bluuebunny/crossref_metadata_2025 huggingface dataset:
BioKC: a collaborative platform for systems biology model curation and annotation
Authors: Vega Carlos , Grouès Valentin , Ostaszewski Marek , Schneider Reinhard , Satagopam Venkata
Published: October 2020

Curation of biomedical knowledge into standardised and inter-operable systems biology models is essential for studying complex biological processes. However, systems-level curation is a laborious manual process, especially when facing ever increasing growth of domain literature. Currently, these systems-level curation efforts concentrate around dedicated pathway databases, with a limited input from the research community. The demand for systems biology knowledge increases with new findings demonstrating elaborate relationships between multiple molecules, pathways and cells. This new challenge calls for novel collaborative tools and platforms allowing to improve the quality and the output of the curation process. In particular, in the current systems biology environment, curation tools lack reviewing features and are not well suited for an open, community-based curation workflows. An important concern is the complexity of the curation process and the limitations of the tools supporting it. Currently, systems-level curation combines model-building with diagram layout design. However, diagram editing tools offer limited annotation features. On the other hand, text-oriented tools have insufficient capabilities representing and annotating relationships between biological entities. Separating model curation and annotation from diagram editing enables iterative and distributed building of annotated models. Here, we presentBioKC(BiologicalKnowledgeCuration), a web-based collaborative platform for the curation and annotation of biomedical knowledge following the standard data model from Systems Biology Markup Language (SBML).
The economics of organellar gene loss and endosymbiotic gene transfer
Authors: Kelly Steven
Published: October 2020

The endosymbiosis of the bacterial progenitors of mitochondrion and the chloroplast are landmark events in the evolution of life on earth. While both organelles have retained substantial proteomic and biochemical complexity, this complexity is not reflected in the content of their genomes. Instead, the organellar genomes encode fewer than 5% of genes found in living relatives of their ancestors. While many of the 95% of missing organellar genes have been discarded, others have been transferred to the host nuclear genome through a process known as endosymbiotic gene transfer. Here we demonstrate that the difference in the per-cell copy number of the organellar and nuclear genomes presents an energetic incentive to the cell to either delete genes or transfer them to the nuclear genome. We show that, for the majority transferred genes, the energy saved by nuclear-transfer exceeds the costs incurred from importing the encoded protein into the organelle where it can provide its function. Finally, we show that the net energy saved by endosymbiotic gene transfer can constitute an appreciable proportion of total cellular energy budgets, and is therefore sufficient to impart a selectable advantage to the cell. Thus, reduced cellular cost and improved energy efficiency likely played a role in the reductive evolution of mitochondrial and chloroplast genomes and the transfer of organellar genes to the nuclear genome.

Significance statement

The endosymbioses of the mitochondrion and the chloroplast were each followed by substantial gene loss and transfer of organellar genes to the nuclear genome. Here we show that the high per-cell copy number of these organellar genomes creates an energetic incentive for the cell to discard genes or transfer them to the nuclear genome. Thus, organellar gene loss and endosymbiotic gene transfer can be intrinsically advantageous to the cell.
ThePhaeodactylum tricornutumDiaminopimelate Decarboxylase was Acquired via Horizontal Gene Transfer from Bacteria and Displays Substrate Promiscuity
Authors: Bielinski Vincent A. , Brunson John K. , Ghosh Agnidipta , Moosburner Mark A. , Garza Erin A. , Fussy Zoltan , Bai Jing , McKinnie Shaun M.K. , Moore Bradley S. , Allen Andrew E. , Almo Steven C. , Dupont Christopher L.
Published: October 2020

Diatoms are predicted to synthesize certain amino acids within the chloroplast, including L-lysine via a diaminopimelate-dependent pathway. Herein, we report that the model diatom,Phaeodactylum tricornutum, possesses a chimeric lysine biosynthetic pathway, which coalesces bacterial and plant genes, and is terminated by a chloroplast-localized diaminopimelate decarboxylase (DAPDC,PtLYSA). We show that while RNAi ablation ofPtLYSAis either synthetically lethal or concomitant with a slower growth rate, Cas9-mediated mutagenesis ofPtLYSAresults in recovery of heterozygous cells lines, suggesting thatPtLYSAis an essential gene. Previously characterized DAPDCs are unique within the PLP-dependent decarboxylases where catalysis occurs at the D-stereocenter of the substrate and display a strict stereochemical preference for a (D,L)- ormeso-substrate and not the D,D- or L,L-isomers of diaminopimelate (DAP) to synthesize L-lysine. Using decarboxylation assays and differential scanning calorimetry analyses, we validate thatPtLYSA is abona fideDAPDC and uncover its unexpected stereopromiscuous behavior in substrate specificity. The crystal structure ofPtLYSA confirms the enzyme is an obligate homodimer in which both protomers reciprocally participate in the active site. The structure underscores features unique to thePtLYSA clan of DAPDC and provides structural insight into the determinants responsible for the substrate-promiscuity observed inPtLYSA.
Improved Wound Closure Rates and Mechanical Properties Resembling Native Skin in Murine Diabetic Wounds Treated with a Tropoelastin and Collagen Wound Healing Device
Authors: Kellar Robert S. , Diller Robert B. , Tabor Aaron J. , Dominguez Dominic D. , Audet Robert G. , Bardsley Tatum A. , Talbert Alyssa J. , Cruz Nathan , Ingraldi Alison , Ensley Burt D.
Published: October 2020

Chronic wounds in patients suffering from type II diabetes mellitus (DMII) where wounds remain open with a complicated pathophysiology, healing, and recovery process is a public health concern. Normal wound healing plays a critical role in wound closure, restoration of mechanical properties, and the biochemical characteristics of the remodeled tissue. Biological scaffolds provide a tissue substitute to help facilitate wound healing by mimicking the extracellular matrix (ECM) of the dermis. In the current study an electrospun biomimetic scaffold, wound healing device (WHD), containing tropoelastin (TE) and collagen was synthesized to mimic the biochemical and mechanical characteristics of healthy human skin. The WHD was compared to a commercially available porcine small intestinal submucosa (SIS) matrix that has been used in both partial and full-thickness wounds, Oasis®Wound Matrix. Wound closure rates, histochemistry, qPCR, and mechanical testing of treated wound sites were evaluated. The WHD in a splinted, full-thickness, diabetic murine wound healing model demonstrated an enhanced rate of wound closure, decreased tissue inflammation, skin organ regeneration, and a stronger and more durable remodeled tissue that more closely mimics native unwounded skin compared to the control device.
Late cortical potentials are not a reliable marker of somatosensory awareness
Authors: Schröder Pia , Nierhaus Till , Blankenburg Felix
Published: October 2020

Two types of scalp-recorded event-related potentials have been proposed as neural correlates of perceptual awareness in humans: an early, modality-specific negativity and a late, modality-independent positivity. However, whether these potentials genuinely reflect perception or result from task demands remains controversial. To address this question, we compared results from a classical somatosensory detection task (direct report task) to a somatosensory-visual matching task, in which overt reports were decorrelated from target detection, equated the behavioural relevance of detected and undetected stimuli, and mitigated the influence of attentional processes. By means of Bayesian model selection, we show that the early N140 component was the first to reflect target detection in both tasks, whereas the late P300 component was task dependent, with strong detection effects in the direct report task that were absent in the matching task. We conclude that the P300 is not a genuine correlate of somatosensory awareness but reflects postperceptual processing.
The branching code: a model of actin-driven dendrite arborisation
Authors: Stürner Tomke , Castro André Ferreira , Philipps Maren , Cuntz Hermann , Tavosanis Gaia
Published: October 2020

Dendrites display a striking variety of neuronal type-specific morphologies, but the mechanisms and principles underlying such diversity remain elusive. A major player in defining the morphology of dendrites is the neuronal cytoskeleton, including evolutionarily conserved actin-modulatory proteins (AMPs). Still, we lack a clear understanding of how AMPs might support developmental phenomena such as neuron-type specific dendrite dynamics. To address precisely this level ofin vivospecificity, we concentrated on a defined neuronal type, the class III dendritic arborisation (c3da) neuron ofDrosophilalarvae, displaying actin-enriched short terminal branchlets (STBs). Computational modelling reveals that the main branches of c3da neurons follow a general growth model based on optimal wiring, but the STBs do not. Instead, model STBs are defined by a short reach and a high affinity to grow towards the main branches. We thus concentrated on c3da STBs and developed new methods to quantitatively describe dendrite morphology and dynamics based onin vivotime-lapse imaging of mutants lacking individual AMPs. In this way, we extrapolated the role of these AMPs in defining STB properties. We propose that dendrite diversity is supported by the combination of a common step, refined by a neuron type-specific second level. For c3da neurons, we present a molecular model of how the combined action of multiple AMPsin vivodefine the properties of these second level specialisations, the STBs.

In brief

A quantitative morphological dissection of the concerted actin-modulatory protein actions provides a model of dendrite branchlet outgrowth.

Highlights

Actin organisation in small terminal branchlets ofDrosophilaclass III dendritic arborisation neurons

Six actin-modulatory proteins individually control the characteristic morphology and dynamics of branchlets

Quantitative tools for dendrite morphology and branch dynamics enable a comparative analysis

A two-step computational growth model reproduces c3da dendrite morphology
Discovering Key Transcriptomic Regulators in Pancreatic Ductal Adenocarcinoma using Dirichlet Process Gaussian Mixture Model
Authors: Mosaddek Hossain Sk Md , Halsana Aanzil Akram , Khatun Lutfunnesa , Ray Sumanta , Mukhopadhyay Anirban
Published: October 2020

Pancreatic Ductal Adenocarcinoma (PDAC) is the most lethal type of pancreatic cancer (PC), late detection of which leads to its therapeutic failure. This study aims to find out key regulatory genes and their impact on the progression of the disease helping the etiology of the disease which is still largely unknown. We leverage the landmark advantages of time-series gene expression data of this disease, and thereby the identified key regulators capture the characteristics of gene activity patterns in the progression of the cancer. We have identified the key modules and predicted gene functions of top genes from the compiled gene association network (GAN). Here, we have used the natural cubic spline regression model (splineTimeR) to identify differentially expressed genes (DEG) from the PDAC microarray time-series data downloaded from gene expression omnibus (GEO). First, we have identified key transcriptomic regulators (TR) and DNA binding transcription factors (DbTF). Subsequently, the Dirichlet process and Gaussian process (DPGP) mixture model is utilized to identify the key gene modules. A variation of the partial correlation method is utilized to analyze GAN, which is followed by a process of gene function prediction from the network. Finally, a panel of key genes related to PDAC is highlighted from each of the analyses performed.

Please note: Abbreviations should be introduced at the first mention in the main text – no abbreviations lists. Suggested structure of main text (not enforced) is provided below.
Simultaneous orientation and 3D localization microscopy with a Vortex point spread function
Authors: Hulleman Christiaan N. , Thorsen Rasmus Ø. , Stallinga Sjoerd , Rieger Bernd
Published: October 2020

We have developed an engineered Point Spread Function (PSF) to enable the simultaneous estimation of dipole orientation, 3D position and degree of rotational constraint of single-molecule emitters from a single 2D focal plane. Besides giving access to orientation information, the Vortex PSF along with the vectorial PSF fitter avoids localization bias common in localization microscopy for fixed dipole emitters. We demonstrate this technique on reorienting single-molecules and using binding-activated localization microscopy on DNA intercalators, corroborating perpendicular azimuthal angles to the DNA axis for in-plane emitters but find a non-uniform distribution as a function of the polar angle. The Vortex PSF is realized by an affordable glass phase mask and has a compact footprint that can easily be combined with localization microscopy techniques on rotationally constrained emitters.
A likelihood-based deconvolution of bulk gene expression data using single-cell references
Authors: Erdmann-Pham Dan D. , Fischer Jonathan , Hong Justin , Song Yun S.
Published: October 2020

Direct comparison of bulk gene expression profiles is complicated by distinct cell type mixtures in each sample which obscure whether observed differences are actually due to changes in expression levels themselves or simply due to differing cell type compositions. Single-cell technology has made it possible to measure gene expression in individual cells, achieving higher resolution at the expense of increased noise. If carefully incorporated, such single-cell data can be used to deconvolve bulk samples to yield accurate estimates of the true cell type proportions, thus enabling one to disentangle the effects of differential expression and cell type mixtures. Here, we propose a generative model and a likelihood-based inference method that uses asymptotic statistical theory and a novel optimization procedure to perform deconvolution of bulk RNA-seq data to produce accurate cell type proportion estimates. We demonstrate the effectiveness of our method, called RNA-Sieve, across a diverse array of scenarios involving real data and discuss extensions made uniquely possible by our probabilistic framework, including a demonstration of well-calibrated confidence intervals.
Intestinal epithelium-derived high density lipoprotein restrains liver injury via the portal vein
Authors: Han Yong-Hyun , Onufer Emily J. , Huang Li-Hao , Czepielewski Rafael S. , Warner Brad W. , Randolph Gwendalyn J.
Published: October 2020

Assembly of high density lipoprotein (HDL) requires apoA1 and the cholesterol transporter ABCA1. Although the liver generates most HDL in blood, HDL synthesis also occurs in the small intestine. However, distinct functions for intestinal HDL are unknown. Here we show that HDL in the portal vein, which connects intestine to liver, derivesd mainly from intestine and potently neutralizes lipopolysaccharide (LPS). In a mouse model of short bowel syndrome where liver inflammation and fibrosis was driven by the LPS receptor TLR4, loss of intestine-derived HDL worsened liver injury, whereas liver status was improved by therapeutics that elevated and depended upon intestinal HDL production. Thus, protection of the liver from injury in response to gut-derived signals like LPS is a major function of intestinally synthesized HDL.
A hybrid mesh and voxel based Monte Carlo algorithm for accurate and efficient photon transport modeling in complex bio-tissues
Authors: Yan Shijie , Fang Qianqian
Published: October 2020

Over the past decade, an increasing body of evidence has suggested that threedimensional (3-D) Monte Carlo (MC) light transport simulations are affected by the inherent limitations and errors of voxel-based domain boundaries. In this work, we specifically address this challenge using a hybrid MC algorithm, namely split-voxel MC or SVMC, that combines both mesh and voxel domain information to greatly improve MC simulation accuracy while remaining highly flexible and efficient in parallel hardware, such as graphics processing units (GPU). We achieve this by applying a marching-cubes algorithm to a pre-segmented domain to extract and encode sub-voxel information of curved surfaces, which is then used to inform ray-tracing computation within boundary voxels. This preservation of curved boundaries in a voxel data structure demonstrates significantly improved accuracy in several benchmarks, including a human brain atlas. The accuracy of the SVMC algorithm is comparable to that of mesh-based MC (MMC), but runs 2x-6x faster and requires only a lightweight preprocessing step. The proposed algorithm has been implemented in our open-source software and is freely available athttp://mcx.space.
Standard and Non-Standard Measurements of Acidity and the Bacterial Ecology of Northern Temperate Mineral Soils
Authors: Braus Michael J. , Whitman Thea
Published: October 2020

Databases of soil pH values today guide the decisions of land managers and the experimental designs of microbiologists and biogeochemists. Soil acidity underpins fundamental properties and functions in the soil, such as the solubilities of exchangeable ions and nutrients, or bacterial use of gradients of internal and external acidity to generate ATP and turn flagellar motors. Therefore, it is perhaps unsurprising that soil pH has emerged as the strongest predictor of soil bacterial community composition. However, the measurement of these particular values today does not address whether soil pH accurately represents the in situ acidity of soil microhabitats where microorganisms survive and reproduce. This study analyzes and compares soils of a large-scale natural soil pH gradient and a long-term experimental soil pH gradient for the purposes of testing new methods of measuring and interpreting soil acidity when applied to soil ecology. We extracted and prepared soil solutions using laboratory simulation of levels of carbon dioxide and soil moisture more typical of soil conditions while also miniaturizing extraction methods using a centrifuge for extractions. The simulation of in situ soil conditions resulted in significantly different estimates of soil pH. Furthermore, for soils from the long-term experimental soil pH gradient trial, the simulated soil pH values substantially improved predictions of bacterial community composition (from R2 = 0.09 to R2 = 0.16). We offer suggestions and cautions for researchers considering how to better represent soil pH as it exists in situ.
Development of a species diagnostic molecular tool for an invasive pest,Mythimna loreyiusing LAMP
Authors: Nam Hwa Yeun , Kwon Min , Kim Hyun Ju , Kim Juil
Published: October 2020

TheMythimna loreyi(Duponchel) is one of the well-known a noctuid pest in Africa, Australia, and many Asian countries. This species has recently emerged as an invasive pest of some cereal crops in Korea. However, it is extremely difficult to identify the morphologically similar species,Mythimna separate, which occur at the cornfield in the larvae stage. Therefore, it is hard to accurately investigate invasive pests. In this study, the LAMP assay was developed for rapid, simple, effective species identification. By analyzing the mt genome, the species-specific sequence was found at the coding region of the NADH dehydrogenase subunit 5 gene. Based on this unique sequence, four LAMP primers and two loop primers were designed. The F3 and B3 primers were able to diagnose species-specific in general and multiplex PCR, and specifically reacted within the inner primers in LAMP assay. The optimal incubation condition of the LAMP assay was 61 □ for 60 minutes with four LAMP primers, though additional loop primer, BF and LF, did not significantly shorten the amplification time. The broad range of DNA concentration was workable in LAMP assay, in which the minimum detectable DNA concentration was 100 pg. Here, DNA releasing method was applied which took five minutes of incubation at 95 □ without the DNA extraction process, and only some pieces of tissue from larvae and adult samples were needed. The incidence of invasive pests is gradually diversifying, therefore, this simple and accurate LAMP assay possibly applied in the intensive field monitoring for the invasive pests and integrated management ofMythimna loreyi.
scAAVengr: Single-cell transcriptome-based quantification of engineered AAVs in non-human primate retina
Authors: Öztürk Bilge E. , Johnson Molly E. , Kleyman Michael , Turunç Serhan , He Jing , Jabalameli Sara , Xi Zhouhuan , Visel Meike , Dufour Valérie L. , Iwabe Simone , Marinho Felipe Pompeo , Aguirre Gustavo D. , Sahel José-Alain , Schaffer David V. , Pfenning Andreas R. , Flannery John G. , Beltran William A. , Stauffer William R. , Byrne Leah C.
Published: October 2020

Adeno-associated virus (AAV)-mediated gene therapies are rapidly advancing to the clinic, and AAV engineering has resulted in vectors with increased ability to deliver therapeutic genes. Although the choice of vector is critical, quantitative comparison of AAVs, especially in large animals, remains challenging. Here, we developed an efficient single-cell AAV engineering pipeline (scAAVengr) to quantify efficiency of AAV-mediated gene expression across all cell types. scAAVengr allows for definitive, head-to-head comparison of vectors in the same animal. To demonstrate proof-of-concept for the scAAVengr workflow, we quantified – with cell-type resolution – the abilities of naturally occurring and newly engineered AAVs to mediate gene expression in primate retina following intravitreal injection. A top performing variant, K912, was used to deliver SaCas9 and edit the rhodopsin gene in macaque retina, resulting in editing efficiency similar to infection rates detected by the scAAVengr workflow. These results validate scAAVengr as a powerful method for development of AAV vectors.
Museum genomics illuminate the high specificity of a bioluminescent symbiosis across a genus of reef fish
Authors: Gould Alison L. , Fritts-Penniman Allison , Gaisiner Ana
Published: October 2020

Symbiotic relationships between bioluminescent bacteria and fishes have evolved multiple times across hundreds of fish taxa, but relatively little is known about the specificity of these associations and how conserved they have been through time. This study describes the degree of specificity of a bioluminescent symbiosis between cardinalfishes in the genus Siphamia and luminous bacteria in the Vibrio family. Primarily using museum specimens, we investigate the co-divergence of host and symbiont and test for patterns of divergence that correlate with both biogeography and time. Contrary to expectations, we determined that the light organ symbionts of all 14 Siphamia species examined belong to one genetic clade of Photobacterium mandapamensis (Clade II), indicating that the association is highly specific and conserved across the host genus. Thus, we did not find evidence of codivergence among hosts and symbionts. We did observe that symbionts hosted by individuals sampled from colder water regions were more divergent, containing more than three times as many single nucleotide polymorphisms than the rest of the symbionts examined. Overall our findings indicate that the symbiosis between Siphamia fishes and P. mandapamensis Clade II has been highly conserved across a broad geographic range and through time despite the facultative nature of the bacterial symbiont. These results suggest that this bioluminescent symbiosis could have played a key role in the evolution of the host genus and that there are conserved mechanisms regulating its specificity that have yet to be defined.
Potent mouse monoclonal antibodies that block SARS-CoV-2 infection
Authors: Guo Youjia , Kawaguchi Atsushi , Takeshita Masaru , Sekiya Takeshi , Hirohama Mikako , Yamashita Akio ,   the Keio Donner Project, Siomi Haruhiko , Murano Kensaku
Published: October 2020

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has developed into a global pandemic since its first outbreak in the winter of 2019. An extensive investigation of SARS-CoV-2 is critical for disease control. Various recombinant monoclonal antibodies of human origin that neutralize SARS-CoV-2 infection have been isolated from convalescent patients and will be applied as therapies and prophylaxis. However, the need for dedicated monoclonal antibodies in molecular pathology research is not fully addressed. Here, we produced mouse anti-SARS-CoV-2 spike monoclonal antibodies that exhibit not only robust performance in immunoassays including western blotting, ELISA, immunofluorescence, and immunoprecipitation, but also neutralizing activity against SARS-CoV-2 infectionin vitro. Our monoclonal antibodies are of mouse origin, making them compatible with the experimental immunoassay setups commonly used in basic molecular biology research laboratories, and large-scale production and easy distribution are guaranteed by conventional mouse hybridoma technology.
Assessingin vivomutation frequencies and creating a high-resolution genome-wide map of fitness costs of Hepatitis C virus
Authors: Tisthammer Kaho H. , Solis Caroline , Oracles Faye , Nzerem Madu , Winstead Ryan , Dong Weiyan , Joy Jeffrey B. , Pennings Pleuni S.
Published: October 2020

Like many viruses, Hepatitis C Virus (HCV) has a high nutation rate, which helps the virus adapt quickly, but mutations come with fitness costs. Fitness costs can be studied by different approaches, such as experimental or frequency-based approaches. The frequency-based approach is particularly useful to estimatein vivofitness costs, but this approach works best with deep sequencing data from many hosts, are. In this study, we applied the frequency-based approach to a large dataset of 195 patients and estimated the fitness costs of mutations at 7957 sites along the HCV genome. We used beta regression and random forest models to better understand how different factors influenced fitness costs. Our results revealed that costs of nonsynonymous mutations were three times higher than those of synonymous mutations, and mutations at nucleotides A or T had higher costs than those at C or G. Genome location had a modest effect, with lower costs for mutations in HVR1 and higher costs for mutations in Core and NS5B. Resistance mutations were, on average, costlier than other mutations. Our results show thatin vivofitness costs of mutations can be virus specific, reinforcing the utility of constructingin vivofitness cost maps of viral genomes.

Author Summary

Understanding how viruses evolve within patients is important for combatting viral diseases, yet studying viruses within patients is difficult. Laboratory experiments are often used to understand the evolution of viruses, in place of assessing the evolution in natural populations (patients), but the dynamics will be different. In this study, we aimed to understand the within-patient evolution of Hepatitis C virus, which is an RNA virus that replicates and mutates extremely quickly, by taking advantage of high-throughput next generation sequencing. Here, we describe the evolutionary patterns of Hepatitis C virus from 195 patients: We analyzed mutation frequencies and estimated how costly each mutation was. We also assessed what factors made a mutation more costly, including the costs associated with drug resistance mutations. We were able to create a genome-wide fitness map of within-patient mutations in Hepatitis C virus which proves that, with technological advances, we can deepen our understanding of within-patient viral evolution, which can contribute to develop better treatments and vaccines.
Forecasting the SARS-CoV-2 effective reproduction number using bulk contact data from mobile phones
Authors: Rüdiger Sten , Konigorski Stefan , Edelman Jonathan , Zernick Detlef , Thieme Alexander , Lippert Christoph
Published: October 2020

Over the last months, cases of SARS-CoV-2 surged repeatedly in many countries and could often be controlled with non-pharmaceutical interventions such as social distancing. We analyzed de-identified GPS tracking data from 1.15 to 1.4 million cell phones in Germany per day between March-November 2020 to identify encounters between individuals and statistically evaluate large-scale contact behavior. Using graph sampling theory we estimated the contact index (CI), a metric for number and heterogeneity of contacts and found that the contact index, and not the total number of contacts, is an accurate predsictor for the effective reproduction number R. A high correlation between CI and R occurring more than two weeks later allows timely assessment of the social behavior well before the infections become detectable. The CI quantifies the role of superspreading and allows assigning risks to specific contact behavior. We provide a critical CI-value beyond which R is expected to rise above 1 and propose to use it to leverage the social distancing interventions for the coming months.
Detecting cryptic clinically-relevant structural variation in exome sequencing data increases diagnostic yield for developmental disorders
Authors: Gardner Eugene J. , Sifrim Alejandro , Lindsay Sarah J. , Prigmore Elena , Rajan Diana , Danecek Petr , Gallone Giuseppe , Eberhardt Ruth Y. , Martin Hilary C. , Wright Caroline F. , FitzPatrick David R. , Firth Helen V. , Hurles Matthew E.
Published: October 2020

Structural Variation (SV) describes a broad class of genetic variation greater than 50bps in size. SVs can cause a wide range of genetic diseases and are prevalent in rare developmental disorders (DD). Patients presenting with DD are often referred for diagnostic testing with chromosomal microarrays (CMA) to identify large copy-number variants (CNVs) and/or with single gene, gene-panel, or exome sequencing (ES) to identify single nucleotide variants, small insertions/deletions, and CNVs. However, patients with pathogenic SVs undetectable by conventional analysis often remain undiagnosed. Consequently, we have developed the novel tool ‘InDelible’, which interrogates short-read sequencing data for split-read clusters characteristic of SV breakpoints. We applied InDelible to 13,438 probands with severe DD recruited as part of the Deciphering Developmental Disorders (DDD) study and discovered 64 rare, damaging variants in genes previously associated with DD missed by standard SNV, InDel or CNV discovery approaches. Clinical review of these 64 variants determined that about half (30/64) were plausibly pathogenic. InDelible was particularly effective at ascertaining variants between 21-500 bps in size, and increased the total number of potentially pathogenic variants identified by DDD in this size range by 42.3%. Of particular interest were seven confirmed de novo variants in MECP2 which represent 35.0% of all de novo protein truncating variants in MECP2 among DDD patients. InDelible provides a framework for the discovery of pathogenic SVs that are likely missed by standard analytical workflows and has the potential to improve the diagnostic yield of ES across a broad range of genetic diseases.
Integrative, multi-omics, analysis of blood samples improves model predictions: applications to cancer
Authors: Ponzi Erica , Thoresen Magne , Nøst Therese Haugdahl , Møllersen Kajsa
Published: October 2020

Background

Cancer genomic studies often include data collected from several omics platforms. Each omics data source contributes to the understanding of the underlying biological process via source specific (“individual”) patterns of variability. At the same time, statistical associations and potential interactions among the different data sources can reveal signals from common biological processes that might not be identified by single source analyses. These common patterns of variability are referred to as “shared” or “joint”. In this work, we show how the use of joint and individual components can lead to better predictive models, and to a deeper understanding of the biological process at hand. We identify joint and individual contributions of DNA methylation, miRNA and mRNA expression collected from blood samples in a lung cancer case-control study nested within the Norwegian Women and Cancer (NOWAC) cohort study, and we use such components to build prediction models for case-control and metastatic status. To assess the quality of predictions, we compare models based on simultaneous, integrative analysis of multi-source omics data to a standard non-integrative analysis of each single omics dataset, and to penalized regression models. Additionally, we apply the proposed approach to a breast cancer dataset from The Cancer Genome Atlas.

Results

Our results show how an integrative analysis that preserves both components of variation is more appropriate than standard multi-omics analyses that are not based on such a distinction. Both joint and individual components are shown to contribute to a better quality of model predictions, and facilitate the interpretation of the underlying biological processes in lung cancer development.

Conclusion

In the presence of multiple omics data sources, we recommend the use of data integration techniques that preserve the joint and individual components across the omics sources. We show how the inclusion of such components increases the quality of model predictions of clinical outcomes.
Inorganic and black carbon hotspots constrain blue carbon mitigation services across tropical seagrass and temperate tidal marshes
Authors: Gallagher John Barry , Prahalad Vishnu , Aalders John
Published: October 2020

Total organic carbon (TOC) sediment stocks as a CO2mitigation service requires exclusion of allochthonous black (BC) and particulate inorganic carbon corrected for water– atmospheric equilibrium (PICeq). For the first time, we address this bias for a temperate salt marsh and a coastal tropical seagrass in BC hotspots. Seagrass TOC stocks were similar to the salt marshes with soil depths < 1 m (59.3 ± 11.3 and 74.9 ± 18.9 MgC ha-1, CI 95% respectively) and sequestration rates of 1.134 MgC ha-1yr-1. Both ecosystems showed larger BC constraints than their pristine counterparts. However, the seagrass meadows’ mitigation services were largely constrained by both higher BC/TOC and PICeq/TOC fractions (38.0% ± 6.6% and 43.4% ± 5.9%, CI 95%) and salt marshes around a third (22% ± 10.2% and 6.0% ± 3.1% CI 95%). The results demonstrate a need to account for both BC and PIC within blue carbon mitigation assessments.
Development and characterization of nanobodies specifically targeting the oncogenic Phosphatase of Regenerating Liver-3 (PRL-3)
Authors: Smith Caroline N. , Kihn Kyle , Williamson Zachary A. , Chow K. Martin , Hersh Louis B. , Korotkov Konstantin V. , Deredge Daniel , Blackburn Jessica S.
Published: October 2020

Phosphatase of Regenerating Liver-3 (PRL-3) is associated with cancer progression and metastasis in various solid tumors and leukemias. The mechanisms that drive PRL-3’s oncogenic functions are not well understood, in part due to a lack of research tools available to study this protein. In particular, small molecules do not exhibit binding specificity for PRL-3 over highly homologous family members PRL-1 and PRL-2, and antibodies directed against PRL-3 are limited by assay type. We have begun to address these issues by developing alpaca-derived single domain antibodies, or nanobodies, targeting PRL-3 with a KDof 30-300 nM and no activity towards PRL-1 and PRL-2. Hydrogen deuterium exchange mass spectrometry (HDX-MS) and co-immunoprecipitation with a known PRL-3 substrate showed the nanobodies bind PRL-3 outside of the active site, meaning they can be used to study PRL-3 interaction with binding partners. The nanobodies were also specific to PRL-3 over other PRLs in immunoprecipitation and immunofluorescence experiments in human cancer cells that overexpressed the PRL family. We found that N-terminal tags on PRL-3, such as GFP and FLAG, changed PRL-3 localization compared to untagged protein, indicating that the nanobodies may provide new insights into PRL-3 trafficking and function. The anti-PRL-3 nanobodies represent an important expansion of the research tools available to study PRL-3 function and can be used to define the role of PRL-3 in cancer progression.
Bacterial surface properties influence the activity of the TAT-RasGAP317-326 antimicrobial peptide
Authors: Georgieva Maria , Heinonen Tytti , Vitale Alessandra , Hargraves Simone , Causevic Senka , Pillonel Trestan , Eberl Leo , Widmann Christian , Jacquier Nicolas
Published: October 2020

Antibiotic resistance is an increasing threat for public health, underscoring the need for new antibacterial agents. Antimicrobial peptides (AMPs) represent an alternative to classical antibiotics. TAT-RasGAP317-326 is a recently described AMP effective against a broad range of bacteria, but little is known about the conditions that may influence its activity. Using RNA-sequencing and screening of mutant libraries, we show that Escherichia coli and Pseudomonas aeruginosa respond to TAT-RasGAP317-326 by regulating metabolic and stress response pathways, possibly implicating two-component systems. Our results also indicate that bacterial surface properties, in particular integrity of the lipopolysaccharide layer, influence peptide binding and entry. Finally, we found differences between bacterial species with respect to their rate of resistance emergence against this peptide. Our findings provide the basis for future investigation on the mode of action of this peptide and its potential clinical use as an antibacterial agent.
Transposable element expression at unique loci in single cells with CELLO-seq
Authors: Berrens Rebecca V , Yang Andrian , Laumer Christopher E , Lun Aaron TL , Bieberich Florian , Law Cheuk-Ting , Lan Guocheng , Imaz Maria , Gaffney Daniel , Marioni John C
Published: October 2020

The role of Transposable Elements (TEs) in regulating diverse biological processes, from early development to cancer, is becoming increasing appreciated. However, unlike other biological processes, next generation single-cell sequencing technologies are ill-suited for assaying TE expression: in particular, their highly repetitive nature means that short cDNA reads cannot be unambiguously mapped to a specific locus. Consequently, it is extremely challenging to understand the mechanisms by which TE expression is regulated and how they might themselves regulate other protein coding genes. To resolve this, we introduce CELLO-seq, a novel method and computational framework for performing long-read RNA sequencing at single cell resolution. CELLO-seq allows for full-length RNA sequencing and enables measurement of allelic, isoform and TE expression at unique loci. We use CELLO-seq to assess the widespread expression of TEs in 2-cell mouse blastomeres as well as human induced pluripotent stem cells (hiPSCs). Across both species, old and young TEs showed evidence of locus-specific expression, with simulations demonstrating that only a small number of very young elements in the mouse could not be mapped back to with high confidence. Exploring the relationship between the expression of individual elements and putative regulators revealed surprising heterogeneity, with TEs within a class showing different patterns of correlation, suggesting distinct regulatory mechanisms.
Two independent approaches converge to the cloning of a newLeptosphaeria maculansavirulence effector gene,AvrLmS-Lep2
Authors: Neik Ting Xiang , Ghanbarnia Kaveh , Ollivier Bénédicte , Scheben Armin , Severn-Ellis Anita , Larkan Nicholas J. , Haddadi Parham , Fernando W.G. Dilantha , Rouxel Thierry , Batley Jacqueline , Borhan Hossein M. , Balesdent Marie-Hélène
Published: October 2020

Leptosphaeria maculans, the causal agent of blackleg disease, interacts withBrassica napus(oilseed rape, canola) in a gene-for-gene manner. The avirulence genesAvrLmS and AvrLep2were described to be perceived by the resistance genesRlmSandLepR2, respectively, present in the cultivar Surpass 400. Here we report cloning ofAvrLmSandAvrLep2using two independent methods.AvrLmSwas cloned using combinedin vitrocrossing between avirulent and virulent isolates with sequencing of DNA bulks from avirulent or virulent progeny (Bulked-Segregant-Sequencing) to rapidly identify one candidate avirulence gene present in the effector repertoire ofL. maculans. AvrLep2was cloned using a bi-parental cross of avirulent and virulentL. maculansisolates and a classical map-based cloning approach. Taking these two approaches independently, we found thatAvrLmSandAvrLep2are the same gene. Complementation of virulent isolates with this gene confirmed its role in inducing resistance on Surpass 400 and Topas-LepR2. The gene renamedAvrLmS-Lep2encodes for a small cysteine-rich protein of unknown function with an N-terminal secretory signal peptide, which are common features of the majority of effectors from extracellular fungal plant pathogens. TheAvrLmS-Lep2/LepR2interaction phenotype was found to vary from a typical hypersensitive response to intermediate resistance sometimes at the edge of, or evolving toward, susceptibility depending on the inoculation conditions.AvrLmS-Lep2was nevertheless sufficient to significantly reduce the stem lesion size on plant genotypes withLepR2, indicating the potential efficiency of this resistance to control the disease in the field.
Leveraging high-throughput screening data and conditional generative adversarial networks to advance predictive toxicology
Authors: Green Adrian J. , Mohlenkamp Martin J. , Das Jhuma , Chaudhari Meenal , Truong Lisa , Tanguay Robyn L. , Reif David M.
Published: October 2020

There are currently 85,000 chemicals registered with the Environmental Protection Agency (EPA) under the Toxic Substances Control Act, but only a small fraction have measured toxicological data. To address this gap, high-throughput screening (HTS) methods are vital. As part of one such HTS effort, embryonic zebrafish were used to examine a suite of morphological and mortality endpoints at six concentrations from over 1,000 unique chemicals found in the ToxCast library (phase 1 and 2). We hypothesized that by using a conditional Generative Adversarial Network (cGAN) and leveraging this large set of toxicity data, plus chemical structure information, we could efficiently predict toxic outcomes of untested chemicals. CAS numbers for each chemical were used to generate textual files containing three-dimensional structural information for each chemical. Utilizing a novel method in this space, we converted the 3D structural information into a weighted set of points while retaining all information about the structure.In vivotoxicity and chemical data were used to train two neural network generators. The first used regression (Go-ZT) while the second utilized cGAN architecture (GAN-ZT) to train a generator to produce toxicity data. Our results showed that both Go-ZT and GAN-ZT models produce similar results, but the cGAN achieved a higher sensitivity (SE) value of 85.7% vs 71.4%. Conversely, Go-ZT attained higher specificity (SP), positive predictive value (PPV), and Kappa results of 67.3%, 23.4%, and 0.21 compared to 24.5%, 14.0%, and 0.03 for the cGAN, respectively. By combining both Go-ZT and GAN-ZT, our consensus model improved the SP, PPV, and Kappa, to 75.5%, 25.0%, and 0.211, respectively, resulting in an area under the receiver operating characteristic (AUROC) of 0.663. Considering their potential use as prescreening tools, these models could providein vivotoxicity predictions and insight into untested areas of the chemical space to prioritize compounds for HT testing.

A conditional Generative Adversarial Network (cGAN) can leverage a large chemical set of experimental toxicity data plus chemical structure information to predict the toxicity of untested compounds.
Comparing Fecal, Saliva and Chicha Microbiomes Between Mothers and Children in an Indigenous Ecuadorian Cohort
Authors: Adams Eric , Oliver Andrew , Gille Alexandria , Alaniz Nadia , Jaime Carolina , Patton John , Whiteson Katrine
Published: October 2020

Recent research has elucidated many factors which play a role in the development and composition of human microbiomes. In this study we briefly examine the microbiomes of saliva and fecal samples from 71 indigenous individuals, and chicha samples from 28 single family households in a remote community in the Ecuadorian Amazon. Fecal and saliva samples were collected at two separate time points whereas chicha samples were collected at four time points, once each day of the fermentation process. In total 324 samples were collected: 113 saliva, 108 chicha, and 103 fecal. Microbial composition and diversity were assessed using shotgun metagenome sequence data. Chicha samples were found to be nearly entirely composed of the orderLactobacillales, accounting for 90.1% of the relative abundance. Saliva samples also contained a high relative abundance ofLactobacillales(31.9%) as well as being composed ofNeisseriales(12.8%),Actinomycineae(8.7%),Bacteroidales(7.0%),Clostridiales(6.8%),Micrococcineae(6.5%), andPasteurellales(6.0%). Fecal samples were largely composed of the three ordersClostridiales(33.7%),Bacteroidales(21.9%), andBifidobacteriales(16.5%). Comparison of α-diversity, as calculated by Shannon’s Diversity Index, in mothers and their offspring showed no significant difference between the two groups in either fecal or saliva samples. Comparison of β-diversity in fecal and saliva samples, as calculated by the Bray-Curtis Dissimilarity measure, within household units and between differing households showed that members of the same household were significantly less dissimilar to each other than to members of other households in the community. Average microbiome composition for individuals within fecal and saliva samples was assessed to determine the impact of an individual’s household on the composition of their microbiome. Household was determined to have a significant impact on both fecal and oral microbiome compositions.