally advanced phenology across all elevations. Even modest increases in spring minimum temperatures caused substantial shift in phenology. We documented variability in the effect of climate on phenology across sites, among species within a site and among populations of the same species across different sites with variability among species within a site being especially pronounced. We also found that climate influences different aspects of the flight period differently (e.g., timing versus duration), underscoring the need to move beyond single metrics such as day of first flight. These findings highlight the importance of examining the entire flight period and considering the interplay of species-specific traits to improve predictions of how climate change impacts phenology. Such approaches might be essential for designing more targeted and effective conservation strategies in response to ongoing climate change.
Lactate dehydrogenase is the Achilles’ heel of Lyme disease bacteriumBorreliella burgdorferi
Authors: Sze Ching Wooen , Lynch Michael J , Zhang Kai , Neau David B. , Ealick Steven E. , Crane Brian R , Li Chunhao
Published: February 2025

As a zoonotic pathogen, the Lyme disease bacteriumBorreliella burgdorferihas evolved unique metabolic pathways, some of which are specific and essential for its survival and thus present as ideal targets for developing new therapeutics.B. burgdorferidispenses with the use of thiamin as a cofactor and relies on lactate dehydrogenase (BbLDH) to convert pyruvate to lactate for balancing NADH/NAD+ratios. This report first demonstrates that BbLDH is a canonical LDH with some unique biochemical and structural features. A loss-of-function study then reveals that BbLDH is essential forB. burgdorferisurvival and infectivity, highlighting its therapeutic potential. Drug screening identifies four previously unknown LDH inhibitors with minimal cytotoxicity, two of which inhibitB. burgdorferigrowth. This study provides mechanistic insights into the function of BbLDH in the pathophysiology ofB. burgdorferiand lays the groundwork for developing genus-specific metabolic inhibitors againstB. burgdorferiand potentially other tick-borne pathogens as well.
Structural basis of flagellar rod assembly on the FliPQR protein-export channel
Authors: Kinoshita Miki , Miyata Tomoko , Makino Fumiaki , Imada Katsumi , Namba Keiichi , Minamino Tohru
Published: February 2025

The FliPQR complex constitutes a channel for export of the bacterial flagellar proteins involved in axial structure assembly. It also serves as a template for flagellar rod assembly. A periplasmic gate, formed by the N-terminal α-helices of FliP and FliR, remains closed until FliE assembles onto FliP and FliR. The mechanism by which FliE opens the gate and assembles has remained unclear. Here, we present a cryoEM structure of the FliPQR complex in closed form at 3.0 Å resolution. A β-cap formed by the N-terminal β-strands of FliP and FliR creates a tight seal in the closed gate. Interaction of FliE with FliP and FliR induces a conformational change in FliP and FliR, with their N-terminal α-helices move up and outward. Consequently, the N-terminal β-strands of FliP and FliR start opening the periplasmic gate one after another and form a docking site for FliE to initiate rod assembly.
Real-time capture of σNtranscription initiation intermediates reveals mechanism of ATPase-driven activation by limited unfolding
Authors: Mueller Andreas U. , Molina Nina , Darst Seth A.
Published: February 2025

Bacterial σ factors bind RNA polymerase (E) to form holoenzyme (Eσ), conferring promoter specificity to E and playing a key role in transcription bubble formation. σNis unique among σ factors in its structure and functional mechanism, requiring activation by specialized AAA+ ATPases. EσNforms an inactive promoter complex where the N-terminal σNregion I (σN-RI) threads through a small DNA bubble. On the opposite side of the DNA, the ATPase engages σN-RI within the pore of its hexameric ring. Here, we perform kinetics-guided structural analysis ofde novoformed EσNinitiation complexes and engineer a biochemical assay to measure ATPase-mediated σN-RI translocation during promoter melting. We show that the ATPase exerts mechanical action to translocate about 30 residues of σN-RI through the DNA bubble, disrupting inhibitory structures of σNto allow full transcription bubble formation. A local charge switch of σN-RI from positive to negative may help facilitate disengagement of the otherwise processive ATPase, allowing subsequent σNdisentanglement from the DNA bubble.
Massively parallel assessment of gene regulatory activity at human cortical structure associated variants
Authors: Matoba Nana , McAfee Jessica C. , Krupa Oleh , Bell Jess , Le Brandon D. , Valone Jordan M. , Crawford Gregory E. , Won Hyejung , Stein Jason L.
Published: February 2025

Genetic association studies have identified hundreds of largely non-coding loci associated with inter-individual differences in the structure of the human cortex, though the specific genetic variants that impact regulatory activity are unknown. We implemented a Massively Parallel Reporter Assay (MPRA) to measure the regulatory activity of 9,092 cortical structure associated DNA variants in human neural progenitor cells during Wnt stimulation and at baseline. We identified 918 variants with regulatory potential from 150 cortical structure associated loci (76% of loci studied), of which >50% showed allelic effects. Wnt stimulation modified regulatory activity at a subset of loci that functioned as condition-dependent enhancers. Regulatory activity in MPRA was largely induced by Alu elements that were hypothesized to contribute to cortical expansion. The regionally specific impact of genetic variants that disrupt motifs is likely mediated through the levels of transcription factor expression during development, further clarifying the molecular mechanisms altering cortical structure.
Power-law decay of force on cell membrane tethers reflects long-ranged relaxation of membrane tension
Authors: Laborie Emeline , Callan-Jones Andrew
Published: February 2025

Membrane tension is an acknowledged regulator of a wide array of cell functions; however, whether it acts locally or globally in different contexts remains debated. Recent experiments that locally perturb tension and measure the response elsewhere on the membrane are not conclusive, and the mechanism of diffusive tension relaxation has been called into doubt. Here, we consider the tension response to a sudden extension of a membrane tether, and report a quantitative signature of dynamic tension relaxation, which up to now is missing. We present a theory based on tension diffusion leading to a prediction of power-law decay in time of the force holding the tether, with a material-independent exponent of 1/3. This prediction is confirmed to within a few percent by re-analyzing eleven sets of tether data from two cell types with distinct membrane cortical architectures. Overall, our scaling results indicate the absence of a relevant characteristic length and therefore generically reflect tension relaxation by long-range membrane lipid flows.
Multi-sample, multi-platform isoform quantification using empirical Bayes
Authors: Talukder Arghamitra , Thavarekere Shree , Knowles David A.
Published: February 2025

Accurate quantification of RNA isoform abundance is crucial for understanding gene regulation, cellular behavior, and disease mechanisms. While short-read (SR) sequencing provides high-throughput and cost-effective transcript quantification, it suffers from read-to-transcript ambiguity. Long-read (LR) sequencing reduces this ambiguity but faces challenges such as high error rates, biases, and lower throughput. Existing methods rely on either SR or LR data and operate on single or merged samples, failing to leverage the variability across multiple samples and the complementary strengths of both technologies. As a result, they struggle to accurately quantify low-abundance and moderate-expressed isoforms and often require complex models for sample-specific bias correction. To address these limitations, we introduceJOLI, a hierarchical model that leverages multi-sample learning to enhance transcript quantification by jointly integrating SR and LR sequencing data. By incorporating multi-sample learning, JOLI captures shared transcript structures, corrects for systematic biases, and enhances statistical power, particularly for low- and moderate-abundance isoforms. Our model applies an empirical Bayes framework, learning a shared prior across samples to improve inference consistency. By jointly modeling SR and LR data, it integrates the strengths of both technologies, achieving higher accuracy and reproducibility in transcript quantification. Through benchmarking on simulated and real RNA-seq datasets, we show that JOLI consistently outperforms single-sample EM method by improving ranking consistency, proportional agreement, and estimation accuracy while enhancing reproducibility. Specifically, in simulations, JOLI multi-sample improves Spearman correlation by 9.8% for LR and 7.7% for SR data compared to single-sample method, while for real data, the improvements are 2.56% (LR) and 1.28% (SR), respectively. Multi-sample learning further improves the quantification of isoforms with low to moderate expression levels. Furthermore, JOLI performs competitively with state-of-the-art methods, highlighting its robustness in transcript quantification.
TLR4 Modulates Simvastatin’s Impact on HDL Cholesterol and Glycemic Control
Authors: Tian Xiao , Zhang Peixiang
Published: February 2025

Statins lower cardiovascular risk by inhibiting HMG-CoA reductase, with their efficacy and adverse effects linked to SREBP-regulated cholesterol metabolism. Nutritional states— particularly the alternating fasting and feeding cycles, rather than intrinsic circadian rhythms— exert tight control over hepatic lipid metabolism via SREBP-mediated regulation of cholesterol and fatty acid synthesis. We exploited the natural diurnal oscillations in food intake in mice to determine how nutritional state modulates simvastatin’s metabolic actions. When administered during fasting, simvastatin impaired glucose homeostasis through SREBP-2–driven autophagy that enhanced PPARα activity, whereas simvastatin given during feeding reduced HDL cholesterol and improved glucose metabolism. Mechanistically, a feeding-induced surge in lipopolysaccharide (LPS) suppressed hepatic oxysterol synthesis, thereby enabling simvastatin to further deplete oxysterols and inhibit activation of LXR and SREBP-1c—key regulators of PPARα signaling under both postprandial and fasting conditions. This cascade resulted in decreased HDL cholesterol levels and improved glycemic control. Moreover, TLR4 deficiency disrupted the LPS–simvastatin interplay on LXR/SREBP-1c/PPARα signaling, reversing the HDL-lowering and glucose-improving effects seen during feeding. Together, these results identify feeding-induced LPS–TLR4 signaling as a critical determinant of simvastatin’s metabolic effects and suggest strategies to optimize statin therapy based on nutritional state.
Vagus nerve stimulation modulates information representation of sustained activity in layer specific manner in the rat auditory cortex
Authors: Shiramatsu Tomoyo Isoguchi , Ibayashi Kenji , Kawai Kensuke , Takahashi Hirokazu
Published: February 2025

The brain of a living organism enables stable information processing in response to constantly changing external environments and internal states. As one of such cortical modulation, the present study focused on the effect of vagus nerve stimulation (VNS) therapy on information representation of the auditory cortex. By quantifying sound representation using machine learning, we investigated whether VNS alters cortical information representation in a layer-specific and frequency band-specific manner. A microelectrode array meticulously mapped the band-specific power and phase-locking value of sustained activities in every layer of the rat auditory cortex. Sparse logistic regression was used to decode the test frequency from these neural characteristics. The comparison of decoding accuracy before and after the application of VNS indicated that sound representation of the high-gamma band activity was impaired in the deeper layers, i.e., layers 5 and 6, while it was slightly improved in the superficial layers, i.e., layers 2, 3, and 4. Moreover, there was an improvement of sound representation in theta band activity in the deeper layers, demonstrating the layer-specific and frequency band-specific effect of VNS. Given that the cortical laminar structure and oscillatory activity in multiple frequency bands helps the auditory cortex to act as a hub for feed-forward and feed-back pathways in various information processing, the current findings support the possibility that VNS provide complex effects on brain function by altering the balance of cortical activity between layers and frequency bands.
Complementary MR measures of white matter and their relation to cardiovascular health and cognition
Authors: Raykov Petar P. , Correia Marta , Tsvetanov Kamen , Henriques Rafael N. , Del Cerro León Alberto , Bracher-Smith Matthew , Escott-Price Valentina , Raykov Yordan P. , Henson Richard N.
Published: February 2025

Magnetic Resonance Imaging (MRI) offers many ways to non-invasively estimate the properties of white matter (WM) in the brain. In addition to the various metrics derived from diffusion-weighted MRI, one can estimate total WM volume from T1-weighted MRI, WM hyper-intensities from T2-weighted MRI, myelination from the T1:T2 ratio, or from the magnetisation-transfer ratio (MTR). Here we utilise the presence of all of these MR contrasts in a population based life-span cohort of 650 healthy adults [CamCAN cohort] to identify the latent factors underlying the covariance of 11 commonly-used WM metrics. Four factors were needed to explain 89% of the variance, which we interpreted in terms of 1) fibre density / myelination, 2) free-water / tissue damage, 3) fibre-crossing complexity and 4) microstructural complexity. These factors showed distinct effects of age and sex. To test the validity of these factors, we related them to measures of cardiovascular health and cognitive performance. Specifically, we ran path analyses 1) linking cardio-vascular measures to the WM factors, given the idea that WM health is related to cardiovascular health, and 2) linking the WM factors to cognitive measure, given the idea that WM health is important for cognition. Even after adjusting for age, we found that a vascular factor related to pulse pressure predicted the WM factor capturing free-water / tissue damage, and that several WM factors made unique predictions for fluid intelligence and processing speed. Our results show that there is both complementary and redundant information across common MR measures of WM, and their underlying latent factors may be useful for pinpointing the differential causes and contributions of white matter health in healthy aging.
An integrative model of AMPA receptor trafficking reveals the central contribution of local translation in subtype-specific kinetics
Authors: Wagle Surbhit , Kracht Maximilian K. , Bührke Anne , Acker-Palmer Amparo , Kraynyukova Nataliya , Hafner Anne-Sophie , Schuman Erin M. , Tchumatchenko Tatjana
Published: February 2025

AMPA-type glutamate receptors (AMPARs) underlie most of the excitatory synaptic transmission in the brain and are crucial for implementing long-term synaptic plasticity. AMPARs are multi-protein complexes composed of two types of subunits: pore-forming subunits GluA1-4 that assemble in the endoplasmic reticulum and form the glutamate-gated ion channel, and auxiliary subunits that modulate receptor bio-physical properties and mediate their forward trafficking to the plasma membrane. Here, using a combination of theoretical and experimental approaches, we elucidate the kinetics of essential trafficking steps and the protein sources necessary to explain the experimentally observed distribution of AMPARs and the response of different AMPAR subtypes to LTP induction. Our data indicate that the mRNA coding for one of the most abundant AMPAR auxiliary subunits, CNIH-2, is abundant in dendrites. Consistent with this mRNA distribution, CNIH-2 is locally synthesized. In contrast, the pore-forming subunits GluA1 and GluA2 are mostly synthesized in the cell body. CNIH-2 synthesis increases after the (chemical) induction of long-term potentiation. Strikingly, the translation of CNIH-2 is required for the plasma membrane insertion of GluA2-containing receptors and not GluA1-homomeric AMPARs. Using the selective trafficking of GluA2-containing AMPARs by CNIH-2, our computational model can explain the distinct temporal profiles in response to plasticity induction of two major subtypes of AMPARs, the slow-response of the calciumimpermeable (GluA2-containing) and fast kinetics of the calcium-permeable (GluA2-lacking) AMPARs.
Chronically implantable µLED arrays for optogenetic cortical surface stimulation in mice
Authors: Greer Ryan , Verdier Antonin , Butt Emma , Cheng Yunzhou , Callas Ella , McAlinden Niall , Dawson Martin D. , Bathellier Brice , Mathieson Keith
Published: February 2025

Cortical implants are a proven clinical neurotechnology with the potential to transform our understanding of cognitive processes. These processes rely on complex neuronal networks that are difficult to selectively probe or stimulate. Optogenetics offers cell-type specificity, but achieving the density and coverage required for chronic, high-resolution modulation remains a challenge. Here we present a 100-element µLED array (200 µm pixel pitch, 2 × 2 mm2 footprint) coupled into a miniaturised, flexible system suitable for chronic implantation and optogenetic stimulation of the surface of the mouse cortex. The µLEDs can remain stable for over 300 hours continuous operation timein-vivo, allowing for months-long chronic experiments. Simultaneous electrophysiology recordings confirmed robust neuronal responses corresponding to low µLED drive currents (<5 mA), minimising thermal effects and supporting future wireless operation. The spatial resolution of neuronal responses was consistent with a simulated model of light scattering in the cortical layers, enabling device optimisation. Behavioural experiments with chronically implanted mice demonstrated robust learning during discrimination tasks using spatially distinct optogenetic stimulation patterns.
Community-level plant functional strategies explain ecosystem carbon storage across a tropical elevational gradient
Authors: Mauki Dickson , Manning Peter , Schleuning Matthias , Hemp Andreas , Costa David Schellenberger , Cornejo Natalia Sierra , Becker Joscha N. , Ensslin Andreas , Rutten Gemma , Neyret Margot
Published: February 2025

1. Plant functional traits play an important role in shaping plant ecological responses to environmental conditions and influencing ecosystem functioning. However, how whole-plant functional strategies manifest at the community level to influence aboveground and belowground carbon storage across environmental gradients remains poorly understood.

2. We measured aboveground and belowground carbon stocks and the variation in whole-plant (above- and belowground) functional strategies at the community level in twelve ecosystem types across a broad savanna-forest-alpine elevational gradient of climate and land use on Mt. Kilimanjaro, Tanzania. Using Structural Equation Models, we disentangled the direct and land use mediated influences of climate on carbon storage from indirect influences mediated by variation in plant functional strategies.

3. We found strong coordination between above- and belowground functional traits at the whole community level, which corresponded with functional strategies related to two major trade-offs: aslow-conservation tofast-resource acquisition axis represented by a spectrum from high leaf dry matter content to high fine root nitrogen concentration; and a size-relatedwoodytograssycommunity axis represented by a spectrum spanning high canopy height to high specific root length. Theslow-fastandwoody-grassystrategy axes were primarily driven by precipitation and land-use intensity, respectively.

4. Both functional strategies mediated the effects of climate on carbon storage. Theslow-faststrategy axis was strongly and positively associated with aboveground carbon stocks. Meanwhile, thewoody-grassystrategy axis was negatively associated with both aboveground carbon stocks and soil organic carbon stocks.

5.Synthesis. We demonstrated that major plant functional strategies manifest at the community level along elevational gradients. These strategies also explain variation in carbon storage, although aboveground storage is mostly driven by trait effects, and belowground storage by direct effects of climate. Together, these results underscore the importance of incorporating functional community data into future analysis of climate change impacts on carbon storage, which would enhance our ability to predict potential shifts in ecosystem functioning.
CDKN2ALowcancer cells outcompete macrophages for microenvironmental zinc to drive immunotherapy resistance
Authors: Buj Raquel , Cole Aidan R. , Danielson Jeff , Xu Jimmy , Hurd Drew , Kishore Akash , Kedziora Katarzyna M. , Chen Jie , Yang Baixue , Barras David , Uboveja Apoorva , Amalric Amandine , Apiz Saab Juan J. , Wickramasinghe Jayamanna , Tangudu Naveen Kumar , Levasseur Evan , Wang Hui , Minasyan Aspram , Dadey Rebekah E. , Sharrow Allison C. , Vendetti Frank P. , Rivadeneira Dayana B. , Bakkenist Christopher J. , Delgoffe Greg M. , Hempel Nadine , Snyder Nathaniel W. , Bao Riyue , Soloff Adam C. , Kirkwood John M. , Dangaj Laniti Denarda , Kossenkov Andrew V. , Muir Alexander , Das Jishnu , Davar Diwakar , Mesaros Clementina , Aird Katherine M.
Published: February 2025

Approximately 50% of cancers exhibit decreasedCDKN2Aexpression (CDKN2ALow), which is linked to immune checkpoint blockade (ICB) resistance. WhileCDKN2Ais traditionally recognized as a tumor suppressor and cell cycle regulator, we have previously put forth a new paradigm demonstrating its role in intracellular metabolic reprogramming. Whether the metabolic derangement due toCDKN2Aloss alters metabolites within the tumor microenvironment (TME) and how that affects the immune compartment and ICB response has never been investigated. Here we found thatCDKN2ALowcancer cells reorganize zinc compartmentalization by upregulating the zinc importer SLC39A9 in the plasma membrane, leading to intracellular zinc accumulation in cancer cells and concurrent zinc depletion in the TME. This competition for zinc results in zinc-starved macrophages, leading to reduced phagocytic activity. Remarkably, restoring zinc levels in the TME through a dietary intervention re-educates macrophages to a pro-phagocytic phenotype, sensitizingCDKN2ALowtumors to ICB. Unexpectedly, T cells are not required for this response. Clinically, macrophages fromCDKN2ALowcancer patients have decreased zinc signatures, corresponding to reduced phagocytosis signatures. Moreover, patients with low circulating zinc levels have reduced time-to-event outcomes compared to those with higher zinc levels. Our work reveals a previously unrecognized mechanism through whichCDKN2ALowcancer cells outcompete macrophages for zinc, directly disrupting their function and ICB efficacy.
The substrate changes matrix metalloprotease-1 dynamics, allostery, and ligand binding affinity
Authors: Harms Chase , Nash Anthony , Sarkar Susanta K.
Published: February 2025

Using single-molecule experiments, ensemble assays, and Molecular Dynamics (MD) simulations, we showed that collagen actively influences MMP1 interdomain dynamics. This paper extends the previous experimental work to validate MD simulations and gain more insights into MMP1-collagen interactions. We include virtual screening with free energy calculations to uncover key insights regarding substrate-dependent dynamics, allostery, and ligand binding. Our findings reveal that MMP1 interdomain dynamics are influenced by the strain in collagen, and collagen-specific allosteric residues exhibit strong correlations with the active site. Additionally, allosteric paths connecting these residues to the active site bypass the linker region. Collagen also induces changes in the configurations of the catalytic motif. Furthermore, MD simulation and virtual screening identify molecules that bind to allosteric residues, alter MMP1 dynamics, and potentially change activity. Free energy calculations highlight the essential role of the substrate in small molecule screening against a protein. We have developed a comprehensive framework for identifying substrate-specific allosteric residues in MMP1 and screening small molecules incorporating protein dynamics in the presence of substrates. These results significantly impact our understanding of MMP1 interactions with collagen fibrils and pave the way for selectively modulating specific MMP1 functions without altering its other functions in future applications.

Significance

In this paper, we validated all-atom simulations of free and collagen-bound MMP1 and gained insights into MMP1 function. We have found that collagen changes dynamics, allostery, and ligand binding in MMP1. Collagen strain, known to be age-dependent, also changes MMP1 dynamics and ligand binding. Interdomain allosteric paths do not go through the linker connecting the MMP1 domains. Instead, paths from the collagen-specific allosteric residue to the active site have non-bonded interactions. Screening of small molecules against collagen-specific MMP1 residue suggests that collagen alters ligand binding to MMP1. These results will significantly impact understanding MMPs and small molecule screening against proteins. Substrate-specific allosteric residues may enable controlling one function of MMPs without altering their other functions, leading to fewer side effects.