bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterizing the Cancer-Associated Microbiome with Small RNA Sequencing Data
Authors: Lee Wei-Hao , Chen Kai-Pu , Wang Kai , Huang Hsuan-Cheng , Juan Hsueh-Fen 
Published: October 2019

AbstractThe microbiome is recognized as a quasi-organ in the human body. In particular, the gut microbiome is correlated with immune function, metabolism, and tumorigenesis. When dysbiosis of the microbiome occurs, this variation may contribute to alterations in the microenvironment, potentially inducing an inflammatory immune response and providing a niche for neoplastic growth. However, there is limited evidence regarding the correlation and interaction between the microbiome and tumorigenesis. By utilizing microRNA sequencing data of patients with colon and rectal cancer from The Cancer Genome Atlas, we designed a novel analytical process to extract non-human small RNA sequences and align them with the microbial genome to obtain a comprehensive view of the cancer-associated microbiome. In the present study, we identified > 1000 genera among 630 colorectal samples and clustered these samples into three distinctive colorectal enterotypes. Each cluster has its own distinctive microbial composition and interactions. Furthermore, we found 12 genera from these clusters that are associated with cancer stages and revealed their putative functions. Our results indicate that the proposed analytical approach can effectively determine the cancer-associated microbiome. It may be readily applied to explore other types of cancer, in which specimens of the microbiome are difficult to collect.
Simultaneous electrophysiological recording and fiber photometry in freely behaving mice
Authors: Patel Amisha A , McAlinden Niall , Mathieson Keith , Sakata Shuzo 
Published: October 2019

AbstractIn vivo electrophysiology is the gold standard technique used to investigate sub-second neural dynamics in freely behaving animals. However, monitoring cell-type-specific population activity is not a trivial task. Over the last decade, fiber photometry based on genetically encoded calcium indicators has been widely adopted as a versatile tool to monitor cell-type-specific population activity in vivo. However, this approach suffers from low temporal resolution. Here, we combine these two approaches to monitor both sub-second field potentials and cell-type-specific population activity in freely behaving mice. By developing an economical custom-made system, and constructing a hybrid implant of an electrode and a fiber optic cannula, we simultaneously monitor artifact-free pontine field potentials and calcium transients in cholinergic neurons across the sleep-wake cycle. We find that pontine cholinergic activity co-occurs with sub-second pontine waves, called P-waves, during rapid eye movement sleep. Given the simplicity of our approach, simultaneous electrophysiological recording and cell-type-specific imaging provides a novel and valuable tool for interrogating state-dependent neural circuit dynamics in vivo.
KOPTIC: A novel approach forin silicoprediction of enzyme kinetics and regulation
Authors: Schroeder Wheaton L. , Saha Rajib 
Published: October 2019

AbstractKinetic models of metabolism (kMMs) provide not only a more accurate method for designing novel biological systems but also characterization of system regulations; however, the multi-‘omics’ data required is prohibitive to their development and widespread use. Here, we introduce a new approach namedKineticOPTimization usingIntegerConditions (KOPTIC), which can circumvent the ‘omics’ data requirement and semi-automate kMM construction usingin silicoreaction flux data and metabolite concentration estimates derived from a metabolic network model to return plausible reaction mechanisms, regulations, and kinetic parameters (defined as ‘reactomics’) using an optimization-based approach. As a benchmark for the performance of KOPTIC, a previously published, four-tissue (leaf, root, seed, and stem) metabolic model ofArabidopsis thalianawas used, consisting of major primary carbon metabolism pathways, named p-ath780 (1015 reactions, 901 metabolites, and 780 genes). Data required for KOPTIC was derived from an Arabidopsis’ lifecycle of 61 days. Nine separate regulator restriction sets (allowing multiple solutions) defining KOPTIC runs hypothesized 3577 total regulatory interactions involving metabolic, allosteric, and transcriptional regulatory mechanisms (with nearly 40 verified by existing literature) with a median fit error of 13.44%. Flux rates of most KOPTIC fits were found to be significantly correlated with (93.6% withp< 0.05) and approximately 1:1 (r= 0.775,p≪ 0.001) to the input time-series data. Thus, KOPTIC can hypothesize maps the regulatory landscape for a specific reaction, out of which the most relevant regulatory interaction(s) can be defined by the desired growth/stress conditions or the desired genetic interventions for use in the creation of kMMs.
Dynamics of apomictic and sexual reproduction during primary succession on a glacier forefield in the Swiss Alps
Authors: Sailer Christian , Stöcklin Jürg , Grossniklaus Ueli 
Published: October 2019

AbstractApomixis, the asexual reproduction through seeds, is thought to provide reproductive assurance when ploidy is not even and/or when population density is low. Therefore, apomicts are expected to be more abundant, and the frequency of apomictic offspring higher, at early stages of primary succession when mates are rare.To test this hypothesis, we sampled facultative apomictic Hieracium pilosella L. along the successional gradient on a glacier forefield and determined their ploidy, the level of apomixis in their offspring, and the genetic diversity of the entire meta-population and within subpopulations.We found that apomixis is more common in odd- and aneuploid cytotypes, which are more frequent at early stages of primary succession. However, apomixis was uncommon at all successional stages and sexual hexaploids were dominating throughout. Reproductive assurance was reflected in the higher fertility of all odd-ploid apomictic plants (3x, 5x) by avoiding meiosis, illustrating that apomixis provides an escape from sterility, as proposed by Darlington. Odd-ploid plants are supposedly better colonizers (Baker’s law), which is supported by their higher occurrence close to the glacier snout. Independent of succession, we found gene flow between apomicts and sexuals, which allows for the continuous creation of new apomictic and sexual genotypes.We conclude that apomixis in H. pilosella does indeed provide an escape from sterility, and therefore reproductive assurance, in aneuploid cytotypes. We further propose that apomixis preserves beneficial combinations of unlinked alleles in every generation for as long as apomictic genotypes persist in the population.
Association of SYNE2 variants in accelerating the progress of DYT1 early-onset isolated dystonia
Authors: Lee Feng-Chin , Wu Steve , Hsu Chih-Sin , Huang Shih-Ming , Hong Jau-Shyong , Hu Chih-Fen 
Published: October 2019

AbstractDYT1 early-onset isolated dystonia (DYT1 dystonia), a rare autosomal dominant (AD) primary dystonia, is categorized as a monogenic disease. While it is a well-known AD inherited disease, the relatively low penetrance rate implicates potential modifiers in play for disease progression. In this report, an affected individual withTOR1Agene (c.907_909delGAG, p.E303del) variant, was identified along with three additional AD carriers in the family. Since we failed to find the second hit variant from TOR1A (D216H, F323_Y328del and F205I) and major binding proteins, including TOR1AIP1 and 2 or HSPA8 proteins, subsequent whole exome sequencing on the patient, the carriers and a non-carrier family member were performed to screen for candidate modifiers of TOR1A (E303del). The result reveals that this patient distinctly carries one copy ofTOR1Agene (c.907_909delGAG, p.E303del) and one or two copy ofSYNE2gene (c.1721T>C, c.12001T>C, and c.12002G>A), encoding I574T, W4001R, and W4001Ter variants. We propose that these SYNE2 variants are linked to earlier disease onset in this patient by impacting the protein-protein interaction between TOR1A and SYNE2. Our study suggestsSYNE2gene maybe a culprit to lower the threshold for DYT1 dystonia progression and provides one novel gene target for further screening diagnosis of DYT1 dystonia.
Predicting the fMRI signal fluctuation with echo-state neural networks trained on vascular network dynamics
Authors: Sobczak Filip , He Yi , Sejnowski Terrence J. , Yu Xin 
Published: October 2019

AbstractResting-state functional MRI (rs-fMRI) studies have revealed specific low-frequency hemodynamic signal fluctuations (<0.1 Hz) in the brain, which could be related to oscillations in neural activity through several mechanisms. Although the vascular origin of the fMRI signal is well established, the neural correlates of global rs-fMRI signal fluctuations are difficult to separate from other confounding sources. Recently, we reported that single-vessel fMRI slow oscillations are directly coupled to brain state changes. Here, we used an echo-state network (ESN) to predict the future temporal evolution of the rs-fMRI slow oscillatory feature from both rodent and human brains. rs-fMRI signals from individual blood vessels that were strongly correlated with neural calcium oscillations were used to train an ESN to predict brain state-specific rs-fMRI signal fluctuations. The ESN-based prediction model was also applied to recordings from the Human Connectome Project (HCP), which classified variance-independent brain states based on global fluctuations of rs-fMRI features. The ESN revealed brain states with global synchrony and decoupled internal correlations within the default-mode network.
Epigenetic gene silencing by heterochromatin primes fungal resistance
Authors: Torres-Garcia Sito , Audergon Pauline N. C. B. , Shukla Manu , White Sharon A. , Pidoux Alison L. , Allshire Robin C. 
Published: October 2019

SummaryGenes embedded in H3 lysine 9 methylation (H3K9me)–dependent heterochromatin are transcriptionally silenced1-3. In fission yeast,Schizosaccharomyces pombe, H3K9me heterochromatin silencing can be transmitted through cell division provided the counteracting demethylase Epe1 is absent4,5. It is possible that under certain conditions wild-type cells might utilize heterochromatin heritability to form epimutations, phenotypes mediated by unstable silencing rather than changes in DNA6,7. Here we show that resistant heterochromatin-mediated epimutants are formed in response to threshold levels of the external insult caffeine. ChIP-seq analyses of unstable resistant isolates revealed new distinct heterochromatin domains, which in some cases reduce the expression of underlying genes that are known to confer resistance when deleted. Targeting synthetic heterochromatin at implicated loci confirmed that resistance results from heterochromatin-mediated silencing. Our analyses reveal that epigenetic processes allow wild-type fission yeast to adapt to non-favorable environments without altering their genotype. In some isolates, subsequent or co-occurring gene amplification events enhance resistance. Thus, heterochromatin-dependent epimutant formation provides a bet-hedging strategy that allows cells to remain genetically wild-type but transiently adapt to external insults. As unstable caffeine-resistant isolates show cross-resistance to the fungicide clotrimazole it is likely that related heterochromatin-dependent processes contribute to anti-fungal resistance in both plant and human pathogenic fungi.
Broad and thematic remodeling of the surface glycoproteome on isogenic cells transformed with driving proliferative oncogenes
Authors: Leung Kevin K. , Wilson Gary M. , Kirkemo Lisa L. , Riley Nicholas M. , Coon Joshua J. , Wells James A. 
Published: October 2019

AbstractThe cell surface proteome, the surfaceome, is the interface for engaging the extracellular space in normal and cancer cells. Here we apply quantitative proteomics of N-linked glycoproteins to reveal how a collection of some 700 surface proteins is dramatically remodeled in an isogenic breast epithelial cell line stably expressing any of six of the most prominent proliferative oncogenes, including the receptor tyrosine kinases, EGFR and HER2, and downstream signaling partners such as KRAS, BRAF, MEK and AKT. We find that each oncogene has somewhat different surfaceomes but the functions of these proteins are harmonized by common biological themes including up-regulation of nutrient transporters, down-regulation of adhesion molecules and tumor suppressing phosphatases, and alteration in immune modulators. Addition of a potent MEK inhibitor that blocks MAPK signaling brings each oncogene-induced surfaceome back to a common state reflecting their strong dependence on the MAPK pathway to propagate signaling. Using a recently developed glyco-proteomics method of activated ion electron transfer dissociation (AI-ETD) we found massive oncogene-induced changes in 142 N-linked glycans and differential increases in complex hybrid glycans especially for KRAS and HER2 oncogenes. Overall, these studies provide a broad systems level view of how specific driver oncogenes remodel the surface glycoproteome in a cell autologous fashion, and suggest possible surface targets, and combinations thereof, for drug and biomarker discovery.Significant statementThe cell surface glycoproteome (surfaceome) mediates interactions between the cell and the extracellular environment, and is a major target for immunotherapy in cancer. Using state-of-the-art proteomics methods, we compared how six neighboring proliferative oncogenes cause large and bidirectional expression of some 700 surface proteins and the 142 different glycans that decorate them. While each oncogene induces large and somewhat unique glycoproteomes relative to non-transformed cells, we find common functional consequences that are massively reversed by small molecule inhibition of the MAPK pathway. This large-scale comparative study provides important insights for how oncogenes remodel isogenic cells in a cell autologous fashion, and suggest possible new opportunities for antibody drug discovery in more complex tumor settings.
Synchrotron FTIR as a tool for studying populations and individual living cells of green algae
Authors: Goff Kira L. , Ellis Thomas , Wilson Kenneth E. 
Published: October 2019

AbstractFourier transform infrared (FTIR) spectromicroscopy was used to study individual living cells of three closely-related species of the green algae Chlamydomonas. This study differentiated these three species based on differences in lipid and protein profiles, as well explored sources of variation in our measurements. Significant spectral variation was observed between individual cells within a single culture, as well as between control cultures of a species obtained on different days. Despite this, we were able to differentiate between the three close-related species. Differences in the spectra were confirmed using principal component analysis. Understanding the interplay of underlying variation and the degree of induced spectral differences is essential for the deployment of FTIR measurements in both bulk cultures and for individual living cells.
Beyond generalization: Enhancing accurate interpretation of flexible models
Authors: Genkin Mikhail , Engel Tatiana A. 
Published: October 2019

ABSTRACTMachine learning optimizes flexible models to predict data. In scientific applications, there is a rising interest in interpreting these flexible models to derive hypotheses from data. However, it is unknown whether good data prediction guarantees accurate interpretation of flexible models. We test this connection using a flexible, yet intrinsically interpretable framework for modeling neural dynamics. We find that many models discovered during optimization predict data equally well, yet they fail to match the correct hypothesis. We develop an alternative approach that identifies models with correct interpretation by comparing model features across data samples to separate true features from noise. Our results reveal that good predictions cannot substitute for accurate interpretation of flexible models and offer a principled approach to identify models with correct interpretation.
Investigating tissue-relevant causal molecular mechanisms of complex traits using probabilistic TWAS analysis
Authors: Zhang Yuhua , Quick Corbin , Yu Ketian , Barbeira Alvaro ,   The GTEx Consortium, Luca Francesca , Pique-Regi Roger , Im Hae Kyung , Wen Xiaoquan 
Published: October 2019

AbstractTranscriptome-wide association studies (TWAS), an integrative framework using expression quantitative trait loci (eQTLs) to construct proxies for gene expression, have emerged as a promising method to investigate the biological mechanisms underlying associations between genotypes and complex traits. However, challenges remain in interpreting TWAS results, especially regarding their causality implications. In this paper, we describe a new computational framework, probabilistic TWAS (PTWAS), to detect associations and investigate causal relationships between gene expression and complex traits. We use established concepts and principles from instrumental variables (IV) analysis to delineate and address the unique challenges that arise in TWAS. PTWAS utilizes probabilistic eQTL annotations derived from multi-variant Bayesian fine-mapping analysis conferring higher power to detect TWAS associations than existing methods. Additionally, PTWAS provides novel functionalities to evaluate the causal assumptions and estimate tissue- or cell-type specific causal effects of gene expression on complex traits. These features make PTWAS uniquely suited for in-depth investigations of the biological mechanisms that contribute to complex trait variation. Using eQTL data across 49 tissues from GTEx v8, we apply PTWAS to analyze 114 complex traits using GWAS summary statistics from several large-scale projects, including the UK Biobank. Our analysis reveals an abundance of genes with strong evidence of eQTL-mediated causal effects on complex traits and highlights the heterogeneity and tissue-relevance of these effects across complex traits. We distribute software and eQTL annotations to enable users performing rigorous TWAS analysis by leveraging the full potentials of the latest GTEx multi-tissue eQTL data.
Stress-induced dendritic branching inC. elegansrequires both common arborization effectors and stress-responsive molecular pathways
Authors: Androwski Rebecca J. , Asad Nadeem , Wood Janet G. , Hofer Allison , Locke Steven , Smith Cassandra M. , Rose Becky , Schroeder Nathan E. 
Published: October 2019

ABSTRACTStress influences the shape of dendritic arbors in neurons. During the stress-induced dauer stage ofCaenorhabditis elegans, the IL2 neurons arborize to cover the anterior body wall. In contrast, the FLP neurons arborize to cover the anterior body wall during non-dauer development. Previous work showed that the membrane-bound receptor DMA-1 regulates FLP branching as part of a larger protein complex. Using forward genetics, we show that the IL2 neurons also use the DMA-1 complex to regulate branching. To understand the coordination of the IL2s and FLPs we conducted a time-course examination of FLPs and found previously undescribed branching patterns indicating a neighborhood effect wherein the FLPs and IL2s in the anterior have differential branching compared to the more posteriorly located PVD arborizing neurons. To determine how the IL2s and FLPs differentially regulate branching, we examined several regulators of DMA-1 localization. We show that the unfolded protein response sensor IRE-1, required for FLP branching, is only required for dauer-specific branching at elevated temperatures. Interestingly, we found thatire-1mutants have broad, organism-wide temperature-dependent effects on dauer remodeling, suggesting a previously undescribed role for IRE-1 in phenotypic plasticity. We also found that defects in other regulators of dauer remodeling including DAF-16/FOXO, DAF-9/Cytochrome P450, and DAF-18/PTEN are required for proper IL2 arborization, but dispensable for FLP branching. Interestingly, we find that TOR adaptor protein DAF-15/RAPTOR is both required for promoting IL2 branching and inhibiting precocious development of the FLPs. Our results demonstrate specific genotypic by environmental interactions regulating dendrite arborization.SIGNIFICANCE STATEMENTNeurons have extensions called dendrites that receive information. Dendrites are often elaborately shaped with many branches. Adverse stress can reduce branching in some neurons, while increasing it in others. How stress can cause some neurons to change shape is unclear. We previously found a set of neurons in the head of the well-studied roundwormC. elegansthat undergo reversible branching following exposure to specific adverse environmental conditions. Using various genetic tools, we find that branching in these neurons is controlled by a combination of branching genes common to many neuron types and others that only regulate branching in stress-responsive neurons. Our data demonstrate how experiencing stress acts through genetics pathways to cause changes to specific neurons.
When two are better than one: Modeling the mechanisms of antibody mixtures
Authors: Einav Tal , Bloom Jesse D. 
Published: October 2019

AbstractIt is difficult to predict how antibodies will behave when mixed together, even after each has been independently characterized. Here, we present a statistical mechanical model for the activity of antibody mixtures that accounts for whether pairs of antibodies bind to distinct or overlapping epitopes. This model requires measuring n individual antibodies and their pairwise interactions to predict the 2n potential combinations. We apply this model to epidermal growth factor receptor (EGFR) antibodies and find that the activity of antibody mixtures can be predicted without positing synergy at the molecular level. In addition, we demonstrate how the model can be used in reverse, where straightforward experiments measuring the activity of antibody mixtures can be used to infer the molecular interactions between antibodies. Lastly, we generalize this model to analyze engineered multidomain antibodies, where components of different antibodies are tethered together to form novel amalgams, and characterize how well it predicts recently designed influenza antibodies.Author summaryWith the rise of new antibody combinations in therapeutic regimens, it is important to understand how antibodies work together as well as individually. Here, we investigate the specific case of monoclonal antibodies targeting a cancer-causing receptor or the influenza virus and develop a statistical mechanical framework that predicts the effectiveness of a mixture of antibodies. The power of this model lies in its ability to make a large number of predictions based on a limited amount of data. For example, once 10 antibodies have been individually characterized and their epitopes have been mapped, our model can predict how any of the 210 = 1024 combinations will behave. This predictive power can aid therapeutic efforts by assessing which combinations of antibodies will elicit the most effective response.