bluuebunny/crossref_metadata_2025 huggingface dataset:
The semantic control network mediates the relationship between symbolic numerical order processing and arithmetic performance in children
Authors: Sommerauer Gerrit , Grass Karl-Heinz , Grabner Roland H. , Vogel Stephan E.
Published: October 2019

Behavioral and neuroimaging studies have recently demonstrated that symbolic numerical order processing (i.e., deciding whether numbers are in an increasing/decreasing sequence or not) may engages different cognitive mechanisms and brain regions compared to symbolic numerical magnitude processing (e.g., deciding which of two numerals is larger). Because of this behavioral dissociation, growing interest has emerged to better understand the neurocognitive mechanisms of symbolic numerical order processing and their relationship to individual differences in arithmetic performance. In the present functional imaging work, we further investigated this link in a group of thirty children (7.2-10.25 years) from elementary school, who completed a symbolic numerical order verification (are the numbers going up? e.g., 1-2-3), a symbolic numerical magnitude comparison task (which is the larger number? e.g., 5-7), as well as an arithmetic fluency test outside the scanner. Behavioral results demonstrated the unique role of numerical order to predict children’s arithmetic skills and confirmed its mediating power to explain the association between numerical magnitude and arithmetic performance. Imaging results showed a significant association between numerical order and arithmetic in the intersection of the right inferior frontal gyrus and insula, as well as the posterior middle temporal gyrus. An age-dependent change in brain activity was found in the left intraparietal sulcus. These findings solidify the developmental importance of symbolic numerical order processing in children and provides new evidence that the semantic control network mediates the relationship with arithmetic performance.

Highlights

Reaction times of numerical order are a unique predictor of arithmetic (73)

Numerical order mediates the relationship of numerical magnitude with arithmetic (83)

Brain activation of numerical order processing changes with age in the left IPS (82)

The semantic control network mediates the relationship with arithmetic (79)
Pancreas-specific miR-216a regulates proliferation and endocrine and exocrine cell functionin vivo
Authors: Erener Suheda , Ellis Cara E. , Ramzy Adam , Glavas Maria M. , O’Dwyer Shannon , Pereira Sandra , Wang Tom , Pang Janice , Bruin Jennifer E. , Riedel Michael J. , Baker Robert K. , Webber Travis D. , Kopp Janel L. , Herzig Stephan , Kieffer Timothy J.
Published: October 2019

Pancreas is a vital organ composed of exocrine and endocrine cells that aid digestion of food and regulate blood glucose levels. Perturbations in the function of pancreatic cells leads to the development of life-burdening and/or threatening diseases such as diabetes and pancreatic cancer. Thus, it is critical to understand the molecular check-points that maintain normal pancreas physiology. MicroRNAs (miRNAs) are small non-coding RNAs involved in regulating gene expression in normal and diseased tissues. Several miRNAs have tissue-specific patterns consistent with crucial functions in many biological processes. Yet, there is limited knowledge about the role of pancreas-specific miRNAs in pancreatic pathologies. Here, we report that miR-216a is a conserved, pancreas-specific miRNA that is expressed in both endocrine and exocrine cells. Deletion of miR-216a in mice leads to reduced β-cell mass and a reduction in islet size under both chow and high-fat diet feeding conditions. We show that inhibition of miR-216a increases apoptosis and decreases cell proliferation in β- and exocrine cells.Smad7is upregulated in miR-216a deficient islets and cell cycle and proliferation are among the most significantly regulated biological processes in miR-216 knockout pancreata. Re-introduction of miR-216a in the pancreatic cancer line, PANC-1, increases cell migration more than 2-fold.In vivo, deletion of miR-216a in the pancreatic cancer prone mouse lineKrasG12D;Ptf1aCreERinhibits the propensity of pancreatic cancer precursor lesions. Our study identifies miR-216a as an important pancreas-specific miRNA which may have implications for both diabetes and pancreatic cancer.
Comparative Genomics Shows Differences in the Electron Transport and Carbon Metabolic Pathways ofMycobacterium africanumrelative toMycobacterium tuberculosisand suggests an adaptation to low oxygen tension
Authors: Ofori-Anyinam Boatema , Riley Abi Janet , Jobarteh Tijan , Gitteh Ensa , Sarr Binta , Faal-Jawara Tutty Isatou , Rigouts Leen , Senghore Madikay , Kehinde Aderemi , Onyejepu Nneka , Antonio Martin , Jong Bouke C. de , Gehre Florian , Meehan Conor J.
Published: October 2019

The geographically restrictedMycobacterium africanumlineages (MAF) are primarily found in West Africa, where they account for a significant proportion of tuberculosis. Despite this phenomenon, little is known about the co-evolution of these ancient lineages with West Africans. MAF andM. tuberculosissensu stricto lineages (MTB) differ in their clinical, in vitro and in vivo characteristics for reasons not fully understood. Therefore, we compared genomes of 289 MAF and 205 MTB clinical isolates from the 6 main human-adaptedM. tuberculosiscomplex lineages, for mutations in their Electron Transport Chain and Central Carbon Metabolic pathway in order to explain these metabolic differences. Furthermore, we determined, in silico, whether each mutation could affect the function of genes encoding enzymes in these pathways.

We found more mutations with the potential to affect enzymes in these pathways in MAF lineages compared to MTB lineages. We also found that similar mutations occurred in these pathways between MAF and some MTB lineages.

Generally, our findings show further differences between MAF and MTB lineages that may have contributed to the MAF clinical and growth phenotype and indicate potential adaptation of MAF lineages to a distinct ecological niche, which we suggest includes areas characterized by low oxygen tension.
The lhfpl5 ohnologs lhfpl5a and lhfpl5b are required for mechanotransduction in distinct populations of sensory hair cells in zebrafish
Authors: Erickson Timothy , Pacentine Itallia V. , Venuto Alexandra , Clemens Rachel , Nicolson Teresa
Published: October 2019

1

Hair cells sense and transmit auditory, vestibular, and hydrodynamic information by converting mechanical stimuli into electrical signals. This process of mechano-electrical transduction (MET) requires a mechanically-gated channel localized in the apical stereocilia of hair cells. In mice, lipoma HMGIC fusion partner-like 5 (LHFPL5) acts as an auxiliary subunit of the MET channel whose primary role is to correctly localize PCDH15 and TMC1 to the mechanotransduction complex. Zebrafish have two lhfpl5 genes (lhfpl5a and lhfpl5b), but their individual contributions to MET channel assembly and function have not been analyzed.

Here we show that the zebrafish lhfpl5 genes are expressed in discrete populations of hair cells: lhfpl5a expression is restricted to auditory and vestibular hair cells in the inner ear, while lhfpl5b expression is specific to hair cells of the lateral line organ. Consequently, lhfpl5a mutants exhibit defects in auditory and vestibular function, while disruption of lhfpl5b affects hair cells only in the lateral line neuromasts. In contrast to previous reports in mice, localization of Tmc1 does not depend upon Lhfpl5 function in either the inner ear or lateral line organ. In both lhfpl5a and lhfpl5b mutants, GFP-tagged Tmc1 and Tmc2b proteins still localize to the stereocilia of hair cells. Using a stably integrated GFP-Lhfpl5a transgene, we show that the tip link cadherins Pcdh15a and Cdh23, along with the Myo7aa motor protein, are required for correct Lhfpl5a localization at the tips of stereocilia. Our work corroborates the evolutionarily conserved co-dependence between Lhfpl5 and Pcdh15, but also reveals novel requirements for Cdh23 and Myo7aa to correctly localize Lhfpl5a. In addition, our data suggest that targeting of Tmc1 and Tmc2b proteins to stereocilia in zebrafish hair cells occurs independently of Lhfpl5 proteins.
Sticky Situations: Bacterial Attachment Deciphered by Interferometry of Silicon Microstructures
Authors: Leonard Heidi , Holtzman Liran , Haimov Yuri , Weizman Daniel , Halachmi Sarel , Kashi Yechezkel , Segal Ester
Published: October 2019

The peculiarities of surface-bound bacterial cells are often overshadowed by the study of planktonic cells in clinical microbiology. Thus, we employ phase-shift reflectometric interference spectroscopic measurements to observe the interactions between bacterial cells and abiotic, microstructured material surfaces in a label-free, real-time manner. Both material characteristics (i.e., substrate surface charge and wettability) and characteristics of the bacterial cells (i.e., motility, cell charge, biofilm formation, and physiology) drive bacteria to adhere to a particular surface. We conclude that the attachment of bacterial cells to a surface is determined by the culmination of numerous factors. When specific characteristics of the bacteria are met with factors of the surface, enhanced cell attachment and biofilm formation occur. Such knowledge can be exploited to predict antibiotic efficacy, biofilm development, enhance biosensor development, as well as prevent biofouling.
Integration of Multi-level Molecular Scoring for the Interpretation of RAS-Family Genetic Variation
Authors: Tripathi Swarnendu , Dsouza Nikita R. , Urrutia Raul A. , Zimmermann Michael T.
Published: October 2019

Protein-coding genetic variants are the first considered in most studies and Precision Medicine workflows, but their interpretation is primarily driven by DNA sequence-based analytical tools and annotations. Thus, more specific and mechanistic interpretations should be attainable by integrating DNA-based scores with scores from the protein 3D structure. However, reliable and reproducible standardization of methods that use 3D structure for genomic variation is still lacking. Further, we believe that the current paradigm of aiming to directly predict the pathogenicity of variants skips the critical step of inferring, with precision, molecular mechanisms of dysfunction. Thus, we report herein the development and evaluation of single and composite 3D structure-based scores and their integration with protein and DNA sequence-based scores to better understand not only if a genomic variant alters a protein, but how. We believe this is a critical step for understanding mechanistic changes due to genomic variants, designing functional validation tests, and for improving disease classifications. We applied this approach to the RAS gene family encoding seven distinct proteins and their 935 unique missense variants present somatically in cancer, in rare diseases (termed RASopathies), and in the currently healthy adult population. This knowledge shows that protein structure-based scores are distinct from information available from genomic annotation, that they are useful for interpreting genomic variants, and they should be taken into consideration in future guidelines for genomic data interpretation.

Significance Statement

Genetic information from patients is a powerful data type for understanding individual differences in disease risk and treatment, but most of the genetic variation we observe has no mechanistic interpretation. This lack of interpretation limits the use of genomics data in clinical care. Standard methods for genomics data interpretation take advantage of annotations available for the human reference genome, but they do not consider the 3D protein molecule. We believe that changes to the 3D molecule must be considered, to augment current practice and lead to more precise interpretation. In this work, we present our initial process for systematic multi-level molecular scores, including 3D, to interrogate 935 RAS-family variants that are relevant in both cancer and rare diseases.
OpenCRAVAT, an open source collaborative platform for the annotation of human genetic variation
Authors: Pagel Kymberleigh A , Kim Rick , Moad Kyle , Busby Ben , Zheng Lily , Hynes-Grace Matthew , Tokheim Collin , Ryan Michael , Karchin Rachel
Published: October 2019

PURPOSE

The modern researcher is confronted with hundreds of published methods to interpret genetic variants. There are databases of genes and variants, phenotype-genotype relationships, algorithms that score and rank genes, andin silico variant effect prediction tools. Because variant prioritization is a multi-factorial problem, a welcome development in the field has been the emergence of decision support frameworks, which make it easier to integrate multiple resources in an interactive environment. Current decision support frameworks are typically limited by closed proprietary architectures, access to a restricted set of tools, lack of customizability, web dependencies that expose protected data, or limited scalability.

METHODS

We present OpenCRAVAT, a new open source, scalable decision support system for variant and gene prioritization. We have designed the resource catalog to be open and modular to maximize community and developer involvement, and as a result the catalog is being actively developed and growing every month. Resources made available via the store are well-suited for analysis of cancer, as well as Mendelian and complex diseases.

RESULTS

OpenCRAVAT offers both command line utility and dynamic GUI, allowing users to install with a single command, easily download tools from an extensive resource catalog, create customized pipelines, and explore results in a richly detailed viewing environment. We present several case studies to illustrate the design of custom workflows to prioritize genes and variants.

CONCLUSION

OpenCRAVAT is distinguished from similar tools by its capabilities to access and integrate an unprecedented amount of diverse data resources and computational prediction methods, which span germline, somatic, common, rare, coding and non-coding variants. OpenCRAVAT is freely available athttps://opencravat.org
Structural controllability predicts functional patterns and brain stimulation benefits associated with working memory
Authors: Beynel L. , Deng L. , Crowell C.A. , Dannhauer M. , Palmer H. , Hilbig S. , Peterchev A.V. , Luber B. , Lisanby S.H. , Cabeza R. , Appelbaum L.G. , Davis S.W.
Published: October 2019

The brain is an inherently dynamic system, and much work has focused on the ability to modify neural activity through both local perturbations and changes in the function of global network ensembles. Network controllability is a recent concept in network science that purports to predict the influence of individual cortical sites on global network states and state changes, thereby creating a unifying account of local influences on global brain dynamics. Here, we present an integrated set of multimodal brain–behavior relationships, acquired from functional magnetic resonance imaging during a transcranial magnetic stimulation intervention, that demonstrate how network controllability influences network function, as well as behavior. This work helps to outline a clear technique for integrating structural network topology and functional activity to predict the influence of a potential stimulation target on subsequent behaviors and prescribes next steps towards predicting neuromodulatory and behavioral responses after brain stimulation.

Highlights

- This study tested the strength of network controllability using fMRI and rTMS

- Controllability correlates with functional modulation of working memory demand load

- Controllability is also correlated with the memory improvement from applied rTMS

- These findings link network control theory with physiology and behavior.

In brief

Beynel et al. show that the benefits of functionally targeted brain stimulation on working memory performance can be predicted by network control properties at the stimulated site. Structural controllability and functional activity independently predict this cognitive benefit.

Author Contributions

Conceptualization & Methodology: L.B, S.W.D., B.L., R.C., L.G.A.; Investigation: L.B., L.D., S.W.D., C.A.C., M.D., H.P., S.H.; Writing—Original Draft: L.B., L.D., S.W.D.; Writing—Review & Editing: L.B., L.D., S.W.D., L.G.A., A.V.P.; Funding Acquisition: S.W.D., R.C., B.L., S.H.L., A.V.P.; Resources: L.G.A., B.L., R.C.; Supervision: L.G.A., S.W.D.
Opportunistically collected photographs can be used to estimate large-scale phenological trends
Authors: Taylor Shawn D. , Guralnick Robert P.
Published: October 2019

Premise

Research on large-scale patterns of phenology have utilized multiple sources of data to analyze the timing of events such as flowering, fruiting, and leaf out. In-situ observations from standardized surveys are ideal, but remain spatially sparse. Herbarium records and phenology-focused citizen science programs provide a source of historic data and spatial replication, but the sample sizes for any one season are still relatively low. A novel and rapidly growing source of broad-scale phenology data are photographs from the iNaturalist platform, but methods utilizing these data must generalize to a range of different species with varying season lengths and occurring across heterogenous areas. They must also be robust to different sample sizes and potential biases toward well travelled areas such as roads and towns.

Methods/Results

We developed a spatially explicit model, the Weibull Grid, to estimate flowering onset across large-scales, and utilized a simulation framework to test the approach using different phenology and sampling scenarios. We found that the model is ideal when the underlying phenology is non-linear across space. We then use the Weibull Grid model to estimate flowering onset of two species using iNaturalist photographs, and compare those estimates with independent observations of greenup from the Phenocam network. The Weibull Grid model estimate consistently aligned with Phenocam greenup across four years and broad latitudes.

Conclusion

iNaturalist observations can considerably increase the amount of phenology observations and also provide needed spatial coverage. We showed here they can accurately describe large-scale trends as long as phenological and sampling processes are considered.
Sites of Circadian Clock Neuron Plasticity Mediate Sensory Integration and Entrainment
Authors: Fernández MP , Pettibone HL , Roell CJ , Davey CE , Huynh KV , Lennox SM , Kostadinov BS , Shafer OT
Published: October 2019

Networks of circadian timekeeping in the brain display marked daily changes in neuronal morphology. In Drosophila melanogaster, the striking daily structural remodeling of the dorsal medial termini of the small ventral lateral neurons has long been hypothesized to mediate endogenous circadian timekeeping. To test this model, we have specifically abrogated these sites of daily neuronal remodeling through the reprogramming of neural development and assessed the effects on circadian timekeeping and clock outputs. Remarkably, the loss of these sites has no measurable effects on endogenous circadian timekeeping or on any of the major output functions of the small ventral lateral neurons. Rather, their loss reduces sites of glutamatergic sensory neurotransmission that normally encodes naturalistic time-cues from the environment. These results support an alternative model: structural plasticity in critical clock neurons is the basis for proper integration of light and temperature and gates sensory inputs into circadian clock neuron networks.
Noninvasive Sleep Scoring in Mice using Electric Field Sensors
Authors: Kloefkorn H , Aiani LM , Lakhani A , Nagesh S , Moss A , Goolsby W , Rehg JM , Pedersen NP , Hochman S
Published: October 2019

Background

Rodent sleep scoring in principally reliant on electroencephalogram (EEG) and electromyogram (EMG), but this approach is invasive, can be expensive, and requires expertise and specialized equipment. Affordable, simple to use, and noninvasive ways to accurately quantify rodent sleep are needed.

New method

We developed and validated a new method for sleep-wake staging in mice using cost-effective, noninvasive electric field (EF) sensors that detect respiration and other movements. We validated recordings from EF sensors attached to the exterior of specialty chambers used to continuously capture sleep with EEG/EMG, then compared this to EF sensors attached to vivarium home-cages.

Results

EF sensors quantified 3-state sleep architecture (wake, rapid eye movement – REM – sleep, and non-REM sleep) with high agreement (>93%) and comparable inter- and intra-scorer error as expert EEG/EMG scoring. Novices given an instruction document with examples were able to score sleep comparable to expert scorers (>91% agreement). Additionally, EF sensors were able to quantify 3-state sleep scoring in traditional mouse home cages.

Comparison with existing method

Most noninvasive sleep assessment technology requires animal contact, altered cage environments, and/or can only discern 2 states of arousal (wake or asleep). The EF sensors are able to discriminate REM from non-REM sleep accurately and from outside the animal’s home cage.

Conclusions

EF sensors provide a simple and reliable method to accurately score 3-state sleep architecture; (i) from outside the typical home cage, (ii) where noninvasive approaches are preferred, or (iii) which EEG/EMG is not possible.

Graphical Abstract
Molecular Mechanism of Brassinosteroids Perception by the Plant Growth Receptor BRI1
Authors: Aldukhi Faisal , Deb Aniket , Zhao Chuankai , Moffett Alexander S. , Shukla Diwakar
Published: October 2019

Brassinosteroids (BRs) are essential phytohormones which bind to the plant receptor, BRI1, to regulate various physiological processes. The molecular mechanism of the perception of BRs by the ectodomain of BRI1 remains not fully understood. It also remains elusive why a substantial difference in biological activity exists between the BRs. In this work, we study the binding mechanisms of the two most bioactive BRs, brassinolide (BLD) and castasterone (CAT) using molecular dynamics simulations. We report free energy landscapes of the binding processes of both ligands as well as detailed ligand binding pathways. Our results suggest that CAT has lower binding affinity compared to BLD due to its inability to form hydrogen bonding interactions with a tyrosine residue in the island domain of BRI1. We uncover a conserved non-productive binding state for both BLD and CAT, which is more stable for CAT and may further contribute to the bioactivity difference. Finally, we validate past observations about the conformational restructuring and ordering of the island domain upon BLD binding. Overall, this study provides new insights into the fundamental mechanism of the perception of two most bioactive BRs, which may create new avenues for genetic and agrochemical control of their signaling cascade.
Detecting Zero-Inflated Genes in Single-Cell Transcriptomics Data
Authors: Clivio Oscar , Lopez Romain , Regier Jeffrey , Gayoso Adam , Jordan Michael I. , Yosef Nir
Published: October 2019

In single-cell RNA sequencing data, biological processes or technical factors may induce an overabundance of zero measurements. Existing probabilistic approaches to interpreting these data either model all genes as zero-inflated, or none. But the overabundance of zeros might be gene-specific. Hence, we propose the AutoZI model, which, for each gene, places a spike-and-slab prior on a mixture assignment between a negative binomial (NB) component and a zero-inflated negative binomial (ZINB) component. We approximate the posterior distribution under this model using variational inference, and employ Bayesian decision theory to decide whether each gene is zero-inflated. On simulated data, AutoZI outperforms the alternatives. On negative control data, AutoZI retrieves predictions consistent to a previous study on ERCC spike-ins and recovers similar results on control RNAs. Applied to several datasets and instances of the 10x Chromium protocol, AutoZI allows both biological and technical interpretations of zero-inflation. Finally, AutoZI’s decisions on mouse embyronic stem-cells suggest that zero-inflation might be due to transcriptional bursting.
Activity labeling in vivo using CaMPARI2 reveals electrophysiological differences between neurons with high and low firing rate set points
Authors: Trojanowski Nicholas F , Turrigiano Gina G.
Published: October 2019

Individual excitatory neurons in visual cortex (V1) display remarkably stable mean firing rates over many days, even though these rates can differ by several orders of magnitude between neurons. When perturbed, each neuron’s firing rate is slowly regulated back to its pre-perturbation level, demonstrating that neurons maintain their mean firing rate around an individual firing rate set point (FRSP). To better understand the mechanisms that neurons within a single cell type use to maintain different FRSPs in vivo, we implemented a novel method of activity labeling that uses CaMPARI2, a fluorescent protein that undergoes Ca2+- and UV-dependent green-to-red photoconversion, to permanently label neurons in freely behaving mice based on their firing rates. We found that immediate early gene (IEG) expression was correlated with CaMPARI2 red/green ratio following an activity stimulation paradigm, and that neurons with greater photoconversion in vivo tended to have a higher firing rate ex vivo. In layer 4 (L4) pyramidal neurons in mouse monocular V1, which comprise a single transcriptional cell type, we found that high activity neurons had a left-shifted F-I curve, lower rheobase current, and decreased spike adaptation index relative to low activity neurons, demonstrating increased intrinsic excitability. Surprisingly, we found no difference in total excitatory or inhibitory synaptic current or in E/I ratio between high and low activity neurons. Thus, within a single cell type differences in intrinsic excitability and spike frequency adaptation can contribute to divergent activity set points. These results reveal that E/I ratio plays only a minor role in determining the firing rate set point of L4 pyramidal neurons, while intrinsic excitability is an important factor.
FB5P-seq: FACS-based 5-prime end single-cell RNAseq for integrative analysis of transcriptome and antigen receptor repertoire in B and T cells
Authors: Attaf-Bouabdallah Noudjoud , Cervera-Marzal Iñaki , Dong Chuang , Gil Laurine , Renand Amédée , Spinelli Lionel , Milpied Pierre
Published: October 2019

Single-cell RNA sequencing (scRNA-seq) allows the identification, characterization, and quantification of cell types in a tissue. When focused on B and T cells of the adaptive immune system, scRNA-seq carries the potential to track the clonal lineage of each analyzed cell through the unique rearranged sequence of its antigen receptor (BCR or TCR, respectively), and link it to the functional state inferred from transcriptome analysis. Here we introduce FB5P-seq, a FACS-based 5’-end scRNA-seq method for cost-effective integrative analysis of transcriptome and paired BCR or TCR repertoire in phenotypically defined B and T cell subsets. We describe in details the experimental workflow and provide a robust bioinformatics pipeline for computing gene count matrices and reconstructing repertoire sequences from FB5P-seq data. We further present two applications of FB5P-seq for the analysis of human tonsil B cell subsets and peripheral blood antigen-specific CD4 T cells. We believe our novel integrative scRNA-seq method will be a valuable option to study rare adaptive immune cell subsets in immunology research.
Insights from a survey-based analysis of the academic job market
Authors: Fernandes Jason D. , Sarabipour Sarvenaz , Smith Christopher T. , Niemi Natalie M. , Jadavji Nafisa M. , Kozik Ariangela J. , Holehouse Alex S. , Pejaver Vikas , Symmons Orsolya , Bisson Filho Alexandre W. , Haage Amanda
Published: October 2019

Applying for a faculty position is a critical phase of many postdoctoral careers, but most postdoctoral researchers in STEM fields enter the academic job market with little knowledge of the process and expectations. A lack of data has made it difficult for applicants to assess their qualifications relative to the general applicant pool and for institutions to develop effective hiring policies. We analyzed responses to a survey of faculty job applicants between May 2018 and May 2019. We establish various background scholarly metrics for a typical faculty applicant and present an analysis of the interplay between those metrics and hiring outcomes. Traditional benchmarks of a positive research track record above a certain threshold of qualifications were unable to completely differentiate applicants with and without offers. Our findings suggest that there is no single clear path to a faculty job offer and that metrics such as career transition awards and publications in high impact factor journals were neither necessary nor sufficient for landing a faculty position. The applicants perceived the process as unnecessarily stressful, time-consuming, and largely lacking in feedback, irrespective of a successful outcome. Our findings emphasize the need to improve the transparency of the faculty job application process. In addition, we hope these and future data will help empower trainees to enter the academic job market with clearer expectations and improved confidence.
Degradation of the repetitive genomic landscape in a close relative ofC. elegans
Authors: Woodruff Gavin C. , Teterina Anastasia A.
Published: October 2019

The abundance, diversity, and genomic distribution of repetitive elements is highly variable among species. These patterns are thought to be driven in part by reproductive mode and the interaction of selection and recombination, and recombination rates typically vary by chromosomal position. In the nematodeC. elegans,repetitive elements are enriched at chromosome arms and depleted on centers, and this mirrors the chromosomal distributions of other genomic features such as recombination rate. How conserved is this genomic landscape of repeats, and what evolutionary forces maintain it? To address this, we compared the genomic organization of repetitive elements across fiveCaenorhabditisspecies with chromosome-level assemblies. As previously reported, repeat content is enriched on chromosome arms in mostCaenorhabditisspecies, and no obvious patterns of repeat content associated with reproductive mode were observed. However, the fig-associatedCaenorhabditis inopinatahas experienced rampant repetitive element expansion and reveals no association of global repeat content with chromosome position. Patterns of transposable element superfamily-specific distributions reveal this global pattern is driven largely by a few transposable element superfamilies that inC. inopinatahave expanded in number and have weak associations with chromosome position. Additionally, 15% of predicted protein-coding genes inC. inopinataalign to transposon-related proteins. When these are excluded, C. inopinatahas no enrichment of genes in chromosome centers, in contrast to its close relatives who all have such clusters. Forward evolutionary simulations reveal that chromosomal heterogeneity in recombination rate is insufficient for generating structured genomic repetitive landscapes. Instead, heterogeneity in the fitness effects of transposable element insertion is needed to promote heterogeneity in repetitive landscapes. Thus, patterns of gene density along chromosomes are likely drivers of global repetitive landscapes in this group, although other historical or genomic factors are needed to explain the idiosyncrasy of genomic organization of various transposable element taxa withinC. inopinata.Taken together, these results highlight the power of comparative genomics and evolutionary simulations in testing hypotheses regarding the causes of genome organization.
Foreign body responses in central nervous system mimic natural wound responses and alter biomaterial functions
Authors: O’Shea Timothy M. , Wollenberg Alexander L. , Kim Jae H. , Ao Yan , Deming Timothy J. , Sofroniew Michael V.
Published: October 2019

Biomaterials hold promise for diverse therapeutic applications in the central nervous system (CNS). Little is known about molecular factors that determine CNS foreign body responses (FBRs)in vivo, or about how such responses influence biomaterial function. Here, we probed these factors using a platform of injectable hydrogels readily modified to present interfaces with different representative physiochemical properties to host cells. We show that biomaterial FBRs mimic specialized multicellular CNS wound responses not present in peripheral tissues, which serve to isolate damaged neural tissue and restore barrier functions. Moreover, we found that the nature and intensity of CNS FBRs are determined by definable properties. For example, cationic, anionic or nonionic interfaces with CNS cells elicit quantifiably different levels of stromal cell infiltration, inflammation, neural damage and amyloid production. The nature and intensity of FBRs significantly influenced hydrogel resorption and molecular delivery functions. These results characterize specific molecular mechanisms that drive FBRs in the CNS and have important implications for developing effective biomaterials for CNS applications.
Small molecule activation of metabolic enzyme pyruvate kinase muscle isozyme 2, PKM2, provides photoreceptor neuroprotection
Authors: Wubben Thomas J. , Pawar Mercy , Weh Eric , Smith Andrew , Sajjakulnukit Peter , Zhang Li , Dai Lipeng , Hager Heather , Pai Manjunath P. , Lyssiotis Costas A. , Besirli Cagri G.
Published: October 2019

Photoreceptor cell death is the ultimate cause of vision loss in many retinal disorders, and there is an unmet need for neuroprotective modalities to improve photoreceptor survival. Similar to cancer cells, photoreceptors maintain pyruvate kinase muscle isoform 2 (PKM2) expression, which is a critical regulator in aerobic glycolysis. Unlike PKM1, which has constitutively high catalytic activity, PKM2 is under complex regulation. Recently, we demonstrated that genetically reprogramming photoreceptor metabolism via PKM2-to-PKM1 substitution is a promising neuroprotective strategy. Here, we explored the neuroprotective effects of pharmacologically activating PKM2 via ML-265, a small molecule activator of PKM2, during acute outer retinal stress. We found that ML-265 increased PKM2 activity in 661W cells and in vivo in rat eyes without affecting the expression of genes involved in glucose metabolism. ML-265 treatment did, however, alter metabolic intermediates of glucose metabolism and those necessary for biosynthesis in cultured cells. Long-term exposure to ML-265 did not result in decreased photoreceptor function or survival under baseline conditions. Notably, though, ML-265-treatment did reduce entrance into the apoptotic cascade in in vitro and in vivo models of outer retinal stress. These data suggest that reprogramming metabolism via activation of PKM2 is a novel, and promising, therapeutic strategy for photoreceptor neuroprotection.
Landscape of Dysregulated Placental RNA Editing Associated with Preeclampsia
Authors: Yang Xiaoxue , Yang Jing , Liang Xiaozhen , Chen Qian , Jiang Sijia , Liu Haihua , Gao Yue , Ren Zhonglu , Yu Yanhong , Zhong Mei , Yang Xinping
Published: October 2019

Dysregulated RNA editing is well documented in several diseases such as cancer. The extent to which RNA editing might be involved in diseases originated in the placenta remains unknown, because RNA editing has rarely been studied in the placenta. Here, we have systematically profiled RNA editome on the placentae from 9 patients with early-onset severe preeclampsia (EOSPE) and 32 normal subjects, and a widespread RNA editing dysregulation in EOSPE has been identified. The mis-edited gene set is enriched with known preeclampsia-associated genes and differentially expressed genes in EOSPE. The “RNA editing events” at two microRNA binding sites in 3’-UTR of the LEP mRNA were generated, which could lead to increased expression level of LEP in trophoblast cells. Upregulation of LEP were also observed in the placentae of PE patients. These results suggest that widespread placental RNA editing may be involved in placental development and dysregulation of RNA editing in the placenta may contribute to the pathogenesis of preeclampsia.
A Quantitative Proteome Map of the Human Body
Authors: Jiang Lihua , Wang Meng , Lin Shin , Jian Ruiqi , Li Xiao , Chan Joanne , Fang Huaying , Dong Guanlan ,   GTEx Consortium, Tang Hua , Snyder Michael P.
Published: October 2019

Determining protein levels in each tissue and how they compare with RNA levels is important for understanding human biology and disease as well as regulatory processes that control protein levels. We quantified the relative protein levels from 12,627 genes across 32 normal human tissue types prepared by the GTEx project. Known and new tissue specific or enriched proteins (5,499) were identified and compared to transcriptome data. Many ubiquitous transcripts are found to encode highly tissue specific proteins. Discordance in the sites of RNA expression and protein detection also revealed potential sites of synthesis and action of protein signaling molecules. Overall, these results provide an extraordinary resource, and demonstrate that understanding protein levels can provide insights into metabolism, regulation, secretome, and human diseases.

Quantitative proteome study of 32 human tissues and integrated analysis with transcriptome data revealed that understanding protein levels could provide in-depth knowledge to post transcriptional or translational regulations, human metabolism, secretome, and diseases.
Disentangling the Behavioural Variability of Confined Cell Migration
Authors: Brückner David B. , Fink Alexandra , Rädler Joachim O. , Broedersz Chase P.
Published: October 2019

Cell-to-cell variability is inherent to numerous biological processes, including cell migration. Quantifying and characterizing the variability of migrating cells is challenging, as it requires monitoring many cells for long time windows under identical conditions. Here, we observe the migration of single human breast cancer cells (MDA-MB-231) in confining two-state micropatterns. To describe the stochastic dynamics of this confined migration, we employ a dynamical systems approach. We identify statistics to measure the behavioural variance of the migration, which significantly exceed those predicted by a population-averaged stochastic model. This additional variance can be explained by the combination of an ‘aging’ process and population heterogeneity. To quantify population heterogeneity, we decompose the cells into subpopulations of slow and fast cells, revealing the presence of distinct classes of dynamical systems describing the migration, ranging from bistable to limit cycle behaviour. Our findings highlight the breadth of migration behaviours present in cell populations.
Complex roles for reactive astrocytes in the triple transgenic mouse model of Alzheimer disease
Authors: Guillemaud Océane , Ceyzériat Kelly , Saint-Georges Thomas , Cambon Karine , Petit Fanny , Ben Haim Lucile , Carrillo-de Sauvage Maria-Angeles , Guillermier Martine , Bernier Sueva , Hérard Anne-Sophie , Joséphine Charlène , Pierre Bémelmans Alexis , Brouillet Emmanuel , Hantraye Philippe , Bonvento Gilles , Escartin Carole
Published: October 2019

In Alzheimer disease (AD), astrocytes undergo complex changes and become reactive. The consequences of this reaction are still unclear. To evaluate the net impact of reactive astrocytes in AD, we recently developed viral vectors targeting astrocytes that either activate or inhibit the JAK2-STAT3 pathway, a central cascade controlling astrocyte reaction.

We aimed to evaluate whether reactive astrocytes contribute to Tau as well as amyloid pathologies in the hippocampus of 3xTg-AD mice, an AD model that develops Tau hyperphosphorylation and aggregation in addition to amyloid deposition. JAK2-STAT3 pathway-mediated modulation of reactive astrocytes in the hippocampus of 3xTg-AD mice, did not significantly influence Tau phosphorylation or amyloid processing and deposition, at early, advanced and terminal stage of the disease. Interestingly, inhibition of the JAK2-STAT3 pathway in hippocampal astrocytes did not improve short-term spatial memory in the Y maze but it reduced anxiety in the elevated plus maze. Our unique approach to specifically manipulate reactive astrocytes in situ show these cells may impact behavioral outcomes without influencing Tau or amyloid pathology.
Environmental DNA survey captures patterns of fish and invertebrate diversity across a tropical seascape
Authors: Nguyen Bryan N. , Shen Elaine W. , Seemann Janina , Correa Adrienne M.S. , O’Donnell James L. , Altieri Andrew H. , Knowlton Nancy , Crandall Keith A. , Egan Scott P. , McMillan W. Owen , Leray Matthieu
Published: October 2019

Accurate, rapid, and comprehensive biodiversity assessments are critical for investigating ecological processes and supporting conservation efforts. Environmental DNA (eDNA) surveys show promise as a way to effectively characterize fine-scale patterns of community composition, but most studies to date have evaluated its effectiveness in single habitats and for conspicuous taxonomic groups in temperate ecosystems. We tested whether a single PCR survey of eDNA in seawater using a broad metazoan primer could identify differences in community composition between five adjacent habitats at 19 sites across a tropical Caribbean bay in Panama. We paired this effort with visual fish surveys to compare methods for a conspicuous taxonomic group. eDNA revealed a tremendous diversity of animals (8,586 operational taxonomic units), including many small taxa that would be undetected in traditional in situ surveys. Fish comprised only 0.07% of the taxa detected by a broad COI primer, yet included 43 species not observed in the visual survey. eDNA revealed significant differences in fish and invertebrate community composition across adjacent habitats and areas of the bay driven in part by taxa known to be habitat-specialists or tolerant to wave action. Our results demonstrate the ability of broad eDNA surveys to identify biodiversity patterns in the ocean.
Fatty acid bioconversion in harpacticoid copepods in a changing environment: a transcriptomic approach
Authors: Boyen Jens , Fink Patrick , Mensens Christoph , Hablützel Pascal I. , De Troch Marleen
Published: October 2019

By 2100, global warming is predicted to significantly reduce the capacity of marine primary producers for long-chain polyunsaturated fatty acid (LC-PUFA) synthesis. Primary consumers such as harpacticoid copepods (Crustacea) might mitigate the resulting adverse effects on the food web by increased LC-PUFA bioconversion. Here, we present a high-quality de novo transcriptome assembly of the copepod Platychelipus littoralis, exposed to changes in both temperature (+3°C) and dietary LC-PUFA availability. Using this transcriptome, we detected multiple transcripts putatively encoding for LC-PUFA-bioconverting front-end fatty acid desaturases and elongases, and performed phylogenetic analyses to identify their relationship with sequences of other (crustacean) taxa. While temperature affected the absolute fatty acid concentrations in copepods, LC-PUFA levels remained unaltered even when copepods were fed a LC-PUFA-deficient diet. While this suggests plasticity of LC-PUFA bioconversion within P. littoralis, none of the putative front-end desaturase or elongase transcripts were differentially expressed under the applied treatments. Nevertheless, the transcriptome presented here provides a sound basis for future ecophysiological research on harpacticoid copepods.
A sub-exponential branching process to study early epidemic dynamics with application to Ebola
Authors: Zarebski Alexander E. , Moss Robert , McCaw James M.
Published: October 2019

Exponential growth is a mathematically convenient model for the early stages of an outbreak of an infectious disease. However, for many pathogens (such as Ebola virus) the initial rate of transmission may be sub-exponential, even before transmission is affected by depletion of susceptible individuals.

We present a stochastic multi-scale model capable of representing sub-exponential transmission: an in-homogeneous branching process extending the generalised growth model. To validate the model, we fit it to data from the Ebola epidemic in West Africa (2014–2016). We demonstrate how a branching process can be fit to both time series of confirmed cases and chains of infection derived from contact tracing. Our estimates of the parameters suggest transmission of Ebola virus was sub-exponential during this epidemic. Both the time series data and the chains of infections lead to consistent parameter estimates. Differences in the data sets meant consistent estimates were not a foregone conclusion. Finally, we use a simulation study to investigate the properties of our methodology. In particular, we examine the extent to which the estimates obtained from time series data and those obtained from chains of infection data agree.

Our method, based on a simple branching process, is well suited to real-time analysis of data collected during contact tracing. Identifying the characteristic early growth dynamics (exponential or sub-exponential), including an estimate of uncertainty, during the first phase of an epidemic should prove a useful tool for preliminary outbreak investigations.

Author Summary

Epidemic forecasts have the potential to support public health decision making in outbreak scenarios for diseases such as Ebola and influenza. In particular, reliable predictions of future incidence data may guide surveillance and intervention responses. Existing methods for producing forecasts, based upon mechanistic transmission models, often make an implicit assumption that growth is exponential, at least while susceptible depletion remains negligible. However, empirical studies suggest that many infectious disease outbreaks display sub-exponential growth early in the epidemic. Here we introduce a mechanistic model of early epidemic growth that allows for sub-exponential growth in incidence. We demonstrate how the model can be applied to the types of data that are typically available in (near) real-time, including time series data on incidence as well as individual-level case series and chains of transmission data. We apply our methods to publically available data from the 2014–2016 West Africa Ebola epidemic and demonstrate that early epidemic growth was sub-exponential. We also investigate the statistical properties of our model through a simulation re-estimation study to identify it performance characteristics and avenues for further methodological research.