bluuebunny/crossref_metadata_2025_split huggingface dataset:
Developmental and environmental plasticity in opsin gene expression in Lake Victoria cichlid fish
Authors: Irazábal-González Lucia , Wright Daniel Shane , Maan Martine 
Published: September 2021

AbstractIn many organisms, sensory abilities develop and evolve according to the changing demands of navigating, foraging and communication across different environments and life stages. Teleost fish inhabit heterogeneous light environments and exhibit a large diversity in visual system properties among species. Cichlids are a classic example of this diversity, generated by different tuning mechanisms that involve both genetic factors and phenotypic plasticity. Here, we document the developmental progression of visual pigment gene expression in Lake Victoria cichlids and test if these patterns are influenced by variation in light conditions. We reared two sister species of Pundamilia to adulthood in two distinct visual conditions that resemble the two light environments that they naturally inhabit in Lake Victoria. We also included interspecific first-generation hybrids. We then quantified (using RT-qPCR) the expression of the four Pundamilia opsins (SWS2B, SWS2A, RH2A and LWS) at 14 time points. We find that opsin expression profiles progress from shorter-wavelength sensitive opsins to longer-wavelength sensitive opsins with increasing age, in both species and their hybrids. The developmental trajectories of opsin expression also responded plastically to the visual conditions. Finally, we found subtle differences between reciprocal hybrids, possibly indicating parental effects and warranting further investigation. Developmental and environmental plasticity in opsin expression may provide an important stepping stone in the evolution of cichlid visual system diversity.Research highlightsIn Lake Victoria cichlid fish, expression levels of opsin genes (encoding visual pigments) differ between developmental stages and between experimental light treatments. This plasticity may contribute to the evolution of cichlid visual system diversity.
SHOOT: phylogenetic gene search and ortholog inference
Authors: Emms D.M. , Kelly S. 
Published: September 2021

AbstractDetermining the evolutionary relationships between genes is fundamental to comparative biological research. Here we present the phylogenetic search, SHOOT. SHOOT searches a user query sequence against a database of phylogenetic trees and returns a tree with the query sequence correctly placed within it. We show that SHOOT performs this analysis with comparable speed to a BLAST search. We demonstrate that SHOOT phylogenetic placements are as accurate as conventional tree inference and it can identify orthologs with high accuracy. In summary, SHOOT is a fast and accurate tool for phylogenetic analyses of novel query sequences. It is available online at www.shoot.bio.
Microtubule retrograde flow retains neuronal polarization in a fluctuating state
Authors: Schelski Max , Bradke Frank 
Published: September 2021

ABSTRACTIn developing vertebrate neurons, a neurite is formed by more than a hundred microtubules. While individual microtubules are dynamic, the microtubule array itself has been regarded as stationary. Using live cell imaging in combination with photoconversion techniques and pharmacological manipulations, we uncovered that the microtubule array flows retrogradely within neurites to the soma. This microtubule retrograde flow drives cycles of microtubule density, a hallmark of the fluctuating state before axon formation. Shortly after axon formation, microtubule retrograde flow slows down in the axon, which stabilizes microtubule density cycles and thereby functions as a molecular wedge to enable axon extension. We propose microtubule retrograde flow and its specific slowdown in the axon to be the long-sought mechanism to single one neurite out to drive neuronal polarization.
pSiteExplorer: Visualization of the mass spectrometric data underlying phospho-site quantification
Authors: Plank Michael J. 
Published: September 2021

AbstractMass spectrometry based phospho-proteomics is a widely used approach to assess protein phosphorylation. Intensities of phospho-peptide ions are obtained by integrating the MS signal over their chromatographic peaks. How individual peptide measurements mapping to the same phospho-site are combined for the quantification of the given site is, however, in most cases hidden from researchers conducting, reviewing, and reading these studies. I here describe pSiteExplorer, an R script that visualizes the peak intensities associated with phospho-sites in MaxQuant output tables. Barplots of MS intensities originating from phospho-peptides with distinct amino acid sequences due to missed cleavages, different numbers of phosphates and from all off-line chromatographic fractions and charge states are displayed. This tool will help gaining a deeper insight into phospho-site quantifications by contrasting individual and summed phospho-peptide intensities with the site-level values derived by MaxQuant. This will support the validation of quantification results, for example, for the selection of candidates for follow-up studies.
Engineering a thixotropic and biochemically tunable hyaluronan and collagen bioink for biofabrication of multiple tissue construct types
Authors: Aleman Julio , Sivakumar Hemamylammal , DePalma Thomas , Zhou Yu , Mazzocchi Andrea , Huntwork Richard Connor , Yoo KyungMin , Banks Surya , Clark Casey , Maycock Alexandra , Leaks Kalan , Enck Kevin , Opara Emmanuel C , Gatenholm Paul , Welker Mark , Soker Shay , Herberg Samuel , Criswell Tracy , Skardal Aleksander 
Published: September 2021

AbstractThe field of three-dimensional (3D) bioprinting has advanced rapidly in recent years. Significant reduction in the costs associated with obtaining functional 3D bioprinting hardware platforms is both a cause and a result of these advances. As such, there are more laboratories than ever integrating bioprinting methodologies into their research. However, there is a lack of standards in the field of biofabrication governing any requirements or characteristics to support cross-compatibility with biomaterial bioinks, hardware, and different tissue types. Here we describe a modular extracellular matrix (ECM) inspired bioink comprised of collagen and hyaluronic acid base components that: 1) employ reversible internal hydrogen bonding forces to generate thixotropic materials that dynamically reduce their elastic moduli in response to increased shear stress, thus enabling increased compatibility with printing hardware; and 2) modular addons in the form of chemically-modified fibronectin and laminin that when covalently bound within the bioink support a variety of tissue types, including liver, neural, muscle, pancreatic islet, and adipose tissue. These features aim to accelerate the deployment of such bioinks for tissue engineering of functional constructs in the hands of various end users.
Ear pinnae in a neotropical katydid (Orthoptera: Tettigoniidae) function as ultrasound guides for bat detection
Authors: Pulver Christian , Celiker Emine , Woodrow Charlie , Geipel Inga , Soulsbury Carl , Cullen Darron A. , Rogers Stephen M , Veitch Daniel , Montealegre-Z Fernando 
Published: September 2021

AbstractEarly predator detection is a key component of the predator-prey arms race, and has driven the evolution of multiple animal hearing systems. Katydids (Insecta) have sophisticated ears, each consisting of paired tympana on each foreleg that receive sound directly externally, and internally via a narrowing ear canal through the acoustic spiracle. These ears are pressure-time difference receivers capable of sensitive and accurate directional hearing across a wide frequency range, despite the small size of katydids. Many katydid species have cuticular pinnae which form cavities around the outer tympanal surfaces, but their function is unknown. We investigated pinnal function in the katydid Copiphora gorgonensis by combining experimental biophysics and numerical modelling using 3D ear geometries. Results show that the pinnae in C. gorgonensis do not assist in directional hearing for specific call frequencies, but instead pinnae act as ultrasound detector devices. Pinnae induced large sound pressure gains that enhanced sound detection at high ultrasonic frequencies (> 60 kHz), matching the echolocation range of co-occurring insectivorous bats. Comparing pinnal mechanics of sympatric katydid species supports these findings, and suggests that pinnae evolved in katydids primarily for enhanced predator detection. Audiograms (both behavioural and neural) and tympanal cavity resonances obtained from living specimens corroborate our findings.
Functional connectivity of fMRI using differential covariance predicts structural connectivity and behavioral reaction times
Authors: Chen Yusi , Bukhari Qasim , Lin Tiger W. , Sejnowski Terrence J. 
Published: September 2021

AbstractRecordings from resting state functional magnetic resonance imaging (rs-fMRI) reflect the influence of pathways between brain areas. A wide range of methods have been proposed to measure this functional connectivity (FC), but the lack of “ground truth” has made it difficult to systematically validate them. Most measures of FC produce connectivity estimates that are symmetrical between brain areas. Differential covariance (dCov) is an algorithm for analyzing FC with directed graph edges. Applied to synthetic datasets, dCov-FC was more effective than covariance and partial correlation in reducing false positive connections and more accurately matching the underlying structural connectivity. When we applied dCov-FC to resting state fMRI recordings from the human connectome project (HCP) and anesthetized mice, dCov-FC accurately identified strong cortical connections from diffusion Magnetic Resonance Imaging (dMRI) in individual humans and viral tract tracing in mice. In addition, those HCP subjects whose rs-fMRI were more integrated, as assessed by a graph-theoretic measure, tended to have shorter reaction times in several behavioral tests. Thus, dCov-FC was able to identify anatomically verified connectivity that yielded measures of brain integration causally related to behavior.
RORγt-Expressing Pathogenic CD4+T Cells Cause Brain Inflammation During Chronic Colitis
Authors: Mickael Michel Edwar , Bhaumik Suniti , Chakraborti Ayanabha , Umfress Alan , van Groen Thomas , Macaluso Matthew , Totenhagen John , Sorace Anna G , Bibb James A , Standaert David G , Basu Rajatava 
Published: September 2021

AbstractNeurobehavioral disorders and brain abnormalities have been extensively reported in both Crohn’s Disease (CD) and Ulcerative Colitis (UC) patients. However, the mechanism causing neuropathological disorders in inflammatory bowel disease (IBD) patients remains unknown. Studies have linked the Th17 subset of CD4+T cells to brain diseases associated with neuroinflammation and cognitive impairment, including multiple sclerosis (MS), ischemic brain injury and Alzheimer’s disease. To better understand how CD4+T lymphocytes, contribute to brain pathology in chronic intestinal inflammation, we investigated the development of brain inflammation in the T cell transfer model of chronic colitis. Our findings demonstrate that CD4+T cells infiltrate the brain of colitic Rag1-/- mice in proportional levels to colitis severity. Colitic mice developed hypothalamic astrogliosis that correlated with neurobehavioral disorders. Moreover, the brain-infiltrating CD4+T cells expressed Th17 cell transcription factor RORγt and displayed a pathogenic Th17 cellular phenotype similar to colonic Th17 cells. Adoptive transfer of RORγt-deficient naïve CD4+T cells failed to cause brain inflammation and neurobehavioral disorders in Rag1-/- recipients, with significantly less brain infiltration of CD4+T cells. These findings suggest that pathogenic RORγt+CD4+T cells that aggravate colitis migrate preferentially into the brain, contributing to brain inflammation and neurobehavioral disorders, thereby linking colitis severity to neuroinflammation.
Neural Networks for self-adjusting Mutation Rate Estimation when the Recombination Rate is unknown
Authors: Burger Klara Elisabeth , Pfaffelhuber Peter , Baumdicker Franz 
Published: September 2021

Estimating the mutation rate, or equivalently effective population size, is a common task in population genetics. If recombination is low or high, optimal linear estimation methods are known and well understood. For intermediate recombination rates, the calculation of optimal estimators is more challenging. As an alternative to model-based estimation, neural networks and other machine learning tools could help to develop good estimators in these involved scenarios. However, if no benchmark is available it is difficult to assess how well suited these tools are for different applications in population genetics.Here we investigate feedforward neural networks for the estimation of the mutation rate based on the site frequency spectrum and compare their performance with model-based estimators. For this we use the model-based estimators introduced by Fu, Futschik et al., and Watterson that minimize the variance or mean square error for no and free recombination. We find that neural networks reproduce these estimators if provided with the appropriate features and training sets. Remarkably, using the model-based estimators to adjust the weights of the training data, only one hidden layer is necessary to obtain a single estimator that performs almost as well as model-based estimators for low and high recombination rates, and at the same time provides a superior estimation method for intermediate recombination rates. We apply the method to simulated data based on the human chromosome 2 recombination map, highlighting its robustness in a realistic setting where local recombination rates vary and/or are unknown.
How important are functional and developmental constraints on phenotypic evolution? An empirical test with the stomatal anatomy of flowering plants
Authors: Muir Christopher D. , Conesa Miquel Àngel , Galmés Jeroni , Pathare Varsha S. , Rivera Patricia , Rodríguez Rosana López , Terrazas Teresa , Xiong Dongliang 
Published: September 2021

AbstractFunctional and developmental constraints on phenotypic variation may cause traits to covary over millions of years and slow populations from reaching their adaptive optima. Alternatively, trait covariation may result from selective constraint if some trait combinations are generally maladaptive. Quantifying the relative contribution of functional, developmental, and selective constraints on phenotypic variation is a longstanding goal of macroevolution, but it is often difficult to distinguish different types of constraints. The anatomy of leaves with stomata on both surfaces (amphistomatous) present a unique opportunity to test the importance of functional and developmental constraints on phenotypyic evolution. The key insight is that stomata on each leaf surface encounter the same functional and developmental constraints, but potentially different selective constraints because of leaf asymmetry in light capture, gas exchange, and other features. Independent evolution of stomatal traits on each surface imply that functional and developmental constraints alone likely do not explain trait covariance. Packing limits on how many stomata can fit into a finite epidermis and cell-size-mediated developmental integration are hypothesized to constrain variation in stomatal anatomy. The simple geometry of the planar leaf surface and knowledge of stomatal development make it possible to derive equations for phenotypic (co)variance caused by these constraints and compare them with data. We analyzed evolutionary covariance between stomatal density and length in amphistomatous leaves from 236 phylogenetically independent contrasts using a robust Bayesian model. Stomatal anatomy on each surface diverges partially independently, meaning that packing limits and developmental integration are not sufficient to explain phenotypic (co)variation. Hence, selective constraints, which require an adaptive explanation, likely contribute to (co)variation in ecologically important traits like stomata. We show how it is possible to evaluate the contribution of different constraints by deriving expected patterns of (co)variance and testing them using similar but separate tissues, organs, or sexes.
A molecular docking study of human STEAP2 for the discovery of new potential anti-prostate cancer chemotherapeutic candidates
Authors: Ongaba Timothy , Ndekezi Christian , Nakiddu Nana Jaqueline 
Published: September 2021

AbstractProstate cancer refers to uncontrolled abnormal cell growth (Cancer) within the prostate gland. The disease is a rising health concern and accounts for 3.8% of all cancer deaths globally. Uganda has one of the highest incidence rates of the disease in Africa being 5.2% and many of the diagnosed patients are found to have advanced stage prostate cancer. This study aimed to use STEAP2 protein (prostate cancer specific biomarker) for the discovery of new lead compounds against prostate cancer.To determine the most likely compound that can bind to STEAP2 protein, we docked the modelled STEAP2 3 Dimension structure against 2466 FDA (Food and Drug Administration) approved drug candidates using Autodock vina. Protein Basic Local Alignment Search Tool (BLASTp) search, Multiple Sequence Alignment (MSA), and phylogenetics were further carried out to analyse the diversity of this marker and determine its conserved domains as suitable target regions.Six promising drug candidates (ligands) were identified of which Triptorelin had the highest binding energy (-12.1 kcal/mol). Leuprolide was the second most promising candidate with a docking energy of -11.2 kcal/mol. All the top 3 of 6 drugs interacted with highly conserved residues Ser-372 and Gly-369 in close proximity with the iron binding domain that was shown to be important for catalysis of metal reduction.The two drugs had earlier been approved for treatment of advanced prostate cancer but with an elusive mode of action. Thanks to this study we now have an insight on how their interaction with STEAP2 might be important during treatment.Author summaryPrevious studies on prostate cancer prevalence have shown that Uganda among other low to middle income countries has a high prostate cancer incidence rate. Majority of the patients at the time of diagnosis have advanced stage disease. While there has been great improvement in therapeutic options for prostate cancer over the last decade, the drugs currently used are still limited and not 100% effective making cure elusive. This is further compounded by undesirable side-effects from some of the treatments. Altogether this creates a need for the discovery of novel, safe, and efficacious chemotherapeutic agents with minimal or no side effects. In this study, we used a prostate cancer specific protein biomarker; STEAP2 that is highly expressed at all disease stages and is androgen independent and FDA approved drugs from the drugbank to help improve drug specificity, efficacy, and reduce undesirable side effects throughin-silicomethods. The results from the study give an insight on mechanisms of action of current therapy for advanced disease and suggest these very drugs be used even at early stage disease.
MrParse: Finding homologues in the PDB and the EBI AlphaFold database for Molecular Replacement and more
Authors: Simpkin Adam J. , Thomas Jens M. H. , Keegan Ronan M. , Rigden Daniel J. 
Published: September 2021

AbstractCrystallographers have an array of search model options for structure solution by Molecular Replacement (MR). Well-established options of homologous experimental structures and regular secondary structure elements or motifs are increasingly supplemented by computational modelling. Such modelling may be carried out locally or use pre-calculated predictions retrieved from databases such as the EBI AlphaFold database. MrParse is a new pipeline to help streamline the decision process in MR by consolidating bioinformatic predictions in one place. When reflection data are provided, MrParse can rank any homologues found using eLLG which indicates the likelihood that a given search model will work in MR. In-built displays of predicted secondary structure, coiled-coil and transmembrane regions further inform the choice of MR protocol. MrParse can also identify and rank homologues in the EBI AlphaFold database, a function that will also interest other structural biologists and bioinformaticians.
Clinically Relevant Mathematical Model for the BCG-based Treatment Of Type 1 Diabetes
Authors: Lazebnik Teddy , Bunimovich-Mendrazitsky Svetlana , Kiselyov Alex 
Published: September 2021

AbstractThis work introduces a model of immunotherapy treatment, namely the Bacillus Calmette-Guerin (BCG) vaccine, of type 1 diabetes (T1D). The model takes into consideration a clinically relevant interaction network between multiple immune cells and compartments. A set of ordinary differential equations (ODEs) is introduced to capture the connectivity between these variables and clinical presentation of the disease. Four subsets of the T1D patients and healthy controls that exhibit normal and high-level glucose consumption are evaluated. The results that obtained for mice, suggest that BCG treatment of the T1D patients that follow healthy eating habits normalizes glucose to levels observed in non-diabetic controls. Furthermore, glucose consumption profoundly influences disease progression. The stable equilibrium state with constant glucose levels is not attainable without repeated BCG treatment. This outcome suggests that immunotherapy may modulate molecular and cellular manifestations of the disease but it does not eliminate T1D. Of note, our data indicate that the BCG immunotherapy treatment may benefit healthy controls on a high-glucose diet. One may speculate the preventive BCG treatment to provide long-term health benefits in this specific cohort.Author summaryWe proposed a clinically relevant mathematical model of Bacillus Calmette-Guerin (BCG) based immunotherapy for type 1 diabetes (T1D) treatment. The model shows that BCG treatment is able to delay the T1D effects and to provide long-term health benefits while it may modulate molecular and cellular manifestations of the disease but it does not eliminate T1D. The main advantage of the proposed model is the ability to personalize the treatment protocol according to the patient’s metabolism and diet.