bluuebunny/crossref_metadata_2025 huggingface dataset:
SpaGE: Spatial Gene Enhancement using scRNA-seq
Authors: Abdelaal Tamim , Mourragui Soufiane , Mahfouz Ahmed , Reinders Marcel J.T.
Published: May 2020

Single-cell technologies are emerging fast due to their ability to unravel the heterogeneity of biological systems. While scRNA-seq is a powerful tool that measures whole-transcriptome expression of single cells, it lacks their spatial localization. Novel spatial transcriptomics methods do retain cells spatial information but can only measure tens to hundreds of transcripts. To resolve this discrepancy, we developed SpaGE, a method that integrates spatial and scRNA-seq datasets to predict whole-transcriptome expressions in their spatial configuration. Using five dataset-pairs, SpaGE outperformed previously published methods and showed scalability to large datasets. Moreover, SpaGE predicted new spatial gene patterns that are confirmed independently.
Local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits
Authors: Zhang Yiliang , Lu Qiongshi , Ye Yixuan , Huang Kunling , Liu Wei , Wu Yuchang , Zhong Xiaoyuan , Li Boyang , Yu Zhaolong , Travers Brittany G. , Werling Donna M. , Li James J. , Zhao Hongyu
Published: May 2020

Local genetic correlation quantifies the genetic similarity of complex traits in specific genomic regions, which could shed unique light on etiologic sharing and provide additional mechanistic insights into the genetic basis of complex traits compared to global genetic correlation. However, accurate estimation of local genetic correlation remains challenging, in part due to extensive linkage disequilibrium in local genomic regions and pervasive sample overlap across studies. We introduce SUPERGNOVA, a unified framework to estimate both global and local genetic correlations using summary statistics from genome-wide association studies. Through extensive simulations and analyses of 30 complex traits, we demonstrate that SUPERGNOVA substantially outperforms existing methods and identifies 150 trait pairs with significant local genetic correlations. In particular, we show that the positive, consistently-identified, yet paradoxical genetic correlation between autism spectrum disorder and cognitive performance could be explained by two etiologically-distinct genetic signatures with bidirectional local genetic correlations. We believe that statistically-rigorous local genetic correlation analysis could accelerate progress in complex trait genetics research.
Whole-brain modelling of resting state fMRI differentiates ADHD subtypes and facilitates stratified neuro-stimulation therapy
Authors: Iravani Behzad , Arshamian Artin , Fransson Peter , Kaboodvand Neda
Published: May 2020

Recent advances in non-linear computational and dynamical modelling have opened up the possibility to param etrize dynamic neural mechanisms that drive complex behavior. Importantly, building models of neuronal processes is of key importance to fully understand disorders of the brain as it may provide a quantitative platform that is capable of binding multiple neurophysiological processes to phenotype profiles. In this study, we apply a newly developed adaptive frequency-based model of whole-brain oscillations to resting-state fMRI data acquired from healthy controls and a cohort of attention deficit hyperactivity disorder (ADHD) subjects. As expected, we found that healthy control subjects differed from ADHD in terms of attractor dynamics. However, we also found a marked dichotomy in neural dynamics within the ADHD cohort. Next, we classified the ADHD group according to the level of distance of each individual’s empirical network from the two model-based simulated networks. Critically, the model was mirrored in the empirical behavior data with the two ADHD subgroups displaying distinct behavioral phenotypes related to emotional instability (i.e., depression and hypomanic personality traits). Finally, we investigated the applicability and feasibility of our whole-brain model in a therapeutic setting by conducting in silico excitatory stimulations to parsimoniously mimic clinical neuro-stimulation paradigms in ADHD. We tested the effect of stimulating any individual brain region on the key network measures derived from the simulated brain network and its contribution in rectifying the brain dynamics to that of the healthy brain, separately for each ADHD subgroup. This showed that this was indeed possible for both subgroups. However, the current effect sizes were small suggesting that the stimulation protocol needs to be tailored at the individual level. These findings demonstrate the potential of this new modelling framework to unveil hidden neurophysiological profiles and establish tailored clinical interventions.
A Comparison of ‘Pruning’ During Multi-Step Planning in Depressed and Healthy Individuals
Authors: Faulkner Paul , Huys Quentin J.M. , Renz Daniel , Eshel Neir , Pilling Stephen , Dayan Peter , Roiser Jonathan P.
Published: May 2020

Background

Real-life decisions are often complex because they involve making sequential choices that constrain future options. We have previously shown that to render such multi-step decisions manageable, people “prune” (i.e. selectively disregard) branches of decision trees that contain negative outcomes. We have theorized that sub-optimal pruning contributes to depression by promoting an oversampling of branches that result in unsavoury outcomes, which results in a negatively-biased valuation of the world. However, no study has tested this theory in depressed individuals.

Methods

Thirty unmedicated depressed and 31 healthy participants were administered a sequential reinforcement-based decision-making task to determine pruning behaviours, and completed measures of depression and anxiety. Computational, Bayesian and frequentist analyses examined group differences in task performance and relationships between pruning and depressive symptoms.

Results

Consistent with prior findings, participants robustly pruned branches of decision trees that began with large losses, regardless of the potential utility of those branches. However, there was no group difference in pruning behaviours. Further, there was no relationship between pruning and levels of depression/anxiety.

Limitations

The relatively small sample size limited the examination of individual differences. The use of other heuristics that are used to render complex decisions feasible, such as memoization and fragmentation, were not examined.

Conclusions

We found no evidence that sub-optimal pruning is evident in depression. Future research could determine whether maladaptive pruning behaviours are observable in specific sub-groups of depressed patients (e.g. in treatment-resistant individuals), or whether misuse of other heuristics may contribute to depression.
Diversity, host ranges, and potential drivers of speciation among the inquiline enemies of oak gall wasps
Authors: Ward Anna KG , Sheikh Sofia I , Forbes Andrew A
Published: May 2020

Animals that exploit an extended phenotype (e.g., residences, resources, etc.) of other animals are called inquilines. Not strictly parasites, inquilines may nevertheless possess specialized traits that adapt them to particular dimensions of the extended phenotype of their “host”. These adaptations to host traits can in turn lead to fitness tradeoffs that restrict the host range of an inquiline such that shifts to novel hosts might trigger inquiline diversification. Speciationviahost shifting has been studied in many animal parasites, but we know far less about the role of host shifts in inquiline speciation.Synergus(Hymenoptera: Cynipidae: Synergini) is a speciose but taxonomically-challenging group of inquilines that feed on the tissue of galls induced by oak gall wasps (Hymenoptera: Cynipidae: Cynipini). Currently too little is known about NearcticSynergusdiversity or host associations to evaluate whether and how host use affects their diversification. Here, we report on a large collection ofSynergusreared from galls of 33 oak gall wasp species in the upper Midwestern United States. We integrated DNA barcodes, morphology, ecology, and phenology to delimit putative species ofSynergusand describe their host ranges. We find evidence of at least 23Synergusspecies associated with the 33 gall wasp hosts. At least five previously describedSynergusspecies are each a complex of two to five species, while three species fit no prior description. We also find strong evidence that oak tree section and host gall morphology define axes of specialization forSynergus. Without over-interpreting our singlegene tree, it is clear that the North AmericanSynergushave experienced several transitions among gall hosts and tree habitats and that host-use is correlated with reproductive isolation, though it remains too early to tell whether shifts to new hosts are the initiators of speciation events inSynergusinquilines of oak gall wasps, or if host shifts occur after reproductive isolation has already evolved.
Generating synthetic signaling networks for in silico modeling studies
Authors: Xu Jin , Wiley H Steven , Sauro Herbert M
Published: May 2020

Predictive models of signaling pathways have proven to be difficult to develop. Traditional approaches to developing mechanistic models rely on collecting experimental data and fitting a single model to that data. This approach works for simple systems but has proven unreliable for complex systems such as biological signaling networks. Thus, there is a need to develop new approaches to create predictive mechanistic models of complex systems. To meet this need, we developed a method for generating artificial signaling networks that were reasonably realistic and thus could be treated as ground truth models. These synthetic models could then be used to generate synthetic data for developing and testing algorithms designed to recover the underlying network topology and associated parameters. We defined the reaction degree and reaction distance to measure the topology of reaction networks, especially to consider enzymes. To determine whether our generated signaling networks displayed meaningful behavior, we compared them with signaling networks from the BioModels Database. This comparison indicated that our generated signaling networks had high topological similarities with BioModels signaling networks with respect to the reaction degree and distance distributions. In addition, our synthetic signaling networks had similar behavioral dynamics with respect to both steady states and oscillations, suggesting that our method generated synthetic signaling networks comparable with BioModels and thus could be useful for building network evaluation tools.

Highlights

We provided a Julia script to generate synthetic signaling networks.

We defined reaction degree and distance to measure the reaction network topology.

We provided the Python scripts to calculate the reaction network topology.

The synthetic signaling networks had topological similarities with the BioModels.

The synthetic signaling networks had dynamic similarities with the BioModels.
Brain Modeling ToolKit: an Open Source Software Suite for Multiscale Modeling of Brain Circuits
Authors: Dai Kael , Gratiy Sergey L. , Billeh Yazan N. , Xu Richard , Cai Binghuang , Cain Nicholas , Rimehaug Atle E. , Stasik Alexander J. , Einevoll Gaute T. , Mihalas Stefan , Koch Christof , Arkhipov Anton
Published: May 2020

Experimental studies in neuroscience are producing data at a rapidly increasing rate, providing exciting opportunities and formidable challenges to existing theoretical and modeling approaches. To turn massive datasets into predictive quantitative frameworks, the field needs software solutions for systematic integration of data into realistic, multiscale models. Here we describe the Brain Modeling ToolKit (BMTK), a software suite for building models and performing simulations at multiple levels of resolution, from biophysically detailed multi-compartmental, to point-neuron, to population-statistical approaches. Leveraging the SONATA file format and existing software such as NEURON, NEST, and others, BMTK offers consistent user experience across multiple levels of resolution. It permits highly sophisticated simulations to be set up with little coding required, thus lowering entry barriers to new users. We illustrate successful applications of BMTK to large-scale simulations of a cortical area. BMTK is an open-source package provided as a resource supporting modeling-based discovery in the community.
Bumblebees learn a relational rule but switch to a win-stay/lose-switch heuristic after extensive training
Authors: MaBouDi HaDi , Solvi Cwyn , Chittka Lars
Published: May 2020

Mapping animal performance in a behavioural task to underlying cognitive mechanisms and strategies is rarely straightforward, since a task may be solvable in more than one manner. Here, we show that bumblebees perform well on a concept-based visual discrimination task, but spontaneously switch from a concept-based solution to a simpler heuristic with extended training, all while continually increasing performance. Bumblebees were trained in an arena to find reward on displays with shapes of different sizes where they could not use low-level visual cues. One group of bees was rewarded at displays with bigger shapes and another group at displays with smaller shapes. Analysis of total choices shows bees increased their performance over 30 bouts to above chance. However, analyses of first and sequential choices suggest that after approximately 20 bouts, bumblebees changed to a win-stay/lose-switch strategy. Comparing bees’ behaviour to a probabilistic model based on a win-stay/lose-switch strategy further supports the idea that bees changed strategies with extensive training. Analyses of unrewarded tests indicate bumblebees learned and retained the concept of relative size even after they had already switched to a win-stay, lost-shift strategy. We propose that the reason for this strategy switching may be due to cognitive flexibility and efficiency.
Systematic auditing is essential to debiasing machine learning in biology
Authors: Eid Fatma-Elzahraa , Elmarakeby Haitham , Chan Yujia Alina , Martins Nadine Fornelos , ElHefnawi Mahmoud , Van Allen Eli , Heath Lenwood S. , Lage Kasper
Published: May 2020

Representational biases that are common in biological data can inflate prediction performance and confound our understanding of how and what machine learning (ML) models learn from large complicated datasets. However, auditing for these biases is not a common practice in ML in the life sciences. Here, we devise a systematic auditing framework and harness it to audit three different ML applications of significant therapeutic interest: prediction frameworks of protein-protein interactions, drug-target bioactivity, and MHC-peptide binding. Through this, we identify unrecognized biases that hinder the ML process and result in low model generalizability. Ultimately, we show that, when there is insufficient signal in the training data, ML models are likely to learn primarily from representational biases.
Clinical performance of SARS-CoV-2 IgG antibody tests and potential protective immunity
Authors: Kohmer Niko , Westhaus Sandra , Rühl Cornelia , Ciesek Sandra , Rabenau Holger F.
Published: May 2020

As the current SARS-CoV-2 pandemic continues, serological assays are urgently needed for rapid diagnosis, contact tracing and for epidemiological studies. So far, there is little data on how commercially available tests perform with real patient samples and if detected IgG antibodies provide protective immunity. Focusing on IgG antibodies, we demonstrate the performance of two ELISA assays (Euroimmun SARS-CoV-2 IgG & Vircell COVID-19 ELISA IgG) in comparison to one lateral flow assay ((LFA) FaStep COVID-19 IgG/IgM Rapid Test Device) and two in-house developed assays (immunofluorescence assay (IFA) and plaque reduction neutralization test (PRNT)). We tested follow up serum/plasma samples of individuals PCR-diagnosed with COVID-19. Most of the SARS-CoV-2 samples were from individuals with moderate to severe clinical course, who required an in-patient hospital stay.

For all examined assays, the sensitivity ranged from 58.8 to 76.5% for the early phase of infection (days 5-9) and from 93.8 to 100% for the later period (days 10-18) after PCR-diagnosed with COVID-19. With exception of one sample, all positive tested samples in the analysed cohort, using the commercially available assays examined (including the in-house developed IFA), demonstrated neutralizing (protective) properties in the PRNT, indicating a potential protective immunity to SARS-CoV-2. Regarding specificity, there was evidence that samples of endemic coronavirus (HCoV-OC43, HCoV-229E) and Epstein Barr virus (EBV) infected individuals cross-reacted in the ELISA assays and IFA, in one case generating a false positive result (may giving a false sense of security). This need to be further investigated.
A Mathematical Model Approach for Prevention and Intervention Measures of the COVID–19 Pandemic in Uganda
Authors: Mbabazi Fulgensia Kamugisha , Gavamukulya Yahaya , Awichi Richard , Olupot–Olupot Peter , Rwahwire Samson , Biira Saphina , Luboobi Livingstone S.
Published: May 2020

The human–infecting corona virus disease (COVID–19) caused by the novel severe acute respiratory syndrome corona virus 2 (SARS–CoV–2) was declared a global pandemic on March 11th, 2020. Current human deaths due to the infection have raised the threat globally with only 1 African country free of Virus (Lesotho) as of May 6th, 2020. Different countries have adopted different interventions at different stages of the outbreak, with social distancing being the first option while lock down the preferred option for flattening the curve at the peak of the pandemic. Lock down is aimed at adherence to social distancing, preserve the health system and improve survival. We propose a Susceptible–Exposed–Infected–Expected recoveries (SEIR) mathematical model to study the impact of a variety of prevention and control strategies Uganda has applied since the eruption of the pandemic in the country. We analyze the model using available data to find the infection–free, endemic/infection steady states and the basic reproduction number. In addition, a sensitivity analysis done shows that the transmission rate and the rate at which persons acquire the virus, have a positive influence on the basic reproduction number. On other hand the rate of evacuation by rescue ambulance greatly reduces the reproduction number. The results have potential to inform the impact and effect of early strict interventions including lock down in resource limited settings and social distancing.
Broad-spectrum antivirals of protoporphyrins inhibit the entry of highly pathogenic emerging viruses
Authors: Lu Shengsheng , Pan Xiaoyan , Chen Daiwei , Xie Xi , Wu Yan , Shang Weijuan , Jiang Xiaming , Sun Yuan , Fan Sheng , He Jian
Published: May 2020

Severe emerging and re-emerging viral infections such as Lassa fever, Avian influenza (AI), and COVID-19 caused by SARS-CoV-2 urgently call for new strategies for the development of broad-spectrum antivirals targeting conserved components in the virus life cycle. Viral lipids are essential components, and viral-cell membrane fusion is the required entry step for most unrelated enveloped viruses. In this paper, we identified a porphyrin derivative of protoporphyrin IX (PPIX) that showed broad antiviral activitiesin vitroagainst a panel of enveloped pathogenic viruses including Lassa virus (LASV), Machupo virus (MACV), and SARS-CoV-2 as well as various subtypes of influenza A viral strains with IC50values ranging from 0.91±0.25 μM to 1.88±0.34 μM. A mechanistic study using influenza A/Puerto Rico/8/34 (H1N1) as a testing strain showed thatPPIXinhibits the infection in the early stage of virus entry through biophysically interacting with the hydrophobic lipids of enveloped virions, thereby inhibiting the formation of the negative curvature required for fusion and blocking the entry of enveloped viruses into host cells. In addition, the preliminary antiviral activities ofPPIXwere further assessed by testing mice infected with the influenza A/Puerto Rico/8/34 (H1N1) virus. The results showed that compared with the control group without drug treatment, the survival rate and mean survival time of the mice treated withPPIXwere apparently prolonged. These data encourage us to conduct further investigations usingPPIXas a lead compound for the rational design of lipid-targeting antivirals for the treatment of infection with enveloped viruses.
MSCs Successfully Deliver Oncolytic Virotherapy to Diffuse Intrinsic Pontine Glioma
Authors: Chastkofsky Michael , Pituch Katarzyna C. , Katagi Hiroaki , Ilut Liliana , Xiao Ting , Han Yu , Sonabend Adam M. , Curiel David T. , Bonner Erin R. , Nazarian Javad , Horbinski Craig , James Charles D. , Saratsis Amanda M. , Hashizume Rintaro , Lesniak Maciej S. , Balyasnikova Irina V.
Published: May 2020

Diffuse intrinsic pontine glioma (DIPG) is among the deadliest of pediatric brain tumors. Radiation therapy is the standard of care treatment for DIPG, but offers only transient relief of symptoms for DIPG patients without providing significant survival benefit. Oncolytic virotherapy (OV) is an anticancer treatment that has been investigated for treating various types of brain tumors. Here, we have explored the use of mesenchymal stem cells (MSC) for OV delivery and evaluated treatment efficacy using preclinical models of DIPG. Our results show that DIPG cells and tumors exhibit robust expression of cell surface proteins that are important for OV entry, and that MSCs loaded with OV disseminate within and release OV throughout the tumor in mice bearing DIPG brainstem xenografts. When combining administration of OV-loaded MSCs with radiotherapy, mice bearing brainstem DIPG xenografts experience a significant survival benefit, relative to that conferred by either therapy alone (p<0.0001). Our results support further preclinical investigation of cell-based OV therapy with radiation for potential translation in treating DIPG patients.
Emergence and organization of adult brain function throughout child development
Authors: Yates Tristan S. , Ellis Cameron T. , Turk-Browne Nicholas B.
Published: May 2020

Adult cognitive neuroscience has guided the study of human brain development by identifying regions associated with cognitive functions at maturity. The activity, connectivity, and structure of a region can be compared across ages to characterize the developmental trajectory of the corresponding function. However, observed developmental differences may not only reflect the maturation of the function but also its organization across the brain. That is, a function may be mature in children but supported by different brain regions and thus underestimated by focusing on adult regions. To test these possibilities, we investigated the presence, maturity, and localization of adult functions in children using probabilistic shared response modeling, a machine learning approach for functional alignment. After learning a lower-dimensional feature space from fMRI activity as adults watched a movie, we translated these shared features into the anatomical brain space of children 3–12 years old. To evaluate functional maturity, we correlated this reconstructed activity with the children’s actual fMRI activity as they watched the same movie. We found reliable correlations throughout cortex, even in the youngest children. The strength of the correlation in the precuneus, inferior frontal gyrus, and lateral occipital cortex increased over development and predicted chronological age. These age-related changes were driven by three types of developmental trajectories across distinct features of adult function: emergence from absence to presence, consistency in anatomical expression, and reorganization from one anatomical region to another. This data-driven approach to studying brain-wide function during naturalistic perception provides an abstract description of cognitive development throughout childhood.

Significance Statement

When watching a movie, your brain processes many types of information—plotlines, characters, locations, etc. A child watching this movie receives the same input, but some of their cognitive abilities (e.g., motion detection) are more developed than others (e.g., emotional reasoning). Beyond anatomical differences, when does the child brain begin tofunctionlike an adult brain? We used a data-driven approach to extract different aspects of brain activity from adults while they watched a movie during fMRI. We then predicted what the brain activity of a child would look like if they had processed the movie the same way. Comparing this prediction with actual brain activity from children allowed us to track the development of human brain function.
Bypass of DNA Interstrand crosslinks by a Rev1-DNA polymerase ζ complex
Authors: Bezalel-Buch Rachel , Cheun Young K. , Roy Upasana , Schärer Orlando D. , Burgers Peter M.
Published: May 2020

DNA polymerase ζ (Pol ζ) and Rev1 are essential for the repair of DNA interstrand crosslink (ICL) damage. We have used yeast DNA polymerases η, ζ, and Rev1 to study translesion synthesis (TLS) past a nitrogen mustard-based ICL with an 8-atom linker between the crosslinked bases. The Rev1-Pol ζ complex was most efficient in complete bypass synthesis, by 2-3 fold, compared to Pol ζ alone or Pol η. Rev1 protein, but not its catalytic activity, was required for efficient TLS. A dCMP residue was faithfully inserted across the ICL-G by Pol η, Pol ζ, and Rev1-Pol ζ. Rev1-Pol ζ, and particularly Pol ζ alone showed a tendency to stall before the ICL, whereas Pol η stalled just after insertion across the ICL. The stalling of Pol η directly past the ICL is attributed to its autoinhibitory activity, caused by elongation of the short ICL-unhooked oligonucleotide (a six-mer in our study) by Pol η providing a barrier to further elongation of the correct primer. No stalling by Rev1-Pol ζ directly past the ICL was observed, suggesting that the proposed function of Pol ζ as an extender DNA polymerase is also required for ICL repair.
Prolonged impacts of past agriculture and overgrazing on soil fungal communities in restored forests
Authors: Tatsumi Shinichi , Matsuoka Shunsuke , Fujii Saori , Makoto Kobayashi , Osono Takashi , Isbell Forest , Mori Akira S.
Published: May 2020

Soil fungi can help improve ecosystem restoration, yet our understanding of how they reassemble in degraded land is limited. Here, we studied fungal community structure using DNA metabarcoding in reforested sites following agricultural abandonment and overgrazing. Two treatments, namely ‘reforestation using different numbers of tree species’ and ‘deer exclusion,’ have been applied for multiple decades in the study sites. We found that local fungal richness (alpha diversity) and total fungal richness (gamma diversity) were 1.9–2.9 and 1.3–1.9 times greater, respectively, in reforested stands than in natural forests. These results were regardless of the number of tree species planted in the reforested stands. Conversely, reforested stands had a spatially homogenized community structure with relatively lower degrees of compositional dissimilarity among sites within each stand (beta diversity). These findings were attributable to lower environmental heterogeneity, stronger dispersal limitation, and a comparatively shorter time since the onset of community assembly in reforested stands. Deer exclosures had no detectable effect on fungal community structure. Overall, the agricultural legacy in fungal community structure appears to have persisted for decades, even under proactive restoration of aboveground vegetation. Direct human intervention belowground may therefore be necessary for the recovery of soil biota once altered.
Impacts of the Samarco tailing dam collapse on metals and arsenic concentration in freshwater fish muscle from Doce River, southeastern Brazil
Authors: Ferreira Frederico Fernandes , Freitas Mariella Bontempo Duca de , Szinwelski Neucir , Vicente Natállia , Medeiros Laila Carine Campos , Gonçalves Reynaud Schaefer Carlos Ernesto , Dergam Jorge Abdala , Sperber Carlos Frankl
Published: May 2020

On November 2015, Samarco tailings dam in Mariana MG, Brazil, collapsed, releasing 62 million tons of tailings that advanced through 668 km of the Doce River and adjacent floodplain. Although being the worst environmental disaster in Brazil, little is known about consequences to aquatic biota. Here we evaluate the effects of the tailings mudflow on metal and arsenic concentration in fish and how concentration correlates with water and fish characteristics. We quantified semitotal amounts of Ag, Al, As, Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb and Zn in fish muscle tissue using ICP-MS in 255 individuals (34 species) sampled in unaffected and affected along the Doce River basin. Arsenic and Hg were higher in fish from affected sites, likely due to turbulent mixing of previously sedimented material by the giant tailings wave. Silver and Zn concentrations were higher in unaffected sites. Arsenic concentration inGeophagus brasiliensisdecreased with increasing fish weight. Copper and Zn decreased with increasing fish weight considering the whole assembly of fish. The tailings mudflow increased water conductivity and conductivity increased Al concentration in fish, so we expected a larger Al concentration in fishes from affected sites. However, the observed Al concentration in fishes from affected sites was lower than expected by water conductivity. Thus, the tailings mudflow reduced Al uptake or accumulation in fishes. Mercury decreased with increasing water conductivity in both unaffected and affected sites considering all species and inG. brasiliensisalone. Despite the relatively low concentration range of metals and As found in fish, fishes from sites affected by the iron ore tailings mudflow showed higher As and Hg concentration, compared to fishes from unaffected sites. The higher As and Hg in affected sites require further detailed monitoring to ensure safeguards of human health by fishing activity along the Doce River.
Polishing Copy Number Variant Calls on Exome Sequencing Data via Deep Learning
Authors: Özden Furkan , Alkan Can , Çiçek A. Ercüment
Published: May 2020

Accurate and efficient detection of copy number variants (CNVs) is of critical importance due to their significant association with complex genetic diseases. Although algorithms that use whole genome sequencing (WGS) data provide stable results with mostly-valid statistical assumptions, copy number detection on whole exome sequencing (WES) data shows comparatively lower accuracy. This is unfortunate as WES data is cost efficient, compact and is relatively ubiquitous. The bottleneck is primarily due to non-contiguous nature of the targeted capture: biases in targeted genomic hybridization, GC content, targeting probes, and sample batching during sequencing. Here, we present a novel deep learning model,DECoNT, which uses the matched WES and WGS data and learns to correct the copy number variations reported by any off-the-shelf WES-based germline CNV caller. We train DECoNT on the 1000 Genomes Project data, and we show that we can efficiently triple the duplication call precision and double the deletion call precision of the state-of-the-art algorithms. We also show that our model consistently improves the performance independent from (i) sequencing technology, (ii) exome capture kit and (iii) CNV caller. Using DECoNT as a universal exome CNV call polisher has the potential to improve the reliability of germline CNV detection on WES data sets.
Diel Oscillations of Particulate Metabolites Reflect Synchronized Microbial Activity in the North Pacific Subtropical Gyre
Authors: Boysen Angela K. , Carlson Laura T. , Durham Bryndan P. , Groussman Ryan D. , Aylward Frank O. , Ribalet François , Heal Katherine R. , DeLong Edward F. , Armbrust E. Virginia , Ingalls Anitra E.
Published: May 2020

Light is the primary input of energy into the sunlit ocean, driving daily oscillations in metabolism of primary producers. The consequences of this solar forcing have implications for the whole microbial community, yetin situmeasurements of metabolites, direct products of cellular activity, over the diel cycle are scarce. We evaluated community-level biochemical consequences of diel oscillations in the North Pacific Subtropical Gyre by quantifying 79 metabolites in particulate organic matter in surface waters every four hours over eight days. Total particulate metabolite concentration peaked at dusk, even when normalized to biomass estimates. The concentrations of 70% of individual metabolites exhibited 24-hour periodicity. Despite the diverse organisms that use them, primary metabolites involved in anabolic processes and redox maintenance had significant 24-hour periodicity. Osmolytes exhibited the largest diel oscillations, implying rapid turnover and metabolic roles beyond cell turgor maintenance. Metatranscriptome analysis revealed the taxa involved in production and consumption of some metabolites, including the osmolyte trehalose. This compound displayed the largest diel oscillations in abundance and was likely produced by the nitrogen-fixing cyanobacteriumCrocosphaerafor energy storage. These findings demonstrate that paired measurements of particulate metabolites and transcripts resolve strategies microbes use to manage daily energy and redox oscillations.
The role of high cholesterol in age-related COVID19 lethality
Authors: Wang Hao , Yuan Zixuan , Pavel Mahmud Arif , Jablonski Sonia Mediouni , Jablonski Joseph , Hobson Robert , Valente Susana , Reddy Chakravarthy B. , Hansen Scott B.
Published: May 2020

Coronavirus disease 2019 (COVID19) is a respiratory infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originating in Wuhan, China in 2019. The disease is notably severe in elderly and those with underlying chronic conditions. A molecular mechanism that explains why the elderly are vulnerable and why children are resistant is largely unknown. Here we show loading cells with cholesterol from blood serum using the cholesterol transport protein apolipoprotein E (apoE) enhances the entry of pseudotyped SARS-CoV-2 and the infectivity of the virion. Super resolution imaging of the SARS-CoV-2 entry point with high cholesterol shows almost twice the total number of endocytic entry points. Cholesterol concomitantly traffics angiotensinogen converting enzyme (ACE2) to the endocytic entry site where SARS-CoV-2 presumably docks to efficiently exploit entry into the cell. Furthermore, in cells producing virus, cholesterol optimally positions furin for priming SARS-CoV-2, producing a more infectious virion with improved binding to the ACE2 receptor. In vivo, age and high fat diet induces cholesterol loading by up to 40% and trafficking of ACE2 to endocytic entry sites in lung tissue from mice. We propose a component of COVID19 severity based on tissue cholesterol level and the sensitivity of ACE2 and furin to cholesterol. Molecules that reduce cholesterol or disrupt ACE2 localization with viral entry points or furin localization in the producer cells, may reduce the severity of COVID19 in obese patients.
Deep profiling of protease substrate specificity enabled by dual random and scanned human proteome substrate phage libraries
Authors: Zhou Jie , Li Shantao , Leung Kevin K. , O’Donovan Brian , Zou James Y. , DeRisi Joseph L. , Wells James A.
Published: May 2020

Proteolysis is a major post-translational regulator of biology both inside and outside of cells. Broad identification of optimal cleavage sites and natural substrates of proteases is critical for drug discovery and to understand protease biology. Here we present a method that employs two genetically encoded substrate phage display libraries coupled with next generation sequencing (SPD-NGS) that allows up to 10,000-fold deeper sequence coverage of the typical 6 to 8 residue protease cleavage sites compared to state-of-the-art synthetic peptide libraries or proteomics. We applied SPD-NGS to two classes of proteases, the intracellular caspases 2, 3, 6, 7 and 8, and the ectodomains of the membrane sheddases, ADAMs 10 and 17. The first library (Lib 10AA) was used to determine substrate cleavage motifs. Lib 10AA contains a highly diverse randomized 10-mer substrate peptide sequences (109unique members) that was displayed mono-valently on filamentous phage and bound to magnetic beads via an N-terminal biotin. The protease was allowed to cleave the SPD beads, and the released phage subjected to up to three total rounds of positive selection followed by next generation sequencing (NGS). This allowed us to identify from 104to 105unique cleavage sites over a 1000-fold dynamic range of NGS counts (ranging from 3-4000), and produced consensus and optimal cleavage motifs based positional sequencing scoring matrices that closely matched synthetic peptide data. A second SPD-NGS library (Lib hP) was constructed that allowed us to identify candidate human proteome sequences. Lib hP displayed virtually the entire human proteome tiled in contiguous 49AA sequences with 25AA overlaps (nearly 1 million members). After three rounds of positive selection we identified up to 104natural linear cut sites depending on the protease and captured most of the examples previously identified by proteomics (ranging from 30 to 1500) and predicted 10 to 100-fold more. Structural bioinformatics was used to facilitate the identification of candidate natural protein substrates. SPD-NGS is rapid, reproducible, simple to perform and analyze, inexpensive, renewable, with unprecedented depth of coverage for substrate sequences. SPD-NGS is an important tool for protease biologists interested protease specificity for specific assays and inhibitors and to facilitate identification of natural protein substrates.
What doesn’t kill you makes you stronger: detoxification ability as an honest sexually selected signal
Authors: González-Santoyo Isaac , González-Tokman Daniel , Tapia-Rodríguez Miguel , Córdoba-Aguilar Alex
Published: May 2020

Sexual selection maintains colourful signals that increase sexual attractiveness and dominance. Some sexually selected, colourful signals are pigments synthesized from ingested amino acids. The underlying metabolic pathways for these pigments often release toxic byproducts that can reduce individual survival. However, rather than discarding these otherwise harmful byproducts, animals may use them by integrating them into sexually selected traits. We tested this idea using males of the damselflyHetaerina americana, which bear a red-pigmented wing spot that is sexually selected through male-male competition for mating territories. First, by using chromatography and confocal microscopy, we determined that the red wing spots are generated by ommochrome pigments derived from tryptophan metabolism. Second, we injected a group of males with the toxic precursor of these ommochromes, 3-hydroxy-kynurenine (3-Hk), confirming the toxicity of this compound in adult males. Finally, by using spectrophotometry and confocal microscopy, we showed that adult males injected with a LC50of 3-Hk had more ommochromes in their wing spots than controls but similar survival, suggesting that the deposition of ommochrome pigment in the wing detoxifies the tryptophan metabolism process. Thus, we report for the first time that sexually selected pigmented signals involve the biochemical treatment of excreted compounds that could otherwise have lethal effects, a hypothesis we call “detoxifying ability signalling”. Our results provide new insights about the origin and maintenance of sexual signals, elucidating a mechanism for the evolution of honest indicators of quality that could have arisen due to natural selection.
The winning methods for predicting cellular position in the DREAM single cell transcriptomics challenge
Authors: Pham Vu VH , Li Xiaomei , Truong Buu , Nguyen Thin , Liu Lin , Li Jiuyong , Le Thuc D
Published: May 2020

Motivation

Predicting cell locations is important since with the understanding of cell locations, we may estimate the function of cells and their integration with the spatial environment. Thus, the DREAM Challenge on Single Cell Transcriptomics required participants to predict the locations of single cells in the Drosophila embryo using single cell transcriptomic data.

Results

We have developed over 50 pipelines by combining different ways of pre-processing the RNA-seq data, selecting the genes, predicting the cell locations, and validating predicted cell locations, resulting in the winning methods for two out of three sub-challenges in the competition. In this paper, we present anRpackage,SCTCwhatateam, which includes all the methods we developed and theShinyweb-application to facilitate the research on single cell spatial reconstruction. All the data and the example use cases are available in the Supplementary material.

Availability

The scripts of the package are available athttps://github.com/thanhbuu04/SCTCwhatateamand theShinyapplication is available athttps://github.com/pvvhoang/SCTCwhatateam-ShinyApp

Contact

Thuc.Le@unisa.edu.au

Supplementary information

Supplementary data are available atBriefings in Bioinformaticsonline.
Macrophage-derived miR-21 drives overwhelming glycolytic and inflammatory response during sepsis via repression of the PGE2/IL-10 axis
Authors: Melo Paulo , Alvarez Annie Rocio Pineros , Serezani C. Henrique
Published: May 2020

Myeloid cells play a critical role in the development of systemic inflammation and organ damage during sepsis. The mechanisms the development of aberrant inflammatory response remains to be elucidated. MicroRNAs are small non-coding RNAs that could prevent the expression of inflammatory molecules. Although the microRNA-21 (miR-21) is abundantly expressed in macrophages, the role of miR-21 in sepsis is controversial. Here we showed that miR-21 is upregulated in neutrophils and macrophages from septic mice. We found that myeloid-specific miR-21 deletion enhances animal survival, followed by decreased bacterial growth and organ damage during sepsis. Increased resistance against sepsis was associated with a reduction of aerobic glycolysis (as determined by reduced extracellular acidification rate (ECAR) and expression of glycolytic enzymes) and systemic inflammatory response (IL-1βTNFα and IL-6). While miR-21-/- macrophages failed to induce aerobic glycolysis and production of pro-inflammatory cytokines, we observed increased levels of the anti-inflammatory mediators’ prostaglandin E2(PGE2) and IL10. Using blocking antibodies and pharmacological tools, we further discovered that increased survival and decreased systemic inflammation in miR21Δmyelduring sepsis is dependent on the PGE2/IL10-mediated glycolysis inhibition. Together, we are showing a heretofore unknown role of macrophage miR21 in the orchestrating the balance between anti-inflammatory mediators and metabolic reprogramming that drives cytokine storm and tissue damage during sepsis.
Sensitivity of Gene Sets to miRNA Regulation: A Cell-Based Probabilistic Approach
Authors: Mahlab-Aviv Shelly , Linial Nathan , Linial Michal
Published: May 2020

Mature microRNAs (miRNAs) are small, non-coding RNA molecules that function by base-pairing with mRNAs. In multicellular organisms, miRNAs lead to mRNA destabilization and translation arrest. Importantly, the quantities and stichometry of miRNAs/mRNAs determine the miRNA regulation characteristics of specific cells. In this study, we used COMICS (Competition of miRNA Interactions in Cell Systems), a stochastic computational iterative framework to characterize genes by their sensitivity and robustness to miRNA regulation. We monitor the cell state by quantifying the retention level for all mRNAs, at the end of 100,000 simulation iterations. In HeLa cells, we partitioned all genes to five classes according to their decay rates. We show that the largest class (69% of genes) is apparently resistant to miRNA regulation. We created in silico perturbations using overexpressing of all major miRNAs (248 types) at various levels relative to the basal level (x1 to x1000). We further classified genes according to the differential behaviour for any pair of conditions of miRNA expression profile. Based on such measure (OvereXpression Ratio, OXR), we identified a small number of gene sets that are especially sensitive to OXR. Our results expose an overlooked quantitative dimension for set of genes and miRNA regulation in living cells.
Binding partners regulate unfolding of myosin VI to activate the molecular motor
Authors: dos Santos Ália , Fili Natalia , Hari-Gupta Yukti , Gough Rosemarie E. , Wang Lin , Martin-Fernandez Marisa , Aaron Jesse , Wait Eric , Chew Teng-Leong , Toseland Christopher P.
Published: May 2020

Myosin VI is the only minus-end actin motor and is coupled to various cellular processes ranging from endocytosis to transcription. This multi-potent nature is achieved through alternative isoform splicing and interactions with a network of binding partners. There is a complex interplay between isoforms and binding partners to regulate myosin VI. Here, we have compared the regulation of two myosin VI splice isoforms by two different binding partners. By combining biochemical and single-molecule approaches, we propose that myosin VI regulation follows a generic mechanism, independently of the spliced isoform and the binding partner involved. We describe how myosin VI adopts an autoinhibited backfolded state which is released by binding partners. This unfolding activates the motor, enhances actin binding and can subsequently trigger dimerization. We have further expanded our study by using single molecule imaging to investigate the impact of binding partners upon myosin VI molecular organisation and dynamics.
The Starlet Sea Anemone,Nematostella vectensis, possesses body region-specific bacterial associations with spirochetes dominating the capitulum
Authors: Bonacolta A. M. , Connelly M. T. , Rosales S. , del Campo J. , Traylor-Knowles N.
Published: May 2020

Sampling of different body regions can reveal highly specialized bacterial associations within the holobiont and facilitate identification of core microbial symbionts that would otherwise be overlooked by bulk sampling methods. Here we characterized compartment-specific associations present within the model cnidarianNematostella vectensisby dividing its morphology into three distinct body regions. This sampling design allowed us to uncover a capitulum-specific dominance of spirochetes withinN. vectensis. Bacteria from the family Spirochaetaceae made up 66% of the community in the capitulum, while only representing 1.2% and 0.1% of the communities in the mesenteries and physa, respectively. A phylogenetic analysis of the predominant spirochete sequence recovered fromN. vectensisshowed a close relation to spirochetes previously recovered from wildN. vectensis. These sequences clustered closer to the recently described genusOceanispirochaeta, rather thanSpirochaeta perfilievii, supporting them as members of this clade. This suggests a consistent and potentially important association betweenN. vectensisand spirochetes from the order Spirochaetales.