bluuebunny/crossref_metadata_2025 huggingface dataset:
Cryogenic X-ray crystallographic studies of biomacromolecules at Turkish Light Source “Turkish DeLight”
Authors: Atalay Necati , Akcan Enver Kamil , Gül Mehmet , Ayan Esra , Destan Ebru , Ertem Fatma Betül , Tokay Nurettin , Çakilkaya Barış , Nergiz Zeliş , Karakadioğlu Gözde , Kepceoğlu Abdullah , Yapici İlkin , Tosun Bilge , Baldir Nilüfer , Yildirim Günseli , Johnson J Austin , Güven Ömür , Shafiei Alaleh , Arslan Nazlı Eylül , Yilmaz Merve , Kulakman Cahine , Paydos Seyide Seda , Çinal Zeynep Sena , Şabanoğlu Kardelen , Pazarçeviren Ayşegül , Yilmaz Ayşenur , Canbay Başak , Aşci Bengisu , Kartal Esra , Tavli Serra , Çaliseki Mehmet , Göç Günce , Mermer Arif , Yeşilay Gamze , Altuntaş Sevde , Tateishi Hiroshi , Otsuka Masami , Fujita Mikako , Tekin Şaban , Çiftçi Halilibrahim , Durdaği Serdar , Dinler Doğanay Gizem , Karaca Ezgi , Kaplan Türköz Burcu , Kabasakal Burak Veli , Kati Ahmet , Demirci Hasan
Published: September 2022

X-ray crystallography is a robust and powerful structural biology technique that provides high-resolution atomic structures of biomacromolecules. Scientists use this technique to unravel mechanistic and structural details of biological macromolecules (e.g. proteins, nucleic acids, protein complexes, protein-nucleic acid complexes, or large biological compartments). Since its inception, single-crystal cryo-crystallography has never been performed in Türkiye due to the lack of a single-crystal X-ray diffractometer. The X-ray diffraction facility recently established at the University of Health Sciences, Istanbul, Türkiye will enable Turkish and international researchers to easily perform high-resolution structural analysis of biomacromolecules from single crystals. Here, we describe the technical and practical outlook of a state-of-the-art home-source X-ray, using lysozyme as a model protein. The methods and practice described in this article can be applied to any biological sample for structural studies. Therefore, this article will be a valuable practical guide from sample preparation to data analysis.
Expanded utility of the R package qgg with applications within genomic medicine
Authors: Rohde Palle Duun , Sørensen Izel Fourie , Sørensen Peter
Published: September 2022

Here, we present an expanded utility of the R package qgg for quantitative genetic and genomic analyses of complex traits and diseases. One of the major updates of the package is, that it now includes five different Bayesian Linear Regression (BLR) models, which provide a unified framework for mapping of genetic variants, estimation of heritability and genomic prediction from either individual level data or from genome-wide association study (GWAS) summary statistics. To showcase some of the novel implementations, we analysed two quantitative trait phenotypes, body mass index and standing height from United Kingdom Biobank (UKB). We compared genomic prediction accuracies from single and multiple trait models, showed accurate estimation of genomic parameters, illustrate how a BLR model can be used to fine map potential causal loci, and finally, provide an extension of gene set enrichment analyses based on the BLR framework. With this release, the qgg package now provides a wealth of the commonly used methods in analysis of complex traits and diseases, without the need to switch between software tools and data formats.

Availability

Our methodology is implemented in the publicly available R software package qgg using fast and memory efficient algorithms in C++ and is available from CRAN or as a developer version at our GitHub page (https://github.com/psoerensen/qgg). Notes on the implemented statistical genetic models, tutorials and example scripts are available from our accompanied homepage https://qganalytics.com/.

Contact

palledr@hst.aau.dk and pso@qgg.au.dk

Supplementary information

Supplementary data are available online.
The effect of alpha-cyclodextrin on postprandial glucose excursions, a systematic meta analysis Alpha-cyclodextrin and Blood Glucose
Authors: Wittkowski Knut M.
Published: September 2022

Alpha-cyclodextrin (αCD) is a natural bacterial product that is widely used as a food ingredient. In the EU, αCD is regulated as a “dietary fiber” with an authorized health claim “for contributing to the reduction of postprandial glycemic responses”. In the US, αCD is generally recognized as save (GRAS), but on April 25, 2022, the U.S. Food and Drug Administration (FDA) rejected the inclusion of αCD in the list of “dietary fibers” because “the strength of the scientific evidence does not support a finding of a beneficial effect of αCD on postprandial blood glucose …”.

This meta-analysis reviews clinical trials conducted to test the effect of αCD on blood glucose and insulin levels during three hours after consumption of a meal comprising carbohydrates, fats, and proteins.

Several issues related to the standardization of the outcomes, the choice of the statistical methods in the cross-over studies conducted, and the choice of methods for the aggregation of P-values are discussed. In conclusion, the EU decision is confirmed and extended. The administration of αCD not only reduces the postprandial glycemic responses, but the absence of an increase in insulin levels suggests that αCD acts independent of increasing insulin production and, thus, their beneficial effect is not affected by insulin resistance.
Integrated human-machine interface for closed-loop stimulation using implanted and wearable devices
Authors: Sladky Vladimir , Kremen Vaclav , McQuown Kevin , Mivalt Filip , Brinkmann Benjamin H. , Van Gompel Jamie , Miller Kai J. , Denison Timothy , Worrell Gregory A.
Published: September 2022

Recent development in implantable devices for electrical brain stimulation includes sensing and embedded computing capabilities that enable adaptive stimulation strategies. Applications include stimulation triggered by pathologic brain activity and endogenous rhythms, such as circadian rhythms. We developed and tested a system that integrates an electrical brain stimulation & sensing implantable device with embedded computing and uses a distributed system with commercial electronics, smartphone and smartwatch for patient annotations, extensive behavioral testing, and adaptive stimulation in subjects in their natural environments. The system enables precise time synchronization of the external components with the brain stimulating device and is coupled with automated analysis of continuous streaming electrophysiology synchronized with patient reports. The system leverages a real-time bi-directional interface between devices and patients with epilepsy living in their natural environment.
Establishment and characterization of a tumoroid biobank derived from dog patients’ mammary tumors for translational research
Authors: Raffo-Romero Antonella , Aboulouard Soulaimane , Bouchaert Emmanuel , Rybicka Agata , Tierny Dominique , Hajjaji Nawale , Fournier Isabelle , Salzet Michel , Duhamel Marie
Published: September 2022

Breast cancer is the most frequent cancer among women causing the greatest number of cancer-related deaths. Cancer heterogeneity is a main obstacle to therapies. Around 96% of the drugs fail from discovery to the clinical trial phase probably because of the current unreliable preclinical models. New models emerge such as companion dogs who develop spontaneous mammary tumors resembling human breast cancer in many clinical and molecular aspects. The present work aimed at developing a robust canine mammary tumor model in the form of tumoroids which recapitulate the tumor diversity and heterogeneity. We conducted a complete characterization of these canine mammary tumoroids through histologic, molecular and proteomic analysis, demonstrating their strong similarity to the primary tumor. We demonstrated that these tumoroids can be used as a drug screening model. In fact, we showed that Paclitaxel, a human chemotherapeutic, could killed canine tumoroids with the same efficacy as human tumoroids with 0.1 to 1 μM of drug needed to kill 50% of the cells. Due to easy tissue availability, canine tumoroids can be produced at larger scale and cryopreserved to constitute a biobank. We have demonstrated that cryopreserved tumoroids keep the same histologic and molecular features (ER, PR and HER2 expression) as fresh tumoroids. Two techniques of cryopreservation were compared demonstrating that tumoroids made from frozen tumor material allowed to maintain a higher molecular diversity. These findings revealed that canine mammary tumoroids can be easily generated at large scale and can represent a more reliable preclinical model to investigate tumorigenesis mechanisms and develop new treatments for both veterinary and human medicine.
Longitudinal characterization of circulating extracellular vesicles and small RNA during simian immunodeficiency virus infection and antiretroviral therapy
Authors: Huang Yiyao , Liao Zhaohao , Dang Phuong , Queen Suzanne , Abreu Celina Monteiro , Zheng Lei , Witwer Kenneth W.
Published: September 2022

Objectives

Latent infection by human immunodeficiency virus (HIV) hinders viral eradication despite effective antiretroviral treatment (ART), Amongst proposed contributors to viral latency are cellular small RNAs that have also been proposed to shuttle between cells in extracellular vesicles (EVs). Thus, we profiled EV small RNAs during different infection phases to understand the potential relationship between these EV-associated small RNAs and viral infection.

Design

A well characterized simian immunodeficiency virus (SIV)/macaque model of HIV was used to profile EV-enriched blood plasma fractions harvested during pre-infection, acute infection, latent infection/ART treatment, and rebound after ART interruption.

Methods

Measurement of EV concentration, size distribution, and morphology was complemented with qPCR array for small RNA expression, followed by individual qPCR validations. Iodixanol density gradients were used to separate EV subtypes and virions.

Results

Plasma EV particle counts correlated with viral load and peaked during acute infection. However, SIV gag RNA detection showed that virions did not fully explain this peak. EV microRNAs miR-181a, miR-342-3p, and miR-29a decreased with SIV infection and remained downregulated in latency. Interestingly, small nuclear RNA U6 had a tight association with viral load peak.

Conclusions

This study is the first to monitor how EV concentration and EV small RNA expression change dynamically in acute viral infection, latency, and rebound in a carefully controlled animal model. These changes may also reveal regulatory roles in retroviral infection and latency.
Identifying medications underlying communication atypicalities in psychotic and affective disorders: A pharmacovigilance study within the FDA Adverse Event Reporting System
Authors: Fusaroli Michele , Simonsen Arndis , Borrie Stephanie A. , Low Daniel M. , Parola Alberto , Raschi Emanuel , Poluzzi Elisabetta , Fusaroli Riccardo
Published: September 2022

Purpose

Communication atypicalities are considered promising markers of a broad range of clinical conditions. However, little is known about the mechanisms and confounders underlying them. Medications might have a crucial, relatively unknown role both as potential confounders and offering an insight on the mechanisms at work. The integration of regulatory documents with disproportionality analyses provides a more comprehensive picture to account for in future investigations of communication-related markers. The aim of the current study was to identify a list of drugs potentially associated with communicative atypicalities within psychotic and affective disorders.

Method

We developed a query using the Medical Dictionary for Regulatory Activities (MedDRA) to search for communicative atypicalities within the FDA Adverse Event Reporting System (FAERS, updated June 2021). A Bonferroni corrected disproportionality analysis (Reporting Odds Ratio) was separately performed on spontaneous reports involving psychotic, affective, and non-neuropsychiatric disorders, to account for the confounding role of different underlying conditions. Drug adverse event associations not already reported in the SIDER database of labeled adverse drug reactions (unexpected) were subjected to further robustness analyses to account for expected biases.

Results

A list of 291 expected and 91 unexpected potential confounding medications was identified, including drugs that may irritate (inhalants) or desiccate (anticholinergics) the larynx, impair speech motor control (antipsychotics), induce nodules (acitretin) or necrosis (VEGFR-inhibitors) on vocal cords, sedatives and stimulants, neurotoxic agents (antiinfectives), and agents acting on neurotransmitter pathways (dopamine agonists).

Conclusions

We provide a list of medications to account for in future studies of communication-related markers in affective and psychotic disorders. The current test case illustrates rigorous procedures for digital phenotyping, and the methodological tools implemented for large scale disproportionality analyses can be considered a roadmap for investigations of communication-related markers in other clinical populations.
A Multithreaded Model for Cancer Tissue Heterogeneity: An Application
Authors: Chaudhuri Anik , Choudhury Shabnam , Mohanty Anwoy Kumar , Satpathy Manoranjan , Shell M. , Doe J.
Published: September 2022

Studying the heterogeneity in cancerous tissue is challenging in cancer research. It is vital to process the real-world data efficiently to understand the heterogeneous nature of cancer tissue. GPU compatible models, which can estimate the subpopulation of cancerous tissue, are fast if the size of input data, i.e., the number of qPCR (quantitative polymerase chain reaction) gene expression reading is extensive. In the real world, we rarely get that much data to reap the benefits of a GPU’s parallelism. Real experimental data from fibroblasts are much less, and models using those data on a GPU are slower than the CPU multithreaded application. This paper will show a method to run GPU-compatible models for cancer tissue heterogeneity on a multithreaded CPU. Further, we also show that the model running on a multithreaded CPU is faster than the model running on a GPU with real experimental data.
Base Editing for Reprogramming Cyanobacterium Synechococcus elongatus
Authors: Wang Shu-Yan , Li Xin , Wang Shu-Guang , Xia Peng-Fei
Published: September 2022

Global climate change demands carbon-negative innovations to reduce the concentration of atmospheric carbon dioxide (CO2). Cyanobacteria can fix CO2 from the atmosphere and can be genetically reprogrammed for the production of biofuels, chemicals and food products, making an ideal microbial chassis for carbon-negative biotechnology. However, the progress seems to be slowed down due to the lagging-behind synthetic biology toolkits, especially the CRISPR-Cas-based genome-editing tools. As such, we developed a base-editing tool based on the CRISPR-Cas system and deamination for cyanobacterium Synechococcus elongatus. We achieved efficient and precise genome editing at a single-nucleotide resolution, and identified the pure population of edited cells at the first round of selection without extra segregation. By using the base-editing tool, we successfully manipulated the glycogen metabolic pathway via the introduction of premature STOP codons to inactivate the corresponding genes. We demonstrated multiplex base editing by editing two genes at once, obtaining a nearly two-fold increase in the glycogen content. We present here the first report of base editing in the phylum of cyanobacteria, and a paradigm for applying CRISPR-Cas systems in bacteria. We believe that this work will accelerate the synthetic biology of cyanobacteria and drive more innovations to alleviate global climate change.
Copy number variations shape the structural diversity of Arabidopsis metabolic gene clusters and are associated with the climatic gradient
Authors: Marszalek-Zenczak Malgorzata , Satyr Anastasiia , Wojciechowski Pawel , Zenczak Michal , Sobieszczanska Paula , Brzezinski Krzysztof , Iefimenko Tetiana , Figlerowicz Marek , Zmienko Agnieszka
Published: September 2022

Metabolic gene clusters (MGCs) encode at least three different enzymes for a common biosynthetic pathway. Comparative genome analyses highlighted the role of duplications, deletions and rearrangements in MGC formation. We hypothesized that these mechanisms also contribute to MGC intraspecies diversity and play a role in adaptation. We assessed copy number variations (CNVs) of four Arabidopsis thaliana MGCs in a population of 1,152 accessions, with experimental and bioinformatic approaches. The MGC diversity was lowest in marneral gene cluster (one private deletion CNV) and highest in the arabidiol/baruol gene cluster where 811 accessions had gene gains or losses, however, there were no presence/absence variations of the entire clusters. We found that the compact version of thalianol gene cluster was predominant in A. thaliana and more conserved than the noncontiguogus version. In arabidiol/baruol cluster we found a large insertion in 35% of analyzed accessions, that contained duplications of the reference genes CYP705A2 and BARS1. The BARS1 paralog, which we named BARS2, encoded a novel oxidosqualene synthase. Unexpectedly, in accessions with the insertion, the arabidiol/baruol gene cluster was expressed not only in roots but also in leaves. Additionally, they presented different root growth dynamics and were associated with warmer climates compared to the reference-like accessions. We also found that paired genes encoding terpene synthases and cytochrome P450 oxidases had higher copy number variability compared to non-paired ones. Our study highlights the importance of intraspecies variation and nonreference genomes for dissecting secondary metabolite biosynthesis pathways and understanding their role in adaptation and evolution.
The injury-induced circular RNA circGLIS3 activates dermal fibroblasts to promote wound healing
Authors: Toma Maria A. , Wang Qizhang , Li Dongqing , Xiao Yunting , Niu Guanglin , Geara Jennifer , Vij Manika , Piipponen Minna , Liu Zhuang , Zhang Letian , Bian Xiaowei , Wang Aoxue , Sommar Pehr , Xu Landén Ning
Published: September 2022

Delayed skin wound healing and excessive scarring are consequences of an impaired healing process and represent a major health and economic burden worldwide. Current intervention strategies lack efficacy and suffer from high recurrence rates necessitating the investigation into alternative treatment modalities like circular RNAs (circRNAs). By RNA sequencing, we profiled circRNA expression changes during human skin wound healing as well as in keratinocytes and fibroblasts isolated from donor-matched skin and acute wounds. CircGLIS3 was found to be transiently upregulated in the dermal fibroblasts upon skin injury, which was at least partially due to the activated IL-1 signaling. Similarly, overabundant circGLIS3 expression was detected in human keloid lesions compared to the surrounding healthy skin. We found that circGLIS3 resided mainly in the cytoplasm, where it interacted with and stabilized Procollagen C-endopeptidase enhancer 1 (PCPE-1) protein to enhance TGF-β signaling, fibroblast activation, and production of extracellular matrix – important biological processes required for wound repair. Accordingly, knockdown of circGLIS3 in humanex vivowounds potently reduced wound contraction and delayed re-epithelialization. Collectively, we have identified a previously uncharacterized circRNA regulator of human skin wound healing that may open an avenue for circRNA-based therapeutics for abnormal scarring or nonhealing wounds.

One Sentence Summary

Transient increase of the circular RNA circGLIS3 promotes the wound fibroblast activation and extracellular matrix production to facilitate wound closure.
Dual control of lysogeny and phage defense by a phosphorylation-based toxin/antitoxin system
Authors: Guo Yunxue , Tang Kaihao , Sit Brandon , Gu Jiayu , Chen Ran , Lin Jianzhong , Lin Shituan , Liu Xiaoxiao , Wang Weiquan , Gao Xinyu , Nie Zhaolong , Liu Tianlang , Waldor Matthew K. , Wang Xiaoxue
Published: September 2022

Regulatory systems that maintain prophage quiescence integrate phage and host gene expression with environmental conditions1,2. In the opportunistic bacterial pathogenPseudomonas aeruginosa, Pf filamentous bacteriophages play critical roles in biofilm formation and virulence3-5, but mechanisms governing Pf prophage activation in biofilms are largely unknown. Here, we report a new type of prophage regulatory module in a widely-distributedP. aeruginosalineage that not only controls virion production of co-resident Pf prophages, but also mediates defense against diverse lytic phages. By comparing two lineages of the prototypeP. aeruginosastrain PAO1 that harbor different Pf prophages, we identified a prophage-encoded kinase-kinase-phosphatase (KKP) system that controls Pf production in biofilms. KKP components exhibit dynamic stoichiometry, where high kinase levels in planktonic conditions maintain phosphorylation of the host H-NS protein MvaU, repressing prophage activation. During biofilm formation, phosphatase expression is heightened, leading to MvaU dephosphorylation and alleviating repression of prophage gene expression. KKP clusters are present in hundreds of diverse temperate prophages and other mobile elements across Gram-negative bacteria. Characterization of KKP modules from different species revealed that, in addition to regulating Pf phage lysogeny, KKP functions as a tripartite toxin-antitoxin system that mediates host defense from predatory lytic phages. KKP represents a new phosphorylation-based mechanism for prophage regulation and for phage defense. The dual function of this module raises the question of whether other newly described phage defense systems6-9also regulate intrinsic prophage biology in diverse hosts.
A translational repression reporter assay for the analysis of RNA-binding protein consensus sites
Authors: Nowacki Jessica , Malenica Mateo , Schmeing Stefan , Schiller Damian , Buchmuller Benjamin , ‘t Hart Peter
Published: September 2022

RNA-binding proteins are essential regulators of RNA processing and function. Translational repression assays can be used to study how they interact with specific RNA sequences by insertion of such a consensus sequence into the 5’ untranslated region of a reporter mRNA and measuring reporter protein translation. The straightforward set-up of these translational repression assays avoids the need for the isolation of the protein or the RNA providing speed, robustness, and a low-cost method. Here we report the optimization of the assay to function with linear RNA sequences instead of the previously reported hairpin type sequences to allow the study of a wider variety of RNA-binding proteins. Multiplication of a consensus sequence strongly improves the signal allowing analysis by both fluorescence intensity measurements and fluorescence activated cell sorting.
Scavenger receptor B1 facilitates the endocytosis of Escherichia coli via TLR4 signaling in mammary gland infection
Authors: Taban Qamar , Ahmad Syed Mudasir , Mumtaz Peerzada Tajamul , Bhat Basharat , Haq Ehtishamul , Magray Suhail , Saleem Sahar , Shabir Nadeem , Muhee Amatul , Kashoo Zahid Amin , Zargar Mahrukh Hameed , Malik Abrar A. , Ganai Nazir A. , Shah Riaz A.
Published: September 2022

SCARB1 belongs to class B of Scavenger receptors (SRs) that are known to be involved in binding and endocytosis of various pathogens. SRs have emerging role in regulating innate immunity and host-pathogen interactions by acting in co-ordination with Toll-like receptors. Little is known about the function of SCARB1 in milk-derived mammary epithelial cells (MECs). This study reports the role of SCARB1 in infection and its potential association in TLR4 signaling on bacterial challenge in Goat mammary epithelial cells (GMECs). The novelty in the establishment of MEC culture lies in the method that aims to enhance the viability of the cells with intact characteristics upto a higher passage number. We represent MEC culture to be used as a potential infection model for deeper understanding of animal physiology especially around the mammary gland. On E.coli challenge the expression of SCARB1 was significant in induced GMECs at 6 h. Endoribonuclease-esiRNA based silencing of SCARB1 affects the expression of TLR4 and its pathways i.e. MyD88 and TRIF pathways on infection. Knockdown also affected the endocytosis of E.coli in GMECs demonstrating that E.coli uses SCARB1 function to gain entry in cells. Furthermore, we predict 3 unique protein structures of uncharacterized SCARB1 (Capra hircus) protein. Overall, we highlight SCARB1 as a main participant in host defence and its function in antibacterial advances to check mammary gland infections.
Transgressive and parental dominant gene expression and cytosine methylation during seed development inBrassica napushybrids
Authors: Orantes-Bonilla Mauricio , Wang Hao , Lee HueyTyng , Golicz Agnieszka A. , Hu Dandan , Li Wenwen , Zou Jun , Snowdon Rod J.
Published: September 2022

The enhanced performance of hybrids though heterosis remains a key aspect in plant breeding, however the underlying mechanisms are still not fully elucidated. To investigate the potential role of transcriptomic and epigenomic patterns in early expression of hybrid vigour, we investigated gene expression, small RNA abundance and genome-wide methylation in hybrids from two distantBrassica napusecotypes during seed and seedling developmental stages using next-generation sequencing technologies. A total of 71217, 773, 79518 and 31825 differentially expressed genes, microRNAs, small interfering RNAs and differentially methylated regions were identified, respectively. Approximately 70% of the differential expression and methylation patterns observed could be explained due to parental dominance levels. Via gene ontology enrichment and microRNA-target association analyses during seed development we found copies of reproductive, developmental and meiotic genes with transgressive and paternal dominance patterns. Interestingly, maternal dominance was more prominent in hypermethylated and downregulated features during seed formation. This contrasts to the general maternal gamete demethylation reported during gametogenesis in most plant species. Associations between methylation and gene expression allowed identification of putative epialleles with diverse pivotal biological functions during seed formation. Furthermore, most differentially methylated regions, differentially expressed siRNAs and transposable elements were found in regions flanking genes that had no differential expression. This suggests that differential expression and methylation of epigenomic features may help maintain expression of pivotal genes in a hybrid context. Differential expression and methylation patterns during seed formation in an F1 hybrid provide novel insight into genes and mechanisms with a potential role in early heterosis.

Key message

Transcriptomic and epigenomic profiling of gene expression and small RNAs during seed and seedling development reveals expression and methylation dominance levels with implications on early stage heterosis in oilseed rape.
Plants stand still but hide: imperfect and heterogeneous detection is the rule when counting plants
Authors: Perret Jan , Besnard Aurélien , Charpentier Anne , Papuga Guillaume
Published: September 2022

The estimation of population size and its variation across space and time largely relies on counts of individuals, generally carried out within spatial units such as quadrats or sites. Missing individuals during counting (i.e. imperfect detection) results in biased estimates of population size and trends. Imperfect detection has been shown to be the rule in animal studies, and most studies now correct for this bias by estimating detection probability. Yet this correction remains exceptional in plant studies, suggesting that most plant ecologists implicitly assume that all individuals are always detected.

To assess if this assumption is valid, we conducted a field experiment to estimate individual detection probability in plant counts conducted in 1×1 m quadrats. We selected 30 herbaceous plant species along a gradient of conspicuousness at 24 sites along a gradient of habitat closure, and asked groups of observers to count individuals in 10 quadrats using three counting methods requiring progressively increasing times to complete (quick count, unlimited count and cell count). In total, 158 participants took part in the experiment, allowing an analysis of the results of 5,024 counts.

Over all field sessions, no observer succeeded in detecting all the individuals in the 10 quadrats. The mean detection rate was 0.44 (ranging from 0.11 to 0.82) for the quick count, 0.59 for the unlimited count (range 0.18–0.87) and 0.74 for the cell count (range 0.46-0.94).

Detection probability increased with the conspicuousness of the target species and decreased with the density of individuals and habitat closure. The observer’s experience in botany had little effect on detection probability, whereas detection was strongly affected by the time observers spent counting. Yet although the more time-consuming methods increased detection probability, none achieved perfect detection, nor did they reduce the effect on detection probability of the variables we measured.

Synthesis. Our results show that detection is imperfect and highly heterogeneous when counting plants. To avoid biased estimates when assessing the size, temporal or spatial trends of plant populations, plant ecologists should use methods that estimate the detection probability of individuals rather than relying on raw counts.
Metamodelling of a two-population spiking neural network
Authors: Skaar Jan-Eirik W. , Haug Nicolai , Stasik Alexander J. , Plesser Hans Ekkehard , Einevoll Gaute T. , Tøndel Kristin
Published: September 2022

In computational neuroscience, hypotheses are often formulated as bottom-up mechanistic models of the systems in question, consisting of differential equations that can be numerically integrated forward in time. Candidate models can then be validated by comparison against experimental data. The model outputs of neural network models depend on both neuron parameters, connectivity parameters and other model inputs. Successful model fitting requires sufficient exploration of the model parameter space, which can be computationally demanding. Additionally, identifying degeneracy in the parameters, i.e. different combinations of parameter values that produce similar outputs, is of interest, as they define the subset of models consistent with the data. In this computational study, we apply metamodels to a two-population recurrent spiking network of point-neurons, the so-called Brunel network. Metamodels are data-driven approximations to more complex models with more desirable computational properties, which can be run considerably faster than the original model. Specifically, we apply two different metamodelling techniques, Masked Autoregressive Flows and Deep Gaussian Process Regression, to estimate the power spectra of two different signals; the population spiking activities and the local field potential. We find that the metamodels are able to accurately model the power spectra in the asynchronous irregular regime. Using the metamodels, we invert the network, and estimate the probability distributions over parameters that can give rise to observed simulation outputs. We find that these distributions correctly identify parameter combinations that give similar model outputs, and that the parameters are constrained to different degrees by observing the two different signals.

Author summary

In computational neuroscience, mechanistic models are used to simulate networks of neurons. These models exhibit complex dynamics, and the parameters of the neurons and connections between neurons shape the model’s behaviour. Due to the model complexity, running the simulations and fitting the model to experimental data can be computationally demanding. In this study, we apply metamodelling techniques, data-driven approximations that are much faster to run, to two different signals generated by a two-population recurrent network model, the population spiking activities and the local field potential (LFP). Further, we invert the metamodels, and demonstrate that it can reliably find the different combinations of parameters that can give rise to an observed simulation output. We compare the metamodels on both the forward and inverse problem, and investigate to what degree the parameters are constrained by the two different signals.
Unravelling the impact of aging on the human endothelial lncRNA transcriptome
Authors: Drekolia Maria-Kyriaki , Talyan Sweta , Emidio Rebeca Cordellini , Boon Reinier Abraham , Guenther Stefan , Looso Mario , Dumbović Gabrijela , Bibli Sofia-Iris
Published: September 2022

The incidence and prevalence of cardiovascular disease is highest among the elderly. There is a need to further understand the mechanisms behind endothelial cell aging in order to achieve vascular rejuvenation and minimize the onset of age-related vascular diseases. Long non-coding RNAs (lncRNAs) have been proposed to regulate numerous processes in the human genome, yet their function in vascular aging and their therapeutic potential remain largely unknown. This is primarily because the majority of studies investigating the impact of aging on lncRNA expression heavily rely on in vitro studies based on replicative senescence. Here, using a unique collection of young and aged endothelial cells isolated from native human arteries, we sought to characterize the age-related alterations in lncRNA expression profiles. We were able to detect a total of 4463 lncRNAs expressed in the human endothelium from which ∼17% (798) were altered in advanced age. One of the most affected lncRNAs in aging was the primate-specific, Prostate Cancer Associated Transcript (PCAT) 14. In our follow up analysis, using single molecule RNA FISH, we showed that PCAT14 is relatively abundant, localized almost exclusively in the nucleus of young endothelial cells, and silenced in the aged endothelium. Functionally, our studies proposed that PCAT14 affects multiple endothelial cell functions including endothelial cell migration, sprouting and inflammatory responses. Taken together, our data highlight that endothelial cell aging correlates with altered expression of lncRNAs, which could impair the endothelial regenerative capacity and enhance inflammatory phenotypes.
The amyloid precursor protein regulates synaptic transmission at medial perforant path synapses
Authors: Lenz Maximilian , Eichler Amelie , Kruse Pia , Galanis Christos , Kleidonas Dimitrios , Jedlicka Peter , Müller Ulrike , Deller Thomas , Vlachos Andreas
Published: September 2022

The perforant path provides the main cortical excitatory input to the hippocampus. Due to its important role in information processing and coding, entorhinal projections to the dentate gyrus have been studied in considerable detail. Nevertheless, a characterization of synaptic transmission between individual connected pairs of entorhinal stellate cells and dentate granule cells is still pending. Here, we have used organotypic entorhino-hippocampal tissue cultures, in which the entorhino-dentate (EC-GC) projection is present and EC-GC pairs can be studied using whole-cell patch clamp recordings. Using cultures of wildtype mice, the properties of EC-GC synapses formed by afferents from the lateral and medial entorhinal cortex were compared and differences in short-term plasticity were revealed. Since the perforant path is severely affected in Alzheimer’s disease, we used cultures of APP-deficient mice to address the role of the amyloid-precursor protein (APP) at this synapse. APP-deficiency caused alterations in excitatory neurotransmission at medial perforant path synapses that were accompanied by transcriptomic and ultrastructural changes. Moreover, the deletion of pre- but not postsynaptic APP through the local injection of Cre-expressing AAVs in conditional APPflox/flox tissue cultures increased the efficacy of neurotransmission at perforant path synapses. Together, these data suggest a physiological role for presynaptic APP at medial perforant path synapses, which may be adversely affected under conditions of altered APP processing.
Substrate availability and not thermal-acclimation controls microbial temperature sensitivity response to long term warming
Authors: Domeignoz-Horta Luiz A. , Pold Grace , Erb Hailey , Sebag David , Verrecchia Eric , Northen Trent , Louie Katherine , Eloe-Fadrosh Emiley , Pennacchio Christa , Knorr Melissa A. , Frey Serita D. , Melillo Jerry M. , DeAngelis Kristen M.
Published: September 2022

Microbes are responsible for cycling carbon (C) through soils, and the predictions of how soil C stocks change with warming are highly sensitive to the assumptions made about the mechanisms controlling the microbial physiology response to climate warming. Two mechanisms, microbial thermal-acclimation and changes in the quantity and quality of substrates available for microbial metabolism have been suggested to explain the long-term warming impact on microbial physiology. Yet studies disentangling these two mechanisms are lacking. To resolve the drivers of changes in microbial physiology in response to long-term warming, we sampled soils from 13- and 28-year old soil warming experiments in different seasons. We performed short-term laboratory incubations across a range of temperatures to measure the relationship between temperature sensitivity of physiology (growth, respiration, carbon use efficiency and extracellular enzyme activity) and the chemical composition of soil organic matter. We observed apparent thermal acclimation in microbial processes important for C cycling, but only when warming had exacerbated the seasonally-induced, already small soil organic matter pools. Irrespective of warming, greater quantity and quality of soil carbon enhanced the extracellular enzymatic pool and its temperature sensitivity. We suggest that fresh litter input into the system seasonally cancels apparent thermal acclimation of C-cycling processes. Our findings reveal that long-term warming has indirectly affected microbial physiology via reduced C availability in this system, implying that earth system models including these negative feedbacks may be best suited to describe long-term warming impact in soils.
Accurate flux predictions using tissue-specific gene expression in plant metabolic modeling
Authors: Kaste Joshua A.M. , Shachar-Hill Yair
Published: September 2022

Motivation

The accurate prediction of complex phenotypes such as metabolic fluxes in living systems is a grand challenge for systems biology and central to efficiently identifying biotechnological interventions that can address pressing industrial needs. The application of gene expression data to improve the accuracy of metabolic flux predictions using mechanistic modeling methods such as Flux Balance Analysis (FBA) has not been previously demonstrated in multi-tissue systems, despite their biotechnological importance. We hypothesized that a method for generating metabolic flux predictions informed by relative expression levels between tissues would improve prediction accuracy.

Results

Relative gene expression levels derived from multiple transcriptomic and proteomic datasets were integrated into Flux Balance Analysis predictions of a multi-tissue, diel model of Arabidopsis thaliana’s central metabolism. This integration dramatically improved the agreement of flux predictions with experimentally based flux maps from 13C Metabolic Flux Analysis (MFA) compared with a standard parsimonious FBA approach. Disagreement between FBA predictions and MFA flux maps, as measured by weighted averaged percent error values, dropped from between 169-180% and 94-103% in high light and low light conditions, respectively, to between 10-12% and 9-11%, depending on the gene expression dataset used. The incorporation of gene expression data into the modeling process also substantially altered the predicted carbon and energy economy of the plant.

Availability

Code is available fromhttps://github.com/Gibberella/ArabidopsisGeneExpressionWeights

Contact

yairhill@msu.edu
Bridging The Evolving Semantics: A Data Driven Approach to Knowledge Discovery In Biomedicine
Authors: Jha Kishlay
Published: September 2022

Recent progress in biological, medical and health-care technologies, and innovations in wearable sensors provide us with unprecedented opportunities to accumulate massive data to understand disease prognosis and develop personalized treatments and interventions. These massive data supplemented with rapid growth in computing infrastructure has enabled bio-medical researchers to perform more comprehensive experiments and detailed case-studies. At the same time, performing these experiments are not only monetarily expensive but also time consuming. Thus, there is a growing need to provide tools to the researchers that will allow them to pose queries that will assist them in focusing on interesting “hypotheses”. However, such a tool would require capabilities to derive inferences based on existing known relationship between medical concepts. In this paper, we tackle this problem as one of non-factoid question answering wherein we try to answer the user-post questions by leveraging both authoritative as well as social media posts. While the former provides us with well knowledge on well researched topics, the latter provides us with real-time feedback on variety of topics like adverse drug effect (ADE), symptoms-drug relationship, etc. The challenge with leveraging the authoritative sources to infer answers for non-factoid question lies in: (a) The effective navigation of the answer search-space for timely response to the queries, (b) Ranking the candidate answers derived in step-(a) to enable non-trivial and novel discoveries, and (c) Being robust to perform confirmatory as well as discovery type of tasks.
Streamlined single-molecule RNA-FISH of core clock mRNAs in clock neurons in whole mount Drosophila brains
Authors: Yuan Ye , Padilla Marc-Antonio , Clark Dunham , Yadlapalli Swathi
Published: September 2022

Circadian clocks are ∼24-hour timekeepers that control rhythms in almost all aspects of our behavior and physiology. While it is well known that subcellular localization of core clock proteins plays a critical role in circadian regulation, very little is known about the spatiotemporal organization of core clock mRNAs and its role in generating ∼24-hr circadian rhythms. Here we describe a streamlined single molecule Fluorescence In Situ Hybridization (smFISH) protocol and a fully automated analysis pipeline to precisely quantify the number and subcellular location of mRNAs of Clock, a core circadian transcription factor, in individual clock neurons in whole mount Drosophila adult brains. Specifically, we used ∼48 fluorescent oligonucleotide probes that can bind to an individual Clock mRNA molecule, which can then be detected as a diffraction-limited spot. Further, we developed a machine learning-based approach for 3-D cell segmentation, based on a pretrained encoder-decoder convolutional neural network, to automatically identify the cytoplasm and nuclei of clock neurons. We combined our segmentation model with a spot counting algorithm to detect Clock mRNA spots in individual clock neurons. Our results demonstrate that the number of Clock mRNA molecules cycle in large ventral lateral clock neurons (lLNvs) with peak levels at ZT4 (4 hours after lights are turned on) with ~80 molecules/neuron and trough levels at ZT16 with ∼30 molecules/neuron. Our streamlined smFISH protocol and deep learning-based analysis pipeline can be employed to quantify the number and subcellular location of any mRNA in individual clock neurons in Drosophila brains. Further, this method can open mechanistic and functional studies into how spatiotemporal localization of clock mRNAs affect circadian rhythms.
Decomposing spatial heterogeneity of cell trajectories with Paella
Authors: Hou Wenpin , Ji Zhicheng
Published: September 2022

Spatial transcriptomics provides a unique opportunity to study continuous biological processes in a spatial context. We developed Paella, a computational method to decompose a cell trajectory into multiple spatial sub-trajectories and identify genes with differential temporal patterns across spatial sub-trajectories. Applied to spatial transcriptomics datasets of cancer, Paella identified spatially varying genes associated with tumor progression, providing insights into the spatial heterogeneity of cancer development.
The mitochondrial Cu+transporter PiC2 (SLC25A3) is a target of MTF1 and contributes to the development of skeletal musclein vitro
Authors: McCann Cat , Quinteros Michael , Adelugba Ifeoluwa , Morgada Marcos N. , Castelblanco Aida R. , Davis Emily J. , Lanzirotti Antonio , Hainer Sarah J. , Vila Alejandro J. , Navea Juan G. , Padilla-Benavides Teresita
Published: September 2022

The loading of copper (Cu) into cytochrome c oxidase (COX) in mitochondria is essential for energy production in cells. Extensive studies have been performed with mitochondrial cuproenzymes, such as Sco1, Sco2 and Cox17, which contributes to the metallation of the oxidase. However, limited information is available on the upstream mechanism of Cu transport and delivery to mitochondria, especially through Cu-impermeable membranes, in mammalian cells. The mitochondrial phosphate transporter SLC25A3, also known as PiC2, is also able to bind Cu+and acts as an active copper transporter in eukaryotic cells through these membranes, and ultimately aid in the metallation of COX. We used a well-established differentiation model of primary myoblasts derived from mouse satellite cells, where Cu availability is necessary for growth and maturation, and showed PiC2 is a target of MTF1, its expression is induced during myogenesis and favored by Cu supplementation. PiC2 deletion using CRISPR/Cas9 showed that the transporter is required for proliferation and differentiation of primary myoblasts, as both processes are delayed uponPiC2knock-out. The effects ofPiC2deletion were ameliorated by the addition of Cu to the growth medium, implying the deleterious effects ofPiC2knockout in myoblasts may be in part due to a failure to deliver sufficient Cu to the mitochondria, which can be compensated by other mitochondrial cuproproteins. Co-localization and co-immunoprecipitation of PiC2 and COX also strongly suggest that PiC2 may act to directly load Cu into COX, which was verified byin vitroCu+-transfer experiments. The data indicate an important role for PiC2 in both the delivery of Cu to the mitochondria, COX and, subsequently, the differentiation of primary myoblasts.
Activity in the human superior colliculus associated with reaching for tactile targets
Authors: Prabhu Nikhil G , Himmelbach Marc
Published: September 2022

The superior colliculus (SC) plays a major role in orienting movements of eyes and the head and in the allocation of attention. Functions of the SC have been mostly investigated in animal models, including non-human primates. Differences in the SC’s anatomy and function between different species question extrapolations of these studies to humans without further validation. Few electrophysiological and neuroimaging studies in animal models and humans have reported an unexpected role of the SC in visually guided reaching movements. Using BOLD fMRI imaging, we sought to decipher if the SC is also active during reaching movements guided by tactile stimulation. Participants executed reaching movements to visual and tactile target positions. When contrasted against visual and tactile stimulation without reaching, we found increased SC activity with reaching not only for visual but also for tactile targets. We conclude that the SC’s involvement in reaching does not rely on visual inputs. It is also independent from a specific sensory modality. Our results indicate a general involvement of the human SC in upper limb reaching movements.