bluuebunny/crossref_metadata_2025_split huggingface dataset:
Perturbations both trigger and delay seizures due to generic properties of slow-fast relaxation oscillators
Authors: Pérez-Cervera Alberto , Hlinka Jaroslav 
Published: December 2020

AbstractThe mechanism underlying the emergence of seizures is one of the most important unresolved issues in epilepsy research. In this paper, we study how perturbations, exogenous of endogenous, may promote or delay seizure emergence. To this aim, due to the increasingly adopted view of epileptic dynamics in terms of slow-fast systems, we perform a theoretical analysis of the phase response of a generic relaxation oscillator. As relaxation oscillators are effectively bistable systems at the fast time scale, it is intuitive that perturbations of the non-seizing state with a suitable direction and amplitude may cause an immediate transition to seizure. By contrast, and perhaps less intuitively, smaller amplitude perturbations have been found to delay the spontaneous seizure initiation. By studying the isochrons of relaxation oscillators, we show that this is a generic phenomenon, with the size of such delay depending on the slow flow component. Therefore, depending on perturbation amplitudes, frequency and timing, a train of perturbations causes an occurrence increase, decrease or complete suppression of seizures. This dependence lends itself to analysis and mechanistic understanding through methods outlined in this paper. We illustrate this methodology by computing the isochrons, phase response curves and the response to perturbations in several epileptic models possessing different slow vector fields. While our theoretical results are applicable to any planar relaxation oscillator, in the motivating context of epilepsy they elucidate mechanisms of triggering and abating seizures, thus suggesting stimulation strategies with effects ranging from mere delaying to full suppression of seizures.Author summaryDespite its simplicity, the modelling of epileptic dynamics as a slow-fast transition between low and high activity states mediated by some slow feedback variable is a relatively novel albeit fruitful approach. This study is the first, to our knowledge, characterizing the response of such slow-fast models of epileptic brain to perturbations by computing its isochrons. Besides its numerical computation, we theoretically determine which factors shape the geometry of isochrons for planar slow-fast oscillators. As a consequence, we introduce a theoretical approach providing a clear understanding of the response of perturbations of slow-fast oscillators. Within the epilepsy context, this elucidates the origin of the contradictory role of interictal epileptiform discharges in the transition to seizure, manifested by both pro-convulsive and anti-convulsive effect depending on the amplitude, frequency and timing. More generally, this paper provides theoretical framework highlighting the role of the of the slow flow component on the response to perturbations in relaxation oscillators, pointing to the general phenomena in such slow-fast oscillators ubiquitous in biological systems.
Lactate receptor HCAR1 regulates neurogenesis and microglia activation after neonatal hypoxia-ischemia
Authors: Kennedy Lauritz H. , Glesaaen Emilie R. , Palibrk Vuk , Pannone Marco , Wang Wei , Al-Jabri Ali H.J. , Suganthan Rajikala , Meyer Niklas , Lin Xiaolin , Bergersen Linda H. , Bjørås Magnar , Rinholm Johanne E. 
Published: December 2020

AbstractNeonatal cerebral hypoxia-ischemia (HI) is the leading cause of death and disability in newborns with the only current treatment option being hypothermia. An increased understanding of the pathways that facilitate tissue repair after HI can aid the development of better treatments. Here we have studied the role of lactate receptor HCAR1 (Hydroxycarboxylic acid receptor 1) in tissue repair after HI in mice. We show that HCAR1 knockout (KO) mice have reduced tissue regeneration compared with wildtype (WT) mice. Further, proliferation of neural progenitor cells and microglial activation were impaired after HI. Transcriptome analysis showed a strong transcriptional response to HI in the subventricular zone of WT mice involving about 7300 genes. In contrast, the HCAR1 KO mice showed a very modest response to HI, involving about 750 genes. Notably, fundamental processes involved in tissue repair such as cell cycle and innate immunity were dysregulated in HCAR1 KO. Taken together, our data suggest that HCAR1 is a key transcriptional regulator of the pathways that promote tissue regeneration after HI. Thus, HCAR1 could be a promising therapeutic target in the treatment of neonatal HI and other forms of brain ischemia.
Single-cell intracellular epitope and transcript detection revealing signal transduction dynamics
Authors: Rivello Francesca , van Buijtenen Erik , Matuła Kinga , van Buggenum Jessie A.G.L. , Vink Paul , van Eenennaam Hans , Mulder Klaas W. , Huck Wilhelm T. S. 
Published: December 2020

AbstractCurrent high-throughput single-cell multi-omics methods cannot concurrently map changes in (phospho)protein levels and the associated gene expression profiles. We present QuRIE-seq (Quantification of RNA and Intracellular Epitopes by sequencing) and use multi-factor omics analysis (MOFA+) to map signal transduction over multiple timescales. We demonstrate that QuRIE-seq can trace the activation of the B-cell receptor pathway at the minute and hour time-scale and provide insight into the mechanism of action of an inhibitory drug, Ibrutinib.
Oligodendrocytes depend on MCL-1 to prevent spontaneous apoptosis and white matter degeneration
Authors: Cleveland Abigail H. , Romero-Morales Alejandra , Azcona Laurent Alfonso , Herrero Melisa , Nikolova Viktoriya D. , Moy Sheryl , Elroy-Stein Orna , Gama Vivian , Gershon Timothy R. 
Published: December 2020

AbstractNeurologic disorders often disproportionately affect specific brain regions, and different apoptotic mechanisms may contribute to white matter pathology in leukodystrophies or gray matter pathology in poliodystrophies. We previously showed that neural progenitors that generate cerebellar gray matter depend on the anti-apoptotic protein BCL-xL. Conditional deletion ofBcl-xLin these progenitors produces spontaneous apoptosis and cerebellar hypoplasia, while similar conditional deletion ofMcl-1produces no phenotype. Here, we show that, in contrast, postnatal oligodendrocytes depend on MCL-1. We found that brain-wideMcl-1deletion caused apoptosis specifically in mature oligodendrocytes while sparing astrocytes and oligodendrocyte precursors, resulting in impaired myelination and progressive white matter degeneration. Disabling apoptosis through co-deletion ofBaxorBakrescued white matter degeneration, implicating the intrinsic apoptotic pathway inMcl-1-dependence.BaxandBakco-deletions rescued different aspects of theMcl-1-deleted phenotype, demonstrating their discrete roles in white matter stability. MCL-1 protein abundance was reduced ineif2b5-mutant mouse model of the leukodystrophy vanishing white matter disease (VWMD), suggesting the potential for MCL-1 deficiency to contribute to clinical neurologic disease. Our data show that oligodendrocytes require MCL-1 to suppress apoptosis, implicate MCL-1 deficiency in white matter pathology, and suggest apoptosis inhibition as a leukodystrophy therapy.
Deep learning enables rapid and robust analysis of fluorescence lifetime imaging in photon-starved conditions
Authors: Chen Yuan-I , Chang Yin-Jui , Liao Shih-Chu , Nguyen Trung Duc , Yang Jianchen , Kuo Yu-An , Hong Soonwoo , Liu Yen-Liang , Rylander H. Grady , Santacruz Samantha R. , Yankeelov Thomas E. , Yeh Hsin-Chih 
Published: December 2020

AbstractFluorescence lifetime imaging microscopy (FLIM) is a powerful tool to quantify molecular compositions and study the molecular states in the complex cellular environment as the lifetime readings are not biased by the fluorophore concentration or the excitation power. However, the current methods to generate FLIM images are either computationally intensive or unreliable when the number of photons acquired at each pixel is low. Here we introduce a new deep learning-based method termedflimGANE(fluorescence lifetimeimaging based onGenerativeAdversarialNetworkEstimation) that can rapidly generate accurate and high-quality FLIM images even in the photon-starved conditions. We demonstrated our model is not only 258 times faster than the most popular time-domain least-square estimation (TD_LSE) method but also provide more accurate analysis in barcode identification, cellular structure visualization, Förster resonance energy transfer characterization, and metabolic state analysis. With its advantages in speed and reliability,flimGANEis particularly useful in fundamental biological research and clinical applications, where ultrafast analysis is critical.
Long-term persistence of crAss-like phage crAss001 is associated with phase variation inBacteroides intestinalis
Authors: Shkoporov Andrey N. , Khokhlova Ekaterina V. , Stephens Niamh , Hueston Cara , Seymour Samuel , Hryckowian Andrew J. , Scholz Dimitri , Ross R. Paul , Hill Colin 
Published: December 2020

AbstractThe crAss-like phages are ubiquitous and highly abundant members of the human gut virome that infect commensal bacteria of the order Bacteroidales. Although incapable of classical lysogeny, these viruses demonstrate unexplained long-term persistence in the human gut microbiome, dominating the virome in some individuals. Here we demonstrate that rapid phase variation of alternate capsular polysaccharides plays an important role in dynamic equilibrium between phage sensitivity and resistance inB. intestinaliscultures, allowing phage and bacteria to multiply in parallel. The data also suggests the role of concomitant phage persistence mechanisms associated with delayed lysis of infected cells, such as carrier state infection. From an ecological and evolutionary standpoint this type of phage-host interaction is consistent with the Piggyback-the-Winner model, which suggests a preference towards lysogenic or other “benign” forms of phage infection when the host is stably present at high abundance.TeaserCrAss-like phage persistence inBacteroidesis associated with capsule phase-variation and additional unexplored mechanisms.
The Crystal Structures of Bacillithiol Disulfide Reductase YpdA Reveal Structural and Functional Insight into a New Type of FAD-Containing NADPH-Dependent Oxidoreductases
Authors: Hammerstad Marta , Gudim Ingvild , Hersleth Hans-Petter 
Published: December 2020

AbstractLow G+C Gram-positive Firmicutes, such as the clinically important pathogensStaphylococcus aureusandBacillus cereus,use the low-molecular weight (LMW) thiol bacillithiol (BSH) as a defense mechanism to buffer the intracellular redox environment and counteract oxidative stress encountered by human neutrophils during infections. The protein YpdA has recently been shown to function as an essential NADPH-dependent reductase of oxidized bacillithiol disulfide (BSSB) resulting from stress responses and is crucial in maintaining the reduced pool of BSH and cellular redox balance. In this work, we present the first crystallographic structures of YpdAs, namely fromS. aureusandB. cereus.Our analyses reveal a uniquely organized biological tetramer; however, the monomeric subunit has high structural similarity to other flavin disulfide reductases. The absence of a redox active cysteine in the vicinity of the FAD isoalloxazine ring implies a new direct disulfide reduction mechanism, which is backed by the presence of a potentially gated channel, serving as a putative binding site for BSSB in proximity to the FAD cofactor. We also report enzymatic activity for both YpdAs, which along with the structures presented in this work provide important structural and functional insight into a new class of FAD-containing NADPH-dependent oxidoreductases, related to the emerging fight against pathogenic bacteria.
Spoken language comprehension activates the primary visual cortex
Authors: Seydell-Greenwald Anna , Wang Xiaoying , Newport Elissa , Bi Yanchao , Striem-Amit Ella 
Published: December 2020

AbstractPrimary visual cortex (V1) is generally thought of as a low-level sensory area that primarily processes basic visual features. However, in congenitally blind individuals, V1 is involved in language processing, with no evidence of major changes in anatomical connectivity that could explain this seemingly drastic functional change. This is at odds with current accounts of neural plasticity, which emphasize the role of connectivity and conserved function in determining a neural tissue’s role even after atypical early experiences. To reconcile what appears to be unprecedented functional reorganization with known accounts of plasticity limitations, we tested whether V1 also responds to spoken language in sighted individuals. Using fMRI, we found that V1 in normally sighted individuals was indeed activated by comprehensible speech as compared to a reversed speech control condition, in a left-lateralized and focal manner. Activation in V1 for language was also significant and comparable for abstract and concrete words, suggesting it was not driven by visual imagery. Last, this activation did not stem from increased attention to the auditory onset of words, excluding general attention accounts. Together these findings suggest that V1 responds to verbal information even in sighted individuals, potentially to predict visual input. This capability might be the basis for the strong V1 language activation observed in people born blind, re-affirming the notion that plasticity is guided by pre-existing connectivity and abilities in the typically developed brain.Significance statementHow flexible is the human brain? Studies of congenitally blind individuals showed that language activates the primary visual cortex. This has been interpreted as evidence for unprecedented functional plasticity from a low-level visual to a language area. To reconcile these findings with known limitations of plasticity based on intrinsic physiology and connectivity, we tested if similar activation can be found in sighted participants. We show that left-lateralized primary visual cortex is activated by spoken language comprehension in sighted individuals, . This suggests that plasticity even in complete blindness from birth is not limitless and is guided by pre-existing connectivity and abilities in the typically-developed brain.
A thermodynamic model of protein structure evolution explains empirical amino acid rate matrices
Authors: Norn Christoffer , André Ingemar , Theobald Douglas L. 
Published: December 2020

AbstractProteins evolve under a myriad of biophysical selection pressures that collectively control the patterns of amino acid substitutions. Averaged over time and across proteins, these evolutionary pressures are sufficiently consistent to produce global substitution patterns that can be used to successfully find homologues, infer phylogenies, and reconstruct ancestral sequences. Although the factors which govern the variation of protein substitution rates has received much attention, the influence of thermodynamic stability constraints remains unresolved. Here we develop a simple model to calculate amino acid rate matrices from evolutionary dynamics controlled by a fitness function that reports on the thermodynamic effects of amino acid mutations in protein structures. This hybrid biophysical and evolutionary model accounts for nucleotide transition/transversion rate bias, multi-nucleotide codon changes, the number of codons per amino acid, and thermodynamic protein stability. We find that our theoretical model accurately recapitulates the complex pattern of empirical rates observed in common global amino acid substitution matrices used in phylogenetics. These results suggest that selection for thermodynamically stable proteins, coupled with nucleotide mutation bias filtered by the structure of the genetic code, is the primary global driver behind the amino acid substitution patterns observed in proteins throughout the tree of life.
Molecular Transfer Model for pH effects on Intrinsically Disordered Proteins: Theory and Applications
Authors: Mugnai Mauro L. , Thirumalai D. 
Published: December 2020

AbstractWe present a theoretical method to study how changes in pH shape the heterogeneous conformational ensemble explored by intrinsically disordered proteins (IDPs). The theory is developed in the context of coarse-grained models, which enable a fast, accurate, and extensive exploration of conformational space at a given protonation state. In order to account for pH effects, we generalize the Molecular Transfer Model (MTM), in which conformations are re-weighted using the transfer free energy, which is the free energy necessary for bringing to equilibrium in a new environment a “frozen” conformation of the system. Using the semi-grand ensemble, we derive an exact expression of the transfer free energy, which amounts to the appropriate summation over all the protonation states. Because the exact result is computationally too demanding to be useful for large polyelectrolytes or IDPs, we introduce a mean-field (MF) approximation of the transfer free energy. Using a lattice model, we compare the exact and MF results for the transfer free energy and a variety of observables associated with the model IDP. We find that the precise location of the charged groups (the sequence), and not merely the net charge, determines the structural properties. We demonstrate that some of the limitations previously noted for MF theory in the context of globular proteins are mitigated when disordered polymers are studied. The excellent agreement between the exact and MF results poises us to use the method presented here as a computational tool to study the properties of IDPs and other biological systems as a function of pH.
Structure and dynamics of the ESX-5 type VII secretion system ofMycobacterium tuberculosis
Authors: Bunduc Catalin M. , Fahrenkamp Dirk , Wald Jiri , Ummels Roy , Bitter Wilbert , Houben Edith N.G. , Marlovits Thomas C. 
Published: December 2020

AbstractMycobacterium tuberculosiscauses one of the most important infectious diseases in humans, leading to 1.5 million deaths every year. Specialized protein transport systems, called type VII secretion systems (T7SSs), are central for its virulence, but also crucial for nutrient and metabolite transport across the mycobacterial cell envelope. Here we present the first structure of an intact T7SS inner membrane complex ofM. tuberculosis. We show how the 2.32 MDa, 165 transmembrane helices-containing ESX-5 assembly is restructured and stabilized as a trimer of dimers by the MycP5protease. A trimer of MycP5caps a central periplasmic dome-like chamber formed by three EccB5dimers, with the proteolytic sites facing towards the cavity. This chamber suggests a central secretion and processing conduit. Complexes without MycP5show disruption of the EccB5periplasmic assembly and increased flexibility, highlighting the importance of this component for complex integrity. Beneath the EccB5-MycP5chamber, dimers of the EccC5ATPase assemble into three four-transmembrane helix bundles, which together seal the potential central secretion channel. Individual cytoplasmic EccC5domains adopt two distinctive conformations, likely reflecting different secretion states. Our work suggests a novel mechanism of protein transport and provides a structural scaffold to aid drug development against the major human pathogen.
A multi-task deep-learning system for predicting membrane associations and secondary structures of proteins
Authors: Li Bian , Mendenhall Jeffrey , Capra John A. , Meiler Jens 
Published: December 2020

AbstractAccurate prediction of secondary structures and transmembrane segments is often the first step towards modeling the tertiary structure of a protein. Existing methods are either specialized in one class of proteins or developed to predict one type of 1D structural attributes (secondary structure, topology, or transmembrane segment). In this work, we develop a new method for simultaneous prediction of secondary structure, transmembrane segment, and transmembrane topology with no a priori assumption on the class of the input protein sequence. The new method, Membrane Association and Secondary Structures of Proteins (MASSP) predictor, uses multi-tiered neural networks that incorporate recent innovations in machine learning. The first tier is a multi-task multi-layer convolutional neural network (CNN) that learns patterns in image-like input position-specific-scoring matrices (PSSMs) and predicts residue-level 1D structural attributes. The second tier is a long short-term memory (LSTM) neural network that treats the predictions of the first tier from the perspective of natural language processing and predicts the class of the input protein sequence. We curated a non-redundant data set consisting of 54 bitopic, 241 multi-spanning TM-alpha, 77 TM-beta, and 372 soluble proteins, respectively for training and testing MASSP. For secondary structure prediction, the mean three-state accuracy (Q3) of MASSP is 0.830, better than the Q3 of PSIPRED (0.829) and that of SPINE-X (0.813) and substantially better than that of Jufo9D (0.762) and RaptorX-Property (0.741). The mean segment overlap score (SOV) of MASSP is 0.752, gaining at least 7.7% improvement over all the other four methods. For transmembrane topology prediction, MASSP has a performance comparable to OCTOPUS and substantially better than MEMSAT3 and TMHMM2 on TM-alpha proteins, and on TM-beta proteins, MASSP is significantly better than both BOCTOPUS2 and PRED-TMBB2. By integrating prediction of secondary structure and transmembrane segments in a deep-learning framework, MASSP improves performance over previous methods, has broader applicability, and enables proteome scale predictions.
Digestate as Biofertilizer for the Growth of Selected Vegetables and Illumina analysis of Associated Bacterial Community
Authors: Raymond F.C. , Buraimoh O.M. , Akerele O.S. , Ilori M.O. , Ogundipe O.T. 
Published: December 2020

ABSTRACTChemical content of crops above desirable level, high cost, in addition to land and water pollution is a major drawback of applying chemical fertilizers. In this study, Digestate was used as a biofertilizer for the growth of selected vegetables. Furthermore, Illumina platform was employed to unravel the bacteria community of the digestate.Corchorus olitorius,Amaranthus hybridus,Bot-celosia argentiaandTalinum triangularewere grown in 16 experimental pots for 35days using cured digestate. Soil treated with chemical fertilizer was used as a positive control while the soil without any fertilizer was used as a negative control. The plant height ofTalinum triangularefor soil treated with digestate was 23.5cm and 34cm by days 7 and 35 respectively after plant emergence.Corchorus olitoriushad stunted growth under same treatment. Whereas,Bot-celosia argentiaandAmaranthus hybridusgrew poorly on all treatments. The statistical analysis showed a significant difference (p≤0.05) betweenTalinum triangularegrown in soil treated with digestate (plant height = 23.50, plant number =10 at day 7) compared with those treated with NPK (plant height = 18.50, plant number = 6.50 at day 7). The plant height and number for untreated soil at day 7 were 10.90 and 5.0 respectively). The Illumina sequencing of the digestate revealed the presence of some beneficial soil bacteria includingClostridium, Bacillus, Pseudomonas, Actinobacteria,andMicrococcus. The presence of these bacteria known to be Nitrogen fixers and Phosphate solubilizers confer biofertilizer potential to the digestate.