bluuebunny/crossref_metadata_2025_split huggingface dataset:
Critical Residues of Gβγ for the interaction with the SNARE Complex
Authors: Mueller Benjamin K. , Kaya Ali I , Zurawski Zack , Yim Yun Young , Meiler Jens , Hamm Heidi E. 
Published: May 2020

AbstractThe mechanisms and regulation of neurotransmitter release is a complex process involving many co-factors and proteins. One critical interaction is the regulation of exocytosis when G-protein βγ (Gβγ) dimers bind to the soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) protein complex. The complex is comprised of N-ethylmaleimide-sensitive factor attachment protein-25 (SNAP-25), syntaxin 1A, and synaptobrevin. Herein we probe across the entire family of human Gβ and Gγ proteins for residues critical for the interaction with SNARE, by systematically screening peptide sequences for their ability to bind to tSNARE. The coiled-coil region of Gβγ showed high affinity to tSNARE, along with the propeller region of Gβ on the opposite side from the coiled-coil region. Peptides based on Gβ1γ2, shown to have high affinity to SNARE, tSNARE were screened further by alanine scanning to probe for residues critical for binding to tSNARE. Full length Gβ1γ2and SNARE were docked computationally using Rosetta, to examine the experimentally determined binding sites. Docking converged on two possible sites of interaction using two distinct regions of both Gβ1γ2and SNARE.
Clustering NMR: Machine learning assistive rapid (pseudo) two-dimensional relaxometry mapping
Authors: Peng Weng Kung 
Published: May 2020

AbstractLow-field nuclear magnetic resonance (NMR) relaxometry is an attractive approach for point-of-care testing medical diagnosis, industrial food science, andin situoil-gas exploration. One of the problem however is, the inherently long relaxation time of the (liquid) sample, (and hence low signal-to-noise ratio) causes unnecessarily long repetition time. In this work, we present a new class of methodology for rapid and accurate object classification using NMR relaxometry with the aid of machine learning. We demonstrate that the sensitivity and specificity of the classification is substantially improved with higher order of (pseudo)-dimensionality (e.g., 2D or multidimensional). This new methodology (termed as Clustering NMR) is extremely useful for rapid and accurate object classification (in less than a minute) using the low-field NMR.
Nature and effective range of non-cell autonomous activator and inhibitor peptides specifying plant stomatal patterning
Authors: Zeng Scott , Lo Emily K. W. , Hazelton Bryna J. , Morales Miguel F. , Torii Keiko U. 
Published: May 2020

SummaryStomata are epidermal valves that facilitate gas exchange between plants and their environment. Stomatal patterning is regulated by EPIDERMAL PATTERING FACTOR (EPF)-family of secreted peptides: EPF1 enforcing stomatal spacing, whereas EPF-LIKE9, also known as Stomagen, promoting stomatal development. It remains unknown, however, how far these signaling peptides act. Utilizing Cre-Lox recombination-based mosaic sectors that overexpress either EPF1 or Stomagen in Arabidopsis cotyledons, we reveal a range within the epidermis and across the cell layers in which these peptides influence patterns. To quantitatively determine their effective ranges, we developed a computational pipeline, SPACE (Stomata Patterning AutoCorrelation on Epidermis), that describes probabilistic two-dimensional stomatal distributions based upon spatial autocorrelation statistics used in Astrophysics. The SPACE analysis shows that, whereas both peptides act locally, the inhibitor, EPF1, exerts longer-range effects than the activator, Stomagen. Furthermore, local perturbation of stomatal development has little influence on global two-dimensional stomatal patterning. Our findings conclusively demonstrate the nature and extent of EPF peptides as non-cell autonomous local signals and provides a means to quantitatively characterize complex spatial patterns in development.Summary StatementNon-cell autonomous effects of activator and inhibitor peptides on 2-D spatial patterning of stomata were quantitatively characterized using chimeric sectors and a SPACE computational pipeline.
Functional and genetic markers of niche partitioning among enigmatic members of the human oral microbiome
Authors: Shaiber Alon , Willis Amy D. , Delmont Tom O. , Roux Simon , Chen Lin-Xing , Schmid Abigail C. , Yousef Mahmoud , Watson Andrea R. , Lolans Karen , Esen Özcan C. , Lee Sonny T. M. , Downey Nora , Morrison Hilary G. , Dewhirst Floyd E. , Mark Welch Jessica L. , Eren A. Murat 
Published: May 2020

AbstractMicrobial residents of the human oral cavity have long been a major focus of microbiology due to their influence on host health and their intriguing patterns of site specificity amidst the lack of dispersal limitation. Yet, the determinants of niche partitioning in this habitat are yet to be fully understood, especially among the taxa that belong to recently discovered branches of microbial life. Here we assembled metagenomes from daily tongue and dental plaque samples from multiple individuals and reconstructed 790 non-redundant genomes, 43 of which resolved to TM7 that formed six monophyletic clades distinctly associated either with plaque or with tongue. Both pangenomic and phylogenomic analyses grouped tongue-specific TM7 clades with other host-associated TM7 genomes. In contrast, plaque-specific TM7 grouped together with environmental TM7 genomes. Besides offering deeper insights into the ecology, evolution, and the mobilome of the cryptic members of the oral microbiome, our study reveals an intriguing resemblance between dental plaque and non-host environments indicated by the TM7 evolution, suggesting that plaque may have served as a stepping stone for environmental microbes to adapt to host environments for some clades of human associated microbes. Additionally, we report that prophages are widespread amongst oral-associated TM7, while absent from environmental TM7, suggesting that prophages may have played a role in adaptation of TM7 to the host environment.
A synthetic mechanogenetic gene circuit for autonomous drug delivery in engineered tissues
Authors: Nims Robert J. , Pferdehirt Lara , Ho Noelani B. , Savadipour Alireza , Lorentz Jeremiah , Sohi Sima , Kassab Jordan , Ross Alison K. , O’Conor Christopher J. , Liedtke Wolfgang B. , Zhang Bo , McNulty Amy L. , Guilak Farshid 
Published: May 2020

AbstractMechanobiologic signals regulate cellular responses under physiologic and pathologic conditions. Using synthetic biology and tissue engineering, we developed a mechanically-responsive bioartificial tissue that responds to mechanical loading to produce a pre-programmed therapeutic biologic drug. By deconstructing the signaling networks induced by activation of the mechanically-sensitive ion channel transient receptor potential vanilloid 4 (TRPV4), we created synthetic TRPV4-responsive genetic circuits in chondrocytes. We engineered these cells into living tissues that respond to mechanical loading by producing the anti-inflammatory biologic drug, interleukin-1 receptor antagonist. Chondrocyte TRPV4 is activated by osmotic loading and not direct cellular deformation, suggesting tissue loading is transduced into an osmotic signal that activates TRPV4. Either osmotic or mechanical loading of tissues transduced with TRPV4-responsive circuits protected constructs from inflammatory degradation by interleukin-1α. This synthetic mechanobiology approach was used to develop a mechanogenetic system to enable long-term, autonomously regulated drug delivery driven by physiologically-relevant loading.
Hypothalamic circuitry underlying stress-induced insomnia and peripheral immunosuppression
Authors: Li Shi-Bin , Borniger Jeremy C , Yamaguchi Hiroshi , Hédou Julien , Gaudillière Brice , de Lecea Luis 
Published: May 2020

AbstractThe neural substrates of insomnia/hyperarousal induced by stress remain unknown. Here, we show that restraint stress leads to hyperarousal associated with strong activation of corticotropin-releasing hormone neurons in the paraventricular nucleus of hypothalamus (CRHPVN) and hypocretin neurons in the lateral hypothalamus (HcrtLH). CRHPVNneurons are quiescent during natural sleep-wake transitions but are strongly active under restraint stress. CRISPR-Cas9-mediated knockdown of thecrhgene in CRHPVNneurons abolishes hyperarousal elicited by stimulating LH-projecting CRHPVNneurons. Genetic ablation of Hcrt neurons orcrhgene knockdown significantly reduces insomnia/hyperarousal induced by restraint stress. Given the association between stress and immune function, we used single-cell mass cytometry by time of flight (CyTOF) to analyze peripheral blood and found extensive changes to immune cell distribution and functional responses during wakefulness upon optogenetic stimulation of CRHPVNneurons. Our findings suggest both central and peripheral systems are synergistically engaged in the response to stress via CRHPVNcircuitry.
Conformational Selection in Ligand Recognition by the First Tudor Domain of PHF20L1
Authors: Lv Mengqi , Gao Jia , Li Mingwei , Ma Rongsheng , Li Fudong , Liu Yaqian , Liu Mingqing , Zhang Jiahai , Yao Xuebiao , Wu Jihui , Shi Yunyu , Tang Yajun , Pan Yueyin , Zhang Zhiyong , Ruan Ke 
Published: May 2020

AbstractThe first Tudor domain of PHF20L1 (PHF20L1 Tudor1) recognizes both histone methylation and non-histone methylation to play versatile roles, e.g., PHF20L1 Tudor1 binds to the oncogenic target DNA (cytosine-5) methyltransferase 1 (DNMT1) to prevent it from degradation. However, the crystal structure of the PHF20 Tudor domain, a homolog of PHF20L1, reveals a closed aromatic cage of the Tudor domain. It is thus highly desirable to interrogate the ligand-recognition mechanism of PHF20L1 Tudor1, which will in turn validate the potential druggability of this target. Here, we solved the crystal structure of the free form PHF20L1 Tudor1, which adopts the closed conformation similar to PHF20. NMR relaxation dispersion and molecular dynamics (MD) simulations suggest a pre-existing low-population conformation with a remarkable rearrangement of aromatic cage residues. Such structural rearrangement is further revealed by the crystal structures of PHF20L1 Tudor1 in complex with the lysine 142 methylated (K142me1) DNMT1, and a small molecule cosolvent 2-(N-morpholino)ethanesulfonic acid (MES), respectively. This result thus ignites interest in the discovery of small molecule inhibitors against PHF20L1 Tudor1. The hit identified from NMR fragment-based screening protrudes into the same open form aromatic cage of PHF20L1 Tudor1, and blocks the interaction between PHF20L1 Tudor1 and methylated DNMT1. Further free form crystal structures of key mutants reveal one open form and one closed form aromatic cage, which is energetically trapped observed in the NMR relaxation dispersion and MD simulations. The binding of DNMT1 with PHF20L1 Tudor1 mutants was also recapitulated in cancer cells. The mutagenesis thus alters the structure, dynamics and eventually the function of PHF20L1 Tudor1. Our results demonstrate that PHF20L1 Tudor1 utilizes the same conformational selection mechanism to recognize ligands, regardless of whether it is a natural substrate or a small molecule identified from fragment-based screening. Albeit at a low population, the pre-existing ligand-binding conformation shall shift the paradigm in the druggability assessment of a dynamic protein, even though it may lack a small molecule binding pocket in its free form structure. The inhibition of PHF20L1 paves an alternative way to target DNMT1 degradation.
Leveraging biological complexity to predict patch occupancy in a recent host range expansion
Authors: Forister M. L. , Philbin C. S. , Marion Z. H. , Buerkle C. A. , Dodson C. D. , Fordyce J. A. , Forister G. W. , Lebeis S. L. , Lucas L. K. , Nice C. C. , Gompert Z. 
Published: May 2020

AbstractSpecialized plant-insect interactions are a defining feature of life on earth, yet we are only beginning to understand the factors that set limits on host ranges in herbivorous insects. To understand the colonization of alfalfa by the Melissa blue butterfly, we quantified arthropod assemblages and plant metabolites across a wide geographic region, while controlling for climate and dispersal inferred from population genomic variation. The presence of the butterfly is successfully predicted by direct and indirect effects of plant traits and interactions with other species. Results are consistent with the predictions of a theoretical model of parasite host range in which specialization is an epiphenomenon of the many barriers to be overcome rather than a consequence of trade-offs in developmental physiology.One sentence summaryThe formation of a novel plant-insect interaction can be predicted with a combination of biotic and abiotic factors, with comparable importance revealed for metabolomic variation in plants and interactions with mutualists, competitors and enemies.
Experimental Stroke Induces Chronic Gut Dysbiosis and Neuroinflammation in Male Mice
Authors: Brichacek Allison L. , Nwafor Divine C. , Benkovic Stanley A. , Chakraborty Sreeparna , Kenney Sophia M. , Mace Maria E. , Jun Sujung , Gambill Catheryne A. , Wang Wei , Hu Heng , Ren Xuefang , Povroznik Jessica M. , Engler-Chiurazzi Elizabeth B. , Primerano Donald A. , Denvir James , Percifield Ryan , Infante Aniello , Franko Jennifer , Schafer Rosana , Gemoets Darren E. , Brown Candice M. 
Published: May 2020

AbstractRecent literature implicates gut epithelia mucosa and intestinal microbiota as important players in post-stroke morbidity and mortality. As most studies have focused on the acute effects of stroke on gut dysbiosis, our study objective was to measure chronic, longitudinal changes in the gut microbiota and intestinal pathology following ischemic stroke. We hypothesized that mice with experimental ischemic stroke would exhibit chronic gut dysbiosis and intestinal pathology up to 36 days post-stroke compared to sham controls. Male C57BL/6J mice were subjected to 60 minutes of transient middle cerebral artery occlusion (tMCAO) or sham surgery. To determine the long-term effects of tMCAO on gut dysbiosis, fecal boli were collected pre- and post-tMCAO on days 0, 3, 14, and 28. Bioinformatics analysis demonstrate significant differences in abundance among Firmicutes and Bacteroidetes taxa at the phylum, family, and species levels in tMCAO compared to sham mice that persisted up to one month post-stroke. The most persistent changes in post-stroke microbial abundance were a decrease in bacteria family S24-7 and significant increases inRuminococcaceae. Overall, these changes resulted in a persistently increased Firmicutes:Bacteroidetes ratio in stroke animals. Intestinal histopathology showed evidence of chronic intestinal inflammation that included marked increases in immune cell infiltration with mild-moderate epithelial hyperplasia and villous blunting. Increased astrocyte and microglial activity were also detected one-month post-stroke. These results demonstrate that acute, post-stroke disruption of the gut-brain-microbiota axis progresses to chronic gut dysbiosis, intestinal inflammation, and chronic neuroinflammation.Clinical PerspectivesThe microbiota-gut-brain axis, recently implicated in several neurological disorders, remains largely unexplored at chronic time points post-tMCAO.Our results demonstrate chronic gut dysbiosis, prolonged behavioral deficits, and persistent cerebral and intestinal inflammation post-tMCAO in male C57BL/6J mice.These results suggest that manipulation of microbiota may help reduce poor outcomes after stroke and lead to improved post-stroke functional recovery.
ACE2 and TMPRSS2 expression by clinical, HLA, immune, and microbial correlates across 34 human cancers and matched normal tissues: implications for SARS-COV-2 COVID-19
Authors: Bao Riyue , Hernandez Kyle , Huang Lei , Luke Jason J. 
Published: May 2020

AbstractBackgroundPandemic COVID-19 by SARS-COV-2 infection is facilitated by the ACE2 receptor and protease TMPRSS2. Modestly sized case series have described clinical factors associated with COVID-19, while ACE2 and TMPRSS2 expression analyses have been described in some cell types. Cancer patients may have worse outcomes to COVID-19.MethodsWe performed an integrated study of ACE2 and TMPRSS2 gene expression across and within organ systems, by normal versus tumor, across several existing databases (The Cancer Genome Atlas, Census of Immune Single Cell Expression Atlas, The Human Cell Landscape, and more). We correlated gene expression with clinical factors (including but not limited to age, gender, race, BMI and smoking history), HLA genotype, immune gene expression patterns, cell subsets, and single-cell sequencing as well as commensal microbiome.ResultsMatched normal tissues generally display higher ACE2 and TMPRSS2 expression compared with cancer, with normal and tumor from digestive organs expressing the highest levels. No clinical factors were consistently identified to be significantly associated with gene expression levels though outlier organ systems were observed for some factors. Similarly, no HLA genotypes were consistently associated with gene expression levels. Strong correlations were observed between ACE2 expression levels and multiple immune gene signatures including interferon-stimulated genes and the T cell-inflamed phenotype as well as inverse associations with angiogenesis and transforming growth factor-β signatures. ACE2 positively correlated with macrophage subsets across tumor types. TMPRSS2 was less associated with immune gene expression but was strongly associated with epithelial cell abundance. Single-cell sequencing analysis across nine independent studies demonstrated little to no ACE2 or TMPRSS2 expression in lymphocytes or macrophages. ACE2 and TMPRSS2 gene expression associated with commensal microbiota in matched normal tissues particularly from colorectal cancers, with distinct bacterial populations showing strong associations.ConclusionsWe performed a large-scale integration of ACE2 and TMPRSS2 gene expression across clinical, genetic, and microbiome domains. We identify novel associations with the microbiota and confirm host immunity associations with gene expression. We suggest caution in interpretation regarding genetic associations with ACE2 expression suggested from smaller case series.
A Workflow for Protein Structure Determination from Thin Crystal Lamella by Micro-Electron Diffraction
Authors: Beale Emma V. , Waterman David G. , Hecksel Corey , van Rooyen Jason , Gilchrist James B. , Parkhurst James M. , de Haas Felix , Buijsse Bart , Evans Gwyndaf , Zhang Peijun 
Published: May 2020

AbstractMicro-Electron Diffraction (MicroED) has recently emerged as a powerful method for the analysis of biological structures at atomic resolution. This technique has been largely limited to protein nanocrystals which grow either as needles or plates measuring only a few hundred nanometres in thickness. Furthermore, traditional microED data processing uses established X-ray crystallography software that is not optimised for handling compound effects that are unique to electron diffraction data. Here, we present an integrated workflow for microED, from sample preparation by cryo-focused ion beam milling, through data collection with a standard Ceta-D detector, to data processing using the DIALS software suite, thus enabling routine atomic structure determination of protein crystals of any size and shape using microED. We demonstrate the effectiveness of the workflow by determining the structure of proteinase K to 2.0 Å resolution and show the advantage of using protein crystal lamellae over nanocrystals.
Connectomes across development reveal principles of brain maturation
Authors: Witvliet Daniel , Mulcahy Ben , Mitchell James K. , Meirovitch Yaron , Berger Daniel R. , Wu Yuelong , Liu Yufang , Koh Wan Xian , Parvathala Rajeev , Holmyard Douglas , Schalek Richard L. , Shavit Nir , Chisholm Andrew D. , Lichtman Jeff W. , Samuel Aravinthan D.T. , Zhen Mei 
Published: May 2020

AbstractFrom birth to adulthood, an animal’s nervous system changes as its body grows and its behaviours mature. The form and extent of circuit remodelling across the connectome is unknown. We used serial-section electron microscopy to reconstruct the full brain of eight isogenicC. elegansindividuals across postnatal stages to learn how it changes with age. The overall geometry of the brain is preserved from birth to adulthood. Upon this constant scaffold, substantial changes in chemical synaptic connectivity emerge. Comparing connectomes among individuals reveals substantial connectivity differences that make each brain partly unique. Comparing connectomes across maturation reveals consistent wiring changes between different neurons. These changes alter the strength of existing connections and create new connections. Collective changes in the network alter information processing. Over development, the central decision-making circuitry is maintained whereas sensory and motor pathways substantially remodel. With age, the brain progressively becomes more feedforward and discernibly modular. Developmental connectomics reveals principles that underlie brain maturation.
OMAmer: tree-driven and alignment-free protein assignment to subfamilies outperforms closest sequence approaches
Authors: Rossier Victor , Vesztrocy Alex Warwick , Robinson-Rechavi Marc , Dessimoz Christophe 
Published: May 2020

AbstractAssigning new sequences to known protein families and subfamilies is a prerequisite for many functional, comparative and evolutionary genomics analyses. Such assignment is commonly achieved by looking for the closest sequence in a reference database, using a method such as BLAST. However, ignoring the gene phylogeny can be misleading because a query sequence does not necessarily belong to the same subfamily as its closest sequence. For example, a hemoglobin which branched out prior to the hemoglobin alpha/beta duplication could be closest to a hemoglobin alpha or beta sequence, whereas it is neither. To overcome this problem, phylogeny-driven tools have emerged but rely on gene trees, whose inference is computationally expensive.Here, we first show that in multiple animal and plant datasets, 18 to 62% of assignments by closest sequence are misassigned, typically to an over-specific subfamily. Then, we introduce OMAmer, a novel alignment-free protein subfamily assignment method, which limits over-specific subfamily assignments and is suited to phylogenomic databases with thousands of genomes. OMAmer is based on an innovative method using evolutionarily-informedk-mers for alignment-free mapping to ancestral protein subfamilies. Whilst able to reject non-homologous family-level assignments, we show that OMAmer provides better and quicker subfamily-level assignments than approaches relying on the closest sequence, whether inferred exactly by Smith-Waterman or by the fast heuristic DIAMOND.OMAmer is available from the Python Package Index (as omamer), with the source code and a precomputed database available athttps://github.com/DessimozLab/omamer.