bluuebunny/crossref_metadata_2025 huggingface dataset:
Choice of friction coefficient deeply affects tissue behaviour in stochastic epithelial vertex models
Authors: Guerrero Pilar , Perez-Carrasco Ruben
Published: March 2024

To understand the mechanisms that coordinate the formation of biological tissues, the use of numerical implementations is necessary. The complexity of such models involves many assumptions and parameter choices that result in unpredictable consequences, obstructing the comparison with experimental data. Here, we focus on vertex models, a family of spatial models used extensively to simulate the dynamics of epithelial tissues. Usually, in the literature, the choice of the friction coefficient is not addressed using quasi-static deformation arguments that generally do not apply to realistic scenarios. In this manuscript, we discuss the role that the choice of friction coefficient has on the relaxation times and consequently in the conditions of cell cycle progression and division. We explore the effects that these changes have on the morphology, growth rate and topological transitions of the tissue dynamics. These results provide a deeper understanding of the role that an accurate mechanical description plays in the use of vertex models as inference tools.

This article is part of a discussion meeting issue ‘Causes and consequences of stochastic processes in development and disease’.
Krüppel-like Factor (KLF) family members control expression of genes required for serous cavity and alveolar macrophage identities
Authors: Pestal Kathleen , Slayden Leianna C , Barton Gregory M
Published: March 2024

Tissue-resident macrophages adopt distinct gene expression profiles and exhibit functional specialization based on their tissue of residence. Recent studies have begun to define the signals and transcription factors that induce these identities. Here we describe an unexpected and specific role for the broadly expressed transcription factor Kruppel-like Factor 2 (KLF2) in the development of embryonically derived Large Cavity Macrophages (LCM) in the serous cavities. KLF2 not only directly regulates the transcription of genes previously shown to specify LCM identity, such as retinoic acid receptors and GATA6, but also is required for induction of many other transcripts that define the identity of these cells. We identify a similar role for KLF4 in regulating the identity of alveolar macrophages in the lung. These data demonstrate that broadly expressed transcription factors, such as Group 2 KLFs, can play important roles in the specification of distinct identities of tissue-resident macrophages.

Previous studies have identified many specific regulators of macrophage development. This work reveals the requirement of members of the Group 2 KLF transcription factor family in the determination of the identity of distinct tissue-resident macrophages.
Conformational Ensembles Reveal the Origins of Serine Protease Catalysis
Authors: Du Siyuan , Kretsch Rachael C. , Parres-Gold Jacob , Pieri Elisa , Cruzeiro Vinícius Wilian D. , Zhu Mingning , Pinney Margaux M. , Yabukarski Filip , Schwans Jason P. , Martínez Todd J. , Herschlag Daniel
Published: March 2024

Enzymes exist in ensembles of states that encode the energetics underlying their catalysis. Conformational ensembles built from 1231 structures of 17 serine proteases reveal atomic-level changes across their reaction states, identify molecular features that provide catalysis, and quantify their energetic contributions to catalysis. These enzymes precisely position their reactants in destabilized conformers, creating a downhill energetic gradient that selectively favors the motions required for reaction while limiting off-pathway conformational states. A local catalytic motif, the “nucleophilic elbow”, has repeatedly evolved, generating ground state destabilization in 50 proteases and 52 additional enzymes spanning 32 distinct structural folds. Ensemble–function analyses reveal previously unknown catalytic features, provide quantitative models based on simple physical and chemical principles, and identify motifs recurrent in Nature that may inspire enzyme design.

One sentence summary:Ensemble–function analyses provide a quantitative model for serine protease catalysis, reveal previously unknown conformational features that contribute to their catalysis, and identify a structural motif that underlie these features and has evolved in >100 different enzymes from 32 protein folds.
Human calpain-3 and its structural plasticity: dissociation of a homohexamer into dimers on binding titin
Authors: Ye Qilu , Henrickson Amy , Demeler Borries , Serrão Vitor Hugo Balasco , Davies Peter L.
Published: March 2024

Calpain-3 is an intracellular Ca2+-dependent cysteine protease abundant in skeletal muscle. Its physiological role in the sarcomere is thought to include removing damaged muscle proteins after exercise. Loss-of-function mutations in its single-copy gene cause a dystrophy of the limb-girdle muscles. These mutations, of which there are over 500 in humans, are spread all along this 94-kDa multi-domain protein that includes three 40+-residue sequences (NS, IS1, and IS2). The latter sequences are unique to this calpain isoform and are hypersensitive to proteolysis. To investigate the whole enzyme structure and how mutations might affect its activity, we produce the proteolytically more stable 85-kDa calpain-3 ΔNS ΔIS1 form with a C129A inactivating mutation as a recombinant protein inE. coli. During size-exclusion chromatography, this calpain-3 was consistently eluted as a much larger 0.5-MDa complex rather than the expected 170-kDa dimer. Its size, which was confirmed by SEC-MALS, Blue Native PAGE, and AUC, made the complex amenable to single-particle cryo-EM analysis. From two data sets, we obtained a 3.85-Å reconstruction map that shows the complex is a trimer of calpain-3 dimers with six penta-EF-hand domains at its core. Calpain-3 has been reported to bind the N2A region of the giant muscle protein titin. When this 37-kDa region of titin was co-expressed with calpain-3 the multimer was reduced to a 320-kDa particle, which appears to be the calpain dimer bound to several copies of the titin fragment. We suggest that newly synthesized calpain-3 is kept as an inactive hexamer until it binds the N2A region of titin in the sarcomere, whereupon it dissociates into functional dimers.
Auditory Feature-based Perceptual Distance
Authors: Chen Shukai , Thielk Marvin , Gentner Timothy Q.
Published: March 2024

Studies comparing acoustic signals often rely on pixel-wise differences between spectrograms, as in for example mean squared error (MSE). Pixel-wise errors are not representative of perceptual sensitivity, however, and such measures can be highly sensitive to small local signal changes that may be imperceptible. In computer vision, high-level visual features extracted with convolutional neural networks (CNN) can be used to calculate the fidelity of computer-generated images. Here, we propose the auditory perceptual distance (APD) metric based on acoustic features extracted with an unsupervised CNN and validated by perceptual behavior. Using complex vocal signals from songbirds, we trained a Siamese CNN on a self-supervised task using spectrograms rescaled to match the auditory frequency sensitivity of European starlings, Sturnus vulgaris. We define APD for any pair of sounds as the cosine distance between corresponding feature vectors extracted by the trained CNN. We show that APD is more robust to temporal and spectral translation than MSE, and captures the sigmoidal shape of typical behavioral psychometric functions over complex acoustic spaces. When fine-tuned using starlings’ behavioral judgments of naturalistic song syllables, the APD model yields even more accurate predictions of perceptual sensitivity, discrimination, and categorization on novel complex (high-dimensional) acoustic dimensions, including diverging decisions for identical stimuli following different training conditions. Thus, the APD model outperforms MSE in robustness and perceptual accuracy, and offers tunability to match experience-dependent perceptual biases.
Inkject Printed Graphene Microelectrodes for Real-Time Impedance Spectroscopy of Neural Cells in Organ-on-a-Chip
Authors: Gabriel Ouedraogo Lionel Jean , Hashemi Nicole N.
Published: March 2024

This study presents the development and characterization of a graphene-based sensor integrated into a microfluidic chip for real-time monitoring of cell growth and viability. The sensor fabrication involved the metabolization of graphene from graphite using a simple and cost-effective method. The sensor design, created using Solidworks, featured electrodes capable of detecting environmental changes through impedance sensing. A mold was created using a cutter plotter to overcome challenges in achieving the desired sensor shape, and the electrodes were printed on a polyester (PETE) membrane. The conductivity of the electrodes was optimized through annealing, considering the temperature limits of the membrane. Annealing at 150 °C for 40 minutes yielded electrodes with desired conductivity and maintained membrane integrity. Compatibility with cellular growth was confirmed through cell culture experiments. The scaled electrodes were integrated into a microfluidic chip, and their performance was evaluated using cyclic voltammetry and electrochemical impedance spectroscopy. The results demonstrated the successful functioning of the electrodes within the chip. The developed graphene-based sensor offers promising applications in cellular studies and biosensing through real-time monitoring of cell growth and viability was achieved by measuring impedance changes resulting from cell attachment.
Association analysis between an epigenetic alcohol risk score and blood pressure
Authors: Bui Helena , Keshawarz Amena , Wang Mengyao , Lee Mikyeong , Ratliff Scott M. , Lin Lisha , Birditt Kira S. , Faul Jessica D. , Peters Annette , Gieger Christian , Delerue Thomas , Kardia Sharon L. R. , Zhao Wei , Guo Xiuqing , Yao Jie , Rotter Jerome I. , Li Yi , Liu Xue , Liu Dan , Tavares Juliana F. , Pehlivan Gökhan , Breteler Monique M.B. , Karabegovic Irma , Ochoa-Rosales Carolina , Voortman Trudy , Ghanbari Mohsen , van Meurs Joyce B.J. , Nasr Mohamed Kamal , Dörr Marcus , Grabe Hans J. , London Stephanie J. , Teumer Alexander , Waldenberger Melanie , Weir David R. , Smith Jennifer A. , Levy Daniel , Ma Jiantao , Liu Chunyu
Published: March 2024

Background

Epigenome-wide association studies have revealed multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases.

Results

We generated an alcohol consumption epigenetic risk score (ERS) based on previously reported 144 alcohol-associated CpGs and examined the association of the ERS with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension (HTN) in 3,898 Framingham Heart Study (FHS) participants. We found an association of alcohol intake with the ERS in the meta-analysis with 0.09 units higher ERS per drink consumed per day (p< 0.0001). Cross-sectional analyses in FHS revealed that a one-unit increment of the ERS was associated with 1.93 mm Hg higher SBP (p= 4.64E-07), 0.68 mm Hg higher DBP (p= 0.006), and an odds ratio of 1.78 for HTN (p< 2E-16). Meta-analysis of the cross-sectional association of the ERS with BP traits in eight independent external cohorts (n = 11,544) showed similar relationships with blood pressure levels, i.e., a one-unit increase in ERS was associated with 0.74 (p= 0.002) and 0.50 (p= 0.0006) mm Hg higher SBP and DBP, but could not confirm the association with hypertension. Longitudinal analyses in FHS (n = 3,260) and five independent external cohorts (n = 4,021) showed that the baseline ERS was not associated with a change in blood pressure over time or with incident HTN.

Conclusions

Our findings provide proof-of-concept that utilizing an ERS is a useful approach to capture the recent health consequences of lifestyle behaviors such as alcohol consumption.
Compound-SNE: Comparative alignment of t-SNEs for multiple single-cell omics data visualisation
Authors: Cess Colin G. , Haghverdi Laleh
Published: March 2024

One of the first steps in single-cell omics data analysis is visualization, which allows researchers to see how well-separated cell-types are from each other. When visualizing multiple datasets at once, data integration/batch correction methods are used to merge the datasets. While needed for downstream analyses, these methods modify features space (e.g. gene expression)/PCA space in order to mix cell-types between batches as well as possible. This obscures sample-specific features and breaks down local embedding structures that can be seen when a sample is embedded alone. Therefore, in order to improve in visual comparisons between large numbers of samples, we introduce Compound-SNE, which performs what we term a soft alignment of samples in embedding space. We show that Compound-SNE is able to align cell-types in embedding space across samples and data modalities, while preserving local embedding structures from when samples are embedded independently.
SMA Type II Skeletal Muscle Treated with Nusinersen shows SMN Restoration but Mitochondrial Deficiency.
Authors: Grandi Fiorella Carla , Astord Stephanie , Gidaja Elena , Pezet Sonia , Mazzucchi Sabrina , Chapart Maud , Vasseur Stephane , Mamchaoui Kamel , Smeriglio Piera
Published: March 2024

Spinal muscular atrophy (SMA) is a rare autosomal recessive developmental disorder caused by the genetic loss or mutation of the gene SMN1 (Survival of Spinal Motor Neuron 1). SMA is classically characterized by neuromuscular symptoms, including muscular atrophy, weakness of the proximal muscles, especially those of the lower extremities, and hypotonia. Although originally thought of as a purely motor neuron disease, current research has shown that most, if not all, tissues are affected, including the muscle. Until recently, muscle problems in SMA were predominantly considered a consequence of denervation due to the motor neuron death. However, recent work using muscle specific mouse models of SMN loss, as well as skeletal stem cell specific models have shown that there are tissue specific problems in muscle due to SMN deficiency. Several years ago, SMA treatment underwent a radical transformation, with the approval of three different SMN-dependent disease modifying therapies. This includes two SMN2 splicing therapies, Risdiplam and Nusinersen, which can be administered by Type II patients that have symptom onset later in age. One main challenge for Type II SMA patients treated with Risdiplam and Nusinersen is ongoing muscle fatigue, limited mobility, and other skeletal problems, including hip dysplasia and scoliosis. To date, few molecular studies have been conducted on SMA patient derived tissues after treatment, limiting our understanding how different organ systems react to the therapies, and what additional combination therapies may be beneficial. With this goal in mind, we collected paravertebral muscle from the surgical discard in a cohort of 8 SMA Type II patients undergoing spinal surgery for scoliosis, as well as 7 non SMA controls with scoliosis and used RNA sequencing to characterize their molecular profiles. We observed that despite a restoration of the SMN mRNA and protein levels in these patients, at levels at or above the controls, a subset of patients continued to have alterations in mitochondrial metabolism and other markers of cellular stress.
Explainable Deep Learning Framework: Decoding Brain Task and Prediction of Individual Performance in False-Belief Task at Early Childhood Stage
Authors: Bhavna Km , Akhter Azman , Banerjee Romi , Roy Dipanjan
Published: March 2024

Decoding of brain tasks aims to identify individuals’ brain states and brain fingerprints to predict behavior. Deep learning provides an important platform for analyzing brain signals at different developmental stages to understand brain dynamics. Due to their internal architecture and feature extraction techniques, existing machine learning and deep-learning approaches for fMRI-based brain decoding must improve classification performance and explainability. The existing approaches also focus on something other than the behavioral traits that can tell about individuals’ variability in behavioral traits. In the current study, we hypothesized that even at the early childhood stage (as early as 3 years), connectivity between brain regions could decode brain tasks and predict behavioural performance in false-belief tasks. To this end, we proposed an explainable deep learning framework to decode brain states (Theory of Mind and Pain states) and predict individual performance on ToM-related false-belief tasks in a developmental dataset. We proposed an explainable spatiotemporal connectivity-based Graph Convolutional Neural Network (Ex-stGCNN) model for decoding brain tasks. Here, we consider a dataset (age range: 3-12 yrs and adults, samples: 155) in which participants were watching a short, soundless animated movie, ”Partly Cloudy,” that activated Theory-of-Mind (ToM) and pain networks. After scanning, the participants underwent a ToMrelated false-belief task, leading to categorization into the pass, fail, and inconsistent groups based on performance. We trained our proposed model using Static Functional Connectivity (SFC) and Inter-Subject Functional Correlations (ISFC) matrices separately. We observed that the stimulus-driven feature set (ISFC) could capture ToM and Pain brain states more accurately with an average accuracy of 94%, whereas it achieved 85% accuracy using SFC matrices. We also validated our results using five-fold cross-validation and achieved an average accuracy of 92%. Besides this study, we applied the SHAP approach to identify neurobiological brain fingerprints that contributed the most to predictions. We hypothesized that ToM network brain connectivity could predict individual performance on false-belief tasks. We proposed an Explainable Convolutional Variational Auto-Encoder model using functional connectivity (FC) to predict individual performance on false-belief tasks and achieved 90% accuracy.
Brassinosteroid and gibberellin signaling are required for Tomato internode elongation in response to low red: far-red light
Authors: Li Linge , Wonder Jesse , Helming Ticho , van Asselt Gijs , Pantazopoulou Chrysoula K. , van de Kaa Yorrit , Kohlen Wouter , Pierik Ronald , Kajala Kaisa
Published: March 2024

In this study, we explore the dynamic interplay between the plant hormones gibberellins (GA), brassinosteroids (BR), and Indole-3-Acetic Acid (IAA) in their collective impact on plant shade avoidance elongation under varying light conditions. We focus particularly on low Red: Far-red (R:FR) light conditions achieved by supplementing the background light with FR. Our research delves into how these hormones individually and synergistically influence stem elongation in tomato plants. Through meticulous experimental modulations of GA, IAA, and BR, we demonstrate that GA and BR are sufficient but also necessary for inducing stem elongation under low R:FR light conditions. Intriguingly, while IAA alone shows limited effects, its combination with GA yields significant elongation, suggesting a nuanced hormonal balance. Furthermore, we unveil the complex interplay of these hormones under light with low R:FR, where the suppression of one hormone’s effect can be compensated by the others. This study provides insights into the hormonal mechanisms governing plant adaptation to light, highlighting the intricate and adaptable nature of plant growth responses. Our findings have far-reaching implications for agricultural practices, offering potential strategies for optimizing plant growth and productivity in various lighting environments.

Highlight

This study unveils the interplay of brassinosteroids and gibberellins in shade avoidance elongation, revealing how tomatoes acclimate in response to far-red enriched light conditions.
Social transmission of inflammation in mice
Authors: Quintana Silvia Castany , Da Rosa Priscila Batista , Shionoya Kiseko , Blomqvist Anders , Engblom David
Published: March 2024

The ability to detect and respond to sickness in others promotes survival. Here we show that mouse dams respond to immune challenged pups by mirroring their inflammatory response. Thus, dams with pups subjected to immune challenge displayed a marked induction of inflammatory mediators in both the brain and the periphery, accompanied by an increase in maternal behaviors and corticosterone levels. This social transmission of inflammation did not require physical contact, and it contributed to the stress hormone response in the dams. In adult dyads, interaction with an immune challenged cagemate did not elicit robust inflammatory signaling but induced an increased responsiveness to a subsequent immune challenge. The identification of social transmission of inflammation, or inflammatory responsiveness, may open new avenues for research on social behavior, just like the description of similar phenomena such as observational fear and transmitted pain have done.
Unveiling the Power of High-Dimensional Cytometry Data with cyCONDOR
Authors: Kroeger Charlotte , Müller Sophie , Leidner Jacqueline , Kröber Theresa , Warnat-Herresthal Stefanie , Spintge Jannis Bastian , Zajac Timo , Frolov Aleksej , Carraro Caterina , Puccio Simone , Schultze Joachim L , Pecht Tal , Beyer Marc D , Bonaguro Lorenzo
Published: March 2024

High-dimensional cytometry (HDC) is a powerful technology for studying single-cell phenotypes in complex biological systems. Although technological developments and affordability have made HDC broadly available in recent years, technological advances were not coupled with an adequate development of analytical methods that can take full advantage of the complex data generated. While several analytical platforms and bioinformatics tools have become available for the analysis of HDC data, these are either web-hosted with limited scalability or designed for expert computational biologists, making their use unapproachable for wet lab scientists. Additionally, end-to-end HDC data analysis is further hampered due to missing unified analytical ecosystems, requiring researchers to navigate multiple platforms and software packages to complete the analysis.

To bridge this data analysis gap in HDC we developedcyCONDOR, aneasy-to-usecomputational framework covering not only all essential steps of cytometry data analysis but also including an array of downstream functions and tools to expand the biological interpretation of the data. The comprehensive suite of features ofcyCONDOR, including guided pre-processing, clustering, dimensionality reduction, and machine learning algorithms, facilitates the seamless integration ofcyCONDORinto clinically relevant settings, where scalability and disease classification are paramount for the widespread adoption of HDC in clinical practice. Additionally, the advanced analytical features ofcyCONDOR, such as pseudotime analysis and batch integration, provide researchers with the tools to extract deeper insights from their data. We usedcyCONDORon a variety of data from different tissues and technologies demonstrating its versatility to assist the analysis of high dimensionality data from preprocessing to biological interpretation.
Uncovering the genetic diversity inAedes aegyptiinsecticide resistance genes through global comparative genomics
Authors: Spadar Anton , Collins Emma , Messenger Louisa A. , Clark Taane G. , Campino Susana
Published: March 2024

Insecticides are essential to control the transmission of vector-borne diseases to humans and animals, but their efficacy is being threatened by the spread of resistance across multiple medically important mosquito species. An example of this isAedes aegypti- a major vector of arboviruses, including Zika, dengue, yellow fever, West Nile, and Chikungunya, with widespread insecticide resistance reported in the Americas and Asia, while data from Africa is more limited. Here we investigate the global genetic diversity in four insecticide resistance associated genes:ace-1,GSTe2,rdlandvgsc.Apart fromvgsc, the other genes have been less investigated inAe. aegypti, and limited genetic diversity information is available. We explore a large whole-genome sequencing dataset of 729Ae. aegyptiacross 15 countries including nine in Africa. Among the four genes, we identified 1,829 genetic variants including 474 non-synonymous substitutions, as well as putative copy number variations inGSTe2andvgsc. Among these are many previously documented insecticide resistance mutations which were present at different frequencies and combinations depending on origin of samples. Global insecticide resistance phenotypic data demonstrated variable resistance in geographic areas with resistant genotypes. These warrant further investigation to assess their functional contribution to insecticide resistant phenotypes and their potential development into genetic panels for operational surveillance. Overall, our work provides the first global catalogue and geographic distribution of known and new amino-acid mutations and duplications that can be used to guide the identification of resistance drivers inAe. aegyptiand thereby support monitoring efforts and strategies for vector control.
M. bovisPPD Enhances Respiratory Bioenergetics of Human vs. Bovine Macrophages
Authors: Bartens Marie-Christine , Willcocks Sam , Werling Dirk , Gibson Amanda J.
Published: March 2024

The role of macrophage (MØ) cellular metabolism and reprogramming during TB infection is of great interest due to the influence ofMycobacteriumspp. on MØ bioenergetics. Recent studies have shown thatM. tuberculosisinduces a TLR2-dependent shift towards aerobic glycolysis and metabolic reprogramming, comparable to the established LPS induced pro-inflammatory M1 MØ polarisation. Distinct differences in the metabolic profile of murine and human MØ indicates species-specific differences in bioenergetics. So far, studies examining the metabolic potential of cattle are lacking, thus the basic bioenergetics of bovine and human MØ were explored in response to a variety of innate immune stimuli. Cellular energy metabolism kinetics were measured concurrently for both species on a Seahorse XFe96 platform to generate bioenergetic profiles for the response to the bona-fide TLR2 and TLR4 ligands, FSL-1 and LPS respectively. Despite previous reports of species-specific differences in TLR signalling and cytokine production between human and bovine MØ, we observed similar respiratory profiles for both species. Basal respiration remained constant between stimulated MØ and controls, whereas addition of TLR ligands induced increased glycolysis. In contrast to MØ stimulation withM. tuberculosisPPD, another TLR2 ligand,M. bovisPPD treatment significantly enhanced basal respiration rates and glycolysis only in human MØ. Respiratory profiling further revealed significant elevation of ATP-linked OCR and maximal respiration suggesting a strong OXPHOS activation uponM. bovisPPD stimulation in human MØ. Our results provide an exploratory set of data elucidating the basic respiratory profile of bovine vs. human MØ that will not only lay the foundation for future studies to investigate host-tropism of theM. tuberculosiscomplex but may explain inflammatory differences observed for other zoonotic diseases.

Highlights

Similar baseline respiratory profiles for human and bovine macrophages

M. bovisPPD treatment altered metabolic profile only in human MØ

Strong OXPHOS activation uponM. bovisPPD stimulation only in human MØ

Graphical Abstract

Created with BioRender (www.biorender.com) by A. Gibson
Within-host adaptation of a foliar pathogen,Xanthomonas, on pepper in presence of quantitative resistance and ozone stress
Authors: Kaur Amanpreet , Russell Ivory , Liu Ranlin , Holland Auston , Bhandari Rishi , Potnis Neha
Published: March 2024

The evolving threat of new pathogen variants in the face of global environmental changes poses a risk to the plant health and can impact the efficacy of resistance-based disease management.

Here, we studied short-term eco-evolutionary response of the pathogen,Xanthomonas perforans, on quantitative resistant and susceptible pepper during a single growing season in open-top chambers under the influence of elevated Ozone (O3).

We observed increased disease severity, accompanied by higher variation on resistant cultivar under elevated O3, with no apparent change on the susceptible cultivar. This altered resistance response under elevated O3 is linked to altered eco-evolutionary dynamics of pathogen. While a single pathogen genotype remained prevalent on susceptible cultivar, resistant cultivar supported heterogenous pathogen population, with the evidence of short- term evolutionary modifications seeded byde novoparallel mutations. Altered O3 levels led to strain turnover on resistant cultivar with higher within-host polymorphism containing higher proportion of randomde novomutations lacking parallelism.

Population heterogeneity is a mechanism of pathogen adaptation in response to the stressors. While parallel mutations in response to quantitative resistance may provide clues to predicting long-term pathogen evolution, high proportion of transient mutations suggest less predictable pathogen evolution under climatic alterations.
The role of many-to-one mapping of vertebral form to function in Psittaciform tripedal locomotion
Authors: Stuart Anna R. , Granatosky Michael C. , Felice Ryan N. , Marek Ryan D.
Published: March 2024

Parrots highlight the functional diversity of the avian neck by contributing to a range of behaviors, including arboreal locomotion. The parrot neck is used alongside the beak and hindlimb to allow them to successfully navigate arboreal habitats via tripedal locomotion. Whether specific morphological characteristics of the neck enable this behavior are currently unknown. By combining geometric morphometrics with phylogenetic comparative methods we investigate the factors correlate with shape variation in the cervical vertebrae of parrots. We find that phylogeny, allometry, integration, diet and tripedal locomotion all have a significant influence on the morphology of psittaciform cervical vertebrae. However, the influence of diet and tripedal locomotion is weak, with a high degree of morphospace overlap existing between dietary and neck use groups. Additionally, we find no evidence of convergence in parrot neck morphology due to the incidence of tripedal locomotion or dietary specialization. We thus conclude that changes to the neuromuscular control of the neck, not morphological adaptations, are primarily responsible for tripedal locomotion in parrots. We argue that many-to-one mapping of form to function allows parrots with similar neck morphologies to participate in a range of behaviors, and this may be a common feature amongst all birds.
Chromosome-level genome assembly of milk thistle (Silybum marianum(L.) Gaertn.)
Authors: Kim Kyung Do , Shim Jeehyoung , Hwang Ji-Hun , Kim Daegwan , El baidouri Moaine , Park Soyeon , Song Jiyong , Yu Yeisoo , Lee Keunpyo , Ahn Byoung-Ohg , Hong Su Young , Chin Joong Hyoun
Published: March 2024

Silybum marianum(L.) Gaertn., commonly known as milk thistle, is a medicinal plant belonging to the Asteraceae family. This plant has been recognized for its medicinal properties for over 2,000 years. However, the genome of this plant remains largely undiscovered, having no reference genome at a chromosomal level. Here, we assembled the chromosome-level genome ofS. marianum, allowing for the annotation of 53,552 genes and the identification of transposable elements comprising 58% of the genome. The genome assembly from this study showed 99.1% completeness as determined by BUSCO assessment, while the previous assembly (ASM154182v1) showed 36.7%. Functional annotation of the predicted genes showed 50,329 genes (94% of total genes) with known protein functions in public databases. Comparative genome analysis among Asteraceae plants revealed a striking conservation of collinearity betweenS. marianumandC. cardunculus. The genomic information generated from this study will be a valuable resource for milk thistle breeding and for use by the larger research community.
Synthesis of arbitrary interference patterns using a single galvanometric mirror, and its application to Structured Illumination Microscopy
Authors: Guo Ke , Boualam Abderrahim , Manton James D , Rowlands Christopher J
Published: March 2024

We present a new interferometer concept called SWIFT, able to project arbitrary interference patterns constructed from small numbers of plane waves. SWIFT can control each plane wave’s orientation, intensity, polarization and phase using just a single galvanometric mirror. We demonstrate the application of SWIFT to both 2D and 3D Structured Illumination Microscopy, characterizing performance on fluorescent nanoparticles and iFluor 488 phalloidin-stained U-2 OS cells.
Machine learning-based spike sorting reveals how subneuronal concentrations of monomeric Tau cause a loss in excitatory postsynaptic currents in hippocampal neurons
Authors: Brockhoff Marius , Träuble Jakob , Middya Sagnik , Fuchsberger Tanja , Fernandez-Villegas Ana , Stephens Amberley , Robbins Miranda , Dai Wenyue , Haider Belquis , Vora Sulay , Läubli Nino F , Kaminski Clemens F , Malliaras George G , Paulsen Ole , Kaminski Schierle Gabriele S
Published: March 2024

Extracellular recordings of neuronal activity constitute a powerful tool for investigating the intricate dynamics of neural networks and the activity of individual neurons. Microelectrode arrays (MEAs) allow for recordings with a high electrode count, ranging from 10s to 1000s, generating extensive datasets of neuronal information. Furthermore, MEAs capture extracellular field potentials from cultured cells, resulting in highly complex neuronal signals that necessitate precise spike sorting for meaningful data extraction. Nevertheless, conventional spike sorting methods face limitations in recognising diverse spike shapes, thereby constraining the full utilisation of the rich dataset acquired from MEA recordings. To overcome these limitations, we have developed a machine learning algorithm, namedPseudoSort, which employs advanced self-supervised learning techniques, a distinctive density-based pseudo-labelling strategy, and an iterative fine-tuning process to enhance spike sorting accuracy. Through extensive benchmarking on large-scale simulated datasets, we demonstrate the superior performance ofPseudoSortcompared to recently developed machine learning-based (ML) spike sorting algorithms. We showcase the practical application ofPseudoSortby utilising MEA recordings from hippocampal neurons exposed to subneuronal concentrations of monomeric Tau, a protein associated with Alzheimer’s disease (AD). Our results, validated against patch clamp experiments, unveil that monomeric Tau at subneuronal concentrations induces stimulation-dependent disruptions in both local and global activity of hippocampal neurons. Remarkably, patch clamp electrophysiology highlights the effect of combined Tau and neuronal stimulation treatment on excitatory postsynaptic currents, whereasPseudoSortexcels in identifying neuronal clusters that exhibit diminished firing capacity following Tau treatment alone,i.e., in the absence of stimulation. This comprehensive approach validates the prowess ofPseudoSortand unravels the intricate effects of Tau on neuronal activity, particularly in the context of AD.
Robotic Laser Tissue Soldering for Damage-free Soft Tissue Fusion Guided by Fluorescent Nanothermometry
Authors: Cipolato Oscar , Leuthold Tobias , Zaech Marius , Maennel Georg , Aegerter Sam , Sciascia Calinda , Jessernig Alexander , Sarcevic Sima , Rosendorf Jachym , Liska Vaclav , Kundrat Dennis , Quidant Romain , Herrmann Inge K
Published: March 2024

Minimally invasive surgical techniques, including endoscopic and robotic procedures, continue to revolutionize patient care, for their ability to minimize surgical trauma, thus promoting faster recovery and reduced hospital stays. Yet, the suturing of soft tissues ensuring damage-free tissue bonding during these procedures remains challenging due to missing haptics and the fulcrum effect. Laser tissue soldering has potential in overcoming these issues, offering damage-free seamless tissue fusion. To ensure the precision and safety of laser tissue soldering, we introduce feedback controlled fluorescent nanothermometry-guided laser tissue soldering using nanoparticle-protein solders within endoscopic and robotic contexts. Temperature-sensitive fluorescent nanoparticles embedded in the solder provide surgeons with immediate feedback on tissue temperatures during laser application, all while within the confines of minimally invasive (robotic) surgical setups. By integrating fluorescent nanothermometry-guided laser tissue surgery into endoscopic and robotic surgery, we pave the way for a new approach for safe and atraumatic soft tissue joining, especially in regions where traditional suturing is unfeasible.
MASCARA: coexpression analysis in data from designed experiments
Authors: White Fred T.G. , Heintz-Buschart Anna , Dong Lemeng , Bouwmeester Harro J. , Westerhuis Johan A. , Smilde Age K.
Published: March 2024

Experiments in plant transcriptomics are usually designed to induce variation in a pathway of interest. Harsh experimental conditions can cause widespread transcriptional changes between groups. Discovering coexpression within a pathway of interest (here the strigolactone pathway) in this context is hampered by the dominant variance induced by the design. Minor changes in experimental conditions not controlled for may affect the plants, leading to small coordinated differences in genes within pathways of interest and related pathways between replicate plants in the same controlled experimental condition. These systematic differences are usually averaged out, but we argue here that they can be used to improve the detection of genes that co-express. We introduce a novel framework “MASCARA” which combines ANOVA simultaneous component analysis and partial least squares to remove the experimentally induced variance and investigate multivariate relationships in the non-designed variance. MASCARA is tested against a selection of competitors on simulated data, created to mimic a designed transcriptome study, where its benefit is demonstrated. In a coexpression analysis of a real dataset MASCARA detects several uncharacterised but relevant transcripts. Our results indicate that there is sufficient structure left in a typical dataset after correcting for experimental variance and that this residual information is useful to investigate coexpression.

Author Summary

Experiments in the life sciences usually purposefully induce significant variance between different treatments, in order to activate or repress certain mechanisms of interest. Whilst this is necessary it can make it challenging to detect meaningful relationships within pathways of interest, particularly when the experimental conditions are drastically different. Instead of focusing on the drastic changes in response due to the different treatment, MASCARA uses the systematic synchronous variances between replicates to find related features within the pathway of interest. Through simulation studies and application to a real dataset, we demonstrate the effectiveness of MASCARA in detecting relevant transcripts and extracting coexpression patterns from gene expression data.
Self-reported preferences for seasonal Daylight Saving Time meet fundamentals of human physiology: correlations in the 2018 Public Consultation by the European Commission
Authors: Martín-Olalla José María , Mira Jorge
Published: March 2024

We thoroughly analyze the results to question 2 (individual preferences for cancelling or keeping the current clock regulations) from the 2018 Public Consultation on summertime arrangements (DST) conducted by the European Commission.

We reveal correlations in the shares of population for cancelling the regulations and the winter sunrise time (SRW) [R2= 0.177;p= 0.03;N= 25] and the onset of human activity [R2= 0.677;p= 5 × 10−5;N= 17].

The results are in line with the rationale behind the regulations in the range of latitude 35°to 63°: larger values of SRW (larger latitude) brought larger shares against the regulations; and earlier onset of human activity relative to SRW brought larger shares against the regulations.

The shares for cancelling the regulation did not show correlations with time offset (position in time zone), thus challenging the current view within the circadian community.
Bilayered Biofabrication Unlocks the Potential of Skeletal Muscle for Biohybrid Soft Robots
Authors: Balciunaite Aiste , Yasa Oncay , Filippi Miriam , Michelis Mike Y. , Katzschmann Robert K.
Published: March 2024

The emerging field of biohybrid robotics aims to create the next generation of soft and sustainable robots by using engineered biological muscle tissues integrated with soft materials as artificial muscles (bio-actuators). Both cardiac and skeletal muscle cells can be used for biohybrid actuation. Generally, cardiac bio-actuators take the shape of thin cellular films, while locomotive skeletal muscle bio-actuators form bulk tissues. The geometry of a bio-actuator should be optimized for the type of desired motion,e.g., thin film layers are optimal for swimming actuators mimicking fish. Until now, the geometry of skeletal muscle bio-actuators has been constrained to ring- or block-like tissues generally differentiated around a pair of pillars due to the need to oppose the contraction force exerted during the skeletal muscle differentiation process. In this work, we extend the possible geometry of skeletal muscle bio-actuators by demonstrating a bilayered design that mimics the motion of jellyfish. We take advantage of a volumetric printing method,i.e., xolography, which allows us to micropattern poly(ethylene glycol) diacrylate and gelatin methacrylate hydrogels to serve as scaffolds for seeding a layer of the skeletal muscle cell matrix. We demonstrate the locomotion speed of our bio-actuators is 3.4x faster than previously reported counterparts. In addition, our skeletal bio-actuators outperform most cardiac ones. Further optimization of our bilayer biofabrication for improved reproducibility of the maturation process of the skeletal muscle tissue will pave the way for the next generation of performant skeletal muscle-based actuators for biohybrid robots.
Acceleratingde novoSINE annotation in plant and animal genomes
Authors: Liao Herui , Sun Yanni , Ou Shujun
Published: March 2024

Genome annotation is an important but challenging task. Accurate identification of short interspersed nuclear elements (SINEs) is particularly difficult due to their lack of highly conserved sequences. AnnoSINE is state-of-the-art software for annotating SINEs in plant genomes, but its homology-based module is not available for animals and it is computationally inefficient for large genomes. Therefore, we propose AnnoSINE_v2, which extends accurate SINE annotation for animal genomes with greatly optimized computational efficiency. Our results show that AnnoSINE_v2’s annotation of SINEs has over 20% higher F1-score compared to the existing tools on animal genomes and enables the processing of complicated genomes, like human and zebrafish, which were beyond the capabilities of AnnoSINE_v1. AnnoSINE_v2 is freely available on Conda and GitHub:https://github.com/liaoherui/AnnoSINE_v2.
Scvi-hub: an actionable repository for model-driven single cell analysis
Authors: Ergen Can , Pour Amiri Valeh Valiollah , Kim Martin , Streets Aaron , Gayoso Adam , Yosef Nir
Published: March 2024

The accumulation of single-cell omics datasets in the public domain has opened new opportunities for reusing and leveraging the vast amount of information they contain. Such uses, however, are complicated by the need for complex and resource-consuming procedures for data transfer, normalization and integration that must be addressed prior to any analysis. Here we present scvi-hub: a platform for efficiently sharing and accessing single-cell omics datasets using pre-trained probabilistic models. We demonstrate that scvi-hub allows immediate access to a slew of fundamental tasks like visualization, imputation, annotation, outlier detection, and deconvolution of new (query) datasets, using state of the art algorithms and with a requirement for storage and compute resources that is much lower compared to standard approaches. We also show that the pre-trained models enable efficient analysis and new discoveries with existing references, including large atlases such as the CZ CELLxGENE Discover Census. Scvi-hub is built within the scvi-tools open source environment and integrated into scverse. It provides powerful and readily available tools for utilizing a large collection of already-loaded datasets while also enabling easy inclusion of new datasets, thus putting the power of atlas-level analysis at the fingertips of a broad community of users.
pTAC3 and pTAC14 are required for binding of plastid-encoded RNA polymerase to DNA
Authors: Wang Joyful , Palomar V. Miguel , Min Ji-Hee , Wierzbicki Andrzej T.
Published: March 2024

Plastid-encoded RNA polymerase (PEP) is a bacterial-type multisubunit RNA polymerase responsible for the majority of transcription in chloroplasts. PEP consists of four core subunits, which are orthologs of their cyanobacterial counterparts. InArabidopsis thaliana, PEP associates with 12 PEP-associated proteins (PAPs), which serve as peripheral subunits of the RNA polymerase. The exact contributions of PAPs to PEP function are still poorly understood. We use ptChIP-seq to show that PAP1/pTAC3, a peripheral subunit of PEP, binds to the same genomic loci as RpoB, a core subunit of PEP. Thepap1/ptac3mutant shows a complete loss of RpoB binding to DNA throughout the genome, indicating that PAP1/pTAC3 is necessary for RpoB binding to DNA. A similar loss of RpoB binding to DNA is observed in thepap7/ptac14mutant, which is defective in another peripheral PEP subunit. We propose that the peripheral subunits of PEP are required for the recruitment of core PEP subunits to DNA.

KEY MESSAGE

The peripheral subunits of plastid-encoded RNA polymerase play a crucial role in recruiting the core PEP subunits to DNA in Arabidopsis chloroplasts.
Expression based polygenic scores - A gene network perspective to capture individual differences in biological processes
Authors: Barth Barbara , de Mendonça Filho Euclides José , Arcego Danusa Mar , Pokhvisneva Irina , Meaney Michael J. , Silveira Patrícia Pelufo
Published: March 2024

Incorporating functional aspects into polygenic scores may accelerate early diagnosis and the discovery of therapeutic targets. Yet, existing polygenic scores summarize information from genome wide statistical associations between SNPs and phenotypes. We developed the novel biologically informed, expression-based polygenic scores (ePRS or ePGS). The method characterizes tissue specific gene co-expression networks from genome-wide RNA sequencing data and incorporates this information into polygenic scores. Performance and characteristics of the ePGS were compared to traditional polygenic risk score (PRS). We observed that ePGS differs from PRS for aggregating information on; i. the relation between different genes (co-expression); ii. the levels of tissue-specific gene expression; iii. the genetic variation of the target sample; iv. the tissue-specific effect size of the association between genotyping and gene expression; v. the portability across different ancestries. Variations in the ePGS represent individual variations in the expression of a tissue-specific gene co-expression network, and this methodology may profoundly influence the way we study human disease biology.