bluuebunny/crossref_metadata_2025_split huggingface dataset:
An integrative trait-based framework to infer resource budgets and life-histories of long-lived plants
Authors: Cooksley Huw , Schleuning Matthias , Neu Alexander , Esler Karen J. , Schurr Frank M. 
Published: April 2023

AbstractA fundamental assumption of functional ecology is that functional traits determine life-histories. Yet correlations between traits and life-history components are often weak, especially for long lived plants. This is because trade-offs, constraints, dynamic resource budgets and the scaling from single organs to entire plants cause complex relationships between traits and life-history. To elucidate these relationships, we present an integrated Trait-Resource-Life-History (TRL) framework that infers how functional traits affect organ-level costs and benefits of different life history components, how these costs and benefits shape the dynamics of whole-plant resource acquisition and allocation, and how these dynamics translate into life history. We illustrate this framework by developing a TRL model for a functionally diverse group of woody plants (22 species of the genusProteafrom the South African Greater Cape Floristic Region). Using hierarchical Bayesian latent state-space modelling, we statistically parameterise this model from data on year-to-year variation in growth, reproduction and maternal care (serotiny) for 600 individuals. The parameterised model reveals that higher resource acquisition translates into both larger absolute resource pools and greater proportional resource allocation to reproduction. Accordingly, specific leaf area, a key trait increasing resource acquisition, is associated with larger resource pools, an earlier age of maturity as well as increased vegetative and reproductive performance at young to intermediate ages. In contrast, seed nitrogen content has opposing effects on the benefits of different organs and thus only shows weak correlations with life-history components. Importantly, the TRL model identifies trait and resource-mediated trade-offs at the level of organs, whole-plant resource budgets and life-histories. It can thus quantify key components of life-history theory that are so far largely inaccessible for long-lived plants. This permits novel insights into ecological and evolutionary mechanisms shaping life-histories. Application of the proposed framework to a broad range of plant systems should be facilitated by the increasing availability of trait and demographic data, whole-plant phenotyping and high resolution remote sensing. The integration of the TRL framework with models of biotic interactions further holds promise for a resource-based understanding of community dynamics across trophic levels and a closer integration of functional ecology, evolutionary ecology, community ecology and ecosystem science.
Genome-scale and pathway engineering for the sustainable aviation fuel precursor isoprenol production inPseudomonas putida
Authors: Banerjee Deepanwita , Yunus Ian S. , Wang Xi , Kim Jinho , Srinivasan Aparajitha , Menchavez Russel , Chen Yan , Gin Jennifer W. , Petzold Christopher J. , Martin Hector Garcia , Adams Paul D. , Mukhopadhyay Aindrila , Kim Joonhoon , Lee Taek Soon 
Published: April 2023

AbstractSustainable aviation fuel (SAF) will significantly impact global warming in the aviation sector, and important SAF targets are emerging. Isoprenol is a precursor for a promising SAF compound DMCO (1,4-dimethylcyclooctane), and has been produced in several engineered microorganisms. Recently,Pseudomonas putidahas gained interest as a future host for isoprenol bioproduction as it can utilize carbon sources from inexpensive plant biomass. Here, we engineer metabolically versatile hostP. putidafor isoprenol production. We employ two computational modeling approaches (Bilevel optimization and Constrained Minimal Cut Sets) to predict gene knockout targets and optimize the “IPP-bypass” pathway inP. putidato maximize isoprenol production. Altogether, the highest isoprenol production titer fromP. putidawas achieved at 3.5 g/L under fed-batch conditions. This combination of computational modeling and strain engineering onP. putidafor an advanced biofuels production has vital significance in enabling a bioproduction process that can use renewable carbon streams.
DDX5 (p68) orchestrates β-catenin, RelA and SP1 mediated MGMT gene expression: Implication in TMZ chemoresistance
Authors: Shaw Rajni , Karmakar Subhajit , Basu Malini , Ghosh Mrinal K. 
Published: April 2023

AbstractDDX5 (p68) upregulation has been linked with various cancers of different origins, especially Colon Adenocarcinomas. Similarly, across cancers, MGMT has been identified as the major contributor of chemoresistance against DNA alkylating agents like Temozolomide (TMZ). TMZ is an emerging potent chemotherapeutic agent across cancers under the arena of drug repurposing. Recent studies have established that patients with open MGMT promoters are prone to be innately resistant or acquire resistance against TMZ compared to its closed conformation. However, not much is known about the transcriptional regulation of MGMT gene in the context of colon cancer. This necessitates studying MGMT gene regulation, which directly impacts the cellular potential to develop chemoresistance against alkylating agents. Our study aims to uncover an unidentified mechanism of DDX5-mediated MGMT gene regulation. Experimentally, we found that both mRNA and protein expression levels of MGMT were elevated in response to p68 overexpression in multiple human colon cancer cell lines and vice-versa. Since p68 cannot directly interact with the MGMT promoter, transcription factorsviz., β-catenin, RelA (p65) and SP1 were also studied as reported contributors. Through co-immunoprecipitation and GST-pull-down studies, p68 was established as an interacting partner of SP1 in addition to β-catenin and NF-κB (p50-p65). Mechanistically, luciferase reporter and chromatin-immunoprecipitation assays demonstrated that p68 interacts with the MGMT promoterviaTCF4-LEF, RELA and SP1 sites to enhance its transcription. To the best of our knowledge, this is the first report of p68 as a transcriptional co-activator of MGMT promoter and our study identifies p68 as a novel and master regulator of MGMT gene expression.
AstroglialHmgb1regulates postnatal astrocyte morphogenesis and cerebrovascular maturation
Authors: Freitas-Andrade Moises , Comin Cesar H. , Dyken Peter Van , Ouellette Julie , Raman-Nair Joanna , Blakeley Nicole , Liu Qing Yan , Leclerc Sonia , Pan Youlian , Liu Ziying , Carrier Micaël , Thakur Karan , Savard Alexandre , Rurak Gareth M. , Tremblay Marie-Ève , Salmaso Natalina , Costa Luciano Da F. , Coppola Gianfilippo , Lacoste Baptiste 
Published: April 2023

AbstractAstrocytes are intimately linked with brain vessels, a relationship that is critical for neuronal health and function. However, astroglial factors driving these physical and functional associations during postnatal brain development have yet to be identified. We characterized structural and transcriptional changes in mouse cortical astrocytes and microvessels during the first two postnatal weeks and found that high-mobility group box 1 (Hmgb1), normally upregulated with injury and involved in adult cerebrovascular repair, was highly expressed in astrocytes at birth and then decreased rapidly. Astrocyte-selective ablation ofHmgb1at birth affected astrocyte morphology and endfoot placement, altered distribution of endfoot proteins connexin43 and aquaporin-4, induced transcriptional changes in astrocytes related to cytoskeleton remodeling, and profoundly disrupted endothelial ultrastructure. While lack of astroglialHmgb1did not affect the blood-brain barrier or angiogenesis postnatally, it impaired neurovascular coupling and behavior in adult mice. These findings identify astroglialHmgb1as a key player in postnatal gliovascular maturation.
Identification of B56α, B56γ and BAP1 as PRR14L binding partners
Authors: Chase Andrew , Carreño-Tarragona Gonzalo , Lin Feng , Yapp Sarah , Score Joanna , Bryant Catherine , Cross Nicholas CP 
Published: April 2023

AbstractTruncating mutations have been previously described inPRR14Lassociated with acquired isodisomy of chromosome 22 in myeloid neoplasms. Very little is known about the function of PRR14L, but previous work showed localization to the midbody and binding to KIF4A. Here we confirm binding of PRR14L to PP2A components B56α and B56γ. Similar to the related protein PRR14, PRR14L binds B56α via a conserved short linear motif within the C-terminal Tantalus domain. We also confirmed binding to BAP1, which forms the H2A deubiquinating complex PR-DUB with ASXL1, thereby linking PRR14L to a protein with established leukemogenic significance. AlphaFold data predicts PRR14L structure to be largely disordered, consistent with a possible role as a scaffold protein.
Enhancing extracellular vesicle cargo loading and functional delivery by engineering protein-lipid interactions
Authors: Peruzzi Justin A. , Gunnels Taylor F. , Edelstein Hailey I. , Lu Peilong , Baker David , Leonard Joshua N. , Kamat Neha P. 
Published: April 2023

AbstractNaturally generated lipid nanoparticles termed extracellular vesicles (EVs) hold significant promise as engineerable therapeutic delivery vehicles. However, active loading of protein cargo into EVs in a manner that is useful for delivery remains a challenge. Here, we demonstrate that by rationally designing proteins to traffic to the plasma membrane and associate with lipid rafts, we can enhance loading of protein cargo into EVs for a set of structurally diverse transmembrane and peripheral membrane proteins. We then demonstrate the capacity of select lipid tags to mediate increased EV loading and functional delivery of an engineered transcription factor to modulate gene expression in target cells. We envision that this technology could be leveraged to develop new EV-based therapeutics that deliver a wide array of macromolecular cargo.
Snowprint: a predictive tool for genetic biosensor discovery
Authors: d’Oelsnitz Simon , Stofel Sarah K. , Ellington Andrew D. 
Published: April 2023

AbstractBioengineers increasingly rely on ligand-inducible transcription regulators for chemical-responsive control of gene expression, yet the number of regulators available is limited. Novel regulators can be mined from genomes, but an inadequate understanding of their DNA specificity complicates genetic design. Here we present Snowprint, a simple yet powerful bioinformatic tool for predicting regulator:DNA interactions. Benchmarking results demonstrate that Snowprint predictions are significantly similar for >45% of experimentally validated regulator:operator pairs from organisms across nine phyla and for regulators that span five distinct structural families. We then use Snowprint to design promoters for 33 previously uncharacterized regulators sourced from diverse phylogenies, of which 28 were shown to influence gene expression and 24 produced a >20-fold signal-to-noise ratio. A panel of the newly domesticated regulators were then screened for response to biomanufacturing-relevant compounds, yielding new sensors for a polyketide (olivetolic acid), terpene (geraniol), steroid (ursodiol), and alkaloid (tetrahydropapaverine) with induction ranges up to 10.7-fold. Snowprint represents a unique, generalizable tool that greatly facilitates the discovery of ligand-inducible transcriptional regulators for bioengineering applications.Abstract Figure
Actin- and microtubule-based motors contribute to clathrin-independent endocytosis in yeast
Authors: Woodard Thaddeus K. , Rioux Daniel J. , Prosser Derek C. 
Published: April 2023

AbstractMost eukaryotic cells utilize clathrin-mediated endocytosis as well as multiple clathrin-independent pathways to internalize proteins and membranes. Although clathrin-mediated endocytosis has been studied extensively and many machinery proteins have been identified, clathrin-independent pathways remain poorly characterized by comparison. We previously identified the first known yeast clathrin-independent endocytic pathway, which relies on the actin-modulating GTPase Rho1, the formin Bni1 and unbranched actin filaments, but does not require the clathrin coat or core clathrin machinery proteins. In this study, we sought to better understand clathrin-independent endocytosis in yeast by exploring the role of myosins as actin-based motors, since actin is required for endocytosis in yeast. We find that Myo2, which transports secretory vesicles, organelles and microtubules along actin cables to sites of polarized growth, participates in clathrin-independent endocytosis. Unexpectedly, the ability of Myo2 to transport microtubule plus ends to the cell cortex appears to be required for its role in clathrin-independent endocytosis. In addition, dynein, dynactin and proteins involved in cortical microtubule capture are also required. Thus, our results suggest that interplay between actin and microtubules contributes to clathrin-independent internalization in yeast.Summary StatementClathrin-independent endocytosis is a poorly-understood but conserved process. Here, we provide evidence of a role for myosin and dynein as motor proteins involved the yeast clathrin-independent pathway.
Exploring The Ability Of Machine Learning-Based Virtual Screening Models To Identify The Functional Groups Responsible For Binding
Authors: Hadfield Thomas E. , Scantlebury Jack , Deane Charlotte M. 
Published: April 2023

AbstractMany recently proposed structure-based virtual screening models appear to be able to accurately distinguish high affinity binders from non-binders. However, several recent studies have shown that they often do so by exploiting ligand-specific biases in the dataset, rather than identifying favourable intermolecular interactions in the input protein-ligand complex. In this work we propose a novel approach for assessing the extent to which machine learningbased virtual screening models are able to identify the functional groups responsible for binding. To sidestep the difficulty in establishing the ground truth importance of each atom of a large scale set of protein-ligand complexes, we propose a protocol for generating synthetic data where the label of an example is assigned by a 3-dimensional deterministic binding rule. This allows us to precisely quantify the ground truth importance of each atom and compare it to the model generated attributions.Using our generated datasets, we demonstrate that a recently proposed deep learning-based virtual screening model, PointVS, identified the most important functional groups with 39% more efficiency than a fingerprint-based random forest, suggesting that it would generalise more effectively to new examples.In addition, we found that ligand-specific biases, such as those present in widely used virtual screening datasets, substantially impaired the ability of all ML models to identify the most important functional groups.We have made our synthetic data generation framework available to facilitate the benchmarking of new virtual screening models. Code is available athttps://github.com/tomhadfield95/synthVS.
Abnormal homeostasis of P53 gene knockout mice can be reflected in urinary proteome
Authors: Pan Xuanzhen , Yang Minhui , Bao Yijin , Liu Yongtao , Gao Youhe 
Published: April 2023

AbstractIn this experiment, the urinary proteome analysis of p53 knockout mice at four relatively early time points before death was performed from three dimensions. One was to compare the differential proteins screened by homozygote and heterozygote at the same time point; the other was to compare the differential proteins screened by homozygote and wild-type as well as heterozygote and wild-type at the same time point; the third was to compare the differential proteins screened by homozygote and heterozygote before and after each time point, and to screen the differential proteins of three mice by self-control analysis and screening. Later, enrichment analysis of the differential proteins was performed mainly by Metascape and String, and disease association analysis of gene or variant genotype-phenotype with the help of DisGeNET and Monarch. We found that the biological pathways mainly related to metabolism were most abundant, and at the same time abnormal homeostasis, cancer and tumor, cardiovascular diseases, and neurodegenerative diseases appeared. However, under the analysis of Monarch, homozygotes or heterozygotes contained abnormal homeostasis at all time points, and most of them ranked the first or at least the top, while all timepoints in the growth and development of each normal rat were not enriched to abnormal homeostasis and other disease pathways.
A single-cell atlas of the aging murine ovary
Authors: Isola José V. V. , Ocañas Sarah R. , Hubbart Chase R. , Ko Sunghwan , Ali Mondal Samim , Hense Jessica D. , Carter Hannah N. C. , Schneider Augusto , Kovats Susan , Alberola-Ila José , Freeman Willard M. , Stout Michael B. 
Published: April 2023

ABSTRACTOvarian aging leads to diminished fertility, dysregulated endocrine signaling, and increased chronic disease burden. These effects begin to emerge long before follicular exhaustion. Around 35 years old, women experience a sharp decline in fertility, corresponding to declines in oocyte quality. Despite a growing body of work, the field lacks a comprehensive cellular map of the transcriptomic changes in the aging ovary to identify early drivers of ovarian decline. To fill this gap, we performed single-cell RNA sequencing on ovarian tissue from young (3-month-old) and reproductively aged (9-month-old) mice. Our analysis revealed a doubling of immune cells in the aged ovary, with lymphocyte proportions increasing the most, which was confirmed by flow cytometry. We also found an age-related downregulation of collagenase pathways in stromal fibroblasts, which corresponds to rises in ovarian fibrosis. Follicular cells displayed stress response, immunogenic, and fibrotic signaling pathway inductions with aging. This report raises provides critical insights into mechanisms responsible for ovarian aging phenotypes.
Ancestral genome reconstruction enhances transposable element annotation by identifying degenerate integrants
Authors: Matsushima Wayo , Planet Evarist , Trono Didier 
Published: April 2023

AbstractGrowing evidence indicates that transposable elements (TEs) play important roles in evolution by providing genomes with coding and non-coding elements. Identification of TE-derived functional elements, however, has relied on TE annotations in individual species, which limits its scope to relatively intact TE sequences and misses elements derived from evolutionarily old TEs. Here, we report a novel approach to uncover previously unannotated degenerate TEs (degTEs) by probing multiple ancestral genomes reconstructed from hundreds of species. We applied this method to the human genome and discovered 1,452,810 degTEs, representing a 10.8% increase over the most recent human TE coverage. Further, we discovered that degTEs contribute to variouscis-regulatory elements as well as transcription factor binding sites, including those of a known TE-controlling family, the KRAB zinc-finger proteins. We also report unannotated chimeric transcripts between degTEs and human genes expressed in embryos. This study provides a novel methodology and a freely available resource that will facilitate the investigation of TE co-option events on a full scale.
The murine meninges acquire lymphoid tissue properties and harbour autoreactive B cells during chronicTrypanosoma bruceiinfection
Authors: Quintana Juan F. , Sinton Matthew C. , Chandrasegaran Praveena , Dubey Lalit Kumar , Ogunsola John , Samman Moumen Al , Haley Michael , McConnell Gail , Swar Nono-Raymond Kuispond , Ngoyi Dieudonne Mumba , Bending David , Lecea Luis de , MacLeod Annette , Mabbott Neil A. 
Published: April 2023

AbstractThe meningeal space is a critical brain structure providing immunosurveillance for the central nervous system, but the impact of infections on the meningeal immune landscape is far from being fully understood. The extracellular protozoan parasiteTrypanosoma brucei, which causes Human African Trypanosomiasis (HAT) or sleeping sickness, accumulates in the meningeal spaces, ultimately inducing severe meningitis and resulting in death if left untreated. Thus, sleeping sickness represents an attractive model to study immunological dynamics in the meninges during infection. Here, by combining single cell transcriptomics and mass cytometry by time of flight (CyTOF) within vivointerventions, we found that chronicT. bruceiinfection triggers the development of ectopic lymphoid aggregates (ELAs) in the murine meninges. These infection-induced ELAs were defined by the presence of ER-TR7+fibroblastic reticular cells, CD21/35+follicular dendritic cells, CXCR5+PD1+T follicular helper-like phenotype, GL7+CD95+GC-like B cells, and plasmablasts/plasma cells. Furthermore, the B cells found in the infected meninges produced high-affinity autoantibodies able to recognise mouse brain antigens, in a process dependent on LTβ signalling. A mid-throughput screening identified several host factors recognised by these autoantibodies, including myelin basic protein (MBP), coinciding with cortical demyelination and brain pathology. In humans, we identified the presence of autoreactive IgG antibodies in the cerebrospinal fluid of second stage HAT patients that recognised human brain lysates and MBP, consistent with our findings in experimental infections. Lastly, we found that the pathological B cell responses we observed in the meninges required the presence ofT. bruceiin the CNS, as suramin treatment before the onset of the CNS stage prevented the accumulation of GL7+CD95+GC-like B cells and brain-specific autoantibody deposition. Taken together, our data provide evidence that the meningeal immune response during chronicT. bruceiinfection results in the acquisition of lymphoid tissue-like properties, broadening our understanding of meningeal immunity in the context of chronic infections. These findings have wider implications for understanding the mechanisms underlying the formation ELAs during chronic inflammation resulting in autoimmunity in mice and humans, as observed in other autoimmune neurodegenerative disorders, including neuropsychiatric lupus and multiple sclerosis.
Weakly supervised contrastive learning predicts tumor infiltrating macrophages and immunotherapy benefit in breast cancer from unannotated pathology images
Authors: Yu Guobang , Zuo Yi , Wang Bin , Liu Hui 
Published: April 2023

AbstractThe efficacy of immune checkpoint inhibitors is significantly influenced by the tumor immune microenvironment (TIME). RNA sequencing of tumor biopsies or surgical specimens can offer valuable insights into TIME, but its high cost and long turnaround time seriously restrict its utility in routine clinical examinations. Several recent studies have suggested that ultra-high resolution pathology images can infer cellular and molecular characteristics. However, studies on revealing TIME from pathology images are still limited.In this paper, we proposed a novel weakly supervised contrastive learning model to deduce tumor immune microenvironment features from whole slide images (WSIs) of H&E stained pathological sections. The high-resolution WSIs are split into tiles, and then contrastive learning is applied to extract features of each tile. After aggregating the features at the tile level, we employ weak supervisory signals to fine-tune the encoder for various downstream tasks. Comprehensive downstream experiments on two independent breast cancer cohorts and spatial transcriptomics data demonstrate that our computational pathological features accurately predict the proportion of tumor infiltrating immune cells, particularly the infiltration level of macrophages, as well as the immune subtypes and biomarker gene expression levels. These findings demonstrate that our model effectively captures pathological features beyond human vision, establishing a mapping relationship between cellular compositions and histological morphology, thus expanding the clinical applications of digital pathology images.