bluuebunny/crossref_metadata_2025 huggingface dataset:
On-microscope staging of live cells reveals changes in the dynamics of transcriptional bursting during differentiation
Authors: Jeziorska D.M. , Tunnacliffe E.A.J. , Brown J.M. , Ayyub H. , Sloane-Stanley J. , Sharpe J.A. , Lagerholm B.C. , Babbs C. , Smith A.J.H. , Buckle V.J. , Higgs D.R.
Published: November 2021

Determining the mechanisms by which genes are switched on and off during development and differentiation is a key aim of current biomedical research. Gene transcription has been widely observed to occur in a discontinuous fashion, with short bursts of activity interspersed with longer periods of inactivity. It is currently not known if or how this dynamic behaviour changes as mammalian cells differentiate. To investigate this, using a newly developed on-microscope analysis, we monitored mouse α-globin transcription in live cells throughout sequential stages of erythropoiesis. We find that changes in the overall levels ofα-globin transcription are most closely associated with changes in the fraction of time a gene spends in the active transcriptional state. We identify differences in the patterns of transcriptional bursting throughout differentiation, with maximal transcriptional activity occurring in the mid-phase of differentiation. Early in differentiation, we observe increased fluctuation in the patterns of transcriptional activity whereas at the peak of gene expression, in early and intermediate erythroblasts, transcription appears to be relatively stable and efficient. Later during differentiation asα-globin expression declines, we again observed more variability in transcription within individual cells. We propose that the observed changes in transcriptional behaviour may reflect changes in the stability of enhancer-promoter interactions and the formation of active transcriptional compartments as gene expression is turned on and subsequently declines at sequential stages of differentiation.
Layer-specific developmentally precise axon targeting of transient suppressed-by-contrast retinal ganglion cells (tSbC RGCs)
Authors: Tien Nai-Wen , Badea Tudor C. , Kerschensteiner Daniel
Published: November 2021

The mouse retina encodes diverse visual features in the spike trains of more than 40 retinal ganglion cell (RGC) types. Each RGC type innervates a specific subset of the more than 50 retinorecipient brain areas. Our catalog of RGC types and feature representations is nearing completion. Yet, we know little about where specific RGC types send their information. Furthermore, the developmental strategies by which RGC axons choose their targets and pattern their terminal arbors remain obscure. Here we identify a genetic intersection (Cck-Cre and Brn3cCKOAP) that selectively labels transient Suppressed-by-Contrast (tSbC) RGCs, a member of an evolutionarily conserved functionally mysterious RGC subclass. We find that tSbC RGCs selectively innervate the dorsolateral and ventrolateral geniculate nuclei of the thalamus (dLGN and vLGN), the superior colliculus (SC), and the nucleus of the optic tract (NOT). They binocularly innervate dLGN and vLGN but project only contralaterally to SC and NOT. In each target, tSbC RGC axons occupy a specific sublayer, suggesting that they restrict their input to specific circuits. The tSbC RGC axons span the length of the optic tract by birth and remain poised there until they simultaneously innervate their four targets around postnatal day five. The tSbC RGC axons make no errors in choosing their targets and establish mature stratification patterns from the outset. This precision is maintained in the absence of Brn3c. Our results provide the first map of SbC inputs to the brain, revealing a narrow target set, unexpected laminar organization, target-specific binocularity, and developmental precision.

Significance statement

In recent years, we have learned a lot about the visual features encoded by retinal ganglion cells (RGCs), the eye’s output neurons. In contrast, we know little about where RGCs send their information and how RGC axons, which carry this information, target specific brain areas during development. Here, we develop an intersectional strategy to label a unique RGC type, the tSbC RGC, and map its projections. We find that tSbC RGC axons are highly selective. They innervate few retinal targets and restrict their arbors to specific sublayers within these targets. The selective tSbC RGC projection patterns develop synchronously and without trial and error, suggesting molecular determinism and coordination.
STAMP: Simultaneous Training and Model Pruning for Low Data Regimes in Medical Image Segmentation
Authors: Dinsdale Nicola K. , Jenkinson Mark , Namburete Ana I. L.
Published: November 2021

Acquisition of high quality manual annotations is vital for the development of segmentation algorithms. However, to create them we require a substantial amount of expert time and knowledge. Large numbers of labels are required to train convolutional neural networks due to the vast number of parameters that must be learned in the optimisation process. Here, we develop the STAMP algorithm to allow the simultaneous training and pruning of a UNet architecture for medical image segmentation with targeted channelwise dropout to make the network robust to the pruning. We demonstrate the technique across segmentation tasks and imaging modalities. It is then shown that, through online pruning, we are able to train networks to have much higher performance than the equivalent standard UNet models while reducing their size by more than 85% in terms of parameters. This has the potential to allow networks to be directly trained on datasets where very low numbers of labels are available.
Evidence for alternate stable states in an Ecuadorian Andean Cloud Forest
Authors: Mariscal Chávez Ana , Thomas Daniel Churchill , Haffenden Austin , Manobanda Rocío , Duvauchelle Laurence , Defas William , Chinchero Miguel Angel , Simba Danilo , Jaramillo Edison , Roy Bitty A. , Peck Mika
Published: November 2021

We analyzed a set of historical data from rapid vegetation inventories in a tropical montane cloud forest in northern Andean Ecuador. Trees in plots from several types of forest were counted and measured, including: (1) primary forest, including mature and recently closed-canopy sites and naturally formed gaps, (2) abandoned pasture, and (3) intensively-farmed sites. The goal of the study was to understand in a specific period of time the similarities and differences among natural and anthropogenic disturbances and their potential long term effect on the forest plant community. We found that mature and intermediate close canopy sites are similar. Also old forest is quite resilient to gap-forming disturbance. Natural gaps are quickly colonized by old-forest-associated plant species, and return to an old-forest-type community of trees in a short time. In contrast, forests regenerating from anthropogenic disturbance appear to have multiple possible states: some regenerating forest sites where the anthropogenic disturbance were low are coming to closely resemble old-forest-type communities, but some where the anthropogenic disturbance was intense appear to be changing in a very different direction, which does not resemble any other vegetation community type currently in the forest. A major predictor of present ecological state is the type of land use before reforestation: pastures can occasionally transition back to the pre-disturbance state of forest. More intensively used sites, many of which are abandoned sugar cane plantations, do not return to a pre-disturbance ecological state, instead forming a new and different kind of forest, dominated by a different community of trees. We examined tree-seedling communities to understand the trajectory of the forest into the future, and find that new forest types may be forming that do not resemble any existing associationsintensive agricultural sites. We also found that Los Cedros is extremely diverse in tree species. We estimate approximately 500 species of tree in only the small southeastern area of the reserve that has been explored scientifically. Additionally, the forest tree community shows extremely rapid distance decay (beta-diversity), approaching near complete turn-over in the limited spatial extent of the study. This suggests that hundreds of other tree species remain to be observed in the reserve, in addition to the 350+ that are directly observed in the present study, including new observations of species with IUCN threatened-endangered status. We also highlight the conservation value of Reserva Los Cedros, which has managed to reverse deforestation within its boundaries despite a general trend of extensive deforestation in the surrounding region, and to protect large, contiguous areas of highly-endangered Andean primary cloud forest habitat.
NODeJ: an ImageJ plugin for 3D segmentation of nuclear objects
Authors: Dubos Tristan , Poulet Axel , Thomson Geoffrey , Péry Emilie , Chausse Frédéric , Tatout Christophe , Desset Sophie , van Wolfswinkel Josien C. , Jacob Yannick
Published: November 2021

Background

The three-dimensional nuclear arrangement of chromatin impacts many cellular processes operating at the DNA level in animal and plant systems. Chromatin organization is a dynamic process that can be affected by biotic and abiotic stresses. Three-dimensional imaging technology allows to follow these dynamic changes, but only a few semi-automated processing methods currently exist for quantitative analysis of the 3D chromatin organization.

Results

We present an automated method, Nuclear Object DetectionJ (NODeJ), developed as an imageJ plugin. This program segments and analyzes high intensity domains in nuclei from 3D images. NODeJ performs a Laplacian convolution on the mask of a nucleus to enhance the contrast of intra-nuclear objects and allows their detection. We reanalyzed public datasets and determined that NODeJ is able to accurately identify heterochromatin domains from a diverse set of Arabidopsis thaliana nuclei stained with DAPI or Hoechst. NODeJ is also able to detect signals in nuclei from DNA FISH experiments, allowing for the analysis of specific targets of interest.

Conclusion and availability

NODeJ allows for efficient automated analysis of subnuclear structures by avoiding the semi-automated steps, resulting in reduced processing time and analytical bias. NODeJ is written in Java and provided as an ImageJ plugin with a command line option to perform more high-throughput analyses. NODeJ can be downloaded from https://gitlab.com/axpoulet/image2danalysis/-/releases with source code, documentation and further information avaliable at https://gitlab.com/axpoulet/image2danalysis. The images used in this study are publicly available at https://www.brookes.ac.uk/indepth/images/ and https://doi.org/10.15454/1HSOIE.
Neural tracking as a diagnostic tool to assess the auditory pathway
Authors: Gillis Marlies , Van Canneyt Jana , Francart Tom , Vanthornhout Jonas
Published: November 2021

When a person listens to sound, the brain time-locks to specific aspects of the sound. This is called neural tracking and it can be investigated by analysing neural responses (e.g., measured by electroencephalography) to continuous natural speech. Measures of neural tracking allow for an objective investigation of a range of auditory and linguistic processes in the brain during natural speech perception. This approach is more ecologically valid than traditional auditory evoked responses and has great potential for research and clinical applications. This article reviews the neural tracking framework and highlights three prominent examples of neural tracking analyses: neural tracking of the fundamental frequency of the voice (f0), the speech envelope and linguistic features. Each of these analyses provides a unique point of view into the human brain’s hierarchical stages of speech processing. F0-tracking assesses the encoding of fine temporal information in the early stages of the auditory pathway, i.e., from the auditory periphery up to early processing in the primary auditory cortex. Envelope tracking reflects bottom-up and top-down speechrelated processes in the auditory cortex and is likely necessary but not sufficient for speech intelligibility. Linguistic feature tracking (e.g. word or phoneme surprisal) relates to neural processes more directly related to speech intelligibility. Together these analyses form a multi-faceted objective assessment of an individual’s auditory and linguistic processing.
Allelic correlation is a marker of tradeoffs between barriers to transmission of expression variability and signal responsiveness in genetic networks
Authors: Boe Ryan H. , Ayyappan Vinay , Schuh Lea , Raj Arjun
Published: November 2021

Accurately functioning genetic networks should be responsive to signals but prevent transmission of stochastic bursts of expression. Existing data in mammalian cells suggests that such transcriptional “noise” is transmitted by some genes and not others, suggesting that noise transmission is tunable, perhaps at the expense of other signal processing capabilities.However, systematic claims about noise transmission in genetic networks have been limited by the inability to directly measure noise transmission. Here we build a mathematical framework capable of modeling allelic correlation and noise transmission. We find that allelic correlation and noise transmission correspond across a broad range of model parameters and network architectures. We further find that limiting noise transmission comes with the trade-off of being unresponsive to signals, and that within the parameter regimes that are responsive to signals, there is a further trade-off between response time and basal noise transmission. Using a published allele specific single cell RNA-sequencing dataset, we found that genes with high allelic odds ratios are enriched for cell-type specific functions, and that within multiple signaling pathways, factors which are upstream in the pathway have higher allelic odds ratios than downstream factors. Overall, our findings suggest that some degree of noise transmission is required to be responsive to signals, but that minimization of noise transmission can be accomplished by trading-off for a slower response time.
Host Induced Gene Silencing of theSclerotinia sclerotiorum ABHYDROLASE-3gene reduces disease severity inBrassica napus
Authors: Wytinck Nick , Ziegler Dylan J. , Walker Philip L. , Sullivan Daniel S. , Biggar Kirsten T. , Khan Deirdre , Sakariyahu Solihu K. , Wilkins Olivia , Whyard Steve , Belmonte Mark F.
Published: November 2021

Sclerotinia sclerotiorumis a pathogenic fungus that infects hundreds of crop species, causing extensive yield loss every year. Chemical fungicides are used to control this phytopathogen, but with concerns about increasing resistance and impacts on non-target species, there is a need to develop alternative control measures. In the present study, we engineeredBrassica napusto constitutively express a hairpin (hp)RNA molecule to silenceABHYRDOLASE-3inS. sclerotiorum. We demonstrate the potential for Host Induced Gene Silencing (HIGS) to protectB. napusfromS. sclerotiorumusing leaf, stem and whole plant infection assays. The interaction between the transgenic host plant and invading pathogen was further characterized at the molecular level using dual-RNA sequencing and at the anatomical level through microscopy to understand the processes and possible mechanisms leading to increased tolerance to this damaging necrotroph. We observed significant shifts in the expression of genes relating to plant defense as well as cellular differences in the form of structural barriers around the site of infection in the HIGS-protected plants. Our results provide proof-of-concept that HIGS is an effective means of limiting damage caused byS. sclerotiorumto the plant and demonstrates the utility of this biotechnology in the development of resistance against fungal pathogens.
Fitness costs associated with spinetoram resistance inSpodoptera frugiperdais driven by host plants
Authors: Kanno Rubens H. , Guidolin Aline S. , Padovez Fernando E. O. , Rodrigues Juliana G. , Omoto Celso
Published: November 2021

Insecticide resistance is usually associated with fitness costs. The magnitude of fitness costs is affected by environmental and ecological factors. Here, we explored how host plants could affect fitness costs associated with insecticide resistance. Initially, spinetoram-resistant (RR) and susceptible (SS) strains ofSpodoptera frugiperdawere selected using F2screen from a population collected in São Desidério, Bahia State, Brazil in 2018. Besides de RR and SS strains, fitness costs were also assessed for a heterozygous strain (RS). Life-history traits were evaluated to estimate population growth parameters of neonate larvae of each strain fed on corn, soybean and cotton plants. Compared to the SS strain, the relative fitness of the RR strain, based on intrinsic rate of population increase, was 1.06, 0.84 and 0.67 on plants of corn, soybean and cotton respectively. The relative fitness of the RS strain was similar to the SS strain regardless the host plant, suggesting a recessive fitness cost. No differences were found between the strains fed on corn plants. The larval development time was greater for RR strain fed on soybean and cotton plants compared to RS and SS strain. Low survival rate and fecundity of the RR strain were found when larvae fed on plants of soybean and cotton. The results of this study demonstrated that fitness costs of spinetoram resistance inS. frugiperdadepend strongly on the host plants thatS. frugiperdalarvae fed on. Such information can be used to design resistance management strategies considering the host plants of the agricultural landscape.

Key messages

The presence of fitness costs associated with resistance can be exploited in resistance management strategies.

Host plant influences the fitness costs associated with spinetoram resistance inS. frugiperda.

Information considering the host plants in an agricultural landscape is essential to design effective resistance management programs.
Staphylococcus aureus β-toxin exerts anti-angiogenic effects by inhibiting re-endothelialization and neovessel formation
Authors: Tran Phuong M. , Tang Sharon S. , Salgado-Pabón Wilmara
Published: November 2021

Staphylococcus aureus is the causative agent of numerous severe human infections associated with significant morbidity and mortality worldwide. S. aureus often targets the vascular endothelium to interfere with proper host responses during invasive infections. In this study, we provide evidence that S. aureus β-toxin inhibits wound repair mechanisms in human endothelial cells by preventing cell proliferation and migration. These findings were confirmed in a rabbit aortic explant model where β-toxin impedes sprout formation. Decreased cell proliferation was accompanied by decreased production of the angiogenic proteins endothelin-1, IGFBP-3, thrombospondin-1, TIMP-1, and TIMP-4. Meanwhile, inhibited wound repair was marked by increased HGF secretion from endothelial cells, likely a marker of endothelial cell damage. Together, these findings establish a mechanistic role for β-toxin where it inhibits proper tissue repair processes that likely promote S. aureus infective niche.
Noise in a metabolic pathway leads to persister formation in Mycobacterium tuberculosis
Authors: Quigley Jeffrey , Lewis Kim
Published: November 2021

Tuberculosis is difficult to treat due to dormant cells in hypoxic granulomas, and stochastically-formed persisters tolerant of antibiotics. Bactericidal antibiotics kill by corrupting their energy-dependent targets. We reasoned that noise in the expression of an energy-generating component will produce rare persister cells. In sorted low ATP M. tuberculosis grown on acetate there is considerable cell-to-cell variation in the level of mRNA coding for AckA, the acetate kinase. Quenching the noise by overexpressing ackA sharply decreases persisters, showing that it acts as the main persister gene under these conditions. This demonstrates that a low energy mechanism is responsible for the formation of M. tuberculosis persisters and suggests that the mechanism of their antibiotic tolerance is similar to that of dormant cells in a granuloma. Entrance into a low energy state driven by stochastic variation in expression of energy-producing enzymes is likely a general mechanism by which bacteria produce persisters.
Inhibitory co-transmission from midbrain dopamine neurons relies on presynaptic GABA uptake
Authors: Melani Riccardo , Tritsch Nicolas X.
Published: November 2021

Dopamine (DA)-releasing neurons in the substantia nigra pars compacta (SNcDA) inhibit target cells in the striatum through postsynaptic activation of γ-aminobutyric acid (GABA) receptors. However, the molecular mechanisms responsible for GABAergic signaling remain unclear, as SNcDA neurons lack enzymes typically required to produce GABA or package it into synaptic vesicles. Here we show that aldehyde dehydrogenase 1a1 (Aldh1a1), an enzyme proposed to function as a GABA synthetic enzyme in SNcDA neurons does not produce GABA for synaptic transmission. Instead, we demonstrate that SNcDA axons obtain GABA exclusively through presynaptic uptake using the membrane GABA transporter Gat1 (encoded by Slc6a1). GABA is then packaged for vesicular release using the vesicular monoamine transporter Vmat2. Our data therefore show that presynaptic transmitter recycling can substitute for de novo GABA synthesis and that Vmat2 contributes to vesicular GABA transport, expanding the range of molecular mechanisms available to neurons to support inhibitory synaptic communication.
HiCArch: A Deep Learning-based Hi-C Data Predictor
Authors: Zheng Xiao , Wang Jinghua , Wang Chaochen
Published: November 2021

Abstract

Hi-C sequencing analysis is one of the most popular methods to study three-dimensional (3D) genome structures, which affect the gene expression and other cellular activities by allowing distal regulations in spatial proximity. Hi-C sequencing analysis enhances understanding of chromatin functionality. However, due to the high cost of Hi-C sequencing, the publicly available Hi-C data of high resolutions (such as 10kb) are limited in only a few cell types. In this paper we present HiCArch, a light-weight deep neural network that predicts Hi-C contact matrices from 11 common 1D epigenomic features. HiCArch identifies topological associated domains (TADs) of 10kb resolution within the distance of 10Mb. HiCArch obtains train Pearson correlation score at 0.9123 and test Pearson correlation score at 0.9195 when trained on K562 cell line. which are significantly higher than previous approaches, such as HiC-Reg[1], Akita[2], DeepC[3], and Epiphany[4].
Intralocus sexual conflict can maintain alternative reproductive tactics
Authors: Gamble Madilyn Marisa , Calsbeek Ryan G
Published: November 2021

Alternative reproductive tactics (ARTs) are ubiquitous throughout the animal kingdom. Multiple mechanisms have been proposed to explain the maintenance of ARTs over time, including disruptive and negative frequency-dependent selection and female choice. However, these mechanisms focus exclusively on selection in the sex exhibiting the polymorphism, potentially limiting our understanding of the evolutionary causes and consequences of ARTs. Here we explore the role that intralocus sexual conflict may play in the maintenance of sex-specific ARTs. We use a genetically explicit individual-based model in which female fecundity and male tactic share a genetic architecture. By modeling ART maintenance under varying selection regimes and levels of sex-specific gene expression, we explore the conditions under which intralocus sexual conflict can maintain a hypothetical ART defined by two color morphs that depend on an underlying liability trait. Our models consistently revealed that sexual conflict can result in the persistence of a sex-specific polymorphism over hundreds of generations, even in the absence of negative frequency-dependent selection. ARTs were maintained through correlated selection when one male ART has lower fitness but produces daughters with higher fitness. Importantly, the maintenance of ARTs through sexual conflict resulted in a significant reduction in population growth rate, indicating that the evolutionary mechanism of ART maintenance can have broad ecological consequences. These results highlight the importance of understanding selection on both sexes when attempting to explain the maintenance of ARTs. Our results are consistent with a growing literature documenting genetic correlations between male ARTs and female fitness, suggesting that the maintenance of sex-specific ARTs through intralocus sexual conflict may be common and widespread in nature.
Synaptic Activity-Dependent Changes in the Hippocampal Palmitoylome
Authors: Nasseri Glory , Matin Nusrat , Tosefsky Kira , Stacey Greg , Flibotte Stephane , Hollman Rocio , Wild Angela R. , Foster Leonard J. , Bamji Shernaz X.
Published: November 2021

Dynamic protein S-palmitoylation is critical for neuronal function, development, and synaptic plasticity. Activity-dependent changes in palmitoylation have been observed for several neuronal substrates, however a full characterization of the activity-regulated palmitoylome is lacking. Here, we use an unbiased approach to identify differentially palmitoylated proteins in the mouse hippocampus following context-dependent fear conditioning. Of the 121 differentially palmitoylated proteins identified 63 were synaptic proteins, while others were associated with metabolic functions, cytoskeletal organization, and signal transduction. The vast majority of synaptic proteins exhibited increased palmitoylation following fear conditioning, whereas proteins that exhibited decreased palmitoylation were predominantly associated with metabolic processes. We show a link between dynamic palmitoylation and synapse plasticity by demonstrating that the palmitoylation of one of our identified proteins, PRG-1/LPPR4, is essential for activity-induced insertion of AMPA receptors into the postsynaptic membrane. Together, this study identifies networks of synaptic proteins whose dynamic palmitoylation may play a central role in learning and memory.

This study identifies networks of proteins that undergo dynamic post-translational palmitoylation in response to fear conditioning and demonstrates that palmitoylation of one of these proteins is essential for synapse plasticity. Together, this illustrates the importance of palmitoylation in learning/memory and synapse plasticity.
Identifying Microbial Interaction Networks Based on Irregularly Spaced Longitudinal 16S rRNA sequence data
Authors: Zhou Jie , Gui Jiang , Viles Weston D. , Chen Haobin , Madan Juliette C. , Coker Modupe O. , Hoen Anne G.
Published: November 2021

The microbial interactions within the human microbiome are complex and temporally dynamic, but few methods are available to model this system within a longitudinal network framework. Based on general longitudinal 16S rRNA sequence data, we propose a stationary Gaussian graphical model (SGGM) for microbial interaction networks (MIN) which can accommodate the possible correlations between the high-dimensional observations. For SGGM, an EM-type algorithm is devised to compute theL1-penalized maximum likelihood estimate of MIN which employs the classic graphical LASSO algorithm as the building block and can therefore be implemented easily. Simulation studies show that the proposed algorithms can significantly outperform the conventional algorithms when the correlations between measurements grow large. The algorithms are then applied to a real 16S rRNA gene sequence data set for gut microbiome. With the estimated MIN in hand, module-preserving permutation test is proposed to test the independence of the MIN and the corresponding phylogenetic tree. The results demonstrate strong evidence of an association between the MIN and the phylogenetic tree which indicates that the genetically related taxa tend to have more/stronger interactions. The proposed algorithms are implemented in R packagelglassoathttps://CRAN.R-project.org/package=lglasso.
Phenotype-Centric Modeling for Rational Metabolic Engineering
Authors: Valderrama-Gómez Miguel Á. , Savageau Michael A.
Published: November 2021

Phenotype-centric modeling enables a paradigm shift in the analysis of kinetic models. It brings the focus to a network’s biochemical phenotypes and their relationship with measurable traits (e.g., product yields, system dynamics, signal amplification factors, etc.) and away from computationally intensive parameter sampling and numerical simulation. Here, we explore applications of this new modeling strategy in the field of Rational Metabolic Engineering using the amorphadiene biosynthetic network as a case study. Our phenotype-centric approach not only identifies known beneficial intervention strategies for this network, but it also provides an understanding of mechanistic context for the validity of these predictions. Additionally, we propose a set of hypothetical strains with the potential to outperform reported production strains and enhance the mechanistic understanding of the amorphadiene biosynthetic network. We believe that phenotype-centric modeling can advance the field of Rational Metabolic Engineering by enabling the development of next generation kinetics-based algorithms and methods that do not rely ona prioriknowledge of kinetic parameters but allow a structured, global analysis of the design space of parameter values.
Life Strategies in Placozoa
Authors: Romanova Daria Y. , Nikitin Mikhail A. , Shchenkov Sergey V. , Moroz Leonid L.
Published: November 2021

Placozoans are essential reference species for understanding the origins and evolution of the animal organization. However, little is known about their life strategies in natural habitats. Here, by establishing long-term culturing for four species ofTrichoplaxandHoilungia, we extend our knowledge about feeding and reproductive adaptations relevant to their ecology and immune mechanisms. Three modes of population growth depended upon feeding sources, including induction of social behaviors and different reproductive strategies. In addition to fission, representatives of all haplotypes produced ‘swarmers,’ which could be formed from the lower epithelium (with greater cell- type diversity) as a separate asexual reproduction stage. In aging culture, we reported the formation of specialized structures (‘spheres’) from the upper cell layer as a part of the innate immune defense response with the involvement of fiber cells. Finally, we showed that regeneration could be a part of the adaptive reproductive strategies in placozoans and a unique model for regenerative biology in general.
A middle ground where executive control meets semantics: The neural substrates of semantic-control are topographically sandwiched between the multiple-demand and default-mode systems
Authors: Chiou Rocco , Jefferies Elizabeth , Duncan John , Humphreys Gina F. , Lambon Ralph Matthew A.
Published: November 2021

Semantic control is the capability to operate on meaningful representations, selectively focusing on certain aspects of meaning while purposefully ignoring other aspects based on one’s behavioural aim. This ability is especially vital for comprehending figurative/ambiguous language. It remains unclear, at the topographical level, why/how regions involved in semantic control seem reliably juxtaposed alongside other functionally specialised regions in the association cortex. We investigated this issue by characterising how semantic control regions topographically relate to the default-mode network (associated with memory and abstract cognition) and multiple-demand network (associated with executive control). Topographically, we confirmed that semantic control areas were sandwiched by the default-mode and multi-demand networks, forming an orderly arrangement observed both at the individual- and group-level. Functionally, semantic control regions exhibited ‘hybrid’ responses, fusing a preference for cognitively demanding processing (multiple-demand) and a preference for meaningful representations (default-mode) into a domain-specific preference for difficult operations on meaningful representations. When projected onto the principal gradient of human connectome, the neural activity of semantic control showed a robustly dissociable trajectory from visuospatial control, implying different roles in the functional transition from sensation to cognition. We discuss why the hybrid functional profile of semantic control regions might result from their intermediate topographical positions.
Experimental analysis and biaxial biomechanical behaviour of ex-vivo sheep trachea
Authors: Nemavhola Fulufhelo , Ngwangwa Harry , Pandelani Thanyani
Published: November 2021

Purpose

The purpose of this study is to investigate the mechanical behaviour of the tracheal tissue under biaxial tensile loading. Furthermore, the study examines the material properties of the tissue through a study of the model parameters for six constitutive models.

Materials and methods

The fourteen (n = 13) trachea sheep (Vleis Merino) pieces of tissues measured to be ~ 30 × 20 mm where only the effective area subjected to engineering strain was ~ 25 × 16 mm. In this study, we assume that the tracheal tissue is anisotropic and incompressible, therefore we apply and study the material parameters from six models namely the Fung, Choi-Vito, Holzapfel (2000), Holzapfel (2005), Polynomial (Anisotropic) and Four-Fiber Family models.

Results

The results show that the trachea tissue is twice as stiff along the circumferential direction as it is along the longitudinal direction. It is also observed that the material properties are different (non-homogeneous) along the trachea.

Conclusions

The findings of this study will benefit computational models for the study of tracheal diseases or injuries. Furthermore, these findings will assist in the development of regenerative medicine for different tracheal pathologies and in the bioengineering of replacement tissue in cases of damage.
A chemical-genetic map of the pathways controlling drug potency in Mycobacterium tuberculosis
Authors: Li Shuqi , Poulton Nicholas C. , Chang Jesseon S. , Azadian Zachary A. , DeJesus Michael A. , Ruecker Nadine , Zimmerman Matthew D. , Eckartt Kathryn , Bosch Barbara , Engelhart Curtis , Sullivan Daniel , Gengenbacher Martin , Dartois Véronique A. , Schnappinger Dirk , Rock Jeremy M.
Published: November 2021

Mycobacterium tuberculosis (Mtb) infection is notoriously difficult to treat. Treatment efficacy is limited by Mtb’s intrinsic drug resistance, as well as its ability to evolve acquired resistance to all antituberculars in clinical use. A deeper understanding of the bacterial pathways that govern drug efficacy could facilitate the development of more effective therapies to overcome resistance, identify new mechanisms of acquired resistance, and reveal overlooked therapeutic opportunities. To define these pathways, we developed a CRISPR interference chemical-genetics platform to titrate the expression of Mtb genes and quantify bacterial fitness in the presence of different drugs. Mining this dataset, we discovered diverse and novel mechanisms of intrinsic drug resistance, unveiling hundreds of potential targets for synergistic drug combinations. Combining chemical-genetics with comparative genomics of Mtb clinical isolates, we further identified numerous new potential mechanisms of acquired drug resistance, one of which is associated with the emergence of a multidrug-resistant tuberculosis (TB) outbreak in South America. Lastly, we make the unexpected discovery of an “acquired drug sensitivity.” We found that the intrinsic resistance factor whiB7 was inactivated in an entire Mtb sublineage endemic to Southeast Asia, presenting an opportunity to potentially repurpose the macrolide antibiotic clarithromycin to treat TB. This chemical-genetic map provides a rich resource to understand drug efficacy in Mtb and guide future TB drug development and treatment.
α-Helix stabilization by co-operative side chain charge-reinforced interactions to phosphoserine in a basic kinase-substrate motif
Authors: Batchelor Matthew , Dawber Robert S. , Wilson Andrew J. , Bayliss Richard
Published: November 2021

How cellular functions are regulated through protein phosphorylation events that promote or inhibit protein–protein interactions (PPIs) is key to understanding regulatory molecular mechanisms. Whilst phosphorylation can orthosterically or allosterically influence protein recognition, phospho-driven changes in the conformation of recognition motifs are less well explored. We recently discovered that clathrin heavy chain recognises phosphorylated TACC3 through a helical motif that, in the unphosphorylated protein, is disordered. However, it was unclear whether and how phosphorylation could stabilize a helix in a broader context. In the current manuscript, we address this challenge using poly-Ala based model peptides and a suite of circular dichroism and nuclear magnetic resonance spectroscopies. We show that phosphorylation of a Ser residue stabilizes the α-helix in the context of an Arg(i – 3)pSeri Lys(i + 4) triad through charge-reinforced side chain interactions with positive co-operativity, whilst phosphorylation of Thr induces an opposing response. This is significant as it may represent a general method for control of PPIs by phosphorylation; basic kinase-substrate motifs are common with 55 human protein kinases recognising an Arg at a position –3 from the phosphorylated Ser, whilst the Arg(i – 3)pSeri Lys(i + 4) is a motif found in over 2000 human proteins.
Isolation of a Bacillus safensis from mine tailings in Peru, genomic characterization and characterization of its cyanide-degrading enzyme CynD
Authors: Arevalo Santiago Justo , Sifuentes Daniela Zapata , Portocarrero Andrea Cuba , Reategui Michella Brescia , Pimentel Claudia Monge , Martins Layla Farage , Pierry Paulo Marques , Piroupo Carlos Morais , Santa Cruz Alcides Guerra , Aguilar Mauro Quiñones , Farah Chuck Shaker , Setubal João Carlos , da Silva Aline Maria
Published: November 2021

Cyanide is widely used in industry as a potent lixiviant due to its capacity to tightly bind metals. This property imparts cyanide enormous toxicity to all known organisms. Thus, industries that utilize this compound must reduce its concentration in recycled or waste waters. Physical, chemical, and biological treatments have been used for cyanide remediation; however, none of them meet all the desired characteristics: efficiency, low cost and low environmental impact. A better understanding of metabolic pathways and biochemistry of enzymes involved in cyanide degradation is a necessary step to improve cyanide bioremediation efficacy to satisfy the industry requirements. Here, we used several approaches to explore this topic. We have isolated three cyanide-degrading Bacillus strains from water in contact with mine tailings from Lima, Peru, and classified them as Bacillus safensis PER-URP-08, Bacillus licheniformis PER-URP-12, and Bacillus subtilis PER-URP-17 based on 16S rRNA gene sequencing and core genome analyses. Additionally, core genome analyses of 132 publicly available genomes of Bacillus pumilus group including B. safensis and B. altitudinis allowed us to reclassify some strains and identify two strains that did not match with any known species of the Bacillus pumilus group. We searched for possible routes of cyanide-degradation in the genomes of these three strains and identified putative B. licheniformis PER-URP-12 and B. subtilis PER-URP-17 rhodaneses and B. safensis PER-URP-08 cyanide dihydratase (CynD) sequences possibly involved cyanide degradation. We identified characteristic C-terminal residues that differentiate CynD from B. pumilus and B. safensis, and showed that, differently from CynD from B. pumilus C1, recombinant CynD from the Bacillus safensis PER-URP-08 strain remains active up to pH 9 and presents a distinct oligomerization pattern at pH 8 and 9. Moreover, transcripts of B. safensis PER-URP-08 CynD (CynDPER-URP-08) are strongly induced in the presence of cyanide. Our results warrant further investigation of B. safensis PER-URP-08 and CynDPER-URP-08 as potential tools for cyanide-bioremediation.
OViTAD: Optimized Vision Transformer to Predict Various Stages of Alzheimer's Disease Using Resting-State fMRI and Structural MRI Data
Authors: Sarraf Saman , Sarraf Arman , DeSouza Danielle D. , Anderson John A. E. , Kabia Milton , ADNI The Alzheimer's Disease Neuroimagin
Published: November 2021

Advances in applied machine learning techniques for neuroimaging have encouraged scientists to implement models to diagnose brain disorders such as Alzheimer′s disease at early stages. Predicting the exact stage of Alzheimer′s disease is challenging; however, complex deep learning techniques can manage this with precision. While successful, these complex architectures are difficult to interrogate and computationally expensive. Therefore, using novel, simpler architectures with more efficient pattern extraction capabilities, such as transformers, is of interest to neuroscientists. This study introduced an optimized vision transformer architecture to predict the group membership by separating healthy adults, mild cognitive impairment, and Alzheimer′s′ brains within the same age group (>75 years) using resting-state functional (rs-fMRI) and structural magnetic resonance imaging (sMRI) data. Our optimized architecture known as OViTAD is currently the sole vision transformer-based end-to-end pipeline and outperformed the existing transformer models and most state-of-the-art solutions. Our model achieved F1-scores of 97%±0.0 and 99.55%±0.39 from the testing sets for the rs-fMRI and sMRI modalities in the triple-class prediction experiments. Furthermore, our model reached these performances using 30% fewer parameters than a vanilla transformer. The model was robust and repeatable, producing similar estimates across three runs (we reported the averaged evaluation metrics). Finally, to challenge the model, we observed how it handled increasing noise levels by inserting varying numbers of healthy brains into the two dementia groups. Our findings suggest that optimized vision transformers are a promising and exciting new approach for neuroimaging applications, especially for Alzheimer′s disease prediction.
RNA Profiling of Neuropathic Pain-Associated Human DRGs Reveal Sex-differences in Neuro-immune Interactions Promoting Pain
Authors: Ray Pradipta R. , Shiers Stephanie , Tavares-Ferreira Diana , Sankaranarayanan Ishwarya , Uhelski Megan L. , Li Yan , North Robert Y. , Tatsui Claudio , Dussor Gregory , Burton Michael D. , Dougherty Patrick M. , Price Theodore J.
Published: November 2021

Neuropathic pain is a leading cause of high impact pain, is often disabling and is poorly managed by current therapeutics. Here we focused on a unique group of neuropathic pain patients undergoing thoracic vertebrectomy where the DRG is removed as part of the surgery allowing for molecular characterization and identification of mechanistic drivers of neuropathic pain independently of preclinical models. Our goal was to quantify whole transcriptome RNA abundances using RNA-seq in pain-associated human DRGs from these patients, allowing comprehensive identification of molecular changes in these samples by contrasting them with non-pain associated DRGs. We sequenced 70 human DRGs, including over 50 having mRNA libraries with neuronal mRNA. Our expression analysis revealed profound sex differences in differentially expressed genes including increase ofIL1B,TNF,CXCL14, andOSMin male and includingCCL1,CCL21,PENKandTLR3in female DRGs associated with neuropathic pain. Co-expression modules revealed enrichment in members of JUN-FOS signaling in males, and centromere protein coding genes in females. Neuro-immune signaling pathways revealed distinct cytokine signaling pathways associated with neuropathic pain in males (OSM, LIF, SOCS1) and females (CCL1, CCL19, CCL21). We validated cellular expression profiles of a subset of these findings using RNAscopein situhybridization. Our findings give direct support for sex differences in underlying mechanisms of neuropathic pain in patient populations.
Identification of bacteria by poly-aromatic hydrocarbons biosensors
Authors: Shlosberg Yaniv , Farber Yair , Hasson Salah , Bulatov Valery , Schechter Israel
Published: November 2021

Human health is consistently threatened by different species of pathogenic bacteria. To fight the spread of diseases, it is important to develop rapid methods for bacterial identification. Over the years, different kinds of biosensors were developed for this cause. Another environmental risk are poly-aromatic hydrocarbons (PAHs) that may be emitted from industrial facilities and pollute environmental water and soil. One of the methods for their purification is conducted by the addition of bacteria that can degrade the PAHs, while the bacteria itself can be filtrated at the end of the process. Although many studies reported monitoring of the PAHs degradation by fluorescence, not much attention was dedicated to studying the influence of the PAHs on the intrinsic fluorescence of the degrading bacteria. In this work, we apply synchronous fluorescence (SF) measurements to study the ability of the 5 PAHs: 9-Antracene carboxylic acid (9ACA), Pyrene, Perylene, Pentacene, and Chrysene to interact with bacteria and change its fluorescence spectra. We show that upon incubation of each PAH with the bacterium E.coli only the 2 PAHs 9ACA and Perylene cause an intensity decrease in the emission at λ = 300 – 375 nm, which derives from the emission of Tyrosine and Tryptophane (TT). Also, we show that upon incubation of 9ACA and Perylene with 5 different pathogenic bacteria, the intensity increase or decrease in the TT emission is unique to each bacterial species. Based on this observation, we suggest that the PAHs 9ACA and Perylene can be utilized as biosensors for bacterial identification.
Genome assembly of Danaus chrysippus and comparison with the Monarch Danaus plexippus
Authors: Singh Kumar Saurabh , De-Kayne Rishi , Omufwoko Kennedy Saitoti , Martins Dino J. , Bass Chris , ffrench-Constant Richard , Martin Simon H.
Published: November 2021

Milkweed butterflies in the genus Danaus are studied in a diverse range of research fields including the neurobiology of migration, biochemistry of plant detoxification, host-parasite interactions, evolution of sex chromosomes, and speciation. We have assembled a nearly chromosomal genome for Danaus chrysippus (known as the African Monarch, African Queen, and Plain Tiger) using long read sequencing data. This species is of particular interest for the study of genome structural change and its consequences for evolution. Comparison with the genome of the North American Monarch Danaus plexippus reveals generally strong synteny, but highlights three inversion differences. The three chromosomes involved were previously found to carry peaks of intra-specific differentiation in D. chrysippus in Africa, suggesting that these inversions may be polymorphic and associated with local adaptation. The D. chrysippus genome is over 40% larger than that of D. plexippus, and nearly all of the additional ∼100 Megabases of DNA comprises repeats. Future comparative genomic studies within this genus will shed light on the evolution of genome architecture.