bluuebunny/crossref_metadata_2025 huggingface dataset:
Cross-species transcriptomic analysis identifies mitochondrial dysregulation as a functional consequence of the schizophrenia-associated 3q29 deletion
Authors: Purcell Ryan H. , Sefik Esra , Werner Erica , King Alexia T. , Mosley Trenell J. , Merritt-Garza Megan E. , Chopra Pankaj , McEachin Zachary T. , Karne Sridhar , Raj Nisha , Vaglio Brandon J. , Sullivan Dylan , Firestein Bonnie L. , Tilahun Kedamawit , Robinette Maxine I. , Warren Stephen T. , Wen Zhexing , Faundez Victor , Sloan Steven A. , Bassell Gary J. , Mulle Jennifer G.
Published: January 2023

Recent advances in the genetics of schizophrenia (SCZ) have identified rare variants that confer high disease risk, including a 1.6 Mb deletion at chromosome 3q29 with a staggeringly large effect size (O.R. > 40). Understanding the impact of the 3q29 deletion (3q29Del) on the developing CNS may therefore lead to insights about the pathobiology of schizophrenia. To gain clues about the molecular and cellular perturbations caused by the 3q29 deletion, we interrogated transcriptomic effects in two experimental model systems with complementary advantages: isogenic human forebrain cortical organoids and isocortex from the 3q29Del mouse model. We first created isogenic lines by engineering the full 3q29Del into an induced pluripotent stem cell line from a neurotypical individual. We profiled transcriptomes from isogenic cortical organoids that were aged for 2 months and 12 months, as well as day p7 perinatal mouse isocortex, all at single cell resolution. Differential expression analysis by genotype in each cell-type cluster revealed that more than half of the differentially expressed genes identified in mouse cortex were also differentially expressed in human cortical organoids, and strong correlations were observed in mouse-human differential gene expression across most major cell-types. We systematically filtered differentially expressed genes to identify changes occurring in both model systems. Pathway analysis on this filtered gene set implicated dysregulation of mitochondrial function and energy metabolism, although the direction of the effect was dependent on developmental timepoint. Transcriptomic changes were validated at the protein level by analysis of oxidative phosphorylation protein complexes in mouse brain tissue. Assays of mitochondrial function in human heterologous cells further confirmed robust mitochondrial dysregulation in 3q29Del cells, and these effects are partially recapitulated by ablation of the 3q29Del genePAK2. Taken together these data indicate that metabolic disruption is associated with 3q29Del and is conserved across species. These results converge with data from other rare SCZ-associated variants as well as idiopathic schizophrenia, suggesting that mitochondrial dysfunction may be a significant but overlooked contributing factor to the development of psychotic disorders. This cross-species scRNA-seq analysis of the SCZ-associated 3q29 deletion reveals that this copy number variant may produce early and persistent changes in cellular metabolism that are relevant to human neurodevelopment.
Heterogeneity in quiescent Müller glia in the uninjured zebrafish retina drive differential responses following photoreceptor ablation
Authors: Krylov Aaron J. , Yu Shuguang , Newton Axel , He Jie , Jusuf Patricia R.
Published: January 2023

Loss of neurons in the neural retina is a leading cause of vision loss. While humans do not possess the capacity for retinal regeneration, zebrafish can achieve this through activation of resident Müller glia. Remarkably, despite the presence of Müller glia in humans and other mammalian vertebrates, these cells lack an intrinsic ability to contribute to regeneration. Upon activation, zebrafish Müller glia can adopt a stem cell-like state, undergo proliferation and generate new neurons. However, the underlying molecular mechanisms of this activation subsequent retinal regeneration remains unclear. To address this, we performed single-cell RNA sequencing (scRNA-seq) and report remarkable heterogeneity in gene expression within quiescent Müller glia across distinct dorsal, central and ventral retina pools of such cells. Next, we utilised a genetically driven, chemically inducible nitroreductase approach to study Müller glia activation following selective ablation of three distinct photoreceptor subtypes: long wavelength sensitive cones, short wavelength sensitive cones, and rods. There, our data revealed that a region-specific bias in activation of Müller glia exists in the zebrafish retina, and this is independent of the distribution of the ablated cell type across retinal regions. Notably, gene ontology analysis revealed that injury-responsive dorsal and central Müller glia express genes related to dorsal/ventral pattern formation, growth factor activity, and regulation of developmental process. Through scRNA-seq analysis, we identify a shared genetic program underlying initial Müller glia activation and cell cycle entry, followed by differences that drive the fate of regenerating neurons. We observed an initial expression of AP-1 and injury-responsive transcription factors, followed by genes involved in Notch signalling, ribosome biogenesis and gliogenesis, and finally expression of cell cycle, chromatin remodeling and microtubule-associated genes. Taken together, our findings document the regional specificity of gene expression within quiescent Müller glia and demonstrate unique Müller glia activation and regeneration features following neural ablation. These findings will improve our understanding of the molecular pathways relevant to neural regeneration in the retina.
Elucidating Fibroblast Growth Factor-induced kinome dynamics using targeted mass spectrometry and dynamic modeling
Authors: Veth Tim S. , Francavilla Chiara , Heck Albert J.R. , Altelaar Maarten
Published: January 2023

Fibroblast growth factors (FGFs) are paracrine or endocrine signaling proteins that, activated by their ligands, elicit a wide range of health and disease-related processes, such as cell proliferation and the epithelial-to-mesenchymal transition (EMT). The detailed molecular pathway dynamics that coordinate these responses have remained to be determined. To elucidate these, we stimulated MCF-7 breast cancer cells with either FGF2, FGF3, FGF4, FGF10, or FGF19. Following activation of the receptor, we quantified the kinase activity dynamics of 44 kinases using a targeted mass spectrometry assay. Our system-wide kinase activity data, supplemented with (phospho)proteomics data, reveal ligand-dependent distinct pathway dynamics, elucidate the involvement of not earlier reported kinases such as MARK, and revise some of the pathway effects on biological outcomes. In addition, logic-based dynamic modeling of the kinome dynamics further verifies the biological goodness-of-fit of the predicted models and reveals tight regulation of the RAF kinase family.
Different time scales of common-cause evidence shape multisensory integration, recalibration and motor adaptation
Authors: Debats Nienke B , Heuer Herbert , Kayser Christoph
Published: January 2023

Perception engages the processes of integration, recalibration and sometimes motor adaptation to deal with discrepant multisensory stimuli. These processes supposedly deal with sensory discrepancies on different time scales, with integration reducing immediate ones and recalibration and motor adaptation reflecting the cumulative influence of their recent history. Importantly, whether discrepant signals are bound during perception is guided by the brains’ inference of whether they originate from a common cause. When combined, these two notions lead to the hypothesis that the different time scales on which integration and recalibration (or motor adaptation) operate are associated with different time scales of evidence of a common cause underlying two signals. We tested this prediction in a well‐established visuo‐motor paradigm, in which human participants performed visually guided hand movements. The kinematic correlation between hand and cursor movements indicates their common origin, allowing us to manipulate the common‐cause evidence by this correlation between visual and proprioceptive signals. Specifically, we dissociated hand and cursor signals during individual movements while preserving their correlation across movement endpoints. Following our hypothesis, this manipulation reduced integration compared to a condition in which visual and proprioceptive signals were perfectly correlated. In contrast, recalibration and motor adaption were not affected. This supports the notion that multisensory integration and recalibration are guided by common‐cause evidence but deal with sensory discrepancies on different time scales: while integration is prompted by local common‐cause evidence and reduces immediate discrepancies instantaneously, recalibration and motor adaptation are prompted by global common‐cause evidence and reduce persistent discrepancies.
Long-term herbivore removal experiments reveal different impacts of geese and reindeer on vegetation and ecosystem CO2-fluxes in high-Arctic tundra
Authors: Bon Matteo Petit , Hansen Brage B. , Loonen Maarten J. J. E. , Petraglia Alessandro , Bråthen Kari Anne , Böhner Hanna , Layton-Matthews Kate , Beard Karen H. , Moullec Mathilde Le , Jónsdóttir Ingibjörg S. , van der Wal René
Published: January 2023

Given the current and anticipated rates of global change, with associated shifts in herbivore population densities, understanding the role of different herbivores in shaping ecosystem structure and processes is critical for predicting ecosystem responses. Here, we examined the controls exerted by migratory geese and resident, non-migratory ungulates, two dominating yet functionally contrasting herbivores, on the rapidly warming Arctic tundra.

We collected vegetation and ecosystem carbon flux data at peak plant growing season in the two longest running herbivore removal experiments in high-Arctic Svalbard. Herbivore exclosures had been set up independently in a wet habitat utilised by barnacle geese (Branta leucopsis) in summer and in mesic-to-dry habitats utilised by wild reindeer (Rangifer tarandus platyrhynchus) year-round.

Excluding geese produced vegetation state transitions from heavily grazed, moss-dominated (4 g m-2dry weight of live aboveground vascular plants) to ungrazed, graminoid-dominated (60 g m-2; after 4-yr exclusion) and then horsetail-dominated (150 g m-2; after 15-yr exclusion) tundra. This caused large increases in vegetation carbon and nitrogen pools, dead biomass and moss-layer depth. Modifications in nitrogen concentrations and carbon-to-nitrogen ratios of vegetation and soil suggested overall slower nutrient cycling rates in the short-term absence of geese. Long-term goose removal quadrupled the net ecosystem carbon sequestration by increasing gross ecosystem photosynthesis more than ecosystem respiration.

Excluding reindeer for 21 years also produced detectable, but weaker, increases in live and dead biomass, vegetation carbon and nitrogen pools, moss-layer depth and ecosystem respiration. Yet, reindeer removal did not alter the chemistry of either vegetation or soil, nor net ecosystem carbon sequestration.

Our findings suggest that, though both herbivores were key drivers of ecosystem structure and processes, localised effects of geese, highly concentrated in space and time, are larger than those exerted by more widely dispersed reindeer. We illustrate that the impacts of herbivory across the tundra landscape are contingent on the habitat utilised for foraging, its sensitivity, the exerted grazing pressure, and herbivore characteristics. Our results underscore the conspicuous heterogeneity in how Arctic herbivores control ecosystem functioning, with important implications under current and future global change.
Nesting flight statistics for wind turbine planning: a MoveApps workflow
Authors: Kölzsch Andrea , Gal Johannes
Published: January 2023

As green, renewable energy is increasing by the installation of more and more wind turbines, the assessment of their impact on protected species has to be improved by more automatized, data-driven risk analyses.

We have developed as set of two workflows to extract simple parameters for collision risk models from GPS tracks of sensitive bird species during nesting. The workflows have been integrated into the free MoveApps platform and are available there. The analysis code of all components of the workflows is openly available on GitHub, and improvement and adaption to other, similar requirements is encouraged.

With three example data sets of white storks (WS), red kites (RK) and marsh harriers (MH), we illustrate how the workflows are used. The first workflow identifies nesting sites and time of nesting from the GPS tracks, the second workflow calculates flight speeds, flight duration, flight height and distance from the nest. Estimated flight speeds show low within species variability, with averages of 4.1 m/s (MH), 6.9 m/s (RK) and 10.9 m/s (WS). Extracted times of nesting are widely spread through the season and flight height and distance to the nest when in flight show large differences between individuals and years. Similar to the central evaluation distances around the nest required by national legislation, the 50% in-flight usage thresholds are 700 m (MH), 1100 m (RK) and 1400 m (WS). Flight height during nesting is rather low, on average 16 m (MH), 75 m (RK) and 193 m (WS) above the ground.

These values can help to estimate collision risk with wind turbines for large birds in Central Europe during their nesting period. Finally, the developed MoveApps workflows (an possible adaptions) can be used to extract required parameters from tracking studies of any other vulnerable species or populations in an unbiased, automated manner to improve wind turbine placement in relation to nesting sites.
Protein aggregation in wound fluid confines bacterial lipopolysaccharide and reduces inflammation
Authors: Petrlova Jitka , Hartman Erik , Petruk Ganna , Hwee Lim Jeremy Chun , Adav Sunil Shankar , Kjellström Sven , Puthia Manoj , Schmidtchen Artur
Published: January 2023

Bacterial lipopolysaccharide (LPS) induces the rapid formation of protein aggregates in human wound fluid. We aimed to define such LPS-induced aggregates and the functional consequences of protein aggregation using a combination of mass spectrometry analyses, biochemical imaging, and experimental animal models. We show that such wound-fluid aggregates contain a multitude of protein classes, including sequences from coagulation factors, annexins, histones, antimicrobial proteins/peptides, and apolipoproteins. Proteins and peptides with a high aggregation propensity were identified, and selected components were verified biochemically by western blot analysis. Staining by thioflavin T and the Amytracker probe demonstrated the presence of amyloid-like aggregates formed after exposure to LPS in vitro in human wound fluid and in vivo in porcine wound models. Using NF-κB-reporter mice and IVIS bioimaging, we show that such wound-fluid LPS aggregates induce a significant reduction in local inflammation compared with LPS in plasma. The results show that protein/peptide aggregation is a mechanism for confining LPS and reducing inflammation and further underscore the connection between host defense and amyloidogenesis.
DeepERA: deep learning enables comprehensive identification of drug-target interactions via embedding of heterogeneous data
Authors: Li Le , Wierbowski Shayne D. , Yu Haiyuan
Published: January 2023

Drug-target interaction prediction is a crucial step in drug development, discovery, and repurposing. Due to the tremendous combinatorial search space of all drug-protein pairs, machine learning algorithms have been utilized to facilitate the identification of novel drug-target interactions. Deep learning, known as a powerful learning system, has recently shown superior performance to traditional machine learning in many biological and biomedical areas. In this paper, we proposed an end-to-end deep learning model, DeepERA, to identify drug-target interactions based on heterogeneous data. This model assembles three independent feature embedding modules (intrinsic embedding, relational embedding, and annotation embedding) which each represent different attributes of the dataset and jointly contribute to the comprehensive predictions. This is the first work that, to our knowledge, applied deep learning models to learn each intrinsic features, relational features, and annotation features and combine them to predict drug-protein interactions. Our results showed that DeepERA outperformed other deep learning approaches proposed recently. The studies of individual embedding modules explained the dominance of DeepERA and confirmed the effects of the “guilt by associations” assumption on the performance of the prediction model. Using our DeepERA framework, we identified 45,603 novel drug-protein interactions for the whole human proteome, including 356 drug-protein interactions for the human proteins targeted by SARS-CoV-2 viral proteins. We also performed computational docking for the selected interactions and conducted a two-way statistical test to “normalize” the docking scores of different proteins/drugs to support our predictions.
Synthetic lethality in large-scale integrated metabolic and regulatory network models of human cells
Authors: Barrena Naroa , Valcárcel Luis V. , Olaverri-Mendizabal Danel , Apaolaza Iñigo , Planes Francisco J.
Published: January 2023

Synthetic lethality (SL) is a promising concept in cancer research. A wide array of computational tools has been developed to predict and exploit synthetic lethality for the identification of tumour-specific vulnerabilities. Previously, we introduced the concept of genetic Minimal Cut Sets (gMCSs), a theoretical approach to SL for genome-scale metabolic networks. The major challenge in our gMCS framework is to go beyond metabolic networks and extend existing algorithms to more complex protein-protein interactions. We present here a novel computation approach that adapts our previous gMCS formulation to incorporate linear regulatory pathways. Our novel approach is applied to calculate gMCSs in integrated metabolic and regulatory models of human cells. In particular, we integrate the most recent genome-scale metabolic network, Human1, with 3 different regulatory network databases: Omnipath, Dorothea and TRRUST. Based on the computed gMCSs and transcriptomic data, we detail new essential genes and their associated synthetic lethals for different cancer cell lines. The performance of the different integrated models is assessed with available large-scalein-vitrogene silencing data. Finally, we discuss the most relevant gene essentiality predictions based on published literature in cancer research.
Prefrontal Cortex Encodes Value Pop-out in Visual Search
Authors: Abbaszadeh Mojtaba , Panjehpour Armin , Alemohammad Mohammad Amin , Ghavampour Ali , Ghazizadeh Ali
Published: January 2023

Recent evidence shows that long-term object value association can lead to efficient visual search. However, the neural mechanism of this value pop-out has yet to be understood. Given the known role of the ventrolateral prefrontal cortex (vlPFC) in visual search and value memory, we recorded its single-unit activity (n=526) in two macaque monkeys while they engaged in the value-driven search. Monkeys had to determine whether a high-value target was present within a variable number of low-value objects. Interestingly, differential neural firing, as well as gamma-band power, indicated the presence of a target within ∼150ms of display onset. This differential activity was negatively correlated with search time and became less display size-dependent for more efficient searches. On the other hand, neural firing and its variability were higher in inefficient searches. These findings reveal the neural code within vlPFC for rapid detection of valuable targets, which can be crucial for animals faced with competition.

Significance Statement

Search for rewarding objects is ubiquitous and crucial for animals and humans alike. Up until recently, it was thought that visual search for valuable targets that were otherwise not distinct by low-level features should be serial and slow. Contrary to this belief, we showed that given sufficient reward training, valuable objects can be found efficiently in search suggesting a value pop-out neural mechanism. Importantly, we reveal the neural activity in the prefrontal cortex (PFC) to be predictive of the degree of value-driven search efficiency. Given the role of PFC in object value memory, these results show how PFC can translate such memories to emulate the parallel processing of visual information independent of low-level visual features.
Two conserved vocal central pattern generators broadly tuned for fast and slow rates generate species-specific vocalizations inXenopusclawed frogs
Authors: Yamaguchi Ayako , Peltier Manon
Published: January 2023

Across phyla, species-specific vocalizations are used by males to attract females. Functional analyses of the neural circuitry underlying behavior have been difficult, particularly in vertebrates. However, using anex vivobrain preparation that produces fictive vocalizations, we previously identified anatomically distinct fast and slow central pattern generators (CPGs) that drive the fast and slow clicks of male courtship calls in male African clawed frogs,Xenopus laevis. To gain insight into the evolution of neural circuits underlying courtship calls, we extended this approach to four additional species. Here, we show that although the exact rate and duration of the clicks are unique to each species, fast and slow CPGs identified in maleX. laevisare conserved across species. Further, we show that the development of fast CPGs depends on testosterone in a species-specific manner: testosterone facilitates the development of fast CPGs in a species with a courtship call containing fast clicks, but not in a species with a courtship call made entirely of slow clicks. Finally, we showed that, unlike other vestigial neural circuits that remain latent, the fast CPGs are not inherited by all species; rather, they are possessed only by the species that produce fast clicks. The results suggest that species-specific calls of the genusXenopushave evolved by utilizing conserved fast or slow CPGs that are broadly tuned to generate fast or slow trains of clicks, the development of which appear to be regulated by a strategic expression of testosterone receptors in the brain of each species.
Provision of essential resources as a persistence strategy in food webs
Authors: Raatz Michael
Published: January 2023

Pairwise interactions in food webs, including those between predator and prey are often modulated by a third species. Such higher-order interactions are important structural components of natural food webs that can increase the stability of communities against perturbations and ensure continued ecosystem functioning. Particularly the flux of rare organic and inorganic compounds that are essential to species in the community can create higher-order interactions. Even though many such compounds exist, their effect on structuring communities is little understood. In this study, I perform invasion analyses on a general food web model that depicts apparent and exploitative competition. Introducing the provision of essential resources by a prey species to either its competitor or its predator as a higher-order interaction, I find that this mechanism can ensure the focal prey’s persistence. Larger dietary essentiality, i.e. a stronger dependence of the predator or the competitor on the essential resource can increase the invasion growth rate of the focal prey to positive values, thus promoting its persistence when it would go extinct for low essentiality. This research shows that essential resources and the higher-order interactions created by them should be considered in community ecology.
Natural variation in salt-induced root growth phases and their contribution to root architecture plasticity
Authors: van Zelm Eva , Bugallo-Alfageme Silvia , Behrouzi Pariya , Meyer A. Jessica , Testerink Christa , Gommers Charlotte M.M.
Published: January 2023

During salt stress, the root system architecture of a plant is important for survival. Different accessions ofArabidopsis thalianahave adopted different strategies in remodeling their root architecture during salt stress. Salt induces a multiphase growth response in roots, consisting of a stop phase, quiescent phase, recovery phase and eventually a new level of homeostasis. We explored natural variation in the length of and growth rate during these phases in both main and lateral roots and find that some accessions lack the quiescent phase. Using mathematical models and correlation-based network, allowed us to correlate dynamic traits to overall root architecture and discover that both the main root growth rate during homeostasis and lateral root appearance are the strongest determinants of overall root architecture. In addition, this approach revealed a trade-off between investing in main or lateral root length during salt stress. By studying natural variation in high-resolution temporal root growth using mathematical modeling, we gained new insights in the interactions between dynamic root growth traits and we identified key traits that modulate overall root architecture during salt stress.

Summary statement

By studying natural variation in salt-induced root growth phases inArabidopsis, we show that main root growth rate during homeostasis and lateral root appearance contribute most to root architecture and we reveal a trade-off between investing in main and lateral root growth during salt stress.
N-of-one differential gene expression without control samples using a deep generative model
Authors: Prada-Luengo Iñigo , Schuster Viktoria , Liang Yuhu , Terkelsen Thilde , Sora Valentina , Krogh Anders
Published: January 2023

Differential gene expression analysis of bulk RNA sequencing data plays a major role in the diagnosis, prognosis, and understanding of disease. Such analyses are often challenging due to a lack of good controls and the heterogeneous nature of the samples. Here, we present a deep generative model that can replace control samples. The model is trained on RNA-seq data from healthy tissues and learns a low-dimensional representation that clusters tissues very well without supervision. When applied to cancer samples, the model accurately identifies representations close to the tissue of origin. We interpret these inferred representations as the closest normal to the disease samples and use the resulting count distributions to perform differential expression analysis ofsinglecancer sampleswithoutcontrol samples. In a detailed analysis of breast cancer, we demonstrate how our approach finds subtype-specific cancer driver and marker genes with high specificity and greatly outperforms the state-of-the-art method in detecting differentially expressed genes, DESeq2. We further show that the significant genes found using the model are highly enriched within cancer-specific driver genes across different cancer types. Our results show that thein silicoclosest normal provides a more favorable comparison than control samples.
Lateral gene transfer leaves lasting traces in Rhizaria
Authors: van Hooff Jolien J.E. , Eme Laura
Published: January 2023

Eukaryotic lineages acquire numerous prokaryotic genes via lateral gene transfer (LGT). However, LGT in eukaryotes holds many unknowns, especially its frequency, its long-term impact, and the importance of eukaryote-to-eukaryote LGT. LGT, and genome evolution in general, has not been rigorously studied in Rhizaria, which is a large and diverse eukaryotic clade whose members are mostly free-living, single-celled phagotrophs. We here explore LGT across Rhizaria since their origin until modern-day representatives, using a systematic, phylogenetic approach. On average, 30% of the genes present in current-day rhizarian genomes have originated through LGT at some point during the history of Rhizaria, which emerged about one billion years ago. We show that while LGTs are outnumbered by gene duplications, transferred genes themselves duplicate frequently, thereby amplifying their impact on the recipient lineage. Strikingly, eukaryote-derived LGTs were more prevalent than prokaryotic ones, and carry distinct signatures. Altogether, we here quantitatively and qualitatively reveal how LGT affected an entire eukaryotic phylum, thereby further demystifying LGT in eukaryotes.
Spindle-locked ripples mediate memory reactivation during human NREM sleep
Authors: Schreiner Thomas , Griffiths Benjamin J. , Kutlu Merve , Vollmar Christian , Kaufmann Elisabeth , Quach Stefanie , Remi Jan , Noachtar Soheyl , Staudigl Tobias
Published: January 2023

Memory consolidation relies on the reactivation of previous experiences during sleep. The precise interplay of sleep-related oscillations (slow oscillations, spindles and ripples) is thought to coordinate the information flow between relevant brain areas, with ripples mediating memory reactivation. However, in humans empirical evidence for a role of ripples in memory reactivation is lacking. Here, we investigated the relevance of sleep oscillations and specifically ripples for memory reactivation during human sleep using targeted memory reactivation (TMR). Intracranial electrophysiology in epilepsy patients and scalp EEG in healthy participants revealed that elevated levels of SO-spindle activity promoted the read-out of TMR induced memory reactivation. Importantly, spindle-locked ripples recorded intracranially from the medial temporal lobe were found to be instrumental for memory reactivation to unfold during non-rapid eye movement (NREM) sleep. Our findings establish ripples as key-oscillation in human systems consolidation and emphasize the importance of the coordinated interplay of the cardinal sleep oscillations.
Overlap in the cortical representation of hand and forearm muscles as assessed by navigated TMS
Authors: Jin Fang , Bruijn Sjoerd M. , Daffertshofer Andreas
Published: January 2023

The representation of upper limb muscles in the motor cortex is complex. It contains areas of excitability that may overlap between muscles. We expected the cortical representations of synergistic muscle pairs to overlap more than those of non-synergistic muscles. To detail this, we used navigated transcranial magnetic stimulation in eight hand and forearm muscles of twenty healthy participants. We transformed the cortical representations of muscles to a template MRI to allow for group analysis. We found that the amount of overlap in cortical representations differed significantly between within-hand and within-forearm muscle combinations. Most synergistic muscle pairs, both within the hand, within the forearm and between them, had a larger overlap than non-synergistic muscle pairs. Our study supports the largely overlapping nature of cortical representations of upper limb muscles. We can particularly underscore that the overlap is elevated in muscles that usually act in a synergistic manner.
Conformational Stability of Peroxidase from latex ofArtocarpus lakoocha: Influence of pH, Chaotropes, and Temperature
Authors: Sonkar Kirti Shila , Pachauri Manendra , Kumar Amit , Jagannadham Medicherla V.
Published: January 2023

A novel heme-peroxidase has been extracted from the latex of the medicinal plantArtocarpus lakoocha (A. lakoocha), known for its potential anti-inflammatory and wound healing properties. To study its stability, structure, and dynamics, this protein was analyzed using far-UV circular dichroism, fluorescence spectroscopy, and activity measurements. The results demonstrated the presence of three folding states: thenative state(N) at neutral pH,intermediate statesincluding molten globule (MG) at pH 2 and acid-unfolded (UA) at pH 1.5 or lower, and acid-refolded (A) at pH 0.5, along with alkaline denatured (UB) at pH 8-12 and the thirddenatured state(D) at GuHCl concentrations exceeding 5 M. Absorbance studies indicated the presence of free heme in the pH range of 1-2. The protein showed stability and structural integrity across a wide pH range (3-10), temperature (70 °C), and high concentrations of GuHCl (5 M) and urea (8 M). This study is the first to report multiple ‘partially folded intermediate states’ ofA. lakoochaperoxidase, with varying amounts of secondary structure, stability, and compactness. These results demonstrate the high stability ofA. lakoochaperoxidase and its potential for biotechnological and industrial applications, making it a valuable model system for further studies on its structure-function relationship.
Heat dissipation from photosynthesis contributes to maize thermoregulation under suboptimal temperature conditions
Authors: Sobejano-Paz Verónica , Mo Xingguo , Liu Suxia , Mikkelsen Teis Nørgaard , He Lihong , Jin Hongxiao , García Mónica
Published: January 2023

The extent to which plants thermoregulate to maintain relatively stable metabolic function in response to gradual and rapid temperature changes that jeopardize crop production is unclear. Maize thermoregulation was investigated based on leaf temperature (TL) measurements and its relationship with photochemistry and stomatal conductance (gs) under dry and wet soil scenarios. Seasonal climatology was simulated in a growth chamber according to Beijing’s climatology with extreme “hot days” based on historical maxima.

Maize behaved as a limited homeotherm, an adaptive strategy to maintain photosynthesis around optimum temperatures (Topt). Plants on drier soil had lower thermoregulatory capacity, with reduced gs, photosynthesis and transpiration, which impacted final yields, despite acclimation with a higher Toptto sustained stress. On hot days thermoregulation was affected by heat stress and water availability, suggesting that strong and frequent heatwaves will reduce crop activity although increased temperatures could bring photosynthesis closer to Toptin the region.

We propose a novel mechanism to explain thermoregulation from the contribution of heat dissipation via non-photochemical quenching (NPQ) to TL, supporting our hypothesis that NPQ acts as a negative feedback mechanism from photosynthesis by increasing TLin suboptimal conditions. These results could help to design adaptation strategies based on deficit irrigation.

Highlight

Maize was able to maintain leaf temperatures in narrower ranges than air temperatures by dissipating sunlight not used in photosynthesis as heat energy with a key role of transpiration cooling to sustain optimum photosynthesis temperature.
Rapid genome functional annotation pipeline anchored to the House sparrow (Passer domesticus, Linnaeus 1758) genome reannotation
Authors: Magallanes-Alba Melisa Eliana , Barricalla Agustín , Rego Natalia , Brun Antonio , Karasov William H. , Caviedes-Vidal Enrique
Published: January 2023

House sparrow (Passer domesticus) is an important avian model for both laboratory and field-based studies of evolutionary genetics, development, neurobiology, physiology, behavior, and ecology. The current annotation of theP. domesticusgenome is available at Ensembl Rapid Release site, which currently only focuses on gene set building. Here, we provide the first functional reannotation of theP. domesticusgenome based on enrichment with intestinal Illumina RNA-Seq libraries. This revised annotation describes 38592 transcripts, compared to 23574 currently for Ensembl, and 14717 predicted protein-coding genes, with 96.4% complete Passeriformes lineage BUSCOs. A key improvement in this revised annotation is the definition of untranslated region (UTR) sequences, with 82.7% and 93.8% of transcripts containing 5’ and 3’ UTRs, respectively. Our reannotation highlights the benefits to genome annotation improvement when additional specific RNA-Seq data is available for analysis and rapid data throughput (>200 Mb h−1) is used.
Complexity of spatiotemporal plantar pressure patterns during everyday behaviours
Authors: Cleland Luke D , Rowland Holly M , Mazzà Claudia , Saal Hannes P
Published: January 2023

The human foot sole is the primary interface with the external world during balance and walking, and also provides important tactile information on the state of contact. However, prior studies on plantar pressure have focused mostly on summary metrics such as overall force or centre of pressure under limited conditions. Here, we recorded spatiotemporal plantar pressure patterns with high spatial resolution while participants completed a wide range of daily activities, including balancing, locomotion, and jumping tasks. Contact area differed across task categories, but was only moderately correlated with the overall force experienced by the foot sole. The centre of pressure was often located outside the contact area or in locations experiencing relatively low pressure, and therefore a result of disparate contact regions spread widely across the foot. Non-negative matrix factorisation revealed low-dimensional spatial complexity that increased during interaction with unstable surfaces. Additionally, pressure patterns at the heel and metatarsals decomposed into separately located and robustly identifiable components, jointly capturing most variance in the signal. These results suggest optimal sensor placements to capture task-relevant spatial information and provide insight into how pressure varies spatially on the foot sole during a wide variety of natural behaviours.
LIMBARE: an Advanced Linear Mixed-effects Breakpoint Analysis with Robust Estimation Method with Applications to Longitudinal Ophthalmic Studies
Authors: Lee TingFang , Schuman Joel S , Ramos Cadena Maria de los Angeles , Zhang Yan , Wollstein Gadi , Hu Jiyuan
Published: January 2023

Purpose

Broken stick analysis is a widely used approach for detecting unknown breakpoints where association between measurements is non-linear. We propose LIMBARE, an advancedlinearmixed-effectsbreakpointanalysis withrobustestimation, especially designed for longitudinal ophthalmic studies. LIMBARE accommodates repeated measurements from both eyes and overtime, and effectively address the presence of outliers.

Methods

The model setup of LIMBARE and computing algorithm for point and confidence interval estimates of the breakpoint was introduced. The performance of LIMBARE and other competing methods was assessed via comprehensive simulation studies and application to a longitudinal ophthalmic study with 216 eyes (145 subjects) followed for an average of 3.7±1.3 years to examine the longitudinal association between structural and functional measurements.

Results

In simulation studies, LIMBARE showed the smallest bias and mean squared error (MSE) for estimating the breakpoint, with empirical coverage probability of corresponding CI estimate closest to the nominal level for scenarios with and without outlier data points. In the application to the longitudinal ophthalmic study, LIMBARE detected two breakpoints between visual field mean deviation (MD) and retinal nerve fiber layer thickness (RNFL) and one breakpoint between MD and cup to disc ratio (CDR), while the cross-sectional analysis approach only detected one and none, respectively.

Conclusions

LIMBARE enhances breakpoint estimation accuracy in longitudinal ophthalmic studies, while cross-sectional analysis approach is not recommended for future studies.

Translational Relevance

Our proposed method and companion software R package provides a valuable computational tool for advancing longitudinal ophthalmology research and exploring the association relationships between ophthalmic variables.
FRETpredict: A Python package for FRET efficiency predictions using rotamer libraries
Authors: Montepietra Daniele , Tesei Giulio , Martins João M. , Kunze Micha B. A. , Best Robert B. , Lindorff-Larsen Kresten
Published: January 2023

Here, we introduce FRETpredict, a Python software program to predict FRET efficiencies from ensembles of protein conformations. FRETpredict uses an established Rotamer Library Approach to describe the FRET probes covalently bound to the protein. The software efficiently operates on large conformational ensembles such as those generated by molecular dynamics simulations to facilitate the validation or refinement of molecular models and the interpretation of experimental data. We demonstrate the performance and accuracy of the software for different types of systems: a relatively structured peptide (polyproline 11), an intrinsically disordered protein (ACTR), and three folded proteins (HiSiaP, SBD2, and MalE). We also describe a general approach to generate new rotamer libraries for FRET probes of interest. FRETpredict is open source (GPLv3) and is available atgithub.com/KULL-Centre/FRETpredictand as a Python PyPI package atpypi.org/project/FRETpredict.

Author Summary

We present FRETpredict, an open-source software to calculate FRET observables from protein structures. Using a previously developed Rotamer Library Approach, FRETpredict helps place multiple conformations of the selected FRET probes at the labeled sites, and use these to calculate FRET efficiencies. Through several case studies, we illustrate the ability of FRETpredict to interpret experimental results and validate protein conformations. We also explain a methodology for generating new rotamer libraries of FRET probes of interest.
A quantitative approach to measure and predict microbiome response to antibiotics
Authors: Tu Vince , Ren Yue , Tanes Ceylan , Mukhopadhyay Sagori , Daniel Scott G. , Li Hongzhe , Bittinger Kyle
Published: January 2023

Background

Although antibiotics induce sizable perturbations in the human microbiome, we lack a systematic and quantitative method to measure and predict the microbiome’s response to specific antibiotics. Here, we introduce such a method, which takes the form of a Microbiome Response Index (MiRIx) for each antibiotic. Antibiotic-specific MiRIx values quantify the overall susceptibility of the microbiota to an antibiotic, based on databases of bacterial phenotypes and published data on intrinsic antibiotic susceptibility.

Results

We applied our approach to five published microbiome studies that carried out antibiotic interventions with vancomycin, metronidazole, ciprofloxacin, amoxicillin, and doxycycline. We show how MiRIx can be used in conjunction with existing microbiome analytical approaches to gain a deeper understanding of the microbiome response to antibiotics. Finally, we generate antibiotic response predictions for the oral, skin, and gut microbiome in healthy humans.

Conclusions

Our approach is implemented as open-source software and is readily applied to microbiome data sets generated by 16S rRNA marker gene sequencing or shotgun metagenomics.
RUNX1 is required in granulocyte-monocyte progenitors to attenuate inflammatory cytokine production by neutrophils
Authors: Zezulin Alexandra U. , Ye Darwin , Howell Elizabeth , Yen Daniel , Bresciani Erica , Diemer Jamie , Ren Jian-gang , Ahmad Mohd Hafiz , Castilla Lucio H. , Touw Ivo P. , Minn Andy J. , Tong Wei , Liu P. Paul , Tan Kai , Yu Wenbao , Speck Nancy A.
Published: January 2023

The transcription factor RUNX1 is mutated in familial platelet disorder with associated myeloid malignancies (FPDMM) and in sporadic myelodysplastic syndrome and leukemia. RUNX1 regulates inflammation in multiple cell types. Here we show that RUNX1 is required in granulocyte-monocyte progenitors (GMPs) to restrict the inflammatory response of neutrophils to toll-like receptor 4 (TLR4) signaling. Loss of RUNX1 in GMPs increased the TLR4 coreceptor CD14 on neutrophils, which contributed to neutrophils’ increased inflammatory cytokine production in response to the TLR4 ligand lipopolysaccharide. RUNX1 loss increased the chromatin accessibility of retrotransposons in GMPs and neutrophils and induced a type I interferon signature characterized by enriched footprints for signal transducer and activator of transcription (STAT1::STAT2) and interferon regulatory factors (IRF) in opened chromatin, and increased expression of interferon-stimulated genes. The overproduction of inflammatory cytokines by neutrophils was reversed by inhibitors of type I IFN signaling. We conclude that RUNX1 restrains the chromatin accessibility of retrotransposons in GMPs and neutrophils, and that loss of RUNX1 increases proinflammatory cytokine production by elevating tonic type I interferon signaling.
scGREAT: Graph-based regulatory element analysis tool for single-cell multi-omics data
Authors: Liu Chaozhong , Wang Linhua , Liu Zhandong
Published: January 2023

Motivation

With the development in single-cell multi-omics sequencing technology and data integration algorithms, we have entered the single-cell multi-omics era. Current multi-omics analysis algorithms failed to systematically dissect the heterogeneity within the datasets when inferring cis-regulatory events. Thus, there is a need for cis-regulatory element inferring algorithms that considers the cellular heterogeneity.

Results

Here, we propose scGREAT, a single-cell multi-omics regulatory state analysis Python package with a rapid graph-based correlation measurementL. The graph-based correlation method assigns each cell a localLindex, pinpointing specific cell groups of certain regulatory states. Such single-cell resolved regulatory state information enables the heterogeneity analysis equipped in the package. Applying scGREAT to the 10X Multiome PBMC dataset, we demonstrated how it could help subcluster cell types, infer regulation-based pseudo-time trajectory, discover feature modules, and find cluster-specific regulatory gene-peak pairs. Besides, we showed that global L index, which is the average of all local L values, is a better replacement for Pearson’s r in ruling out confounding regulatory relationships that are not of research interests.

Availability

https://github.com/ChaozhongLiu/scGREAT