bluuebunny/crossref_metadata_2025 huggingface dataset:
Ongoing loss of viable neurons for weeks after mild perinatal hypoxia-ischemia
Authors: McNally Melanie A. , Lau Lauren A. , Granak Simon , Hike David , Liu Xiaochen , Yu Xin , Donahue Rachel A. , Chibnik Lori B. , Ortiz John V. , Che Alicia , Northington Frances , Staley Kevin
Published: December 2024

Mild hypoxic-ischemic encephalopathy is common in neonates with no evidence-based therapies, and 30-40% of patients experience adverse outcomes. The nature and progression of mild injury is poorly understood. Thus, we studied the evolution of mild perinatal brain injury using longitudinal two-photon imaging of transgenic fluorescent proteins as a novel readout of neuronal viability and activity at cellular resolution. In vitro, perinatal murine organotypic hippocampal cultures underwent 15-20 minutes of oxygen-glucose deprivation. In vivo, mild hypoxia-ischemia was completed in post-natal day 10 mouse pups of both sexes with carotid ligation and 15 minutes of hypoxia. Consistent with a mild injury, minimal immediate neuronal death was seen and there was no volumetric evidence of injury by ex vivo MRI 2.5 weeks after injury. In both the hippocampus and neocortex, these mild injuries resulted in a significantly delayed and progressive neuronal loss in the second week after injury, measured by fluorophore quenching. Mild hypoxia-ischemia transiently suppressed cortical network activity followed by normal maturation. No post-injury seizures were seen. The participation in network activity of individual neurons destined to die was indistinguishable from those that survived for 4 days post-injury. In conclusion, our results showed that mild perinatal brain injury resulted in a prolonged increase of neuronal death. Neurons that died late were functioning normally for days after injury, suggesting a new pathophysiology of neuronal death. Critically, the neurons destined to die late demonstrated multiple biomarkers of viability long after mild injury, suggesting their later death may be modified with neuroprotective interventions.

SIGNIFICANCE STATEMENT

Neonatal encephalopathy due to peripartum hypoxia-ischemia (HI) is a major cause of neonatal mortality and morbidity worldwide. Of these infants, most are categorized as having mild HI. Infants with mild HI have significant long-term disabilities. There are currently no evidence-based therapies, largely because the progression and pathophysiology of mild injury is poorly understood. We have identified, for the first time, that mild perinatal HI results in a delayed and prolonged increase in neuronal death. The cortical and hippocampal neurons that die over a week after injury participate normally in neural network activity and exhibit robust viability for many days after injury, indicating a novel pathophysiology of neuronal death. Clinically, these data suggest an extended therapeutic window for mild perinatal HI.
Skeletal trait measurements for thousands of bird species
Authors: Weeks Brian C. , Zhou Zhizhuo , Probst Charlotte M. , Berv Jacob S. , O’Brien Bruce , Benz Brett W. , Skeen Heather R. , Ziebell Mark , Bodt Louise , Fouhey David F.
Published: December 2024

Large comparative datasets of avian functional traits have been used to address a wide range of questions in ecology and evolution. To date, this work has been constrained by the limited availability of skeletal trait datasets that include extensive inter- and intra-specific sampling. We use computer vision to identify and measure bones from photographs of museum skeletal specimens to assemble an extensive dataset of functionally important skeletal elements in birds. The dataset spans 2,057 species of birds (Aves: Passeriformes) and includes measurements of 12 skeletal elements from 14,419 individuals. In addition to the trait values directly measured from photographs, we leverage the multi-dimensional nature of our dataset and known phylogenetic relationships of the species to impute missing data under an evolutionary model. To facilitate use of the dataset, the taxonomy has been reconciled with an existing comprehensive avian phylogeny and an additional dataset of external functional traits for all birds.
HapCNV: A Comprehensive Framework for CNV Detection in Low-input DNA Sequencing Data
Authors: Yu Xuanxuan , Qin Fei , Liu Shiwei , Brown Noah J. , Lu Qing , Cai Guoshuai , Guler Jennifer L. , Xiao Feifei
Published: December 2024

Copy number variants (CNVs) are prevalent in both diploid and haploid genomes, with the latter containing a single copy of each gene. Studying CNVs in genomes from single or few cells is significantly advancing our knowledge in human disorders and disease susceptibility. Low-input including low-cell and single-cell sequencing data for haploid and diploid organisms generally displays shallow and highly non-uniform read counts resulting from the whole genome amplification steps that introduce amplification biases. In addition, haploid organisms typically possess relatively short genomes and require a higher degree of DNA amplification compared to diploid organisms. However, most CNV detection methods are specifically developed for diploid genomes without specific consideration of effects on haploid genomes. Challenges also reside in reference samples or normal controls which are used to provide baseline signals for defining copy number losses or gains. In traditional methods, references are usually pre-specified from cells that are assumed to be normal or disease-free. However, the use of pre-defined reference cells can bias results if common CNVs are present. Here, we present the development of a comprehensive statistical framework for data normalization and CNV detection in haploid single- or low-cell DNA sequencing data called HapCNV. The prominent advancement is the construction of a novel genomic location specific pseudo-reference that selects unbiased references using a preliminary cell clustering method. This approach effectively preserves common CNVs. Using simulations, we demonstrated that HapCNV outperformed existing methods by generating more accurate CNV detection, especially for short CNVs. Superior performance of HapCNV was also validated in detecting known CNVs in a realP. falciparumparasite dataset. In conclusion, HapCNV provides a novel and useful approach for CNV detection in haploid low-input sequencing datasets, with easy applicability to diploids.
Multiomic foundation model predicts epigenetic regulation by zero-shot
Authors: Yang Zikun , Fan Xueying , Lan Meng , Li Xin , You Yue , Tian Luyi , Church George , Liu Xiaodong , Gu Fei
Published: December 2024

Identifying genomic elements is challenging due to their cell type-specific nature and the influence of both genetic and epigenetic regulations. Unraveling the functional roles of genomic elements on genes and cellular states necessitates considerable resources. Here we propose the cis-Regulatory Element Transformer (CREformer), a large deep learning model to uncover functional and regulatory mechanisms through multimodal approaches. CREformer comprises 3 billion parameters, pretrained by integrating the advantages of both bulk and single-cell datasets, encompassing 55 billion nucleotides in bulk multiomic segments and 165 million single-cell paired multiomic profiles. After pretraining, CREformer performs all predictions in a zero-shot manner, which enables predictions in scenarios where no data is available for fine-tuning. This includes the computational inferences of master regulators, enhancers, gene regulatory networks (GRNs), and functional variants, as well as the in silico modeling of epigenetic perturbations, cellular state transitions, and disease treatments. Moreover, novel tumor treatment targets were discovered with CREformer and were validated in vitro. Overall, the foundational, zero-shot capabilities of CREformer have the potential to accelerate research into the comprehensive discovery of functional elements and their dynamics across a broad spectrum.
Prevalence of Computer Vision Syndrome Among University Students and Faculty During COVID-19 Pandemic
Authors: Al Ashkar Ihab Fouad , Alhammadi Amna Sayah , Bayram Ola Salam , Ammari Maria , Binashour Aisha Saleh , Mohamed Ahmed , Hussein A. , Talaat I
Published: December 2024

Introduction

The COVID-19 lockdown drastically increased screen time among students and faculty members due to online learning. Previous studies suggested increased screen time causes computer vision syndrome (CVS). This study aims to compare the prevalence of CVS among students and faculty in the UAE during the COVID-19 pandemic.

Methods

A descriptive cross-sectional study was conducted among 386 university students and faculty members across the UAE. A self-administered questionnaire was distributed online to collect socio-demographic data, symptoms of CVS, its associated factors, and the use of preventive measures. Informed consent was obtained, and participants who met the inclusion criteria were enrolled in the study. The indicated data were identified and analyzed using the 25th version of the SPSS program.

Results

Females were more likely to have computer vision syndrome, neck pain, back pain, and wrist pain. Students had a higher total screen time and a greater prevalence of Computer vision syndrome, 85.8% compared to faculty members. The prevalence of CVS was highest among students at the College of Science, 91.7%. Subjects who spent more time using the screen had more CVS symptoms than those who spent less time on screens (P= 0.039). Using laptops for more than 5 hours daily had a higher CVS prevalence of 90.6% (p=0.022). Wearing corrective eyeglasses was associated with increased CVS prevalence while taking breaks from the screen, which showed decreased prevalence. 52.5% of those with CVS experienced reduced productivity.

Conclusion

CVS was most prevalent in students; they also had higher screen time levels than faculty members.
Steps on the path to clinical translation – a survey of the UK MRI community
Authors: Markus Julia E , Hubbard Cristinacce Penny L , Punwani Shonit , O’Connor James PB , Mills Rebecca , Lopez Maria Yanez , Grech-Sollars Matthew , Fasano Fabrizio , Waterton John C , Thrippleton Michael J , Hall Matt G , Francis Susan T , Statton Ben , Murphy Kevin , So Po-Wah , Hyare Harpreet
Published: December 2024

Purpose

Our goal was to understand the barriers and challenges to clinical translation of quantitative MR (qMR) as perceived by stakeholders un the UK.

Methods

We conducted an electronic survey on 7 key areas related to clinical translation of qMR, developed at the BIC-ISMRM workshop: “Steps on the path to clinical translation”. Based on the 7 areas identified: (i) clinical workflow, (ii) changes in clinical practice, (ii) improving validation, (iv) standardisation of data acquisition and analysis, (v) sharing of data and code, (vi) improving quality management, and (vii) end-user engagement, a 40-question survey was developed. Members of BIC-ISMRM, MR-PHYSICS, BSNR and institutional mailing lists were invited to respond to the online survey over a 5-week period between September and October 2022. The responses were analysed via descriptive statistics of multiple-choice questions, Likert scores and a thematic analysis of free text questions.

Results

A total of 69 responses were received from predominantly research imaging scientists (69%) in numerous centres across the UK. Three main themes were identified: 1) the need to develop Consensus in terminology, decision making and validation; 2) an appreciation of uniqueness of each clinical situation and the need for Context Dependency; and 3) the importance of developing a Product Profile as early in development as possible.

Conclusion

Effective translation of qMR imaging and spectroscopic biomarkers to achieve their full clinical in the UK and internationally must address the differing needs and expectations of a wide range of stakeholders.
MAETi: Mild acid elution in a tip enables immunopeptidome profiling from 25,000 cells
Authors: Beyrle Julian , Distler Ute , Gomez-Zepeda David , Tenzer Stefan
Published: December 2024

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The identification of MHC class I presented ligands by mass spectrometry (MS)-based immunopeptidomics is an essential tool to characterize antigen processing pathways and to define targets for tumor immunotherapies. However, existing sample preparation workflows typically require large sample inputs, limiting the applicability in high throughput drug screenings, kinetic immunopeptidome studies and for scare samples in clinical contexts. To address this challenge, we developed Mild Acid Elution in a Tip (MAETi), an antibody-free approach for low input MHC-1 immunopeptidome profiling. Using an optimized β-alanine MAE-buffer for MAETi reduces background interferences, enhances peptide coverage, and boosts reproducibility. Comparing bulk β-alanine-based MAE with bulk immunoprecipitation (IP), achieves similar or complementary immunopeptidome depth. Using two protocol layouts we further profiled initial inputs from 25,000 to 1 Million cells with HLA-tailored DDA- and DIA-PASEF schemes yielding on average over 1,000 and 3,000 predicted binders, respectively (DIA). This renders MAETi a facile, fast and scalable method enabling robust MS-based immunopeptidomics for minimal sample inputs.

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Main messages / Highlights

MAETi is a simplified and optimized MAE workflow enabling MHC1-ligandomics profiling from sub-million cell samples down to 25,000 cells

We present a minimal, simplified sample preparation protocol termed Mild Acid Elution in a Tip (MAETi) enabling the MHC-1 ligandome analysis using 25,000 to 100,000,000 cells per sample as initial input

Replacing citric acid in the elution buffer by β-alanine reduced unspecific contaminants, resulted in cleaner LC-MS chromatograms and boosted 8-13mer identifications by over 50% in MAEti samples.

Bulk β-alanine-based MAE provides similar coverage of MHC class 1 ligands compared to bulk immunoprecipitation
Uncovering sex differences in Parkinson’s Disease through metaanalysis of single cell transcriptomic studies
Authors: Gordillo-González Fernando , Soler-Sáez Irene , Galiana-Roselló Cristina , Hidalgo Marta R. , Gómez-Cabañes Borja , Grillo-Risco Rubén , Dolader-Rabinad Beatriz , del Rey Díez Natalia , Virués-Morales Alejandro , Yanguas-Casás Natalia , Ferrer Franc Casanova , García-García Francisco
Published: December 2024

Abundant evidence supports the significant impact of biological sex on various aspects of Parkinson Disease (PD), including incidence, progression, symptoms or response to treatment. The incidence and prevalence of the disease is higher in males, while its age of onset is earlier than in females. There are also sex differences in the symptomatology, both motor and non-motor. In female PD, tremor, pain, depression and dysphagia are predominant, whereas in male PD, freezing of gait, camptocormia, cognitive impairment and urinary dysfunction are more common. Likewise, there are sex differences in the pathophysiology of the disease, related to most of the pathological processes of PD, as is the case of the greater activation of microglia in males or the lower oxidative stress in females. All these findings support the idea that different molecular mechanisms may be involved in PD depending on the sex of the patient. Some explanations for these events are related to biological, genetic, hormonal or environmental factors, such as the possible anti-inflammatory and neuroprotective effect of estrogens. However, the underlying molecular mechanisms have not yet been fully described. Our results show sex differences in gene expression, cell-cell communication and pathway activation in all major brain cell types, highlighting the presence of greater neuroinflammation in men and greater neurodegeneration in the SNpc in men, with the latter appearing to be inverted between sexes when observed in the cortical zone. Finally, we have made all the results available in a publicly accessible webtool, in order to allow the exploration of results to other researchers and to broaden the molecular-level understanding of PD sex differences.
Global diversity of putative functional viral auxiliary metabolic genes and their relationship with soil organic carbon stocks
Authors: Merges Dominik
Published: December 2024

Global biodiversity decline has prompted extensive research and debate on how biodiversity loss affects ecosystem functioning. Microbial taxonomic and functional diversity loss can impair critical processes such as plant biomass degradation or nitrogen fixation. Biotic interactions, especially those involving microbes and their viruses, are increasingly recognized as drivers of such processes. Microbial viruses carry auxiliary metabolic genes (AMGs), functional genes acquired from bacterial hosts, that mediate processes like carbon and nitrogen cycling, positioning viruses as potential reservoirs of essential ecosystem functions. To investigate the putative contribution of viral AMGs to microbial functional diversity and ecosystem functioning in soils, the global dataset of soil viral genomes, comprising 616,935 uncultivated viral genomes and 38,508 unique viral operational taxonomic units from 2,953 soil metagenomes, was mined for carbon (C) and nitrogen (N) cycling genes. For C cycling, 301 viral genomes with AMGs from glycoside hydrolase (GH) families (n cellulase = 182; n hemicellulase = 119) were detected. The viruses containing cellulase and hemicellulase AMGs were distributed across most major ecosystem types, including agricultural, forest, grassland, and permafrost soils, but were absent from deserts, salt marshes, and shrublands. Forest ecosystems harbored the highest abundance of cellulase and hemicellulase AMGs. The ratio of cellulase to hemicellulase AMGs varied by ecosystem, showing near parity in forests but cellulase dominance in agricultural, grassland, and permafrost soils. Relating AMGs to ecosystem functioning, sites with cellulase and hemicellulase AMGs showed significantly lower soil organic carbon (SOC) content in agricultural soils, whereas no significant differences were observed in forest, grassland, or permafrost soils. These results suggest that viral AMGs may influence SOC dynamics, particularly in agricultural systems, and highlight the need for deeper investigation into their functional roles in soil ecosystems. This study underscores the importance of viral contributions to ecosystem functioning, emphasizing the potential of microbial viruses to serve as mutualistic agents in global biogeochemical cycles.
A Palette of Bridged Bicycle-Strengthened Fluorophores
Authors: Zhang Junwei , Zhang Kecheng , Wang Kui , Wang Bo , Zhu Siyan , Qian Hongping , Ma Yumiao , Zhang Mengling , Liu Tianyan , Chen Peng , Shen Yuan , Fu Yunzhe , Fang Shilin , Zhang Xinxin , Zou Peng , Deng Wulan , Mu Yu , Chen Zhixing
Published: December 2024

Organic fluorophores are the keystone of advanced biological imaging. The vast chemical space of fluorophores has been extensively explored in seek of molecules with ideal properties. However, within the current molecular constraints, there appears to be a trade-off between high brightness, robust photostability, and tunable biochemical properties. Herein we report a general strategy to systematically boost the performance of donor-acceptor-type fluorophores by leveraging SO2and O-substituted azabicyclo[3.2.1] octane auxochromes. These bicyclic heterocycles give rise to a collection of ‘Bridged’ dyes (BD) spanning the UV and visible range with top-notch quantum efficiencies, enhanced water solubility, and tunable cell-permeability. Notably, these azabicyclic fluorophores showed remarkable photostability than its tetramethyl or azatidine analogue, at the same time completely resistant to oxidative photobluing rendered by the Bredt’s rule. Functionalized BD dyes are tailored for applications in single-molecule imaging, super-resolution imaging (STED and SIM) in fixed or live mammalian cells and plant cells, and live zebrafish imaging or chemigenetic voltage imaging. Synergizing with advanced imaging methods, the bridge bicycle dyes represent a versatile palette for biological researches.
Sparse Multitask group Lasso for Genome-Wide Association Studies
Authors: Nouira Asma , Azencott Chloé-Agathe
Published: December 2024

A critical hurdle in Genome-Wide Association Studies (GWAS) involves population stratification, wherein differences in allele frequencies among subpopulations within samples are influenced by distinct ancestry. This stratification implies that risk variants may be distinct across populations with different allele frequencies. This study introduces Sparse Multitask Group Lasso (SMuGLasso) to tackle this challenge. SMuGLasso is based on MuGLasso, which formulates this problem using a multitask group lasso framework in which tasks are subpopulations, and groups are population-specific Linkage-Disequilibrium (LD)-groups of strongly correlated Single Nucleotide Polymorphisms (SNPs). The novelty in SMuGLasso is the incorporation of an additional 𝓁1-norm regularization for the selection of population-specific genetic variants. As MuGLasso, SMuGLasso uses a stability selection procedure to improve robustness and gap-safe screening rules for computational efficiency.

We evaluate MuGLasso and SMuGLasso on simulated data sets as well as on a case-control breast cancer data set and a quantitative GWAS inArabidopsis thaliana. We show that SMuGLasso is well suited to addressing linkage disequilibrium and population stratification in GWAS data, and show the superiority of SMuGLasso over MuGLasso in identifying population-specific SNPs. On real data, we confirm the relevance of the identified loci through pathway and network analysis, and observe that the findings of SMuGLasso are more consistent with the literature than those of MuGLasso. All in all, SMuGLasso is a promising tool for analyzing GWAS data and furthering our understanding of population-specific biological mechanisms.

Author summary

Genome-Wide Association Studies (GWAS) scan thousands of genomes to identify loci associated with a complex trait. However, population stratification, which is the presence in the data of multiple subpopulations with differing allele frequencies, can lead to false associations or mask true population-specific associations. We recently proposed MuGLasso, a new computational method to address this issue. However, MuGLasso relied on an ad-hoc post-processing of the results to identify population-specific associations. Here, we present SMuGLasso, which directly identifies both global and population-specific associations.

We evaluate both MuGLasso and SMuGLasso on several datasets, including both case-control (such as breast cancer vs. controls) and quantitative (for example, plant flowering time) traits, and show on simulations that SMuGLasso is better suited than MuGLasso for the identification of population-specific associations. In addition, SMuGLasso’s findings on real case studies are more consistant with the literature than that of MuGLasso, which is possibly due to false discoveries of MuGLasso. These results show that SMuGLasso could be applied to other complex traits to better elucidate the underlying biological mechanisms.
Polyolefin colonization and partial degradation byGordoniasp., andArthrobactersp. isolated from wetlands and compost
Authors: Coughlin Scott A. , McFall Adam , Kelly Stephen A. , Megaw Julianne
Published: December 2024

Plastics and microplastics constitute an ever-increasing pollutant in the biosphere. There is clear evidence that environmental microbes possess enzyme systems and metabolic apparatus to degrade natural high molecular weight polymers, which substantially overlap with those involved in the biodegradation of plastics. This study investigated the presence and activities of plastic-degrading microbes in environments with a high abundance of plant-derived polymers, including cellulosic, chitinous, or lignin-derived compounds. Microbes were enriched in a minimal medium, with low-density polyethylene (LDPE), polypropylene (PP), poly(ethylene terephthalate) (PET), or polystyrene (PS) as the sole carbon source, resulting in 12 bacterial isolates. Plastic mass loss and cell viability were measured over a 28-day incubation period, in addition to assessment of biofilm formation.Gordoniasp. iso11 displayed mass loss of PP of up to 22.8% and formed a viable dense biofilm (109CFU cm-2) on a PP film. A putative alkane-1-monoxygenase (AlkB) was identified from genome sequence analysis, which aligned with a known LDPE-degrading enzyme. Furthermore, reductions in the contact angle of medium supernatant fromGordoniasp. iso11 provided evidence of biosurfactant production which may enhance the bioavailability of the synthetic plastic. To our knowledge, this is the first demonstration of PP degradation byGordonia.
MRS-Sim: Open-Source Framework for Simulating In Vivo-like Magnetic Resonance Spectra
Authors: LaMaster John , Oeltzschner Georg , Li Yan
Published: December 2024

MRS-Sim is a powerful, open-source framework for simulating in vivo-like magnetic resonance spectroscopy data. Its modularity allows it to model the complexities of MRS data for a variety of clinical scenarios. The underlying physical equations include spectral components commonly found in linear-combination fitting routines plus some novel components. The first is a 3DB0field map simulator to modelB0field inhomogeneities, ranging from slight variations to severe distortions. The second is a novel semi-parametric generator that mimics signals from poorly characterized residual water regions and baseline offset contributions. This framework can simulate everything from raw multi-coil transients to preprocessed coil-combined data.

A repository of information has been compiled to help non-expert users with general simulations of MRS data. Simulating realistic clinical-like datasets requires appropriate ranges and distributions for the model parameters, which are best determined by analyzing the parameter estimates from fitting real clinical data. Therefore, accompanying tools within MRS-Sim allow for analyzing the range and distributions of those parameters from in vivo datasets fitted with Osprey. This allows simulations to be tailored to specific clinical datasets.

The modularity of this framework allows for easy customization of simulations to suit a variety of clinical scenarios and encourages continued community development. Using a single framework for various scenarios overcomes the inconsistent protocols in current literature. By simulating in vivo-like data, this framework can aid in many tasks in MRS, including verifying spectral fitting protocols and reproducibility analyses. The accessibility of readily available, synthetic data will also assist deep learning research for MRS, particularly in cases where clinical data is insufficient or unavailable for training and, in general, will help address reproducibility issues and make MRS research more accessible to a wider audience.
Ocular Disease Prevalence in California Sea Lions In Human Care: Freshwater Versus Saltwater Housing
Authors: Brehm Ingrid , Herzner Silas , Baumgartner Katrin , Beckmann Jörg , Simon Ralph , von Fersen Lorenzo
Published: December 2024

California sea lions (Zalophus californianus), are susceptible to various ocular diseases, with some literature suggesting a heightened risk for those kept in freshwater pools as opposed to saltwater. Given the potential implications of housing conditions on animal health, we wanted to analyze the ocular health of two distinct groups of sea lions kept at Nuremberg Zoo, one housed in freshwater and the other in saltwater. Data extracted from the animals’ medical records over a ten-year period were used to compare the incidence of eye conditions and other medical conditions observed. The results revealed no significant difference in the overall prevalence of eye diseases between the two environments. However, a distinct seasonal pattern was noted: sea lions kept in freshwater exhibited a peak in eye disorders during the summer months, while those in saltwater displayed a more uniform distribution of the occurrence of ocular diseases throughout the year. These findings suggest that sun exposure and water quality are potentially more influential factors in the development of ocular diseases in pinnipeds than salinity or UV radiation. Further studies are necessary to elucidate the underlying mechanisms and optimize care practices for these marine mammals.

Simple Summary

This study investigated the ocular health of California sea lions (Zalophus californianus) at Nuremberg Zoo, comparing those housed in freshwater pools to those in saltwater. An analysis of medical records over ten years showed no significant difference in the overall prevalence of eye diseases between the two groups. However, sea lions in freshwater experienced a peak of eye disorders in the summer, while those in saltwater had a more consistent occurrence throughout the year. These results imply that factors such as sun exposure and water quality may play a more crucial in ocular disease development than salinity or UV radiation. The study highlights the need for further research to understand these dynamics and improve care for marine mammals.
CESA: Cross-species Epitope Sequence Analysis for discovery of existing antibodies useful for phospho-specific protein detection in model species
Authors: Hu Yanhui , Gao Chenxi , Mckenna William , Xia Baolong , Ariss Majd , Mohr Stephanie , Perrimon Norbert
Published: December 2024

Signaling pathways play key roles in many important biological processes such as cell division, differentiation, and migration. Phosphorylation site-specific antibodies specifically target proteins phosphorylated on a given tyrosine, threonine, or serine residue. Use of phospho-specific antibodies facilitates analysis of signaling pathway regulation and activity. Given the usefulness of phospho-specific antibodies, a number of collections of these antibodies have been generated, typically for detection of phosphorylated mammalian proteins. Anecdotal evidence shows that some of these are also useful for detection of phosphorylated forms of orthologous proteins in model organisms. We propose that anti-phospho-mammalian protein antibody collections comprise an untapped resource for research in other species. To systematically analyze the potential utility of anti-phospho-mammalian protein antibodies in other species, we developed the Cross-species Epitope Sequence Analysis software tool (CESA). CESA identifies and aligns orthologous proteins in model species, then analyzes conservation of antibody target sites. We used CESA to predict what phospho-specific antibodies in a collection from Cell Signaling Technology (CST) might be useful for studies inDrosophila melanogasterand other species. CESA predicts that more than 232 sites on 116Drosophilaproteins can potentially be targeted by the antibodies initially developed at CST to detect human, mouse, or rat phosphoproteins.
Geology and climate drive alpine plant compositional variation among peaks in the Cascade Range of Washington
Authors: Ertsgaard Erik W. , Gjording Nicholas L. , Bakker Jonathan D. , Kleinkopf Joseph A. , Giblin David E.
Published: December 2024

Alpine areas are host to diverse plant communities that support ecosystems through structural and floral resources and persist through specialized adaptations to harsh high-elevation conditions. An ongoing question in these plant communities is whether composition is shaped by stochastic processes (e.g., dispersal limitations) or by deterministic processes (e.g., climate, geology), and if those processes select for common phylogenetic clades across space. This study evaluates the drivers of dissimilarity in alpine vascular plant communities across 32 peaks in the Cascade Mountain Range of Washington State and examines the effects of incorporating phylogenetic relatedness to these conclusions. We documented an average of 54 species per peak and used our overall inventory of 307 taxa to construct a phylogenetic tree for the entire mountain range plant community sampled. We used multivariate techniques to quantify the phylogenetic and taxonomic differences between alpine plant communities and to relate those differences to each peak’s climate, geology, and topography. Our models indicate that the age of each peak’s parent material formation, precipitation, latitude, and temperature had the largest role in shaping alpine plant communities relative to the baseline effects of distance between peaks and time of sampling. A unique result was a distinct plant community in peaks with ultramafic geologic parent material formed in the Paleozoic Era, which has an extreme geochemistry that we found to form evolutionarily distinct lineages compared to all other peaks. With changing climate conditions and disturbance regimes, understanding facets of alpine plant communities like species turnover, geologic endemism, and responses to precipitation changes are vital to conserving these ecosystems.
Computational Analysis of the Gut Microbiota-Mediated Drug Metabolism
Authors: Chum Sammie , Naveira Montalvo Alberto , Hassoun Soha
Published: December 2024

The gut microbiota, an extensive ecosystem harboring trillions of bacteria, plays a pivotal role in human health and disease, influencing diverse conditions from obesity to cancer. Among the microbiota’s myriad functions, the capacity to metabolize drugs remains relatively unexplored despite its potential implications for drug efficacy and toxicity. Experimental methods are resource-intensive, prompting the need for innovative computational approaches. We present a computational analysis aimed at predicting gut microbiota-mediated drug metabolism (MDM). This computational analysis incorporates data from diverse sources, e.g., UHGG, MagMD, MASI, KEGG, and RetroRules. An existing tool, PROXIMAL2, is used iteratively over all drug candidates from experimental databases queried against biotransformation rules from RetroRules to predict potential drug metabolites along with the enzyme commission number responsible for that biotransformation. These potential metabolites are then categorized into gut microbiota-mediated drug metabolites by cross referencing UHGG. The analysis’ efficacy is validated by its coverage on each of the experimental databases in the gut microbial context, being able to recall up to 74% of experimental data and producing a list of potential metabolites, which an average of about 65% are relevant to the gut microbial context. Moreover, explorations into ranking metabolites, iterative applications to account for multi-step metabolic pathways, and potential applications in experimental studies showcase its versatility and potential impact beyond raw predictions. Overall, this study presents a promising computational analysis for further research and application in the fields of gut MDM, drug development and human health.
Verkko2: Integrating proximity ligation data with long-read De Bruijn graphs for efficient telomere-to-telomere genome assembly, phasing, and scaffolding
Authors: Antipov Dmitry , Rautiainen Mikko , Nurk Sergey , Walenz Brian P. , Solar Steven J. , Phillippy Adam M. , Koren Sergey
Published: December 2024

The Telomere-to-Telomere Consortium recently finished the first truly complete sequence of a human genome. To resolve the most complex repeats, this project relied on the semi-manual combination of long, accurate PacBio HiFi and ultra-long Oxford Nanopore sequencing reads. The Verkko assembler later automated this process, achieving complete assemblies for approximately half of the chromosomes in a diploid human genome. However, the first version of Verkko was computationally expensive and could not resolve all regions of a typical human genome. Here we present Verkko2, which implements a more efficient read correction algorithm, improves repeat resolution and gap closing, introduces proximity-ligation-based haplotype phasing and scaffolding, and adds support for multiple long-read data types. These enhancements allow Verkko to assemble all regions of a diploid human genome, including the short arms of the acrocentric chromosomes and both sex chromosomes. Together, these changes increase the number of telomere-to-telomere scaffolds by twofold, reduce runtime by fourfold, and improve assembly correctness. On a panel of 19 human genomes, Verkko2 assembles an average of 39 of 46 complete chromosomes as scaffolds, with 21 of these assembled as gapless contigs. Together, these improvements enable telomere-to-telomere comparative and pangenomics, at scale.
Navigating the Maze: Identifying Potential Pitfalls in Attention State Classification from fMRI Brain Patterns
Authors: Bressler Ruben Andreas , Ciarlo Assunta , Raible Sophie , Valente Giancarlo , Lührs Michael , Tier Ralph , Linden David E. , Goebel Rainer
Published: December 2024

Multi-voxel pattern analysis (MVPA) is a powerful technique to decode brain states from functional magnetic resonance imaging (fMRI) activity patterns. In neurofeedback (NF) applications, it has been used to perform real-time classification of brain activity patterns, establishing a closed-loop system that provides immediate feedback to the participants, enabling them to learn to control a complex mental state. However, MVPA has many potential limitations when applied to fMRI datasets (especially in real-time analysis) arising from small effect sizes, small number of training samples, high dimensionality of the data and, more generally, design choices. All these factors might produce inaccurate classification results. In this work, we followed a previous NF paradigm for sustained attention training. Participants were presented with composite images superimposing faces and scenes. They were instructed to focus on one class (either face or scene) for an extended period. A logistic regression classifier was trained to determine whether participants were adequately focusing on the instructed category based on their fMRI data. We analysed the classification outputs of the no-feedback training runs using various classifier settings, including whole brain data and different masking approaches, combined with different methods for the computation of single-trial fMRI responses. Furthermore, a ventricle mask was used as a control condition for the classification task, and simulations were carried out to assess the influence of the class order on the classification performances. We found inflation of the decoding accuracy for several common design choices and confounders. In particular, motion artefacts and low frequency drifts coupled with the task timing might have artificially increased the accuracy scores. Furthermore, the simulations revealed that fixed order in the presentation of experimental conditions resulted in further inflation of the classification accuracies especially in GLM-based and average-based trial estimate methods. We discuss the drawbacks of applying MVPA using the analysed sustained attention paradigm and provide insights for future improvements.
An evolutionarily conserved tryptophan cage promotes folding of the extended RNA recognition motif in the hnRNPR-like protein family
Authors: Atsrim Ernest S. , Eichhorn Catherine D.
Published: December 2024

The heterogeneous nuclear ribonucleoprotein (hnRNP) R-like family is a class of RNA binding proteins in the hnRNP superfamily that has diverse functions in RNA processing. Here, we present the 1.90 Å X-ray crystal structure and solution NMR studies of the first RNA recognition motif (RRM) of human hnRNPR. We find that this domain adopts an extended RRM (eRRM1) featuring a canonical RRM with a structured N-terminal extension (Next) motif that docks against the RRM and extends the β-sheet surface. The adjoining loop positions the Nextfor docking to the RRM and forms a tryptophan cage motif, which has only been reported previously in a synthetic peptide. Using a combination of mutagenesis, solution NMR spectroscopy, and thermal denaturation studies we evaluate the importance of residues in the Next-RRM interface and adjoining loop on eRRM folding and conformational dynamics. We find that these sites are essential for protein solubility, thermal stability, and conformational ordering. Consistent with their importance, mutations in the Next-RRM interface and loop are associated with several cancers in a survey of somatic mutations in cancer studies. Sequence and structure comparison of the human hnRNPR eRRM1 to experimentally verified and predicted hnRNPR-like proteins reveal conserved features in the eRRM.

Significance statement

This study provides the first structural and thermodynamic analysis of the hnRNPR extended RNA recognition motif (eRRM1). Here an N-terminal extension docks alongside a canonical RRM, stabilized by an intervening loop containing a tryptophan cage motif. Highly conserved among hnRNPR-like proteins, this motif has only been previously observed in a synthetic peptide. Substitutions that disrupt observed interactions reduce thermal stability and are associated with cancers. These findings significantly advance our understanding of atypical RRM folding.
Genomic and transcriptomic profiling of high-risk bladder cancer reveals diverse molecular and microenvironment ecosystems
Authors: Meghani Khyati , Yu Yanni , Frydenlund Noah , Li Erik Z. , Choy Bonnie , Abdulkadir Sarki A. , Meeks Joshua J.
Published: December 2024

Despite surgical resection, rigorous endoscopic surveillance, and immunotherapy with the Bacillus Calmette–Guérin (BCG) vaccine, 30% of high-risk bladder cancers recur, and 10% result in fatal outcomes within two years of diagnosis. The global shortage of BCG underscores the urgent need for alternative or complementary therapeutic strategies. To address this, we integrated transcriptomic profiling and targeted genomic sequencing to identify four consensus intrinsic subtypes of bladder cancer. Initially derived from bulk RNA profiling, these subtypes were further validated at the cellular and tissue-compartment levels using single-cell RNA sequencing and spatial transcriptomics. Notably, we identified a subtype of inflamed tumors with enhanced endogenous retroelement expression and increased commensal bacterial presence, which showed the highest responsiveness to BCG therapy. Additionally, we developed a machine learning-based model incorporating composite molecular features to predict recurrence risk, achieving a high accuracy (AUC = 0.90). Our findings establish a molecular precision framework for bladder cancer and nominate novel therapeutic targets to reduce reliance on BCG immunotherapy.
tRNA modifying enzymes MnmE and MnmG are essential for Plasmodium falciparum apicoplast maintenance
Authors: Elahi Rubayet , Dinis Luciana Ribeiro , Swift Russell P , Liu Hans B , Prigge Sean T
Published: December 2024

The circular genome of the Plasmodium falciparum apicoplast contains a complete minimal set of tRNAs, positioning the apicoplast as an ideal model for studying the fundamental factors required for protein translation. Modifications at tRNA wobble base positions, such as xm5s2U, are critical for accurate protein translation. These modifications are ubiquitously found in tRNAs decoding two-family box codons ending in A or G in prokaryotes and in eukaryotic organelles. Here, we investigated the xm5s2U biosynthetic pathway in the apicoplast organelle of P. falciparum. Through comparative genomics, we identified orthologs of enzymes involved in this process: SufS, MnmA, MnmE, and MnmG. While SufS and MnmA were previously shown to catalyze s2U modifications, we now show that MnmE and MnmG are apicoplast-localized and contain features required for xm5s2U biosynthetic activity. Notably, we found that P. falciparum lacks orthologs of MnmC, MnmL, and MnmM, suggesting that the parasites contain a minimal xm5s2U biosynthetic pathway similar to that found in bacteria with reduced genomes. Deletion of either MnmE or MnmG resulted in apicoplast disruption and parasite death, mimicking the phenotype observed in ΔmnmA and ΔsufS parasites. Our data strongly support the presence and essentiality of xm5s2U modifications in apicoplast tRNAs. This study advances our understanding of the minimal requirements for protein translation in the apicoplast organelle.
Leukemia escapes immunity by imposing a Type-1 regulatory program on neoantigen-specific CD4+ T cells
Authors: Venkatesh Hrishi , Arroyo Miriam , Heltemes-Harris Lynn , Knutson Todd P. , Qiu Yinjie , Haaning Allison , Webber Beau R. , Bachanova Veronika , Farrar Michael A. , Tracy Sean I.
Published: December 2024

The significance of endogenous immune surveillance in acute lymphoblastic leukemia (ALL) remains controversial. Using clinical B-ALL samples and a novel mouse model, we show that neoantigen-specific CD4+ T cells are induced to adopt type-1 regulatory (Tr1) function in the leukemia microenvironment. Tr1s then inhibit cytotoxic CD8+ T cells, preventing effective leukemia clearance. Leukemic cells induce Tr1s by phenocopying hematopoietic stem cells, which normally are subject to effective surveillance by this CD4+ subset. This mechanism effectively redirects Tr1 cells from a role in preventing cancer to maladaptively promoting clinical relapse. In mouse models, inhibition of Tr1 expansion with IL10 receptor (IL10R) blockade is insufficient to improve leukemia control. In contrast, combined therapy with a cytotoxic agent and anti-PDL1 blockade eradicated measurable residual disease. This correlates with polarization of the neoantigen-specific CD4+ T-cell population from Tr1 towards Th1 states. Our findings uncover a mechanism that enables leukemic relapse and resolves existing controversies on the role of immune surveillance towards this cancer type. Therapeutic polarization of neoantigen-specific CD4+ T cells towards Th1 states may improve contemporary immune therapies by reshaping the immune microenvironment towards states permissive for cytotoxic attack of residual leukemia.

Key Points

B-ALL induces neoantigen-specific CD4+ T cells to adopt Type-1 regulatory states, which protect leukemic cells from immune pressure.

Repolarizing neoantigen-specific CD4+ T-cells towards Th1 states eradicates measurable residual disease.