bluuebunny/crossref_metadata_2025 huggingface dataset:
Perturbations in mitochondrial metabolism associated with defective cardiolipin biosynthesis: Anin-organelloreal-time NMR study
Authors: Rua Antonio J. , Mitchell Wayne , Claypool Steven M. , Alder Nathan N. , Alexandrescu Andrei T.
Published: June 2024

Mitochondria are central to cellular metabolism; hence, their dysfunction contributes to a wide array of human diseases including cancer, cardiopathy, neurodegeneration, and heritable pathologies such as Barth syndrome. Cardiolipin, the signature phospholipid of the mitochondrion promotes proper cristae morphology, bioenergetic functions, and directly affects metabolic reactions carried out in mitochondrial membranes. To match tissue-specific metabolic demands, cardiolipin typically undergoes an acyl tail remodeling process with the final step carried out by the phospholipid-lysophospholipid transacylase tafazzin. Mutations in thetafazzingene are the primary cause of Barth syndrome. Here, we investigated how defects in cardiolipin biosynthesis and remodeling impact metabolic flux through the tricarboxylic acid cycle and associated pathways in yeast. Nuclear magnetic resonance was used to monitor in real-time the metabolic fate of13C3-pyruvate in isolated mitochondria from three isogenic yeast strains. We compared mitochondria from a wild-type strain to mitochondria from a Δtaz1strain that lacks tafazzin and contains lower amounts of unremodeled cardiolipin, and mitochondria from a Δcrd1strain that lacks cardiolipin synthase and cannot synthesize cardiolipin. We found that the13C-label from the pyruvate substrate was distributed through about twelve metabolites. Several of the identified metabolites were specific to yeast pathways, including branched chain amino acids and fusel alcohol synthesis. Most metabolites showed similar kinetics amongst the different strains but mevalonate and α-ketoglutarate, as well as the NAD+/NADH couple measured in separate nuclear magnetic resonance experiments, showed pronounced differences. Taken together, the results show that cardiolipin remodeling influences pyruvate metabolism, tricarboxylic acid cycle flux, and the levels of mitochondrial nucleotides.
PathoLM: Identifying pathogenicity from the DNA sequence through the Genome Foundation Model
Authors: Dip Sajib Acharjee , Shuvo Uddip Acharjee , Chau Tran , Song Haoqiu , Choi Petra , Wang Xuan , Zhang Liqing
Published: June 2024

Pathogen identification is pivotal in diagnosing, treating, and preventing diseases, crucial for controlling infections and safeguarding public health. Traditional alignment-based methods, though widely used, are computationally intense and reliant on extensive reference databases, often failing to detect novel pathogens due to their low sensitivity and specificity. Similarly, conventional machine learning techniques, while promising, require large annotated datasets and extensive feature engineering and are prone to overfitting. Addressing these challenges, we introduce PathoLM, a cutting-edge pathogen language model optimized for the identification of pathogenicity in bacterial and viral sequences. Leveraging the strengths of pre-trained DNA models such as the Nucleotide Transformer, PathoLM requires minimal data for fine-tuning, thereby enhancing pathogen detection capabilities. It effectively captures a broader genomic context, significantly improving the identification of novel and divergent pathogens. We developed a comprehensive data set comprising approximately 30 species of viruses and bacteria, including ESKAPEE pathogens, seven notably virulent bacterial strains resistant to antibiotics. Additionally, we curated a species classification dataset centered specifically on the ESKAPEE group. In comparative assessments, PathoLM dramatically outperforms existing models like DciPatho, demonstrating robust zero-shot and few-shot capabilities. Furthermore, we expanded PathoLM-Sp for ESKAPEE species classification, where it showed superior performance compared to other advanced deep learning methods, despite the complexities of the task.
Full-length direct RNA sequencing reveals extensive remodeling of RNA expression, processing and modification in agingCaenorhabditis elegans
Authors: Schiksnis Erin C. , Nicastro Ian A. , Pasquinelli Amy E.
Published: June 2024

Organismal aging is marked by decline in cellular function and anatomy, ultimately resulting in death. To inform our understanding of the mechanisms underlying this degeneration, we performed standard RNA sequencing and Nanopore direct RNA sequencing over an adult time course inCaenorhabditis elegans.Long reads allowed for identification of hundreds of novel isoforms and age-associated differential isoform accumulation, resulting from alternative splicing and terminal exon choice. Genome-wide analysis reveals a decline in RNA processing fidelity and a rise in inosine and pseudouridine editing events in transcripts from older animals. In this first map of pseudouridine modifications forC. elegans, we find that they largely reside in coding sequences and that the number of genes with this modification increases with age. Collectively, this analysis discovers transcriptomic signatures associated with age and is a valuable resource to understand the many processes that dictate altered gene expression patterns and post-transcriptional regulation in aging.
Acute nicotine vapor normalizes sensorimotor gating and reduces locomotor activity deficits in HIV-1 transgenic rats
Authors: Jha Neal A. , Ayoub Samantha M. , Flesher M. Melissa , Morton Kathleen , Sikkink Megan , de Guglielmo Giordano , Khokhar Jibran Y. , Minassian Arpi , Brody Arthur L. , Young Jared W.
Published: June 2024

Rationale

Despite improved life expectancy of people with HIV (PWH), HIV-associated neurocognitive impairment (NCI) persists, alongside deficits in sensorimotor gating and neuroinflammation. PWH exhibit high smoking rates, possibly due to neuroprotective, anti-inflammatory, and cognitive-enhancing effects of nicotine, suggesting potential self-medication.

Objectives

Here, we tested the effects of acute nicotine vapor exposure on translatable measures of sensorimotor gating and exploratory behavior in the HIV-1 transgenic (HIV-1Tg) rat model of HIV.

Methods

Male and female HIV-1Tg and F344 control rats (n=57) were exposed to acute nicotine or vehicle vapor. Sensorimotor gating was assessed using prepulse inhibition (PPI) of the acoustic startle response, and exploratory behavior was evaluated using the behavioral pattern monitor (BPM).

Results

Vehicle-treated HIV-1Tg rats exhibited PPI deficits at low prepulse intensities compared to F344 controls, as seen previously. No PPI deficits were observed in nicotine-treated HIV-1Tg rats, however. HIV-1Tg rats were hypoactive in the BPM relative to controls, whilst nicotine vapor increased activity and exploratory behavior across genotypes. Cotinine analyses confirmed comparable levels of the primary metabolite of nicotine across genotypes.

Conclusions

Previous findings of PPI deficits in HIV-1Tg rats were replicated and, importantly, attenuated by acute nicotine vapor. Evidence for similar cotinine levels suggest a nicotine-specific effect in HIV-1Tg rats. HIV-1Tg rats had reduced exploratory behavior compared to controls, attenuated by acute nicotine vapor. Therefore, acute nicotine may be beneficial for remediating sensorimotor and locomotor activity deficits in PWH. Future studies should determine the long-term effects of nicotine vapor on similar HIV/NCI-relevant behaviors.
Association between Brain Morphometry and Cognitive Function during Adolescence: Insights from a Comprehensive Large-Scale Analysis from 9 to 15 Years Old
Authors: Yan Jiadong , Iturria-Medina Yasser , Bezgin Gleb , Toussaint Paule Joanne , Hilger Kirstin , Genc Erhan , Evans Alan , Karama Sherif
Published: June 2024

During the adolescent developmental stage, significant changes occur in both brain structure and cognitive function. Brain structure serves as the foundation for cognitive function and can be accurately assessed using a comprehensive set of brain cortical and subcortical morphometry measures. Exploring the association between whole-brain morphometry and cognitive function during adolescence can help elucidate the underlying relationship between brain structural development and cognitive development. Despite extensive research in this area, previous studies have two main limitations. Firstly, they often use a limited number of brain morphometry measures, which do not provide a comprehensive representation of brain structure and did not consider the complementarity among different measures. Secondly, most previous studies rely on relatively small sample sizes, increasing the risk of sampling error, low statistical power, and even overestimation of effects. To address these limitations, we analyzed the Adolescent Brain Cognitive Development (ABCD) dataset, which includes 8543 subjects (13,992 scans) aged 9-15 years. These scans were categorized into 6 groups with one-year intervals based on their ages for independent age-specific analysis. Moreover, we calculated 16 brain regional morphometry measures derived from Structural Magnetic Resonance Imaging (SMRI), Diffusion Tensor Imaging (DTI), and Restriction Spectrum Imaging (RSI), and integrated them with morphometric similarity networks (MSNs). This approach enabled us to calculate 16,563 morphometry measures encompassing brain region, connection, and hub aspects. Subsequently, these measures were input into a robust large-scale computational model to control for each other and investigate their relationship with 8 cognitive performances. We found that the brain areas most significantly associated with cognitive function during adolescence, as well as those showing the greatest variability in their associations between ages 9 and 15, were primarily situated in the frontal and temporal lobes. In contrast, the subcortex was the least involved. Additionally, we observed strong correlations between key brain morphometry measures related to cognitive performances within same domain. Furthermore, we found that SMRI measures demonstrated stronger associations with cognitive performances compared to DTI and RSI measures. And overall structural network measures were more important than local ones. Overall, our study aims to facilitate a comprehensive and reliable understanding of the association between brain morphometry and cognitive function during adolescence.
The Retrosplenial Cortical Role in Delayed Spatial Alternation
Authors: Subramanian Dev Laxman , Miller Adam M.P. , Smith David M.
Published: June 2024

The retrosplenial cortex (RSC) plays an important role in spatial cognition. RSC neurons exhibit a variety of spatial firing patterns and lesion studies have found that the RSC is necessary for spatial working memory tasks. However, little is known about how RSC neurons might encode spatial memory during a delay period. In the present study, we trained control rats and rats with excitotoxic lesions of the RSC on spatial alternation task with varying delay durations and in a separate group of rats, we recorded RSC neuronal activity as the rats performed the alternation task. We found that RSC lesions significantly impaired alternation performance, particularly at the longest delay duration. We also found that RSC neurons exhibited reliably different firing patterns throughout the delay periods preceding left and right trials, consistent with a working memory signal. These differential firing patterns were absent during the delay periods preceding errors. We also found that many RSC neurons exhibit a large spike in firing rate leading up to the start of the trial. Many of these trial start responses also differentiated left and right trials, suggesting that they could play a role in priming the ‘go left’ or ‘go right’ behavioral responses. Our results suggest that these firing patterns represent critical memory information that underlies the RSC role in spatial working memory.
O-Glycosylated RNA Identification and Site-specific Prediction by Solid-phase Chemoenzymatic TnORNA method and PONglyRNA tool
Authors: Li Jiajia , Wang Linshu , Chen Yan , Zhang Shaomei , Wen Zhongmin , Zhen Xuechu , Zhang Haiyun , Zhou Yuan , Xu Longjiang , Yang Shuang
Published: June 2024

Recent studies have shown that the cell surface undergoes post-transcriptional modification by N-linked glycosylation. However, the question of whether RNA can be glycosylated by O-glycans remains to be explored. The presence of O-glycosylation in cells is indirectly revealed by the presence of O-glycans on RNAs following treatment with O-glycoproteases. To identify RNA O-glycosylation, we have developed a chemoenzymatic method for capturing and enriching O-glycosylated RNA (O-glycoRNA) using covalent immobilization on a solid support. GalNAcEXO selectively releases Tn-containing O-glycosylated RNAs (TnORNA). Using this method and SPCgRNA, we compared the expression of O-glycoRNAs and N-glycoRNAs in pancreatic cancer cell lines and tissues. We found that glycosylated miR-103a-3p, miR-122-5p, and miR-4492 regulate pancreatic cancer cell growth and proliferation through the PI3K-Akt pathway. In vitro assays and PDAC tissue analysis confirmed the potential regulatory roles of Tn-O-glycosylated miRNAs in pancreatic tumor growth and metastasis. Furthermore, a significant number (131) of miRNAs carrying both N- and Tn-O-glycosylation were identified, indicating the co-occurrence of N-linked and O-linked glycosylation on small RNAs. We have also developed PONglyRNA, an online bioinformatic tool for the site-specific prediction of RNA glycosylation. PONglyRNA identifies glycosylation motifs based on RNA sequence and has been validated using our glycoRNA data. In conclusion, this study establishes robust experimental and computational tools for identifying O-linked glycoRNAs. Additionally, it uncovers the novel role of glycosylation in PDAC development and progression through altered glycosylation of oncogenic miRNAs.

Graphical Abstract
Label-free visualization of ciliary rootlets in mouse brain
Authors: Murakami Yusuke , Nuriya Mutsuo , Hu Zuliang , Tomioka Masaki , Oketani Ryosuke , Hiramatsu Kotaro , Leproux Philippe , Inoko Akihito , Honjoh Sakiko , Kano Hideaki
Published: June 2024

Neuronal primary cilia are important role in brain development, sensory perception and neurogenesis. Rootletin, a fibrous protein composed of coiled-coil motifs, is a major structural component of ciliary rootlets and is essential for understanding ciliary functions. However, the precise mechanisms by which Rootletin influences ciliary dynamics and impacts neuronal function remain largely unknown, primarily due to the challenges in visualizing these structures. Here, we describe a label-free, rapid, and highly sensitive method to visualize Rootletin molecules in brain tissue. This platform integrates a second harmonic generation (SHG) microscope and background reduction by a one-step chemical pretreatment. Additionally, we employ coherent anti-Stokes Raman scattering imaging to simultaneously determine the cellular regions and intracellular locations of SHG signals. By applying this multimodal multiphoton imaging to mouse hippocampus, we found that neuronal ciliary rootlets were found to exhibit highly organized specific intracellular distributions. Moreover, the formation of ciliary rootlets precedes that of primary cilia. These findings highlight the utility of our label-free imaging platform in developmental and neuroscience research, providing a new tool to characterize ciliary dynamics and neuronal function.
Interaction between mitochondrial translocator protein and aging in inflammatory responses in mouse hippocampus
Authors: Lai Kei Onn , Tham Nevin , Fairley Lauren , Naik Roshan Ratnakar , Wang Yulan , Langley Sarah R. , Barron Anna M.
Published: June 2024

The mitochondrial translocator protein (TSPO) is a biomarker of inflammation which is upregulated in the brain in aging and associated neurodegenerative diseases, such as Alzheimer’s disease (AD). Here we investigated the interaction between aging and TSPO immunomodulatory function in mouse hippocampus, a region severely affected in AD. Aging resulted in a reversal of TSPO knockout transcriptional signatures following inflammatory insult, with TSPO deletion drastically exacerbating inflammatory transcriptional responses in the aging hippocampus whilst dampening inflammation in the young hippocampus. Drugs that disrupt cell cycle and induce DNA-damage such as heat shock protein and topoisomerase inhibitors were identified to mimic the inflammatory transcriptional signature characterizing TSPO-dependent aging most closely. This TSPO-aging interaction is an important consideration in the interpretation of TSPO-targeted biomarker and therapeutic studies, as well asin vitrostudies which cannot model the aging brain.
Integrated Movement Models for Individual Tracking and Species Distribution Data
Authors: Buderman Frances E. , Hanks Ephraim M. , Ruiz-Gutierrez Viviana , Shull Michael , Murphy Robert K. , Miller David A.W.
Published: June 2024

While the quantity, quality, and variety of movement data has increased, methods that jointly allow for population- and species-level movement parameters to be estimated are still needed. We present a formal data integration approach to combine individual-level movement and population-level distribution data. We show how formal data integration can be used to improve precision of individual and population level movement parameters and allow additional population level metrics (e.g., connectivity) to be formally quantified.

We describe three components needed for an Integrated Movement Model (IMM): a model for individual movement, a model for among-individual heterogeneity, and a model to quantify changes in species distribution. We outline a general IMM framework and develop and apply a specific stochastic differential equation model to a case study of telemetry and species distribution data for golden eagles in western North American during spring migration.

We estimate eagle movements during spring migration from data collected between 2011 and 2019. Individual heterogeneity in migration behavior was modeled for two sub-populations, individuals that make significant northward migrations and those that remained in the southern Rocky Mountain region through the summer. As is the case with most tracking studies, the sample population of individual telemetered birds is not representative of the population, and underrepresents the proportion of long-distance migrants in. The IMM was able to provide a more biological accurate subpopulation structure by jointly estimating the structure using the species distribution data. In addition, the integrated approach a) improves accuracy of other estimated movement parameters, b) allows us to estimate the proportion of migratory and non-migratory birds in a given location and time, and c) estimate future spatio-temporal distributions of birds given a wintering location, which provide estimates of seasonal connectivity and migratory routes.

We demonstrate how IMMs can be successfully used to address the challenge of estimating accurate population level movement parameters. Our approach can be generalized to a broad range of available movement models and data types, allowing us to significantly improve our knowledge of migration ecology across taxonomic groups, and address population and continental level information needs for conservation and management.
HumanIslets: An integrated platform for human islet data access and analysis
Authors: Ewald Jessica D. , Lu Yao , Ellis Cara E. , Worton Jessica , Kolic Jelena , Sasaki Shugo , Zhang Dahai , dos Santos Theodore , Spigelman Aliya F. , Bautista Austin , Dai Xiao-Qing , Lyon James G. , Smith Nancy P. , Wong Jordan M. , Rajesh Varsha , Sun Han , Sharp Seth A. , Rogalski Jason C. , Moravcova Renata , Cen Haoning H , Manning Fox Jocelyn E. , Consortium HI-DAS , Atlas Ella , Bruin Jennifer E. , Mulvihill Erin E. , Verchere C. Bruce , Foster Leonard J. , Gloyn Anna L. , Johnson James D. , Pepper Andrew R. , Lynn Francis C. , Xia Jianguo , MacDonald Patrick E.
Published: June 2024

Comprehensive molecular and cellular phenotyping of human islets can enable deep mechanistic insights for diabetes research. We established the Human Islet Data Analysis and Sharing (HI-DAS) consortium to advance goals in accessibility, usability, and integration of data from human islets isolated from donors with and without diabetes at the Alberta Diabetes Institute (ADI) IsletCore. Here we introduceHumanIslets.com, an open resource for the research community. This platform, which presently includes data on 547 human islet donors, allows users to access linked datasets describing molecular profiles, islet function and donor phenotypes, and to perform various statistical and functional analyses at the donor, islet and single-cell levels. As an example of the analytic capacity of this resource we show a dissociation between cell culture effects on transcript and protein expression, and an approach to correct for exocrine contamination found in hand-picked islets. Finally, we provide an example workflow and visualization that highlights links between type 2 diabetes status, SERCA3b Ca2+-ATPase levels at the transcript and protein level, insulin secretion and islet cell phenotypes.HumanIslets.comprovides a growing and adaptable set of resources and tools to support the metabolism and diabetes research community.
Development of a Spectral Flow Cytometry Analysis Pipeline for High-Dimensional Immune Cell Characterization
Authors: Vardaman Donald , Ali Md Akkas , Bolding Chase , Tidwell Harrison , Stephens Holly , Tyrrell Daniel J.
Published: June 2024

Flow cytometry is a widely used technique for immune cell analysis, offering insights into cell composition and function. Spectral flow cytometry allows for high-dimensional analysis of immune cells, overcoming limitations of conventional flow cytometry. However, analyzing data from large antibody panels can be challenging using traditional bi-axial gating strategies. Here, we present a novel analysis pipeline designed to improve analysis of spectral flow cytometry. We employ this method to identify rare T cell populations in aging. We isolated splenocytes from young (2–3 months) and aged (18–19 months) female mice then stained these with a panel of 20 fluorescently labeled antibodies. Spectral flow cytometry was performed, followed by data processing and analysis using Python within a Jupyter Notebook environment to perform batch correction, unsupervised clustering, dimensionality reduction, and differential expression analysis. Our analysis of 3,776,804 T cells from 11 spleens revealed 34 distinct T cell clusters identified by surface marker expression. We observed significant differences between young and aged mice, with certain clusters enriched in one age group over the other. Naïve, effector memory, and central memory CD8+and CD4+T cell subsets exhibited age-associated changes in abundance and marker expression. Additionally, γδ T cell clusters showed differential abundance between age groups. By leveraging high-dimensional analysis methods borrowed from single-cell RNA sequencing analysis, we identified age-related differences in T cell subsets, providing insights into the immune aging process. This approach offers a robust, free, and easily implemented analysis pipeline for spectral flow cytometry data that may facilitate the discovery of novel therapeutic targets for age-related immune dysfunction.
Bisphenol AF induces overactivation of primordial follicles via Hippo signaling and causes premature ovarian insufficiency in mice
Authors: Liu Xiaoyang , Yu Mingxi , Wang Tiancheng , Hu Xiangdong , Zhong Rui , Xiao Yuan , Xu Yan , Zhang Mei , Tang Shuang
Published: June 2024

Premature depletion of ovarian reserve is a cause of female infertility. Plasticizer Bisphenol AF (BPAF) residues have been found in human reproductive-related samples. However, little is known about its influence on the ovarian reserve. Here, we demonstrate that BPAF exposure causes excessive activation of primordial follicles through Hippo signaling in young females, resulting in rapid exhaustion of the ovarian reserve and, ultimately, premature ovarian insufficiency. We found that oral ingestion of BPAF disrupts normal estrous cyclicity and induces constant estrus in a dose-dependent manner. BPAF can upregulate the expression of YAP transcriptional coactivator. Intriguingly, only the high dose of BPAF inhibits Hippo signaling by eliciting a substantial decrease in phospho-YAP levels. Through such regulatory effects, BPAF causes YAP translocation into the nucleus and triggers the overactivation of primordial follicles. Collectively, this study proposes a novel toxicological mechanism explaining the negative impact of BPAF on the ovarian health of young females.
cryoSPHERE: Single-particle heterogeneous reconstruction from cryo EM
Authors: Ducrocq Gabriel , Grunewald Lukas , Westenhoff Sebastian , Lindsten Fredrik
Published: June 2024

The three-dimensional structure of a protein plays a key role in determining its function. Methods like AlphaFold have revolutionized protein structure prediction based only on the amino-acid sequence. However, proteins often appear in multiple different conformations, and it is highly relevant to resolve the full conformational distribution. Single-particle cryo-electron microscopy (cryo EM) is a powerful tool for capturing a large number of images of a given protein, frequently in different conformations (referred to asparticles). The images are, however, very noisy projections of the protein, and traditional methods for cryo EM reconstruction are limited to recovering a single, or a few, conformations. In this paper, we introduce cryoSPHERE, a deep learning method that takes as input a nominal protein structure, e.g. from AlphaFold, learns how to divide it into segments, and how to move these as approximately rigid bodies to fit the different conformations present in the cryo EM dataset. This formulation is shown to provide enough constraints to recover meaningful reconstructions of single protein structures. This is illustrated in three examples where we show consistent improvements over the current state-of-the-art for heterogeneous reconstruction.
Identification of a global gene expression signature associated with the genetic risk of catastrophic fracture in iPSC-derived osteoblasts from Thoroughbred horses
Authors: Palomino Lago Esther , Ross Amy K. C. , McClellan Alyce , Guest Deborah J.
Published: June 2024

Bone fractures are a significant problem in Thoroughbred racehorses. The risk of fracture is influenced by both genetic and environmental factors. To determine the biological processes that are affected in genetically susceptible horses, we utilised polygenic risk scoring to establish induced pluripotent stem cells (iPSCs) from horses at high and low genetic risk. RNA-sequencing on iPSC-derived osteoblasts revealed 112 genes that were significantly differentially expressed. 43 of these genes have known roles in bone, 27 are not yet annotated in the equine genome and 42 currently have no described role in bone. However, many of the proteins encoded by the known and unknown genes have reported interactions. Functional enrichment analyses revealed that the differentially expressed genes were overrepresented in processes regulating the extracellular matrix and pathways known to be involved in bone remodelling and bone diseases. Gene set enrichment analysis also detected numerous biological processes and pathways involved in glycolysis with the associated genes having a higher expression in the iPSC-osteoblasts from horses with low polygenic risk scores for fracture.

Therefore, the differentially expressed genes may be relevant for maintaining bone homeostasis and contribute to fracture risk. A deeper understanding of the consequences of mis-regulation of these genes and the identification of the DNA variants which underpin their differential expression may reveal more about the molecular mechanisms which are involved in equine bone health and fracture risk.
Decoding in the fourth dimension: Classification of temporal patterns and their generalization across locations
Authors: Santos-Mayo Alejandro , Gilbert Faith , Ahumada Laura , Traiser Caitlin , Engle Hannah , Panitz Christian , Ding Mingzhou , Keil Andreas
Published: June 2024

Neuroscience research has increasingly used decoding techniques, in which multivariate statistical methods identify patterns in neural data that allow the classification of experimental conditions or participant groups. Typically, the features used for decoding are spatial in nature, including voxel patterns and electrode locations. However, the strength of many neurophysiological recording techniques such as electroencephalography or magnetoencephalography is in their rich temporal, rather than spatial, content. The present report proposes a new decoding method that relies on the time information contained in neural time series. This information is then used in a subsequent step, generalization across location (GAL), which characterizes the relationship between sensor locations based on their ability to cross-decode. Two datasets are used to demonstrate usage of this method, referred to as time-GAL, involving (1) event-related potentials in response to affective pictures and (2) steady-state visual evoked potentials in response to aversively conditioned grating stimuli. In both cases, experimental conditions were successfully decoded based on the temporal features contained in the neural time series. Cross-decoding occurred in regions known to be involved in visual and affective processing. We conclude that the time-GAL approach holds promise for analyzing neural time series from a wide range of paradigms and measurement domains providing an assumption-free method to quantifying differences in temporal patterns of neural information processing and whether these patterns are shared across sensor locations.

Author summary

Decoding and classification approaches are widely used in computational biology. In the field of neuroscience, pattern classification approaches typically use spatial information. In many instances, neural time series however are best defined by the their temporal, rather than spatial, features. Here, we propose a novel decoding approach taking advantage of the temporal information. Specifically, we utilize the waveform of neural time series as features for decoding experimental conditions and quantify each decoder’s generalization across locations (GAL) in multi-channel recordings. We illustrate the usage of our open source toolbox using two datasets, showing the sensitivity of the method to systematic condition differences in temporal dynamics along with its ability to capture and quantify spatial dependencies between recording locations.
Toxicogenomic Assessment of In Vitro Macrophages Exposed to Profibrotic Challenge Reveals a Sustained Transcriptomic Immune Signature
Authors: Morikka Jack , Federico Antonio , Möbus Lena , Inkala Simo , Pavel Alisa , Sani Saara , Vaani Maaret , Peltola Sanna , Serra Angela , Greco Dario
Published: June 2024

Immune signalling is a crucial component in the progression of fibrosis. However, approaches for the safety assessment of potentially profibrotic substances, providing information on mechanistic immune responses, are underdeveloped. This study utilises a comprehensive analysis of RNA sequencing data from macrophages exposed in vitro to multiple sublethal concentrations of the profibrotic agent bleomycin, over multiple timepoints. Using a toxicogenomic framework, we performed dose-dependent analysis to filter genes truly altered by bleomycin exposure from noise and identified a subset of immune genes with a sustained dose-dependent and differential expression response to profibrotic challenge. We performed an immunoassay and revealed cytokines and proteinases responding to bleomycin exposure that closely correlate to transcriptomic alterations, underscoring the integration between transcriptional immune response and external immune signalling activity. This study not only increases our understanding of the immunological mechanisms of fibrosis, but also offers an innovative framework for the toxicological evaluation of substances with potential fibrogenic effects on macrophage signalling. Our work brings a new immunotoxicogenomic direction for hazard assessment of fibrotic compounds, through implementation of a time and resource efficient in vitro methodology.
Enhancing Cytoplasmic Expression of Exogenous mRNA through Dynamic Mechanical Stimulation
Authors: Chen Jiawen , Patel Aneri , Mir Mohammad , Hudock Maria R. , Pinezich Meghan R. , Guenthart Brandon , Bacchetta Matthew , Vunjak-Novakovic Gordana , Kim Jinho
Published: June 2024

Ionizable lipid nanoparticles (LNPs) have been pivotal in combating COVID-19, and numerous preclinical and clinical studies have highlighted their potential in nucleic acid-based therapies and vaccines. However, the effectiveness of endosomal escape for the nucleic acid cargos encapsulated in LNPs is still low, leading to suboptimal treatment outcomes and side effects. Hence, improving endosomal escape is crucial for enhancing the efficacy of nucleic acid delivery using LNPs. Here, a mechanical oscillation (frequency: 65 Hz) is utilized to prompt the LNP-mediated endosomal escape. The results reveal this mechanical oscillation can induce the combination and fusion between LNPs with opposite surface charges, enhance endosomal escape of mRNA, and increase the transfection efficiency of mRNA. Additionally, cell viability remains high at 99.3% after treatment with oscillation, which is comparable to that of untreated cells. Furthermore, there is no obvious damage to mitochondrial membrane potential and Golgi apparatus integrity. Thus, this work presents a user-friendly and safe approach to enhancing endosomal escape of mRNA and boosting gene expression. As a result, our work can be potentially utilized in both research and clinical fields to facilitate LNP-based delivery by enabling more effective release of LNP-encapsulated cargos from endosomes.
sORFdb – A database for sORFs, small proteins, and small protein families in bacteria
Authors: Hahnfeld Julian M. , Schwengers Oliver , Jelonek Lukas , Diedrich Sonja , Cemič Franz , Goesmann Alexander
Published: June 2024

Small proteins with fewer than 100, particularly fewer than 50, amino acids are still largely unexplored. Nonetheless, they represent an essential part of bacteria’s often neglected genetic repertoire. In recent years, the development of ribosome profiling protocols has led to the detection of an increasing number of previously unknown small proteins. Despite this, they are overlooked in many cases by automated genome annotation pipelines, and often, no functional descriptions can be assigned due to a lack of known homologs. To understand and overcome these limitations, the current abundance of small proteins in existing databases was evaluated, and a new dedicated database for small proteins and their potential functions, called ‘sORFdb’, was created. To this end, small proteins were extracted from annotated bacterial genomes in the GenBank database. Subsequently, they were quality-filtered, compared, and complemented with proteins from Swiss-Prot, UniProt, and SmProt to ensure reliable identification and characterization of small proteins. Families of similar small proteins were created using bidirectional best BLAST hits followed by Markov clustering. Analysis of small proteins in public databases revealed that their number is still limited due to historical and technical constraints. Additionally, functional descriptions were often missing despite the presence of potential homologs. As expected, a taxonomic bias was evident in over-represented clinically relevant bacteria.

This new and comprehensive database is accessible via a feature-rich website providing specialized search features for sORFs and small proteins of high quality. Additionally, small protein families with Hidden Markov Models and information on taxonomic distribution and other physicochemical properties are available. In conclusion, the novel small protein database sORFdb is a specialized, taxonomy-independent database that improves the findability and classification of sORFs, small proteins, and their functions in bacteria, thereby supporting their future detection and consistent annotation. All sORFdb data is freely accessible viahttps://sorfdb.computational.bio.
Predicting the diversity of photosynthetic light-harvesting using thermodynamics and machine learning
Authors: Gray Callum , Chitnavis Samir , Buja Tamara Lucy , Duffy Christopher D. P.
Published: June 2024

Oxygenic photosynthesis is responsible for nearly all biomass production on Earth, and may have been a prerequisite for establishing a complex biosphere rich in multicellular life. Life on Earth has evolved to perform photosynthesis in a wide range of light environments, but with a common basic architecture of a light-harvestingantennasystem coupled to a photochemical reaction centre. Using a generalized thermodynamic model of light-harvesting, coupled with an evolutionary algorithm, we predict the type of light-harvesting structures that might evolve in light of different intensities and spectral profiles. We reproduce qualitatively the pigment composition, linear absorption profile and structural topology of the antenna systems of multiple types of oxygenic photoautotrophs, suggesting that the same physical principles underlie the development of distinct antenna structures in various light environments. Finally we apply our model to representative light environments that would exist on Earth-like exoplanets, predicting that both oxygenic and anoxygenic photosynthesis could evolve around low mass stars, though the latter would seem to work better around the coolest M-dwarfs. We see this as an interesting first step toward a general evolutionary model of basic biological processes and proof that it is meaningful to hypothesize on the nature of biology beyond Earth.
Mouse models of non-dystrophic and dystrophic myotonia exhibit nociplastic pain-like behaviors
Authors: Nelson Tyler S. , Duran Paz , Calderon-Rivera Aida , Gomez Kimberly , Loya-Lopez Santiago , Khanna Rajesh
Published: June 2024

Pain is a prominent and debilitating symptom in myotonic disorders, yet its physiological mechanisms remain poorly understood. This study assessed preclinical pain-like behavior in murine models of pharmacologically induced myotonia and myotonic dystrophy type 1 (DM1). In both myotonia congenita and DM1, impairment of theCLCN1gene, which encodes skeletal muscle voltage-gated CLC-1 chloride channels, reduces chloride ion conductance in skeletal muscle cells, leading to prolonged muscle excitability and delayed relaxation after contraction. We used the CLC-1 antagonist anthracene-9- carboxylic acid (9-AC) at intraperitoneal doses of 30 or 60 mg/kg and HSA LR20b DM1 mice to model CLC-1-induced myotonia. Our experimental approach includedin vivopain behavioral testing,ex vivocalcium imaging, and whole-cell current-clamp electrophysiology in mouse dorsal root ganglion (DRG) neurons. A single injection of 9-AC induced myotonia in mice, which persisted for several hours and resulted in long-lasting allodynic pain-like behavior. Similarly, HSA LR20b mice exhibited both allodynia and hyperalgesia. Despite these pain-like behaviors, DRG neurons did not show signs of hyperexcitability in either myotonic model. These findings suggest that myotonia induces nociplastic pain-like behavior in preclinical rodents, likely through central sensitization mechanisms rather than peripheral sensitization. This study provides insights into the pathophysiology of pain in myotonic disorders and highlights the potential of using myotonic mouse models to explore pain mechanisms and assess novel analgesics. Future research should focus on the central mechanisms involved in myotonia-induced pain and develop targeted therapies to alleviate this significant clinical burden.
Metabolically-driven flows enable exponential growth in macroscopic multicellular yeast
Authors: Narayanasamy Nishant , Bingham Emma , Fadero Tanner , Bozdag G. Ozan , Ratcliff William C , Yunker Peter , Thutupalli Shashi
Published: June 2024

The ecological and evolutionary success of multicellular lineages is due in no small part to their increased size relative to unicellular ancestors. However, large size also poses biophysical challenges, especially regarding the transport of nutrients to all cells; these constraints are typically overcome through multicellular innovations (e.g., a circulatory system). Here we show that an emergent biophysical mechanism — spontaneous fluid flows arising from metabolically-generated density gradients — can alleviate constraints on nutrient transport, enabling exponential growth in nascent multicellular clusters of yeast lacking any multicellular adaptations for nutrient transport or fluid flow. Surprisingly, beyond a threshold size, the metabolic activity of experimentally-evolved snowflake yeast clusters drives large-scale fluid flows that transport nutrients throughout the cluster at speeds comparable to those generated by the cilia of extant multicellular organisms. These flows support exponential growth at macroscopic sizes that theory predicts should be diffusion limited. This work demonstrates how simple physical mechanisms can act as a ‘biophysical scaffold’ to support the evolution of multicellularity by opening up phenotypic possibilities prior to genetically-encoded innovations. More broadly, our findings highlight how cooption of conserved physical processes is a crucial but underappreciated facet of evolutionary innovation across scales.
Notch Signaling in regulating Bone-derived Nanoparticles (BNPs) enhanced Osteogenic Differentiation
Authors: Stellpflug Austin , Caron Justin , Fasciano Samantha , Wang Bo , Wang Shue
Published: June 2024

Mesenchymal stem cells (MSCs)-based bone tissue regeneration has gained significant attention due to their excellent differentiation capacity and immunomodulatory activity. Enhancing osteogenesis regulation is crucial for improving the therapeutic efficacy of MSC- based regeneration. By utilizing the regenerative capacity of bone ECM and the functionality of nanoparticles, we recently engineered bone-based nanoparticles (BNPs) from decellularized porcine bone. The effects of internalization of BNPs on MSCs viability, proliferation, and osteogenic differentiation were first investigated and compared at different time points. The phenotypic behaviors, including cell number, proliferation, and differentiation were characterized and compared. By incorporating this LNA/DNA nanobiosensor and MSCs live cell imaging, we monitored and compared Notch ligand delta-like 4 (Dll4) expression dynamics in cytoplasm and nucleus during osteogenic differentiation. Pharmacological interventions are used to inhibit Notch signaling to examine the mechanisms involved. The results suggest Notch inhibition mediates osteogenic process, with reduced expression of early and late stage of differentiation markers (ALP, calcium mineralization). The internalization of BNPs led to an increase in Dll4 expression, exhibiting a time-dependent pattern that aligned with enhanced cell proliferation and differentiation. Our findings indicate that the observed changes in BNP-treated cells during osteogenic differentiation could be associated with the elevated levels of Dll4 mRNA expression. In summary, this study provides new insights into MSCs osteogenic differentiation and the molecular mechanisms through which BNPs stimulate this process. The results indicate that BNPs influence osteogenesis by modulating Notch ligand Dll4 expression, demonstrating a potential link between Notch signaling and the proteins present in BNPs.
Bin2cell reconstructs cells from high resolution Visium HD data
Authors: Polański Krzysztof , Bartolomé-Casado Raquel , Sarropoulos Ioannis , Xu Chuan , England Nick , Jahnsen Frode L. , Teichmann Sarah A. , Yayon Nadav
Published: June 2024

Visium HD by 10X Genomics is the first commercially available platform capable of capturing full scale transcriptomic data paired with a reference morphology image from archived FFPE blocks at sub-cellular resolution. However, aggregation of capture regions to single cells poses challenges. Bin2cell reconstructs cells from the highest resolution data (2μm bins) by leveraging morphology image segmentation and gene expression information. It is compatible with established Python single cell and spatial transcriptomics software, and operates efficiently in a matter of minutes without requiring a GPU. We demonstrate improvements in downstream analysis when using the reconstructed cells over default 8μm bins on mouse brain and human colorectal cancer data.

Availability and Implementation

Bin2cell is available athttps://github.com/Teichlab/bin2cell, along with documentation and usage examples, and can be installed from pip. Probe design functionality is available athttps://github.com/Teichlab/gene2probe

Contact

ny1@sanger.ac.uk,st9@sanger.ac.uk

Supplementary information

Supplementary data are available online.
Φ-Space: Continuous phenotyping of single-cell multi-omics data
Authors: Mao Jiadong , Deng Yidi , Lê Cao Kim-Anh
Published: June 2024

Single-cell multi-omics technologies have empowered increasingly refined characterisation of the heterogeneity of cell populations. Automated cell type annotation methods have been developed to transfer cell type labels from well-annotated reference datasets to emerging query datasets. However, these methods suffer from some common caveats, including the failure to characterise transitional and novel cell states, sensitivity to batch effects and under-utilisation of phenotypic information other than cell types (e.g. sample source and disease conditions).

We developed Φ-Space, a computational framework for the continuous phenotyping of single-cell multi-omics data. In Φ-Space we adopt a highly versatile modelling strategy to continuously characterise query cell identity in a low-dimensional phenotype space, defined by reference phenotypes. The phenotype space embedding enables various downstream analyses, including insightful visualisations, clustering and cell type labelling.

We demonstrate through three case studies that Φ-Space (i) characterises developing and out-of-reference cell states; (ii) is robust against batch effects in both reference and query; (iii) adapts to annotation tasks involving multiple omics types; (iv) overcomes technical differences between reference and query.

The versatility of Φ-Space makes it applicable to a wide range analytical tasks beyond cell type transfer, and its ability to model complex phenotypic variation will facilitate biological discoveries from different omics types.