bluuebunny/crossref_metadata_2025 huggingface dataset:
Precursor RNA structural patterns at SF3B1 mutation sensitive cryptic 3’ splice sites
Authors: Herbert Austin , Hatfield Abigail , Randazza Alexandra , Miyamoto Valeria , Palmer Katie , Lackey Lela
Published: February 2025

SF3B1 is a core component of the spliceosome involved in branch point recognition and 3’ splice site selection. SF3B1 mutation is common in myelodysplastic syndrome and other blood disorders. The most common mutation in SF3B1 is K700E, a lysine to glutamic acid change within the pre-mRNA interacting heat repeat domain. A hallmark of SF3B1 mutation is an increased use of cryptic 3’ splice sites; however, the properties distinguishing SF3B1-sensitive splice junctions from other alternatively spliced junctions are unknown. We identify a subset of 192 core splice junctions that are mis-spliced with SF3B1 K700E mutation. We use our core set to test whether SF3B1-sensitive splice sites are different from control cryptic 3’ splice sites via RNA structural accessibility. As a comparison, we define a set of SF3B1-resistant splice junctions with cryptic splice site use that does not change with SF3B1 K700E mutation. We find sequence differences between SF3B1-sensitive and SF3B1-resistant junctions, particularly at the cryptic sites. SF3B1-sensitive cryptic 3’ splice sites are within an extended polypyrimidine tract and have lower splice site strength scores. We develop experimental RNA structure data for 83 SF3B1-sensitive junctions and 39 SF3B1-resistant junctions. We find that the pattern of structural accessibility at the NAG splicing motif in cryptic and canonical 3’ splice sites is similar. In addition, this pattern can be found in both SF3B1-resistant and SF3B1-sensitive junctions. However, SF3B1-sensitive junctions have cryptic splice sites that are less structurally distinct from the canonical splice sites. In addition, SF3B1-sensitive splice junctions are overall more flexible than SF3B1-resistant junctions. Our results suggest that the SF3B1-sensitive splice junctions have unique structure and sequence properties, containing poorly differentiated, weak splice sites that lead to altered 3’ splice site recognition in the presence of SF3B1 mutation.
Biplanar nulling coil system for OPM-MEG using printed circuit boards
Authors: Jas Mainak , Kamataris John , Matsubara Teppei , Dong Chunling , Motta Gabriel , Sohrabpour Abbas , Ahlfors Seppo P. , Hämäläinen Matti , Okada Yoshio , Sundaram Padmavathi
Published: February 2025

Optically pumped magnetometers (OPMs) are a promising sensor technology for non-invasive measurement of human electrophysiological signals, in particular the magnetoencephalogram (MEG). OPMs do not need cryogenic cooling and can be placed conformal to the subject’s scalp, thus greatly reducing the sensor-to-source distance and improving signal sensitivity. OPMs, however, require near-zero background magnetic field to achieve linearity and minimize signal distortion. Prior work has proposed the use of biplanar field nulling coils to remove the uniform and gradient components of the background magnetic field. Biplanar coils have been expensive to construct, involving tedious error-prone manual winding of over 1000 m of copper wire. In this work, we designed and fabricated background field nulling coils (three uniform and three gradient components) on two-layer Printed Circuit Boards (PCBs). We used an open-source software (bfieldtools) to determine the current loops needed to produce the target magnetic field in a 50-cm-diameter spherical volume. We developed a software-based approach to connect the discrete current loops into a continuous conducting path traversing the two layers of the PCB. For ease of manufacture, the designed (1.5 × 1.5 m2) coils were cut along the symmetry axis and printed as pairs of 1.5 × 0.75 m2PCBs (2 oz Cu), soldered together and mounted on a sliding aluminum frame. The efficiency of the coils (1.3 - 7.1 nT/mA) was similar or higher than previously reported in the literature. We mapped the field inside the target region after field nulling inside our single-layer shielded room and were able to reduce the largest component of the background field from 21 to 2 nT. Using our nulling coil system, we were able to operate OPMs in a lightly shielded room (background field varying from 6.5 to 108 nT in the floor-to-ceiling direction) to record somatosensory evoked fields (SEFs) comparable to those measured using SQUID-based MEG in a 3-layer shielded room. We disseminate the software and hardware as an open-source packageopmcoils. This work will facilitate access to more affordable field nulling coils for OPM-MEG and help to realize the potential of OPM-MEG as an accessible sensor technology for use in human neuroscience.
Multiphase separation in postsynaptic density regulated by membrane geometry via interaction valency and volume
Authors: Yamada Risa , Brandani Giovanni B. , Takada Shoji
Published: February 2025

Biomolecular condensates are found at various cellular locations, nucleus, cytoplasm, and membrane. These condensates often contain multiple components and can separate into multiple phases with various morphologies such as core-shell droplets, implicating functional roles. Demixing of condensates and their arrangements are determined by competitive interactions and by their locations. Recent studies reported a puzzling multiphase morphology of four components of postsynaptic density: AMPA-receptor, NMDA-receptor, PSD-95, and CaMKII. The multiphase morphology becomes apparently reversed as we move from the solubilized constructs to the membrane. In this study, using this system as a model, we study the multiphase behavior of condensates in solution (3D) and domain formation on and beneath the membrane (2D) and elucidate molecular mechanisms behind the puzzle. Our mesoscopic simulations reproduce that the CaMKII activation induces the core-shell multiphase separation found in 3Din vitroexperiment with AMPA-receptor/PSD-95 at the core and NMDA-receptor/CaMKII in the shell. Then, we obtain a reversed morphology on the postsynaptic membrane. The high valency and large volume of CaMKII appears to be a major factor in this reversal. Interestingly, we find that, while the CaMKII has dominant non-specific volume interaction in the 3D system, the specific multivalent interactions overcome the volume interaction for CaMKII beneath the membrane, reversing the morphology. On the membrane, the layered structures of receptors and CaMKIIs reduce the volume effects of CaMKII on receptors, making the multivalent interaction dominant. The membrane domain formation is distinct from the condensate formation in solution and modulated by their layered arrangement.

Significance

Many proteins form condensates in cells, which are often further separated into two or more phases, implicating functional roles. Recent experiments on postsynaptic density proteins provide an interesting puzzle on a multiphasic morphology; while they form core-shell droplets with AMPA-receptor at the core and NMDA receptor in the shell in soluble constructs, the multiphase morphology is reversed when they form nanodomains on the membrane. This study identifies the mechanism behind the puzzle by using computer simulations with a mesoscale model. While active CaMKII, an inducer of the multiphase morphology, has dominant non-specific volume interactions in solution, its specific domain-domain multivalent interaction overcomes the volume interaction under the membrane with their layered arrangement.
scWGBS-GPT: A Foundation Model for Capturing Long-Range CpG Dependencies in Single-Cell Whole-Genome Bisulfite Sequencing to Enhance Epigenetic Analysis
Authors: Liang Chaoqi , Ye Peng , Yan Hongliang , Zheng Peng , Sun Jianle , Wang Yanni , Li Yu , Ren Yuchen , Jiang Yuanpei , Xiang Junjia , Zhang Sizhe , Jiang Linle , Bai Weiqiang , Ma Xinzhu , Chen Tao , Zuo Wangmeng , Bai Lei , Ouyang Wanli , Li Jia
Published: February 2025

Single-Cell Whole-Genome Bisulfite Sequencing (scWGBS) is a powerful technique for profiling DNA methylation at single-cell and single-nucleotide resolution, providing critical insights into epigenetic regulation in development, disease, and cellular heterogeneity. However, analyzing scWGBS data remains a significant challenge due to ultra-long genomic sequences with millions of CpG sites and sparse, stochastic coverage. Here, we introduce scWGBS-GPT, the first generative foundational language model specifically designed for high-resolution analysis of scWGBS data at the single-CpG level. By combining CpG special token design, Mamba backbone and Cross-Attention head, scWGBS-GPT efficiently processes ultra-long sequences while preserving both local CpG interactions and broader genomic context, enabling biologically meaningful interpretations. Pretrained on 1,000,000 single cells from 28 human and mouse tissues, scWGBS-GPT reconstructs sparse methylation landscapes, enhancing the resolution and accuracy of epigenetic analyses. It significantly outperforms existing methods in key biomedical applications—improving cell clustering to uncover previously unrecognized cellular heterogeneity, enhancing trajectory inference to map precise differentiation pathways, and automating the identification of critical epigenetic biomarkers relevant to disease progression and therapeutic targeting. These advancements establish scWGBS-GPT as a transformative tool in single-cell epigenomics, setting a new standard for DNA methylation analysis and unlocking novel insights into epigenetic mechanisms underlying health and disease. The code for scWGBS-GPT is available athttps://github.com/ChaoqiLiang/scWGBS-GPT.

Highlights

scWGBS-GPT is the first foundation language model for scWGBS data analysis, trained on over 1,000,000 single cells from 28 human and mouse tissues, spanning 221 cell types.

scWGBS-GPT combines CpG special token design, Mamba backbone, and Cross-Attention head for efficient processing of up to 2 million CpG sites per cell.

scWGBS-GPT achieves State-of-the-Art Performance in Cell Clustering, Annotation, Pseudotime Inference.

scWGBS-GPT is compatible with bulk WGBS data and excels in deconvoluting cell-free DNA methylation data, precisely inferring the tissue or organ of origin, enhancing non-invasive diagnostic capabilities.
The Greenland shark genome: insights into deep-sea ecology and lifespan extremes
Authors: Yang Kaqiao , Nishiwaki Kazuya , Mizobata Hideaki , Asakawa Shuichi , Yoshitake Kazutoshi , Watanabe Yuuki Y. , Hussey Nigel E. , Kovacs Kit M. , Lydersen Christian , Kadota Mitsutaka , Kuraku Shigehiro , Kinoshita Shigeharu
Published: February 2025

The Greenland shark (Somniosus microcephalus) is known for its slow metabolism and deep-sea habitat. It is considered the longest-lived vertebrate on Earth, with an estimated lifespan of 392±120 years. Despite its remarkable longevity and lifestyle, there have been no genomic studies on this species. Here, we report the first, chromosome-level assembly of the Greenland shark genome, which is 5.9 Gb in size with an N50 length of 233 Mb, and contains 37,125 predicted genes with a completeness score of 86.5%. We found that the copy numbers of three gene families (TNF,TLR,LRRFIP), which are involved in activating the NF-κB signaling pathway, are significantly increased in the Greenland shark compared to short-lived shark species. In the rhodopsin of this deep-sea dweller, we detected amino acid substitutions that result in spectral tuning for the so-called 'blue shift', suggesting adaptive evolution to dim-light vision. We also elucidate the dynamics of the effective population size (Ne) of the Greenland shark and its close relative, the Pacific sleeper shark (Somniosus pacificus). These genomic analyses offer new insights into the molecular basis of the exceptional longevity of the Greenland shark and highlight potential genetic mechanisms that could inform future research into longevity.
Impact of Long Term Integrated Nutrient Management Practices on Soil Bacterial Diversity: A 16S rRNA-Based Metagenomic Approach
Authors: Ahlawat Vishal , Ahalawat Navjeet , Boora Nisha , Dadarwal R S , Dhanda Deepika , Sangwan Pooja , Kumar Vipin , Kumar Rajiv , Yadav Parmod Kumar
Published: February 2025

The growing world’s population, expected to surpass 9 billion by 2050, demands a 70–100% increase in farm productivity, posing significant challenges for sustainable agriculture. Conventional farming, reliant on chemical fertilizers and pesticides, negatively impacts environmental sustainability and food quality. Metagenomics, a culture-independent technique, has revolutionized the study of microbial communities by enabling comprehensive analysis of microbial diversity and function. This study evaluated the effects of combined nutrient management practices—including farmyard manure (FYM), wheat straw, green manure, and NPK fertilizers—on soil bacterial diversity using 16S rRNA-based metagenomic analysis. Key findings revealed the dominance of bacterial phyla such as Proteobacteria, Actinobacteria, and Firmicutes, which play critical roles in nutrient cycling, organic matter decomposition, and plant growth promotion. Distinct taxonomic distributions were observed across the samples, with Proteobacteria and Firmicutes dominating in control (T1), NPK (T2), and NPK_Green Manure (T5) treatments, while a shift in phyla composition was noted in NPK_FYM (T3) and NPK_WheatStraw (T4). Genus-level analysis revealed that Pseudomonas and Bacillus species were abundant in control (T1) and NPK (T2), while Sphingomonas species were dominant in NPK_FYM (T3). Further diversity analyses revealed significant variation across the samples, with T3 showing the highest richness and control (T1) showing the lowest richness. The rarefaction curve confirmed sufficient sampling for capturing microbial diversity, while beta diversity analysis, including Principal Coordinate Analysis (PCA) and Bray-Curtis clustering, indicated distinct microbial community structures across different treatments. The combined use of organic amendments with NPK fertilizer enhanced microbial diversity and population, indicating their potential to support resilient and productive soil ecosystems.
Detection of human unannotated microproteins by mass spectrometry-based proteomics: a community assessment
Authors: Wacholder Aaron , Deutsch Eric W , Kok Leron W , van Dinter Jip T , Lee Jiwon , Wright James C , Leblanc Sebastien , Jayatissa Ayodya H , Jiang Kevin , Arefiev Ihor , Cao Kevin , Bourassa Francis , Trifiro Felix-Antoine , Bassani-Sternberg Michal , Baranov Pavel V , Bogaert Annelies , Chothani Sonia , Fierro-Monti Ivo , Fijalkowska Daria , Gevaert Kris , Hubner Norbert , Mudge Jonathan M , Ruiz-Orera Jorge , Schulz Jana , Vizcaino Juan Antonio , Prensner John R , Brunet Marie A , Martinez Thomas F , Slavoff Sarah A , Roucou Xavier , Choudhary Jyoti S , van Heesch Sebastiaan , Moritz Robert L. , Carvunis Anne-Ruxandra
Published: February 2025

Thousands of short open reading frames (sORFs) are translated outside of annotated coding sequences. Recent studies have pioneered searching for sORF-encoded microproteins in mass spectrometry (MS)-based proteomics and peptidomics datasets. Here, we assessed literature-reported MS-based identifications of unannotated human proteins. We find that studies vary by three orders of magnitude in the number of unannotated proteins they report. Of nearly 10,000 reported sORF-encoded peptides, 96% were unique to a single study, and 12% mapped to annotated proteins or proteoforms. Manual curation of a benchmark dataset of 406 manually evaluated spectra from 204 sORF-encoded proteins revealed large variation in peptide-spectrum match (PSM) quality between studies, with immunopeptidomics studies generally reporting higher quality PSMs than conventional enzymatic digests of whole cell lysates. We estimate that 65% of predicted sORF-encoded protein detections in immunopeptidomics studies were supported by high-quality PSMs versus 7.8% in non-immunopeptidomics datasets. Our work stresses the need for standardized protocols and analysis workflows to guide future advancements in microprotein detection by MS towards uncovering how many human microproteins exist.
Demystifying The Myelingratio: Its Origin, Derivation and Interpretation
Authors: Gow Alexander
Published: February 2025

Most studies involving myelingratios over the past 120 years assume this metric enumerates changes in myelin thickness (largergratio = thinner myelin) with axon or fiber diameter. And, moreover, such changes are directly correlated with internodal function (conduction velocity). However, such assumptions are warranted only in the absence of experimental errors and artifacts (i.e. under theoretical conditions). In reality,gratios easily under- or overestimate rates of change exceeding 10%, especially for small caliber fibers. Typical analyses of myelin internodes rely on an explicit mathematical model,, where DAis axon diameter and DFis fiber diameter (myelin plus axon). Shown recently and herein, this model approximates normal physiological conditions only when the axon-fiber diameter relation is directly proportional, whence it is concordant with the axomyelin unit model. However, in transient or non-steady states (development/aging, disease or myelin plasticity) with linear but not directly proportional relations,gratios poorly describe myelin structure. Acceptance of this counterintuitive assertion is predicated on a detailed understanding of thegratio – origins, properties and the biology represented – heretofore uncharted. In light of suchgratio limitations, more general and reliable metrics are proposed, the myelingcratio and theg’cline.
Hybrid Neural Network Models Explain Cortical Neuronal Activity During Volitional Movement
Authors: Mao Hongwei , Hasse Brady A , Schwartz Andrew B
Published: February 2025

Massive interconnectivity in large-scale neural networks is the key feature underlying their powerful and complex functionality. We have developed hybrid neural network (HNN) models that allow us to find statistical structure in this connectivity. Describing this structure is critical for understanding biological and artificial neural networks. The HNNs are composed of artificial neurons, a subset of which are trained to reproduce the responses of individual neurons recorded experimentally. The experimentally observed firing rates came from populations of neurons recorded in the motor cortices of monkeys performing a reaching task. After training, these networks (recurrent and spiking) underwent the same state transitions as those observed in the empirical data, a result that helps resolve a long-standing question of prescribed vs ongoing control of volitional movement. Because all aspects of the models are exposed, we were able to analyze the dynamic statistics of the connections between neurons. Our results show that the dynamics of extrinsic input to the network changed this connectivity to cause the state transitions. Two processes at the synaptic level were recognized: one in which many different neurons contributed to a buildup of membrane potential and another in which more specific neurons triggered an action potential. HNNs facilitate modeling of realistic neuron-neuron connectivity and provide foundational descriptions of large-scale network functionality.
Heat-induced secondary dormancy contributes to local adaptation in Arabidopsis thaliana
Authors: Tran Nhu Loc Thuy , Ali Tahir , Schmitz Gregor , de Meaux Juliette
Published: February 2025

Seeds should not germinate under conditions in which seedling development cannot be sustained. Dormancy, which allows seeds to remain inactive in an environment that would otherwise enable germination, helps optimize the timing of germination. The induction of a secondary type of dormancy after seed dispersal allows seeds to fine-tune germination to prevailing environmental conditions. In this study, we explore the relevance of secondary dormancy in response to heat for adaptation to local environments by characterizing natural variation in heat-induced secondary dormancy within a collection of 361Arabidopsis thalianaaccessions originating from across the European geographical range. We found that the acquisition of secondary dormancy varies with levels of primary dormancy and after-ripening. We found that both primary dormancy and heat-induced secondary dormancy formed an adaptive cline along temperature and precipitation gradients. The slope of this cline was steeper for secondary dormancy than for primary dormancy, indicating that secondary dormancy contributes most to local adaptation. Using species distribution models, we find that genotypes with high secondary dormancy are predicted to be more resilient to future climate change. We further identified several regions in the genome that specifically controlled the levels of secondary dormancy, one of which contained a novel candidate gene for secondary dormancy variation. Our findings show that secondary dormancy is a complex adaptive mechanism and a predominant contributor to the dormancy trait syndrome that favors plant survival in habitats exposed to harsh summers.

Summary statement

Secondary dormancy induced by heat exposure allows seed to adjust their germination strategies to the environment. This study shows that heat-induced secondary dormancy inArabidopsis thalianadepends on levels of primary dormancy. Its covariance with climatic parameter indicates that it can contribute to population resilience to climate change. This study further identifies the specific genetics underlying the ability to induce dormancy after dispersal.
The preclinical cardiac phenotype of the DE50-MD dog model of Duchenne muscular dystrophy
Authors: Sargent Julia , Fuentes Virginia Luis , Terry Rebecca , Riddell Dominique O. , Harron Rachel CM , Wells Dominic J. , Piercy Richard J.
Published: February 2025

Cardiomyopathy is the leading cause of death in the X-linked disorder, Duchenne Muscular Dystrophy (DMD) yet optimal management strategies remain undetermined. Advances in the search for novel DMD treatments, particularly at cell and molecular levels, rely heavily on the use of translational animal models. It is crucial that these models faithfully recapitulate the human clinical phenotype to best expedite the development of promising treatments.

We sought comprehensively to describe the cardiac phenotype of DE50-MD dogs, a novel dystrophin-deficient model that harbours a mutation within the principal DMD mutational hotspot. Cardiac magnetic resonance imaging and echocardiographic studies were performed at approximately 12-week intervals in male, 3- to 18- month-old DE50-MD (n=17) and age-matched littermates, wild type (WT, n=14) dogs. Late gadolinium enhancement (LGE) imaging was performed in a subpopulation of DE50-MD (n=10) and WT (n=11) dogs aged 9 to 18 months. The DE50-MD dogs had smaller left ventricular (LV) mass and LV dimensions than WT dogs. While global ventricular systolic function was preserved, DE50-MD dogs showed early differences in strain and strain rate parameters. Only DE50-MD dogs demonstrated LGE (3/8 dogs studied at 18 months); the subepicardial to transmural, mid-to-basal LV LGE distribution resembling that of DMD patients and of other dystrophic dog models. Histopathological assessment confirmed that LGE corresponded to fibrofatty myocardial scarring, as described in DMD patients and other canine models of dystrophin-deficient cardiomyopathy. The DE50-MD early preclinical cardiac phenotype shares key features of DMD cardiomyopathy prior to onset of global LV systolic dysfunction. Their disproportionately low LV volume to mass supports possible combined physiological hypotrophy and tonic contraction in affected animals.
Predicting Neuroplasticity Effects of Continuous Theta Burst Stimulation with Biomarkers from the Motor Evoked Potential TMS Input-Output Curve
Authors: Parchure Shreya , Xu Zihang , Shah-Basak Priyanka , Erickson Brian , Harvey Denise , Wurzman Rachel , McAfee Darrian , Sacchetti Daniela , Faseyitan Olufunsho , Hamilton Roy H.
Published: February 2025

The field of neuromodulation lacks predictors of individual differences in plasticity that influence responses to repetitive transcranial magnetic stimulation (rTMS). Continuous theta burst stimulation (cTBS), a form of rTMS known for its inhibitory effects, shows variable responses between individuals, potentially due to differences in neuroplasticity. Predicting individual cTBS effects could vastly enhance its clinical and experimental utility. This study explores whether motor evoked potential (MEP) input-output (IO) parameters measured prior to neuromodulation can predict motor cortex responses to cTBS. IO curves were sampled from healthy adults by recording MEPs over a range of single pulse TMS intensities to obtain parameters including MEPmaxand S50(midpoint intensity). Subjects later received cTBS over the same location of motor cortex and their MEPs before and after stimulation were compared. Both MEPmaxand S50predicted responses, significantly correlating (p<0.05, R2>0.25) with individuals’ MEP changes at 10, 20, and 30 minutes after cTBS. Further, we introduced and validated an easily implementable biomarker that does not require the time-consuming sampling of full IO curve: MEP130RMT(median of 10 MEPs at 130% RMT). MEP130RMTwas also a strong predictor of cTBS response (p<0.005, R2>0.3). Head-to-head comparison against a previously studied genetic biomarker of rTMS responses (BDNF polymorphism) showed that IO based predictors had a superior performance in explaining more response variability. Thus, IO curves derived prior to cTBS administration can reliably predict cTBS-induced changes in cortical excitability. This work points toward an accessible strategy for tailoring stimulation procedures in both diagnostic and therapeutic applications of rTMS, and potentially boosting response rate to other brain stimulation approaches.

HIGHLIGHTS

Baseline TMS-MEP Input-Output (IO) Curve parameters significantly predict MEP responses to M1 cTBS.

Higher MEPmaxat baseline predicts more robust inhibitory response to cTBS, while higher midpoint intensity (S50) is associated with less response.

D We developed and validated a new biomarker MEP130RMT, which predicts cTBS response using just 10 baseline MEPs from single TMS pulses of 130% RMT intensity.

Head to head comparison against BDNF genotyping shows superior performance of IO biomarkers.
The alternative oxidase reconfigures the larval mitochondrial electron transport system to accelerate growth and development inDrosophila melanogaster
Authors: Garcia Geovana S , Othonicar Murilo F , Campos Antonio Thiago P , Kilbourn Eric A , Bicego Kenia C , Lerchner Johannes , Tennessen Jason M , Oliveira Marcos T
Published: February 2025

The alternative oxidase (AOX) is naturally present in the mitochondrial electron transfer system (ETS) of many organisms but absent in vertebrates and most insects. AOX oxidizes coenzyme Q and reduces O2in H2O, partially replacing the ETS cytochrome c segment and alleviating the oxidative stress caused by ETS overload. As successfully demonstrated in animal models, AOX shows potential in mitigating mitochondrial diseases. However, its non-proton-pumping nature may uncouple mitochondria, leading to excessive heat generation and interference with normal metabolism and physiology. Here we show that AOX from the tunicateCiona intestinalisaccelerates development ofDrosophila melanogaster, elevating larval biomass accumulation (primarily due to increased fat), mobility and food intake, without increasing body heat production. AOX intensifies Leak respiration and lowers oxidative phosphorylation efficiency through functional interactions with the mitochondrial glycerol-3-phosphate dehydrogenase (mGPDH). This is associated with increased complex I (CI)-driven respiration and supercomplex formation, higher cellular NAD+/NADH ratios, and an enhanced flux through the central carbon metabolism. Chemical uncouplers and rotenone confirm the roles of mitochondrial uncoupling and CI in the development of AOX-expressing larvae. Thus, AOX appears to be promoting increased growth by reinforcing the larval proliferative metabolic program via an intricate mechanism that reconfigures the larval ETS.
In vitro reconstitution of minimal human centrosomes
Authors: Rios Manolo U. , Stachera Weronika E. , Familiari Nicole E. , Brito Claudia , Surrey Thomas , Woodruff Jeffrey B.
Published: February 2025

CDK5RAP2/CEP215 is a key pericentriolar material (PCM) protein that recruits microtubule-nucleating factors at human centrosomes. Using anin vitroreconstitution system, we show that CDK5RAP2 is sufficient to form micron-scale scaffolds around a nanometer-scale nucleator in a PLK-1-regulated manner. CDK5RAP2 assemblies recruited and activated gamma tubulin ring complexes (γ-TuRCs) which, in the presence of α/β tubulin, generated microtubule asters. We found that F75 in CDK5RAP2 is partially needed to recruit γ-TuRC yet is indispensable for γ-TuRC activation. Furthermore, our system recapitulated key features of centrosome-amplified cancer cells. CDK5RAP2 scaffolds selectively recruited the molecular motor KifC1/HSET, which enhanced concentration of α/β tubulin, microtubule polymerization, and clustering of the assemblies. Our results highlight the specificity and selectivity ofin vitrogenerated CDK5RAP2 scaffolds and identify a minimal set of components required for human centrosome assembly and function. This minimal centrosome model offers a powerful tool for studying centrosome biology and dysfunction in human health and disease.
CRISPR-CISH: Anin situchromogenic DNA repeat detection system for research and life science education
Authors: Potlapalli Bhanu Prakash , Dassau Fabian , Fuchs Jörg , Sushmoy Deboprio Roy , Houben Andreas
Published: February 2025

In situhybridization is a technique to visualize specific DNA sequences within nuclei and chromosomes. Various DNAin situfluorescent labeling methods have been developed, which typically involve global DNA denaturation prior to the probe hybridization and often require fluorescence microscopes for visualization. Here, we report the development of a CRISPR/dCas9-mediated chromogenicin situDNA detection (CRISPR-CISH) method that combines chromogenic signal detection with CRISPR imaging. This non-fluorescent approach uses 3’ biotin-labeled tracrRNA and target-specific crRNA to form mature gRNA, which activates dCas9 to bind to target sequences. The subsequent application of streptavidin alkaline phosphatase or horseradish peroxidase generates chromogenic, target-specific signals that can be analyzed using conventional bright-field microscopes. Additionally, chromatin counterstains were identified to aid in the interpretation of CRISPR-CISH-generated target signals. This advancement makesin situDNA detection techniques more accessible to researchers, diagnostic applications, and educational institutions in resource-limited settings.
Metalation calculator forE. colistrain BW25113 grown in M9 minimal media
Authors: Clough Sophie E. , Glasfeld Arthur , Robinson Nigel J.
Published: February 2025

Here we provide the background data supporting an additional web-based calculator to predict in-cell metalation of proteins withinE. coliBW25113 grown in M9 media. Intracellular metal availabilities have been estimated from the calibrated responses of DNA-binding, metal-sensing, transcriptional regulators. We have previously tested and validated metalation calculator predictions. They confirm that when proteins are expressed heterologously inE. coliin LB medium, they can become mismatched to metal availability and be mismetalated. Mg2+GTP-CobW fromRhodobacteris predicted to be correctly metalated with cobalt inE. coligrown in M9 media, although mismetalated with zinc in LB-grown heterologous cells. Similarly, MncA fromSynechocystisPCC 6803 is predicted to be correctly metalated with manganese inE. coligrown in M9 media, although mismetalated with iron in LB-grown heterologous cells. The M9 metalation calculator is available online and as a spreadsheet for use in optimising metalation in engineering biology. An MncA-refined metalation calculator for idealised cells, reflecting the midpoint of intracellular metal availabilities, is also included and available online.
Discovery of inhibitors for bacterial Arr enzymes ADP-ribosylating and inactivating rifamycin antibiotics
Authors: Alaviuhkola Juho , Abdulmajeed Sondos , Sowa Sven T. , Lehtiö Lari
Published: February 2025

ADP-ribosylation is an enzymatic process where an ADP-ribose moiety is transferred from NAD+ to an acceptor molecule. While ADP-ribosylation is well-established as a post-translational modification of proteins, rifamycin antibiotics are its only known small-molecule targets. ADP-ribosylation of rifampicin was first identified inMycolicibacterium smegmatis, whose Arr enzyme transfers the ADP-ribose moiety to the 23-hydroxy group of rifampicin preventing its interaction with the bacterial RNA polymerase thereby inactivating the antibiotic. Arr homologues are widely spread among bacterial species and present in several pathogenic species often associated with mobile genetic elements. Inhibition of Arr enzymes offers a promising strategy to overcome ADP-ribosylation mediated rifamycin resistance. We developed a high-throughput activity assay, which was applied to screen an in-house library of human ADP-ribosyltransferase-targeted compounds. We identified 15 inhibitors with IC50values below 5 μM against four Arr enzymes fromM. smegmatis,Pseudomonas aeruginosa,Stenotrophomonas maltophiliaandMycobacteroides abscessus. The observed overall selectivity of the hit compounds over the other homologues indicated structural differences between the proteins. We crystallizedM. smegmatisandP. aeruginosaArr enzymes, the former in complex with its most potent hit compound with an IC50value of 1.3 μM. We observed structural differences in the NAD+ binding pockets of the two Arr homologues explaining the selectivity. Although the Arr inhibitors did not sensitizeM. smegmatisto rifampicin in a growth inhibition assay, the structural information and the collection of inhibitors provide a foundation for rational modifications and further development of the compounds.
N153-linked glycans on envelope protein protect orthoflaviviruses from antibody-mediated clearance
Authors: Ting Donald Heng Rong , Marzinek Jan Kazimierz , Wan Corrine , Palur Raghuvamsi V. , Idris Fakhriedzwan , Xin Tan Eunice Tze , Clara Koh Wei Teng , Lim Xin Ni , Thein Tun-Linn , Lim Cheer Vee , Ng Chin Huan , Buckley Theresa S. C. , Walsh Ian , MacAry Paul A. , Leo Yee-Sin , Anand Ganesh S. , Chan Kuan Rong , Nguyen-Khuong Terry , Bond Peter John , Alonso Sylvie
Published: February 2025

The envelope (E) protein of dengue virus (DENV) is glycosylated at two highly conserved asparagine (N) sites (N67 and N153). The role and importance of these N-linked glycans in DENV pathogenesis has been elusive. Here, we report the critical role of N153-linked glycans on E protein in preventing antibody-mediated viral clearance. A DENV2 mutant lacking N153-linked glycans (N153Q mutant) was engineered and found to be mildly impairedin vitrobut drastically attenuated in a symptomatic mouse model of severe dengue, as evidenced by accelerated viral clearance. In B cell-deficient mouse models, N153Q mutant displayed parental virulence and viremia profile. Homologous and heterologous passive transfers of purified IgM from infected B cell-proficient mice into B cell-deficient mice demonstrated the role of N153Q-specific IgM in N153Q attenuation and accelerated clearance, while WT DENV was unaffected by IgM from both WT- and N153Q-infected mice. Furthermore,in vitroneutralization assay supported that the accelerated clearance of N153Q mutant in mice was mediated by non-neutralizing IgM. Furthermore, using plasma samples from convalescent dengue patients and monoclonal antibodies,in vitroneutralization assays showed that N153Q virus was more susceptible than WT to IgG-mediated neutralization. Glycoproteomics combined with molecular dynamics (MD) simulations revealed that glycan composition on E protein influenced IgG binding. Our findings were extended to all DENV serotypes and ZIKV, hence supporting that the N153 glycans-mediated immune evasion strategy is conserved across orthoflaviviruses.
Automating Imaging Biomarker Analysis for Knee Osteoarthritis Using an Open-Source MRI-Based Deep Learning Pipeline
Authors: Goyal Ananya , Belibi Francesca , Sahani Vyoma , Pedersen Rune , Vainberg Yael , Williams Ashley , Chu Constance , Haddock Bryan , Gold Garry , Chaudhari Akshay , Kogan Feliks , Gatti Anthony
Published: February 2025

Osteoarthritis (OA) is a leading cause of chronic disability worldwide, with knee OA being the most prevalent form. Quantitative assessment of knee joint tissues using Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) has the potential to enhance OA diagnosis and progression tracking. However, current methodologies for segmenting and extracting quantitative metrics from knee joint images are time-consuming, require extensive expertise, and suffer from inter- and intra-reader variability, limiting their clinical translation.

In this study, we present and validate a fully automated AI-based pipeline for comprehensive segmentation and quantitative analysis of knee joint tissues from MRI and PET images. Our pipeline segments key joint tissues, including femoral, tibial, and patellar bones, femoral, patellar, and tibial cartilage, and medial and lateral menisci, using a deep learning-based segmentation model. Furthermore, the pipeline enables automated extraction of critical quantitative OA biomarkers, including regional cartilage thickness and T2 relaxation times, meniscus volume, a neural shape model-derived OA bone shape score, and [18F]NaF PET-based measures of subchondral bone metabolism.

To evaluate the segmentation performance, we validated automated segmentations against manual segmentations from two annotators and compared derived quantitative metrics. Results demonstrated high segmentation accuracy, with DSC values ranging from 0.84 to 0.98 across different tissues. Automated quantitative measurements exhibited good to excellent agreement with manual-derived values for most metrics, with ICC values exceeding 0.89. Our findings suggest that the proposed AI-based pipeline provides a robust, open-source tool for efficient and reproducible quantitative analysis for knee OA studies, accelerating research and clinical adoption of whole-joint quantitative imaging.
A Cluster-Randomized Trial to Compare Effectiveness and Cost-effectiveness of Cash Plus Interventions in Preventing Child Wasting in Somalia: An Evidence-Based Methodology
Authors: Walton Shelley , Alier Kemish Kenneth , Garretson Sydney , Grounds Samantha , Khattak Qundeel , Tripaldi Marina , Loddo Fabrizio , Mohamoud Said Aden , Nur Mohamud Ali , Abdiqadir Sadiq , Mitchell Emily , Mahat Mohamed Billow , Gure Maimun , Jibril Dahir I. , Gedi Dahir , Ocircan Michael , Omer Meftuh , Arays Abdullahi , Mohamed Abdifitah Ahmed , Mohamed Adam Abdulkadir , Akseer Nadia
Published: February 2025

Background

Somalia is a conflict, flood, and drought prone country with high rates of food insecurity and child wasting. Save the Children partnered with Johns Hopkins University to study the most effective and cost-effective combinations of assistance to prevent acute malnutrition among PLW and CU5 in a six-month humanitarian program.

Objectives

This study implemented an cluster-randomized controlled trial using adaptive design methodology to: (A) Estimate and compare wasting incidence and prevalence of CU5 and their mothers receiving on a monthly basis either cash (Arm 1), cash + social and behavior change communication (Arm 2), or cash+ top-up cash (Arm 3); after 3 months and 6 months; (B) Calculate the costs and cost-effectiveness of the different intervention arms; (C) Understand perspectives and experiences of mothers and fathers of CU5 beneficiaries; (D) Monitor the functionality of markets and availability and prices of foods. This paper presents the approach that was designed and implemented to study these objectives.

Methodology

This study employed a mixed-methods approach with a quantitative component conducted at three timepoints to collect anthropometric measurements and household survey data. Primary outcomes, such as child and maternal wasting, were assessed using standardized WHO criteria. Additional data on food security, maternal and child health, and household conditions were collected to evaluate immediate, underlying, and basic causes of malnutrition. Cost analyses evaluated programmatic and societal costs of the intervention. An adaptive trial design was implemented, allowing the methodology to evolve as new challenges emerged.

Conclusion

This trial applied an adaptive mixed methods design to evaluate the effectiveness and cost-effectiveness of cash assistance interventions in Somalia, overcoming complex humanitarian operational challenges. Strong partnerships and flexible trial design allowed us to adjust to unpredictable events and maintain research rigor. These findings highlight the value of adaptive designs and mixed methods for improving child nutrition outcomes in complex settings.

Registration

The cluster-RCT is registered at ClinicalTrials.gov, ID:NCT06642012.
Cardiovascular-kidney-metabolic disease burden in children and adults following heart transplantation
Authors: Huang Shi , Farber-Eger Eric , Tamaroff Jaclyn , Chow Nelson , Siddiqi Hasan K. , Brinkley D. Marshall , Menachem Jonathan N. , Rali Aniket S. , Lindenfeld JoAnn , Ooi Henry , Punnoose Lynn , Tsai Stacy , Pedrotty Dawn , Zalawadiya Sandip , Sacks Suzanne , Wigger Mark , Williams Aaron M. , Bommareddi Swaroop , Lima Brian , Nguyen Duc , Shah Ashish S. , Trahanas John M. , Bearl David W. , Wells Quinn S. , Schlendorf Kelly H. , Amancherla Kaushik
Published: February 2025

Background

Heart transplantation (HT) is the definitive therapy for end-stage heart failure. However, with improving post-HT survival in the modern era, recipients are increasingly cumulatively exposed to unique risk factors for cardiovascular-kidney-metabolic (CKM) dysfunction. An expanded understanding of the incidence and prevalence of CKM dysfunction post-HT may inform screening and therapeutic strategies to mitigate adverse events.

Objectives

The aim of this study was to characterize the incidence and prevalence of CKM risk factors in adult and pediatric HT recipients at a high-volume heart transplant center.

Methods

We conducted a single-center retrospective observational study in adults and children who underwent HT between 1/1/2015 and 6/30/2024. Longitudinal clinical and laboratory data were extracted from the electronic health record. Incidence rates (IRs) of type 2 diabetes mellitus (DM2), overweight or obesity, hypertension, chronic kidney disease (CKD), and dyslipidemia were calculated. We constructed longitudinal predictive models of CKM dysfunction and evaluated the impact of SGLT2 inhibitors (SGLT2i) and GLP1 receptor agonists (GLP1ra) on CKD and body mass index (BMI), respectively.

Results

During the study period, 860 adults and 84 children underwent HT. Among adults, the IR (reported as cases per 100 person-years) of DM2, overweight or obesity, dyslipidemia, and CKD were 28.6, 77.3, 139.1, and 69.7 respectively. Among children, the IR of DM2, overweight or obesity, dyslipidemia, and CKD were 2.8, 26.9, 5.5, and 3.6, respectively. Within 12 months post-HT, 99% of adults developed stage 1 or 2 hypertension and 22.1% of all adults developed HbA1c ≥6.5%, regardless of pre-existing diagnosis of DM2. Similarly, 37.5% of adults developed moderate-severe hypertriglyceridemia and 31.1% manifested worsened LDL-C control. Among adults with an eGFR ≥45 mL/min/1.73 m2pre-HT, 86.2% demonstrated worsening renal function (eGFR <45 mL/min/1.73 m2) within 12-months post-HT. In adults initiated on SGLT2i post-HT (N = 242), there was a non-linear improvement in eGFR during the ensuing 12 months while for individuals initiated on GLP1ra (N = 168), there was a predominantly linear reduction in BMI.

Conclusions

A significant proportion of HT recipients experience new-onset or worsening CKM dysfunction following HT. Our results indicate that SGLT2i and GLP1ra may mitigate the burden of CKM disease.
Involvement of RNase J in CRISPR RNA maturation and degradosome formation in cyanobacteria
Authors: Bilger Raphael , Drepper Friedel , Knapp Bettina , Berndt Tanja , Landerer Helena , Putzer Harald , Huesgen Pitter , Hess Wolfgang R.
Published: February 2025

Many bacteria and archaea use CRISPR-Cas systems, which provide RNA-based, adaptive, and inheritable immune defenses against invading viruses and other foreign genetic elements. The proper processing of CRISPR guide RNAs (crRNAs) is a crucial step in the maturation of the defense complexes and is frequently performed by specialized ribonucleases encoded bycasgenes. However, some systems employ enzymes associated with degradosome or housekeeping functions, such as RNase III or the endoribonuclease RNase E. Here, the endo- and 5′-exoribonuclease RNase J was identified as additional enzyme involved in crRNA maturation, acting jointly with RNase E in the crRNA maturation of a type III-Bv CRISPR-Cas system, and possibly together with a further RNase. Co-IP experiments revealed a small set of proteins that were co-enriched with RNase J, among them PNPase. Despite a measured, strong 3’ exonucleolytic activity of the recombinant enzyme, PNPase was not confirmed to contribute to crRNA maturation. However, the co-IP results indicate that PNPase is a component of the cyanobacterial degradosome that can recruit either RNase E or RNase J, together with additional enriched proteins.
Sequence-based chromatin activity modeling and regulatory impact prediction of genetic variants in farmed animals using deep learning
Authors: Nguyen Dat Thanh , Knutsen Tim Martin , Sandve Simen R. , Lien Sigbjørn , Grønvold Lars
Published: February 2025

Non-coding genomic variations are crucial for the genetic regulation of traits; how-ever, their functional impact in farmed animals remains underexplored due to lim-ited genomic resources and the absence of tailored computational tools. Here, we present a deep learning-based framework that utilizes functional genomics data to generate genome-wide predictions of the regulatory impact of non-coding vari-ants in cattle, chicken, pig, and Atlantic salmon. By leveraging chromatin profiles such as ATAC, DHS, and ChIP-seq data, we train and optimize separate deep networks for each species, achieving robust sequence modeling accuracy specific to each. Motif analysis confirms that the models capture regulatory grammar, while in silico saturation mutagenesis experiments provide meaningful interpretations of the functional impact of putative causal variants. Furthermore, functional scores derived from these models predict eQTL causal variants and enhance genomic prediction performance. Our findings highlight the transformative potential of se-quence to function models in prioritizing causal variants and improving genomic prediction for livestock and aquaculture.