title: A BI-1 mediated cascade improves redox homeostasis during thermal stress and prevents oxidative damage in a preconditioned reef-building coral

abstract:
Global coral reef decline is largely driven by the breakdown of the coral-algal symbiosis during temperature stress. Corals can acclimatize to higher temperatures, but the cellular processes underlying this ability are poorly understood. We show that preconditioning-based improvements in thermal tolerance in Pocillopora acuta are accompanied by increases in host glutathione reductase (GR) activity and expression, which prevents DNA damage. A strong correlation between GR and BI-1 expression in heat-stressed preconditioned corals and the presence of an antioxidant response element (ARE) in the GR promoter suggest BI-1 could regulate GR expression through Nrf2/ARE pathway. To fortify this link, we developed an siRNA- mediated gene knockdown protocol and targeted the coral BI-1 gene. BI-1 knock-down specifically decreased GR expression and activity and increased oxidative DNA damage in heat- stressed preconditioned corals, showing that BI-1-mediated enhanced antioxidant response during acute heat stress is a key mechanism that prevents oxidative DNA damage after preconditioning.

TeaserPreconditioning improves redox homeostasis and prevents oxidative stress in a thermally stressed reef-building coral


title: BI-1 mediated cascade improves redox homeostasis during thermal stress and prevents oxidative damage in a preconditioned stony coral

category: cell biology


title: Thermal preconditioning in a reef-building coral alleviates oxidative damage through a BI-1 mediated antioxidant response

category: molecular biology


title: Methylation studies in Peromyscus: aging, altitude adaptation, and monogamy

abstract: DNA methylation-based biomarkers of aging have been developed for humans and many other mammals and could be used to assess how stress factors impact aging. Deer mice (Peromyscus) are long living rodents that have emerged as an informative model to study aging, adaptation at extreme environments, and monogamous behavior. In the present study we have undertaken an exhaustive, genome-wide analysis of DNA methylation in Peromyscus, spanning different species, stocks, sexes, tissues and age cohorts. We describe DNA methylation-based estimators of age for different species of deer mice based on novel DNA methylation data generated on highly conserved mammalian CpGs measured with a custom array. The multi-tissue epigenetic clock for deer mice was trained on 3 tissue sources (tail, liver, brain). Two dual species human-peromyscus clocks accurately measure age and relative age defined as the ratio of chronological age to maximum age. These analyses also allowed us to accurately manifest the increasing impact of age, sex, genetic relatedness, and ultimately tissue identity, in that order, in the acquisition of specific methylation patterns in the genome. Genes that were differentially methylated across different biological variables were determined and their potential impact is discussed. This study describes highly accurate DNA methylation-based estimators of age in deer mice and illustrates how differential methylation may be linked to adaptation at different conditions.

category: developmental biology


title: Machine learning methods trained on simple models can predict critical transitions in complex natural systems

abstract:
1. Sudden transitions from one stable state to a contrasting state occur in complex systems ranging from the collapse of ecological populations to climatic change, with much recent work seeking to develop methods to predict these unexpected transitions from signals in time series data. However, previously developed methods vary widely in their reliability, and fail to classify whether an approaching collapse might be catastrophic (and hard to reverse) or non-catastrophic (easier to reverse) with significant implications for how such systems are managed.

2. Here we develop a novel detection method, using simulated outcomes from a range of simple mathematical models with varying nonlinearity to train a deep neural network to detect critical transitions - the Early Warning Signal Network (EWSNet).

3. We demonstrate that this neural network (EWSNet), trained on simulated data with minimal assumptions about the underlying structure of the system, can predict with high reliability observed real-world transitions in ecological and climatological data. Importantly, our model appears to capture latent properties in time series missed by previous warning signals approaches, allowing us to not only detect if a transition is approaching but critically whether the collapse will be catastrophic or non-catastrophic.

4. The EWSNet can flag a critical transition with unprecedented accuracy, overcoming some of the major limitations of traditional methods based on phenomena such as Critical Slowing Down. These novel properties mean EWSNet has the potential to serve as a universal indicator of transitions across a broad spectrum of complex systems, without requiring information on the structure of the system being monitored. Our work highlights the practicality of deep learning for addressing further questions pertaining to ecosystem collapse and have much broader management implications.

category: ecology


title: The brown algae Saccharina japonica and Sargassum horneri exhibit species-specific responses to synergistic stress of ocean acidification and eutrophication

abstract: Ocean acidification and eutrophication are two important environmental stressors. They inevitably impact marine macroalgae, and hence the coastal ecosystem of China. Saccharina japonica, as the main culture species in China, is suffering the harmful golden tide caused by Sargassum horneri. However, it remains unclear whether the detrimental effects of S. horneri on S. japonica cultivation become more severe in future acidified and eutrophic scenario. In this study, we respectively investigated the effects of pCO2 (400 atm and 1000 atm) and nutrients (non-enriched and enriched seawater) on the growth, photosynthesis, respiration, chlorophyll contents, and tissue nitrogen of S. japonica and S. horneri. Results indicated that enrichment of nutrients contributed S. horneri to utilize HCO3-. The carbon acquisition pathway shifted from HCO3- to CO2 in S. japonica, while S. horneri remained using HCO3- regulated by nutrient enrichment. S. horneri exhibited better photosynthetic traits than S. japonica, with a higher level of net photosynthetic rate and chlorophyll contents at elevated pCO2 and enriched nutrients. Tissue nitrogen also accumulated richly in the thalli of S. horneri under higher pCO2 and nutrients. Significant enhancement in growth was only detected in S. horneri under synergistic stress. Together, S. horneri showed competitive dominance in current study. These findings suggest that increasing risk of golden tide in acidified and eutrophic ocean can most likely result in great damage to S. japonica cultivation.


title: Functionally distinct T-helper cell phenotypes predict resistance to different types of parasites in a wild mammal

abstract:
O_LIThe adaptive immune system is critical to an effective, long-lasting ability to respond to infection in vertebrates and T-helper (Th) cells play a key role in orchestrating the adaptive immune response. Laboratory studies show that functionally distinct Th responses provide protection against different kinds of parasites (i.e., Th1 responses against microparasites and Th2 against macroparasites).
C_LIO_LINatural populations must deal with challenges from a wide range of infectious agents and co-infection with different types of parasite is the norm, so different Th responses are likely to play an important and dynamic role in maintaining host health and fitness. However, the relationship between T helper immune phenotypes and infection with different types of parasites remains poorly understood in wild animals.
C_LIO_LIIn this study, we characterised variation in functionally distinct Th responses (Th1, Th2, Th17 and regulatory responses) in a wild population of Soay sheep using flow cytometry to detect Th-subset specific transcription factors, and ex vivo lymphocyte stimulation to quantify release of Th-associated cytokines. We specifically tested the prediction that raised Th1 and Th2 responses should predict reduced apicomplexan (coccidian) and helminth (nematode) parasite burdens, respectively.
C_LIO_LICell counts of different Th subsets measured by flow cytometry did not vary with age or sex. However, all measures of Th-associated ex vivo cytokine production increased with age, and Th17- and regulatory Th-associated cytokine production increased more rapidly with age in males than females.
C_LIO_LIIndependent of age and sex, Th2-associated immune measures negatively predicted gastro-intestinal strongyle nematode faecal egg count, while production of the Th1-associated cytokine IFN-{gamma} negatively predicted coccidian faecal oocyst count.
C_LIO_LIOur results provide important support from outside the laboratory that Th1 and Th2 responses confer resistance to different kinds of parasites (micro- and macro-parasites, respectively). They also add to mounting evidence from wild populations that Th1/Th2 trade-offs often observed in controlled laboratory experiments may not readily translate to more complex natural systems.
C_LIO_LIOur study illustrates that harnessing more specific reagents and tools from laboratory immunology has the potential to illuminate our understanding of epidemiology and host-parasite co-evolution in the wild.
C_LI


title: Leakiness at the human-animal interface in Southeast Asia and implications for the spread of antibiotic resistance

abstract: International efforts to curb antimicrobial resistance have focused on drug development and limiting unnecessary use. However, in areas where water, sanitation, and hygiene infrastructure is lacking, and where biosecurity in food-animal production is poor, pathogen-flow between humans and animals could exacerbate the emergence and spread of resistant pathogens. Here, we compared mobile resistance elements among Escherichia coli recovered from humans and meat in Cambodia, a country with substantial connectivity between humans and animals, unregulated antibiotic use, and poor environmental controls. We identified multiple resistance-encoding plasmids and a novel, blaCTX-M and qnrS1-encoding transposon that were widely dispersed in both humans and animals, a phenomenon rarely observed in high-income settings. Our findings indicate that plugging leaks at human-animal interfaces should be a critical part of addressing antimicrobial resistance in low and middle-income countries.


title: Early Spring Snowmelt and Summer Droughts Strongly Impair the Resilience of Key Microbial Communities in Subalpine Grassland Ecosystems

abstract: Subalpine grassland ecosystems are important from biodiversity, agriculture, and touristic perspectives but their resilience to seasonally occurring climatic extremes is increasingly challenged with climate change, accelerating their vulnerability to tipping points. Microbial communities, which are central in ecosystem functioning, are usually considered as more resistant and highly resilient to such extreme events due to their functional redundancy and strong selection in residing habitats. To investigate this, we explored soil microbial responses upon recurrent summer droughts associated with early snowmelt in subalpine grasslands mesocosms set-up at the Lautaret Pass (French Alps). Potential respiration, nitrification and denitrification were monitored over a period of two growing seasons along with quantification of community gene abundances of total bacteria as well as (de)nitrifiers. Results revealed that droughts had a low and short-term adverse impact on bacterial total respiration supporting their hypothesized high resilience, i.e., resistance and ability to recover. Nitrification and abundances of the corresponding functional guilds showed relatively strong resistance to summer droughts but declined in response to early snowmelt. This triggered a cascading effect on denitrification but also on abundances of denitrifying communities which recovered from all climatic extremes except from the summer droughts where nitrifiers were collapsed. Denitrification and respective functional groups faced high impact of applied stresses with strong reduction in abundance and activity of this specialized community. Although, consequently lower microbial competition for nitrate may be positive for plant biomass production, warnings exist when considering the potential nitrogen leaching from these ecosystems as well as risks of greenhouses gases emission such as N2O.


title: Spatial and temporal assessment of the risk associated to bacteria in recreational waters of a large South American Reservoir

abstract: The characterization of risk due to recreational exposure to water needs to assess the concentration of pathogens in the water and the degree of contact with those pathogens. In this study we assessed the risk associated to E. coli and cyanobacteria in a large South American Reservoir heavily used for recreation, by i) gathering field environmental data from two water agencies (six sites, summers 2011-2015), ii) generating satellite data at landscape scale (750 km2, summers 2011-2017) and running a health survey related to water exposure (summer 2017). Field data showed that cyanobacteria abundances recurrently surpassed the moderate and high-risk categories across sites and year analyzed, and a significant positive link between cyanobacteria abundance and microcystin concentration. Nevertheless, microcystin concentrations were in 90% of cases mostly within the low to moderate risk categories. Mean E. coli concentrations during 2011-2015 were within the high-risk category in 30% of the sites, but in 2017, sites identified as low risk had high-risk. The latter underscores the high risk posed by E. coli in the reservoir. Cyanobacteria (cell abundance and microcystin) and coliform bacteria abundances were unrelated, suggesting different responses to environmental or anthropogenic triggers. Satellite data evidenced that the highest risk related to cyanobacteria abundance occurred in the dendritic areas of the Argentinean side of the reservoir, areas which currently remain unmonitored by water agencies. Satellite monitoring bridged the limited spatial and temporal coverage of field samplings for cyanobacteria abundance (yet not for toxicity nor E. coli abundances) and rendered a risk map at landscape scale, which can be used by water agencies to effectively monitor and manage cyanobacteria blooms, and to-coupled with exposure variables-assess health risks related to cyanobacteria. The health survey identified few numbers of suspected patients with symptoms and who bathed in the Salto Grande reservoir. At the time of exposure, sites in the environment evidenced high bacteria concentration (mostly E. coli and to a lesser extent cyanobacteria) denoting situations where aspects of the biophysical environment affect human health. More studies and integration among environmental and health disciplines are needed to assess the impacts of these water born bacteria in human health. Finally, we further assessed how well cyanobacteria quantitative proxies monitored in the field explained the outcome of a qualitative risk communication system-the cyano-traffic-light-which is ongoing since 2011. We obtained a significant predictive model only for cyanobacteria abundance, yet with low predictive value. This probably occurred because the variables used to build each cyano-traffic-light category (cyanobacteria abundance, toxicity and chlorophyll-a, scums) were monitored with different frequencies, and because at least two of these variables needed to surpass the threshold of each category to be allocated into a risk category. Based upon our results we propose several modifications to the current cyano-traffic-light, that believe would better reflect what happens in the field and protect human health: i) include E. coli concentration and satellite estimated cyanobacteria abundance (mostly in areas not covered by field monitoring), ii) relax the thresholds for cyanobacteria abundance and toxicity, and iv) base each risk category upon the surpassing of one of either E. coli, cyanobacteria abundance, microcystin.


title: Allele frequency divergence reveals ubiquitous influence of positive selection in Drosophila

abstract:
Resolving the role of natural selection is a basic objective of evolutionary biology. It is generally difficult to detect the influence of selection because ubiquitous non-selective stochastic change in allele frequencies (genetic drift) degrades evidence of selection. As a result, selection scans typically only identify genomic regions that have undergone episodes of intense selection. Yet it seems likely such episodes are the exception; the norm is more likely to involve subtle, concurrent selective changes at a large number of loci. We develop a new theoretical approach that uncovers a previously undocumented genome-wide signature of selection in the collective divergence of allele frequencies over time. Applying our approach to temporally resolved allele frequency measurements from laboratory and wild Drosophila populations, we quantify the selective contribution to allele frequency divergence and find that selection has substantial effects on much of the genome. We further quantify the magnitude of the total selection coefficient (a measure of the combined effects of direct and linked selection) at a typical polymorphic locus, and find this to be large (of order 1%) even though most mutations are not directly under selection. We find that selective allele frequency divergence is substantial at intermediate allele frequencies, which we argue is most parsimoniously explained by positive -- not purifying -- selection. Thus, in these populations most mutations are far from evolving neutrally in the short term (tens of generations), including mutations with neutral fitness effects, and the result cannot be explained simply as a purging of deleterious mutations.

Author summaryNatural selection is the process fundamentally driving evolutionary adaptation; yet the specifics of how natural selection molds the genome are contentious. A prevailing neutralist view holds that the evolution of most mutations is essentially random. Here, we develop new theory that looks past the stochasticity of individual mutations and instead analyzes the behavior of mutations across the genome as a collective. We find that selection has a strong non-random influence on most of the Drosophila genome over short timescales (tens of generations), including the bulk of mutations that are not themselves directly targeted by selection. We show that this likely involves ongoing positive selection.

category: evolutionary biology


title: Genome assembly of the maize inbred line A188 provides a new reference genome for functional genomics

abstract:
Heretofore, little is known about the mechanism underlying the genotype-dependence of embryonic callus (EC) induction, which has severely inhibited the development of maize genetic engineering. Here, we report the genome sequence and annotation of a maize inbred line with high EC induction ratio, A188, which is assembled from single-molecule sequencing and optical genome mapping. We assembled a 2,210 Mb genome with a scaffold N50 size of 11.61 million bases (Mb), compared to those of 9.73 Mb for B73 and 10.2 Mb for Mo17. Comparative analysis revealed that [~]30% of the predicted A188 genes had large structural variations to B73, Mo17 and W22 genomes, which caused considerable protein divergence and might lead to phenotypic variations between the four inbred lines. Combining our new A188 genome, previously reported QTLs and RNA sequencing data, we reveal 8 large structural variation genes and 4 differentially expressed genes playing potential roles in EC induction.

HighlightOur manuscript presents a high-quality reference genome of the inbred line A188, and provides new insights into candidate genes underlying maize embryonic callus induction and other maize agronomic traits.

category: genetics


title: Super interactive promoters provide insight into cell type-specific regulatory networks in blood lineage cell types

abstract: Existing studies of chromatin conformation have primarily focused on potential enhancers interacting with gene promoters. By contrast, the interactivity of promoters per se, while equally critical to understanding transcriptional control, has been largely unexplored, particularly in a cell type-specific manner for blood lineage cell types. In this study, we leverage promoter capture Hi-C data across a compendium of blood lineage cell types to identify and characterize cell type-specific super-interactive promoters (SIPs). Notably, promoter-interacting regions (PIRs) of SIPs are more likely to overlap with cell type-specific ATAC-seq peaks and GWAS variants for relevant blood cell traits than PIRs of non-SIPs. Further, SIP genes tend to express at a higher level in the corresponding cell type, and show enriched heritability of relevant blood cell trait(s). Importantly, this analysis shows the potential of using promoter-centric analyses of chromatin spatial organization data to identify biologically important genes and their regulatory regions.


title: Genomic Surveillance of Acinetobacter baumannii in the Philippines, 2013-2014

abstract:
Acinetobacter baumannii is an opportunistic nosocomial pathogen that has increasingly become resistant to carbapenems worldwide. In the Philippines, carbapenem resistance and multi-drug resistance (MDR) rates are above 50%. We undertook a genomic study of carbapenem resistant A. baumannii in the Philippines to characterize the population diversity and antimicrobial resistance (AMR) mechanisms.

We sequenced the whole genomes of 117 A. baumannii isolates recovered by 16 hospitals in the Philippines between 2013 and 2014. We determined the multi-locus sequence type (MLST), presence of acquired AMR determinants and relatedness between isolates from the genome sequences. We also compared the phenotypic and genotypic resistance results.

Carbapenem resistance was mainly explained by the acquisition of class-D beta-lactamase gene blaOXA-23. The concordance between phenotypic and genotypic resistance to imipenem was 98.15% and 94.97% overall for the seven antibiotics analysed. Twenty-two different sequence types (ST) were identified, including 7 novel STs. The population was dominated by high-risk international clone 2 (i.e., clonal complex 92), in particular by ST195 and ST208 and their single locus variants. With WGS we identified local clusters representing potential undetected nosocomial outbreaks, as well as multi-hospital clusters indicating inter-hospital transmission. Comparison with global genomes suggested that the establishment of carbapenem-resistant IC2 clones in the Philippines is likely the result of clonal expansion and geographical dissemination and at least partly explained by inadequate hospital infection control and prevention.

This study is the first extensive genomic study of carbapenem-resistant A. baumannii in the Philippines and underscores the importance of hospital infection control and prevention to contain high-risk clones.

category: genomics


title: Population structure of Drosophila suzukii and signals of multiple invasions into the continental United States

abstract: Drosophila suzukii, or spotted-wing drosophila, is now an established pest in many parts of the world, causing significant damage to numerous fruit crop industries. Native to East Asia, D. suzukii infestations started in the United States a decade ago, occupying a wide range of climates. To better understand invasion ecology of this pest, knowledge of past migration events, population structure, and genetic diversity is needed. To improve on previous studies examining genetic structure of D. suzukii, we sequenced whole genomes of 237 individual flies collected across the continental U.S., as well as several representative sites in Europe, Brazil, and Asia, to identify hundreds of thousands of genetic markers for analysis. We analyzed these markers to detect population structure, to reconstruct migration events, and to estimate genetic diversity and differentiation within and among the continents. We observed strong population structure between West and East Coast populations in the U.S., but no evidence of any population structure North to South, suggesting there is no broad-scale adaptations occurring in response to the large differences in regional weather conditions. We also find evidence of repeated migration events from Asia into North America have provided increased levels of genetic diversity, which does not appear to be the case for Brazil or Europe. This large genomic dataset will spur future research into genomic adaptations underlying D. suzukii pest activity and development of novel control methods for this agricultural pest.


title: A NEW CASE OF DIPLOIDY WITHIN A HAPLOID GENUS OF ENTOMOPATHOGENIC FUNGI

abstract: Fungi in the genus Metarhizium are soil-borne plant-root endophytes and rhizosphere colonisers, but also potent insect pathogens with highly variable host ranges. These ascomycete fungi are predominantly asexually reproducing and ancestrally haploid, but two independent origins of persistent diploidy within the Coleoptera-infecting M. majus species complex are known and has been attributed to incomplete chromosomal segregation following meiosis during the sexual cycle. There is also evidence for infrequent sexual cycles in the locust-specific pathogenic fungus Metarhizium acridum (Hypocreales: Clavicipitaceae), which is an important entomopathogenic biocontrol agent used for the control of grasshoppers in agricultural systems as an alternative to chemical control. Here, we show that the genome of the M. acridum isolate ARSEF 324, which is formulated and commercially utilised under the name  Green Guard, is functionally diploid. We used single-molecule real-time (SMRT) sequencing technology to complete a high-quality assembly of ARSEF 324. Kmer frequencies, intragenomic collinearity between contigs and single nucleotide variant read depths across the genome revealed the first incidence of diploidy described within the species M. acridum. The haploid assembly of 44.7 Mb consisting of 20.8% repetitive elements, which is the highest proportion described of any Metarhizium species. The genome assembly and the inferred diploid state, can shed light on past research on this strain and could fuel future investigation into the fitness landscape of aberrant ploidy levels, not least in the contest of biocontrol agents.


title: Cross-species prediction of essential genes in insects through machine learning and sequence-based attributes

abstract: Insects are organisms with a vast phenotypic diversity and key ecological roles. Several insect species also have medical, agricultural and veterinary importance as parasites and vectors of diseases. Therefore, strategies to identify potential essential genes in insects may reduce the resources needed to find molecular players in central processes of insect biology. Furthermore, the detection of essential genes that occur only in certain groups within insects, such as lineages containing insect pests and vectors, may provide a more rational approach to select essential genes for the development of insecticides with fewer off-target effects. However, most predictors of essential genes in multicellular eukaryotes using machine learning rely on expensive and laborious experimental data to be used as gene features, such as gene expression profiles or protein-protein interactions. This information is not available for the vast majority of insect species, which prevents this strategy to be effectively used to survey genomic data from non-model insect species for candidate essential genes. Here we present a general machine learning strategy to predict essential genes in insects using only sequence-based attributes (statistical and physicochemical data). We validate our strategy using genomic data for the two insect species where large-scale gene essentiality data is available: Drosophila melanogaster (fruit fly, Diptera) and Tribolium castaneum (red flour beetle, Coleoptera). We used publicly available databases plus a thorough literature review to obtain databases of essential and non-essential genes for D. melanogaster and T. castaneum, and proceeded by computing sequence-based attributes that were used to train statistical models (Random Forest and Gradient Boosting Trees) to predict essential genes for each species. Both models are capable of distinguishing essential from non-essential genes significantly better than zero-rule classifiers. Furthermore, models trained in one insect species are also capable of predicting essential genes in the other species significantly better than expected by chance. The Random Forest D. melanogaster model can also distinguish between essential and non-essential T. castaneum genes with no known homologs in the fly significantly better than a zero-rule model, demonstrating that it is possible to use our models to predict lineage-specific essential genes in a phylogenetically distant insect order. Here we report, to the best of our knowledge, the development and validation of the first general predictor of essential genes in insects using sequence-based attributes that can, in principle, be computed for any insect species where genomic information is available. The code and data used to predict essential genes in insects are freely available at https://github.com/g1o/GeneEssentiality/.


title: Identification of Japanese Encephalitis Virus Genotype V and Other Mosquito-borne Viruses in Camp Humphreys, Republic of Korea, using Metagenomic Analysis

abstract: Recent outbreaks of emerging and re-emerging viruses such as Zika, West Nile and Japanese encephalitis (JEV) viruses have shown that timely detection of novel arboviruses with epidemic potential is essential to mitigate human health risks. There have been rising concerns that an emergent JEV genotype (genotype V, GV) is circulating in Asia, against which the current US-FDA-approved JEV vaccine may not be efficacious. To ascertain if JEV GV and other arboviruses are circulating in East Asia, we conducted next-generation sequencing on 260 pools of Culex tritaeniorhynchus and Culex bitaeniorhynchus mosquitoes (6,540 specimens) collected at Camp Humphreys, Republic of Korea (ROK), from mid-May - October 2018. Metagenomic analysis demonstrated a highly abundant and diverse virome with correlates of health and ecological relevance. Additionally, two complete JEV GV genome sequences were obtained from separate mosquito pools, indicating that JEV GV is circulating in the Pyeongtaek area near Seoul, ROK. Retrospective sample and sequence analyses showed that JEV GV was also present in 2016 mosquito pools collected in Seoul, ROK. Sequence-based analysis of JEV GV indicates a divergent genotype that is the most distant from the GIII derived live attenuated SA14-14-2 vaccine strain. A GV E protein investigation and 3D modeling in context to SA14-14-2 indicated likely regions responsible for reduced antibody affinity, including clusters of significant amino acid changes at externally exposed domains. These data highlight the critical need for continued mosquito surveillance as a means of detecting and identifying emerging and re-emerging arboviruses of public health relevance. Importantly, our results emphasize recent concerns that there may be a possible shift in the circulating JEV genotype in East Asia and highlights the critical need for a vaccine proven to be efficacious against this re-emergent virus.


title: Sub-second multi-channel magnetic control of select neural circuits in behaving flies

abstract: Precisely timed activation of genetically targeted cells is a powerful tool for studying neural circuits and controlling cell-based therapies. Magnetic control of cell activity or "magnetogenetics" using magnetic nanoparticle heating of temperature-sensitive ion channels enables remote, non-invasive activation of neurons for deep-tissue applications and studies of freely behaving animals. However, the in vivo response time of thermal magnetogenetics is currently tens of seconds, which prevents the precise temporal modulation of neural activity similar to light-based optogenetics. Moreover, magnetogenetics has not provided a means to selectively activate multiple channels to drive behavior. Here we produce sub-second behavioral responses in Drosophila melanogaster by combining magnetic nanoparticles with a rate-sensitive thermoreceptor (TRPA1-A). Furthermore, by tuning the properties of magnetic nanoparticles to respond to different magnetic field strengths and frequencies, we can achieve sub-second, multichannel stimulation, analogous to multi-color optogenetic stimulation. These results bring magnetogenetics closer to the temporal resolution and multiplexed stimulation possible with optogenetics while maintaining the minimal invasiveness and deep-tissue stimulation only possible by magnetic control.

category: bioengineering


title: overlappingCGM: Automatic detection and analysis of overlapping co-expressed gene modules

abstract:
BackgroundWhen it comes to the co-expressed gene module detection, its typical challenges consist of overlap between identified modules and local co-expression in a subset of biological samples. The nature of module detection is the use of unsupervised clustering approaches and algorithms. Those methods are advanced undoubtedly, but the selection of a certain clustering method for sample- and gene-clustering tasks is separate, in which the latter task is often more complicated.

ResultsThis study presented an R-package, Overlapping CoExpressed gene Module (oCEM), armed with the decomposition methods to solve the challenges above. We also developed a novel auxiliary statistical approach to select the optimal number of principal components using a permutation procedure. We showed that oCEM outperformed state-of-the-art techniques in the ability to detect biologically relevant modules additionally.

ConclusionsoCEM helped non-technical users easily perform complicated statistical analyses and then gain robust results. oCEM and its applications, along with example data, were freely provided at https://github.com/huynguyen250896/oCEM.

category: bioinformatics


title: oCEM: Automatic detection and analysis of overlapping co-expressed gene modules


title: dGPredictor: Automated fragmentation method for metabolic reaction free energy prediction and de novo pathway design

abstract:
Group contribution (GC) methods are conventionally used in thermodynamics analysis of metabolic pathways to estimate the standard Gibbs free energy change ({Delta}rG'o) of enzymatic reactions from limited experimental measurements. However, these methods are limited by their dependence on manually curated groups and inability to capture stereochemical information, leading to low reaction coverage. Herein, we introduce an automated molecular fingerprint-based thermodynamic analysis tool called dGPredictor that enables the consideration of stereochemistry within metabolite structures and thus increases reaction coverage. dGPredictor has a higher prediction accuracy as compared to existing GC methods and can capture free energy changes for isomerase and transferase reactions, which exhibit no overall group changes. We also demonstrate dGPredictors ability to predict the Gibbs free energy change for novel reactions and seamless integration within de novo metabolic pathway design tools such as novoStoic. This enables performing a thermodynamic analysis for synthetic pathways, thus safeguarding against the inclusion of reaction steps with infeasible directionalities. To facilitate easy access to dGPredictor, we developed a graphical user interface to predict the standard Gibbs free energy change for reactions at various pH and ionic strengths. The tool allows customized user input of known metabolites as KEGG IDs and novel metabolites as InChI strings (https://github.com/maranasgroup/dGPredictor).

Author summaryThe genome-scale metabolic networks consist of a large number of biochemical reactions interconnected in a complex system. The standard Gibbs free energy change is commonly used to check for the feasibility of enzyme-catalyzed reactions as thermodynamics plays a crucial role in pathway design for biochemical synthesis. The group contribution methods using expert-defined functional groups have been extensively used for estimating standard Gibbs free energy change with limited experimental measurements. However, current methods using functional groups have major issues that limit its ability to cover all the metabolites and reactions as well as the inability to consider stereochemistry leads to erroneous estimation of free energy that undergoes only stereochemical change such as isomerases. Here, we introduce a molecular fingerprint-based thermodynamic tool dGPredictor that enables stereochemistry in metabolites and thus improves the reaction coverage with higher prediction accuracy compared to current GC methods. It also allows the ability to predict free energy change for novel reactions which can aid the de novo metabolic pathway design tool to ensure the reaction feasibility. We apply and test our method on reactions in the KEGG database and isobutanol synthesis pathway. In addition, we provide an open-source user-friendly web interface to facilitate easy access for standard Gibbs free energy change of reactions at different physiological states.


title: BIONIC: Biological Network Integration using Convolutions

abstract: Biological networks constructed from varied data, including protein-protein interactions, gene expression data, and genetic interactions can be used to map cellular function, but each data type has individual limitations such as bias and incompleteness. Network integration promises to address these limitations by combining and automatically weighting input information to obtain a more accurate and comprehensive representation of the underlying biology. However, existing network integration methods may fail to adequately scale to the number of nodes and networks present in genome-scale data, may perform poorly, and may not handle partial network overlap. To address these issues, we developed a deep learning-based network integration algorithm that incorporates a graph convolutional network (GCN) framework to effectively learn dependencies between any input network. Our method, BIONIC (Biological Network Integration using Convolutions), learns features which contain substantially more functional information compared to existing approaches, linking genes that share diverse functional relationships, including co-complex and shared bioprocess annotation. BIONIC can integrate networks in a fully unsupervised manner if functional gene annotations are not available, and it can also leverage available annotations in a semi-supervised manner. BIONIC is scalable in both size and quantity of the input networks, making it feasible to integrate numerous networks on the scale of the human genome. To demonstrate the utility of BIONIC in identifying novel biology, we predicted essential gene chemical-genetic interactions from a small set of diagnostic non-essential gene profiles in yeast, and experimentally validated these predictions. BIONIC correctly predicted many chemical-genetic interactions, and it correctly predicted genes that are required for proper {beta}-1,6-glucan synthesis as significant interactions with the bioactive compound pseudojervine.


title: Multi-omics Data Integration by Generative Adversarial Network

abstract: Accurate disease phenotype prediction plays an important role in the treatment of heterogeneous diseases like cancer in the era of precision medicine. With the advent of high throughput technologies, more comprehensive multi-omics data is now available that can effectively link the genotype to phenotype. However, the interactive relation of multi-omics datasets makes it particularly challenging to incorporate different biological layers to discover the coherent biological signatures and predict phenotypic outcomes. In this study, we introduce omicsGAN, a generative adversarial network (GAN) model to integrate two omics data and their interaction network. The model captures information from the interaction network as well as the two omics datasets and fuse them to generate synthetic data with better predictive signals. Large-scale experiments on The Cancer Genome Atlas (TCGA) breast cancer, lung cancer, and ovarian cancer datasets validate that (1) the model can effectively integrate two omics data (e.g., mRNA and microRNA expression data) and their interaction network (e.g., microRNA-mRNA interaction network). The synthetic omics data generated by the proposed model has a better performance on cancer outcome classification and patients survival prediction compared to original omics datasets. (2) The integrity of the interaction network plays a vital role in the generation of synthetic data with higher predictive quality. Using a random interaction network does not allow the framework to learn meaningful information from the omics datasets; therefore, results in synthetic data with weaker predictive signals.


title: Assessing the Role of CaM's Linker Flexibility in Target Binding

abstract: 1Calmodulin (CaM) is a universal Ca2+ binding protein known to bind at least 300 targets. The selectivity and specificity towards these targets are partially attributed to the proteins flexible alpha-helical linker that connects its N- and C-domains. How this flexible linker mediates the driving forces guiding CaMs binding to regulatory targets is not well-established. Therefore, we utilized the Martini coarse-grained (CG) molecular dynamics simulations to probe interrelationships between CaM/target assembly and the role of its linker region. As a model system, we simulated the binding of CaM to the CaM binding region (CaMBR) of calcineurin (CaN). The simulations were conducted assuming a  wild-type calmodulin with normal flexibility of its linker, as well as a labile, highly flexible linker variant. For the wild-type model, 98% of the 600 simulations across three ionic strengths adopted a bound complex within 2 {micro}s of simulation time; of these, 1.7% sampled the fully-bound state observed in experimentally-determined crystallographic structure. By calculating the mean-first-passage-time for these simulations, we estimated the association rate to be ka = 5.9 x 108 M-1 s-1, which is similar to the experimentally-determined rate of 2.2 x 108 M-1 s-1 [1]. Further, our simulations recapitulated the inverse relationship between the association rate and solution ionic strength reported in the literature. In contrast, although over 97% of the labile linker simulations formed tightly-bound complexes, only 0.3% achieved the fully-bound configuration. This effect appears to stem from a difference in the ensembles of extended and collapsed states controlled by the linker properties. Specifically, the labile linker variant samples fewer extended states compatible with target peptide binding. Therefore, our simulations suggest that variations in the CaM linkers propensity for alpha-helical secondary structure can modulate the kinetics of target binding. This finding is important, as the linker region houses several CaM variants sites for post-translational modifications, that may alter the proteins normal regulatory functions.

category: biophysics


title: Assessing the Role of Calmodulin's Linker Flexibility in Target Binding


title: Dynamic accumulation of a helper NLR at the plant-pathogen interface underpins pathogen recognition

abstract:
Plants employ sensor-helper pairs of NLR immune receptors to recognize pathogen effectors and activate immune responses. Yet the subcellular localization of NLRs pre- and post-activation during pathogen infection remains poorly known. Here we show that NRC4, from the  NRC solanaceous helper NLR family, undergoes dynamic changes in subcellular localization by shuttling to and from the plant-pathogen haustorium interface established during infection by the Irish potato famine pathogen Phytophthora infestans. Specifically, prior to activation, NRC4 accumulates at the extra-haustorial membrane (EHM), presumably to mediate response to perihaustorial effectors, that are recognized by NRC4-dependent sensor NLRs. However not all NLRs accumulate at the EHM, as the closely related helper NRC2, and the distantly related ZAR1, did not accumulate at the EHM. NRC4 required an intact N-terminal coiled coil domain to accumulate at the EHM, whereas the functionally conserved MADA motif implicated in cell death activation and membrane insertion was dispensable for this process. Strikingly, a constitutively autoactive NRC4 mutant did not accumulate at the EHM and showed punctate distribution that mainly associated with the plasma membrane, suggesting that post-activation, NRC4 probably undergoes a conformation switch to form clusters that do not preferentially associate with the EHM. When NRC4 is activated by a sensor NLR during infection however, NRC4 formed puncta mainly at the EHM and to a lesser extent at the plasma membrane. We conclude that following activation at the EHM, NRC4 may spread to other cellular membranes from its primary site of activation to trigger immune responses.

Significance statementPlant NLR immune receptors function as intracellular sensors of pathogen virulence factors known as effectors. In resting state, NLRs localize to subcellular sites where the effectors they sense operate. However, the extent to which NLRs alter their subcellular distribution during infection remains elusive. We describe dynamic changes in spatiotemporal localization of an NLR protein in infected plant cells. Specifically, the NLR protein accumulates at the newly synthesized plant-pathogen interface membrane, where the corresponding effectors are deployed. Following immune recognition, the activated receptor re-organizes to form punctate structures that target the cell periphery. We propose that NLRs are not necessarily stationary immune receptors, but instead may spread to other cellular membranes from the primary site of activation to boost immune responses.

category: plant biology


title: scite: a smart citation index that displays the context of citations and classifies their intent using deep learning

abstract: Citation indices are tools used by the academic community for research and research evaluation which aggregate scientific literature output and measure scientific impact by collating citation counts. Citation indices help measure the interconnections between scientific papers but fall short because they only display paper titles, authors, and the date of publications, and fail to communicate contextual information about why a citation was made. The usage of citations in research evaluation without due consideration to context can be problematic, if only because a citation that disputes a paper is treated the same as a citation that supports it. To solve this problem, we have used machine learning and other techniques to develop a "smart citation index" called scite, which categorizes citations based on context. Scite shows how a citation was used by displaying the surrounding textual context from the citing paper, and a classification from our deep learning model that indicates whether the statement provides supporting or disputing evidence for a referenced work, or simply mentions it. Scite has been developed by analyzing over 23 million full-text scientific articles and currently has a database of more than 800 million classified citation statements. Here we describe how scite works and how it can be used to further research and research evaluation.

category: scientific communication and education


title: Imperfect integration: sensory congruency between multiple sources modulates selective decision-making processes

abstract: AO_SCPLOWBSTRACTC_SCPLOWDecision making on the basis of multiple information sources is common. However, to what extent such decisions differ from those with a single source remains unclear. Here, we combined cognitive modelling and neural-mass modelling to characterise the neurocognitive process underlying decisionmaking with single or double information sources. Ninety-four human participants performed binary decisions to discriminate the coherent motion direction averaged across two independent apertures. Regardless the angular distance of the apertures, separating motion information into two apertures resulted in a reduction in accuracy. Our modelling results further showed that the addition of the second information source led to a lower signal-to-noise ratio of evidence accumulation with two congruent information sources, and a change in the decision strategy of speed-accuracy trade-off with two incongruent sources. Thus, our findings support a robust behavioural change in relation to multiple information sources, which have congruency-dependent impacts on selective decision-making subcomponents.

category: neuroscience


title: Visuomotor information drives interference between the hands more than dynamic motor information during bimanual reaching

abstract: During complex bimanual movements, interference can occur in the form of one hand influencing the action of the contralateral hand. Interference likely results from conflicting sensorimotor information shared between brain regions controlling hand movements via neural crosstalk. However, how visual and force-related feedback processes interact with each other during bimanual reaching is not well understood. In this study, four groups experienced either a visuomotor perturbation, dynamic perturbation, combined visuomotor and dynamic perturbation, or no perturbation in their right hand during bimanual reaches, with each hand controlling its own cursor. The left hand was examined for interference as a consequence of the right-hand perturbation. The results indicated that the visuomotor and combined perturbations showed greater interference in the left hand than the dynamic perturbation, but that the combined and visuomotor perturbations were equivalent. This suggests that dynamic sensorimotor and visuomotor processes do not interact between hemisphere-hand systems, and that primarily visuomotor processes lead to interference between the hands.


title: Foxq2 determines blue cone identity in zebrafish

abstract: Most vertebrate lineages retain a tetrachromatic visual system, which is supported by a functional combination of spectrally distinct multiple cone photoreceptors, UV, blue, green, and red cones. The blue cone identity is ensured by selective expression of blue (sws2) opsin, and the mechanism is poorly understood because SWS2 gene has been lost in mammalian species such as mouse, whose visual system has been extensively studied. Here we pursued loss-of-function studies on transcription factors expressed predominantly in zebrafish cone photoreceptors and identified Foxq2 as a core factor driving sws2 gene expression. foxq2 is expressed only in the blue cone, and loss of foxq2 selectively abolishes sws2 expression. Comparative genomic analysis revealed that a wide range of vertebrate species retain both FOXQ2 and SWS2 genes. We propose that FOXQ2-dependent SWS2 expression is a prevalent regulatory mechanism that was acquired at the early stage of vertebrate evolution


title: Open source timed pressure control hardware and software for delivery of air mediated distensions in animal models

abstract:
AbstractStudying the visceral sensory component of peripheral nervous systems can be challenging due to limited options for consistent and controlled stimulation. One method for mechanical stimulation of hollow organs, including colon and bladder, are controlled distensions mediated by compressed air. For example, distension of the bladder can be used as an assay for bladder nociception. Bladder distension causes a corresponding increase in abdominal electromyography, which increases with distension pressure and is attenuated with analgesics. However, the hardware used to control these distensions are primarily all one-off custom builds, without clear directions how to build your own. This has made it difficult for these methods to be fully utilized and replicated as not everyone has access, knowledge and resources required to build this controller. Here we show an open-source Arduino based system for controlling a solenoid valve to deliver timed pressure distensions in the experimental model. This device can be controlled by one of two methods through direct TTL pulses from the experimenters data acquisition software (ex. CED Spike2) or by a graphical user interface, where the user can set the time before, during, and after distension as well as the number of cycles. This systems low cost and relative ease to build will allow more groups to utilize timed pressure distensions in their experiments.

Specifications table

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title: Analogue representation of a spatial memory by ramp-like neural activity in retrohippocampal cortex

abstract: Neurons in the retrohippocampal cortices play crucial roles in spatial memory. Many retrohippocampal neurons have firing fields associated with specific locations, but whether this is the sole strategy for representing spatial memories is unclear. Here, we demonstrate that during a spatial memory task retrohippocampal neurons also encode location through ramping activity within discrete regions of a track, with rewarded locations represented by offsets or switches in the slope of the ramping activity. These representations do not require cues that mark reward locations indicating that they result from recall of the track structure. Similar representations emerged in recurrent neural networks trained to navigate to a rewarded location. We hypothesize that retrohippocampal ramping activity and its interruption mediates readout of learned models for goal-directed navigation.


title: Readout of a spatial memory by interruption of ramping activity in the retrohippocampal cortex


title: Compulsive drinking is associated with neural activity patterns reflecting diminished behavioral control and enhanced seeking representations in dorsal medial prefrontal cortex

abstract: Drinking despite negative consequences (compulsive drinking) is a central contributor to high-risk alcohol intake and is associated with poor treatment outcomes in humans. We used a rodent model of compulsive drinking to examine the role played by dorsal medial prefrontal cortex (dmPFC), a brain region involved in maladaptive decision-making in addiction, in this clinically critical phenomenon. We developed novel advances in principal component and change point analyses to dissect neural population representations of specific decision-making variables. Compulsive subjects showed weakened representations of behavioral control signals that relate to drinking within a trial, but strengthened session-wide seeking state representations that were associated with drinking engagement at the start of each drinking opportunity. Finally, chemogenetic-based excitation of dmPFC prevented escalation of compulsive drinking. Collectively, these data indicate that compulsive drinking is associated with alterations in dmPFC neural activity that underlie diminished behavioral control and enhanced seeking.


title: The role of ventromedial prefrontal cortex in reward valuation and future thinking during intertemporal choice

abstract: Intertemporal choices require trade-offs between short-term and long-term outcomes. Ventromedial prefrontal cortex (vmPFC) damage causes steep discounting of future rewards (delay discounting; DD) and impoverished episodic future thinking (EFT). The role of vmPFC in reward valuation, EFT, and their interaction during intertemporal choice is still unclear. Here, twelve patients with lesions to vmPFC and forty-one healthy controls chose between smaller-immediate and larger-delayed hypothetical monetary rewards while we manipulated reward magnitude and the availability of EFT cues. In the EFT condition, participants imagined personal events to occur at the delays associated with the larger-delayed rewards. We found that DD was steeper in vmPFC patients compared to controls, and not modulated by reward magnitude. However, EFT cues downregulated DD in vmPFC patients as well as controls. These findings indicate that vmPFC integrity is critical for the valuation of (future) rewards, but not to instill EFT in intertemporal choice.


title: Histone H3 Clipping is a novel signature of Human Neutrophil Extracellular Traps

abstract: Neutrophils are critical to host defence, executing diverse strategies to perform their antimicrobial and regulatory functions. One tactic is the production of neutrophil extracellular traps (NETs). In response to certain stimuli neutrophils decondense their lobulated nucleus and release chromatin into the extracellular space through a process called NETosis. However, NETosis, and the subsequent degradation of NETs, can become dysregulated. NETs are proposed to play a role in infectious as well as many non-infection related diseases including cancer, thrombosis, autoimmunity and neurological disease. Consequently, there is a need to develop specific tools for the study of these structures in disease contexts. In this study, we identified a NET-specific histone H3 cleavage event and harnessed this to develop a cleavage site-specific antibody for the detection of human NETs. By microscopy, this antibody distinguishes NETs from chromatin in purified and mixed cell samples. It also detects NETs in tissue sections. We propose this antibody as a new tool to detect and quantify NETs.

category: immunology


title: Natural Occurring Non-Synonymous Single Nucleotide Polymorphisms in Integrase and RNase H Regulate Assembly and Autoprocessing of HIV-1

abstract:
Recently, a genome-wide association study using plasma HIV RNA reported that 14 naturally occurring non-synonymous single nucleotide polymorphisms (SNPs) in HIV derived from anti-retrovirus naive patients were associated with virus load (VL). However, the impact of each mutation on viral fitness was not investigated. Here, we constructed a series of HIV variants encoding each SNP using site-directed mutagenesis and examined their replicative abilities and biological properties. An HIV variant containing Met-to-Ile change at codon 50 in integrase (HIV(IN:M50I)) was found an impaired virus. Despite the mutation being in integrase, a quantification assay demonstrated that the virus release was significantly suppressed (P<0.001). Transmission electron microscopy analyses revealed that the accumulation of abnormal shapes of buds on the plasma membrane and the released virus particles retained immature forms. Western blot analysis demonstrated a defect in autoprocessing of GagPol and Gag polyproteins in the HIV(IN:M50I) particles. Forster Resonance Energy Transfer (FRET) assay displayed that GagPol containing IN:M50I (GagPol(IN:M50I)) significantly increased the efficiency of homodimerization (P<0.05) and heterodimerization with Gag (P<0.001), compared to GagPol(WT). HIV replication assay using a series of variants of HIV(IN:M50I) elucidated that the C-terminus residues, Asn at codon 288, plays a key role in the defect and the impaired maturation and replication capability was rescued by two other VL-associated SNPs, Ser-to-Asn change at codon 17 in integrase or Asn-to-Ser change at codon 79 in RNase H. These data demonstrate that Gag and GagPol assembly, virus release and autoprocessing are not only regulated by integrase but also RNase H.

ImportanceA nascent HIV-1 is noninfectious. To become an infectious virus, Gag and GagPol polyproteins in the particles need to be cleaved by mature HIV protease (PR). PR is initially translated as an inactive embedded enzyme in a GagPol polyprotein. The embedded PR in homodimerized GagPol polyproteins catalyzes a proteolytic reaction to release the mature PR. This excision step by a self-cleavage is called autoprocessing. Here, during the evaluation of roles of naturally emerging non-synonymous SNPs in HIV RNA, we found that autoprocessing is inhibited by Met-to-Ile change at codon 50 in integrase in GagPol which increases the efficiency of heterodimerization with Gag. This defect was recovered by co-existing of other SNPs: Ser-to-Asn change at codon 17 in integrase or Asn-to-Ser mutation at codon 79 in RNase H, suggesting that autoprocessing is regulated by not only integrase but also RNase H in GagPol polyprotein.

category: microbiology


title: Alternative LC-MS/MS Platforms and Data Acquisition Strategies for Proteomic Genotyping of Human Hair Shafts

abstract:
Protein is a major component of all biological evidence. Proteomic genotyping is the use of genetically variant peptides that contain single amino acid polymorphisms to infer the genotype of matching non-synonymous single nucleotide polymorphisms for the individual who originated the protein sample. This can be used to statistically associate an individual to evidence found at a crime scene. The utility of the inferred genotype increases as the detection of genetically variant peptides increases, which is the direct result of technology transfer to mass spectrometry platforms typically available. Digests of single (2 cm) human hair shafts from three European and two African subjects were analyzed using data dependent acquisition on a Q-Exactive Plus Hybrid Quadrupole-Orbitrap system, data independent acquisition and a variant of parallel reaction monitoring on a Orbitrap Fusion Lumos Tribrid system, and multiple reaction monitoring on an Agilent 6495 triple quadrupole system. In our hands, average genetically variant peptide detection from a selected 24 genetically variant peptide panel increased from 6.5 {+/-} 1.1 and 3.1 {+/-} 0.8 using data dependent and independent acquisition to 9.5 {+/-} 0.7 and 11.7 {+/-} 1.7 using parallel reaction monitoring and multiple reaction monitoring (p < 0.05). Parallel reaction monitoring resulted in a 1.3-fold increase in detection sensitivity, and multiple reaction monitoring resulted in a 1.6-fold increase in detection sensitivity. This increase in biomarker detection has a functional impact on the statistical association of a protein sample and an individual. Increased biomarker sensitivity, using Markov Chain Monte Carlo modeling, produced a median estimated random match probability of over 1 in 10 trillion from a single hair using targeted proteomics. For parallel reaction monitoring and multiple reaction monitoring, detected genetically variant peptides were validated by the inclusion of stable isotope labeled peptides in each sample, which served also as a detection trigger. This research accomplishes two aims: the demonstration of utility for alternative analytical platforms in proteomic genotyping, and the establishment of validation methods for the evaluation of inferred genotypes.

HighlightsO_LITest four mass spectrometry configurations to optimize detection of genetically variant peptides
C_LIO_LITechnology transfer of proteomic genotyping assays
C_LIO_LIImproved sensitivity results in higher level of forensic discrimination for human identification using multiple reaction monitoring
C_LI

Graphical Abstract

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title: The formal demography of kinship III: Kinship dynamics with time-varying demographic rates

abstract:
BackgroundKinship models generally assume time-invariant demographic rates, and compute the kinship structures implied by those rates. It is important to compute the consequences of time variation in demographic rates for kinship stuctures.

ObjectivesOur goal is to develop a matrix model for the dynamics of kinship networks subject to arbitrary temporal variation in survival, fertility, and population structure.

MethodsWe develop a system of equations for the dynamics of the age structure of each type of kin of a Focal individual. The matrices describing survival and fertility vary with time. The initial conditions in the time-invariant model are replaced with a set of boundary conditions for initial time and initial age.

ResultsThe time-varying model maintains the network structure of the time-invariant model. In addition to the results of the time-invariant model, it provides kinship structures by period, cohort, and age. It applies equally to historical sequences of past rates and to projections of future rates. As an illustration, we analyze the kinship structure of Sweden from 1891 to 2120.

ContributionThe time-varying kinship model makes it possible to analyze the consequences of changing demographic rates, in the past or the future. It is easily computable, requires no simulations, and is readily extended to include additional, more distant relatives in the kinship network. The method can also be used to show the growth of families, lineages, and dynasties in populations across time and place and between social groups.


title: Insights into the drivers of radiating diversification in biodiversity hotspots using Saussurea (Asteraceae) as a case

abstract:
O_LIThe Qinghai-Tibet Plateau (QTP) encompasses areas with a remarkably high degree of biodiversity, harboring exceptional species-rich radiations. How these radiations formed by interacting with geology, climate and ecology remains seldom examined.
C_LIO_LIWe investigate the roles of abiotic (environmental) and biotic (species-intrinsic) factors in driving radiating diversification of Saussurea (Asteraceae) by deploying a number of time-dependent, paleoenvironment-dependent and trait-dependent models, as well as ecological distribution data.
C_LIO_LIWe show that three main clades of Saussurea begin to diversify in the Miocene almost simultaneously, with increasing diversification rates toward the present and negative dependence to paleotemperature. Acceleration in diversification rates are correlated with adaptive traits, as well climate lability, niche breadth and species range.
C_LIO_LIWe conclude that fluctuation of paleoclimate along with complex QTP environments provided opportunities for increased diversification rates of Saussurea with diverse adaptive traits, highlighting the importance of combinations of clade-specific traits and ecological niches in driving rapid radiation.
C_LI


title: Insights into the genetic architecture of complex traits in Napier grass (Cenchrus purpureus) and QTL regions governing forage biomass yield, water use efficiency and feed quality traits

abstract: Napier grass is the most important perennial tropical grass native to Sub-Saharan Africa and widely grown in tropical and subtropical regions around the world, primarily as a forage crop for animal feed, but with potential as an energy crop and in a wide range of other areas. Genomic resources have recently been developed for Napier grass that need to be deployed for genetic improvement and molecular dissection of important agro-morphological and feed quality traits. From a diverse set of Napier grass genotypes assembled from two independent collections, a subset of 84 genotypes that best represents the genetic diversity of the collections were selected and evaluated for two years in dry (DS) and wet (WS) seasons under three soil moisture conditions: moderate water stress in DS (DS-MWS); severe water stress in DS (DS-SWS) and, under rainfed (RF) conditions in WS (WS-RF). Data for agro-morphological and feed quality traits, adjusted for the spatial heterogeneity in the experimental blocks, were collected over a two-year period from 2018 to 2020. A total of 135,706 molecular markers were filtered, after removing markers with missing values > 10% and a minor allele frequency (MAF) < 5 %, from the high-density genome-wide markers generated previously using the genotyping by sequencing (GBS) method of the DArTseq platform. A genome-wide association study (GWAS), using two different mixed linear model algorithms, identified more than 58 QTL regions and markers associated with agronomic, morphological and water-use efficiency traits. QTL regions governing purple pigmentation and feed quality traits were also identified. The identified markers will be useful in the genetic improvement of Napier grass through the application of marker-assisted selection and for further characterization and map-based cloning of the QTLs.


title: Large Bi-Ethnic Study of Plasma Proteome Leads to Comprehensive Mapping of cis-pQTL and Models for Proteome-wide Association Studies

abstract: Improved understanding of genetic regulation of proteome can facilitate the identification of causal mechanisms for complex traits. We analyzed data on 4,657 plasma proteins from 7,213 European American (EA) and 1,871 African American (AA) individuals from the ARIC study, and further replicated findings on 467 AA individuals from the AASK study. Here we identified 2,004 proteins in EA and 1,618 in AA, with majority overlapping, which showed associations with common variants in cis-regions. Availability of AA samples led to smaller credible sets and significant number of population-specific cis-pQTLs. Elastic-net produced powerful models for protein prediction in both populations. An application of proteome-wide association studies (PWAS) to serum urate and gout, implicated several proteins, including IL1RN, revealing the promise of the drug anakinra to treat acute gout flares. Our study demonstrates the value of large and diverse ancestry study for genetic mechanisms of molecular phenotypes and their relationship with complex traits.


title: Large Bi-ethnic Study of Plasma Proteome Leads to Comprehensive Mapping of cis-pQTL and Models for Proteome-wide Association Studies


title: Plasma proteome analyses in individuals of European and African ancestry identify cis-pQTLs and models for proteome-wide association studies


title: tbg - a new file format for genomic data

abstract:
MotivationThe question of determining whether a Single-Nucleotide Polymorphism (SNP) or a variant in general leads to a change in the amino acid sequence of a protein coding gene is often a laborious and time-consuming challenge. Here, we introduce the tbg file format for storing genomic data and tbg-tools, a user-friendly toolbox for the faster analysis of SNPs. The file format stores information for each nucleotide in each gene, allowing to predict which change in the amino acid sequence will be caused by a variant in the nucleotide sequence. Our new tool therefore has the potential to make biological sense of the unprecedented amount of genome-wide genetic variation that researchers currently face.

ResultsThe new tab-separated file for storing the nucleotide data can be easily analyzed and used for a wide variety of biological research. It is also possible to automate some of these analyses using the additional analysis tools from tbg-tools

Availabilitytbg-tools is written in Python and allows the installation from the command line. It can be found on https://github.com/Croxa/tbg-tools.

Contactpschoenn@students.uni-mainz.de


title: Comparative Genomics of two Inbred Lines of the Potato Cyst Nematode Globodera rostochiensis reveals disparate Effector Family-specific Diversification Patterns

abstract:
BackgroundPotato cyst nematodes belong to the most harmful pathogens in potato, and durable management of these soil-borne parasites largely depends on host-plant resistances. These resistances are pathotype specific. The current Globodera rostochiensis pathotype scheme that defines five pathotypes (Ro1 - Ro5) is for fundamental and practical reasons barely useful. As a result, resistant potato varieties are worldwide used in a non-informed manner.

ResultsWe generated two novel reference genomes of G. rostochiensis inbred lines derived from a Ro1 and a Ro5 population. These genome sequences comprise 173 and 189 scaffolds respectively, marking a {approx} 24-fold reduction in fragmentation as compared to the current reference genome. We provide copy number variations for 18 effector families. Four dorsal gland effector families were investigated in more detail. SPRYSECs, known to be implicated in immune suppression, constitute by far the most diversified family with 60 and 99 variants in Ro1 and Ro5 distributed over 18 and 26 scaffolds. In contrast, CLEs, effectors involved in feeding site induction, show strong physical clustering. The 10 and 16 variants cluster on respectively 2 and 1 scaffolds. Given that pathotypes are defined by their effectoromes, we pinpoint the disparate nature of the contributing effector families in terms of sequence diversification and loss and gain of variants.

ConclusionTwo novel reference genomes allow for nearly complete inventories of effector diversification and physical organisation within and between pathotypes. Combined with insights we provide on effector family-specific diversification patterns, this constitutes a solid basis for an effectorome-based virulence scheme for this notorious pathogen.


title: CNPY4 inhibits the Hedgehog pathway by modulating membrane sterol lipids

abstract: Introductory paragraphThe Hedgehog (HH) pathway is critical for development and adult tissue homeostasis1. Aberrant HH signaling can cause congenital malformations, such as digit anomalies and holoprosencephaly2, and other diseases, including cancer3. Signal transduction is initiated by HH ligand binding to the Patched 1 (PTCH1) receptor on primary cilia, thereby releasing inhibition of Smoothened (SMO), a HH pathway activator4. Although cholesterol and several oxysterol lipids, which are enriched in the ciliary membrane, play a crucial role in HH activation4,5, the molecular mechanisms governing the regulation of these lipid molecules remain unresolved. Here, we identify Canopy 4 (CNPY4), a Saposin-like protein, as a regulator of the HH pathway that controls membrane sterol lipid levels. Cnpy4-/- embryos exhibit multiple defects consistent with HH signaling perturbations, most notably changes in digit number. Knockdown of Cnpy4 hyperactivates the HH pathway at the level of SMO in vitro, and elevates membrane levels of accessible sterol lipids such as cholesterol, an endogenous ligand involved in SMO activation6. Thus, our data demonstrate that CNPY4 is a negative regulator that fine-tunes the initial steps of HH signal transduction, revealing a previously undescribed facet of HH pathway regulation that operates through control of membrane composition.

category: biochemistry


title: MCMICRO: A scalable, modular image-processing pipeline for multiplexed tissue imaging

abstract: Highly multiplexed tissue imaging makes molecular analysis of single cells possible in a preserved spatial context. However, reproducible analysis of the underlying data poses a substantial computational challenge. Here we describe a modular and open-source computational pipeline (MCMICRO) for performing the sequential steps needed to transform large, multi-channel whole slide images into single-cell data. We demonstrate use of MCMICRO on images of different tissues and tumors acquired using multiple imaging platforms, thereby providing a solid foundation for the continued development of tissue imaging software.


title: Reconstruction of Contemporary Human Stem Cell Dynamics with Oscillatory Molecular Clocks

abstract: Molecular clocks record cellular ancestry. However, currently used clocks  tick too slowly to measure the short-timescale dynamics of cellular renewal in adult tissues. Here we develop  rapidly oscillating DNA methylation clocks where ongoing (de)methylation causes the clock to  tick-tock back-and-forth between methylated and unmethylated states like a pendulum. We identify oscillators using standard methylation arrays and develop a mathematical modelling framework to quantitatively measure human adult stem cell dynamics from these data. Small intestinal crypts were inferred to contain slightly more stem cells than colon (6.5 {+/-} 1.0 vs 5.8 {+/-} 1.7 stem cells/crypt) with slower stem cell replacement in small intestine (0.79 {+/-} 0.5 vs 1.1 {+/-} 0.8 replacements/stem cell/year). Germline APC mutation increased the number of replacements per crypt (13.0 {+/-} 2.4 replacements/crypt/year vs 6.9 {+/-} 4.6 for healthy colon). In blood, we measure rapid expansion of acute leukaemia and slower growth of chronic disease. Rapidly oscillating molecular clocks are a new methodology to quantitatively measure human somatic cell dynamics.


title: Personalized sleep-wake patterns aligned with circadian rhythm relieve daytime sleepiness

abstract: Shift workers and many other groups experience irregular sleep-wake patterns. This can induce excessive daytime sleepiness that decreases productivity and elevates the risk of accidents. However, the degree of daytime sleepiness is not correlated with standard sleep parameters like total sleep time, suggesting other factors are involved. Here, we analyze real-world sleep-wake patterns of shift workers measured by wearables with a newly developed user-friendly computational package that simulates homeostatic sleep pressure - the physiological need for sleep - and the circadian rhythm. This reveals that shift workers who align sleep-wake patterns with their circadian rhythm have lower daytime sleepiness, even if they sleep less. The alignment, quantified by a new parameter, circadian sleep sufficiency, can be increased by dynamically adjusting daily sleep durations according to varying bedtimes. Our computational package provides flexible and personalized real-time sleep-wake patterns for individuals to reduce their daytime sleepiness and could be used with wearable devices to develop smart alarms.

category: systems biology


title: Simple morphometrics for predicting lordosis-induced deviations of body-shape in reared Gilthead seabream (Sparus aurata L.)

abstract: Haemal lordosis, V-shape bending of the haemal vertebrae, is a frequent abnormality of reared fish. Lordosis severity ranges from light deformations of vertebral axis, with insignificant effects on external morphology, to severe axis deformations with significant impact on body-shape. In the present study, we developed a simple morphometric index (PrAn) that links lordosis severity at the juvenile stage with fish body-shape at harvesting, without requiring to radiograph or sacrifice the samples. Examined seabream specimens were part of our previous study (Fragkoulis et al. 2019, Sci. Rep. 9, 9832), which monitored the effects of lordosis on the external morphology of pit-tagged seabream juveniles during their growth, up to harvest size. At both juvenile and adult stages, PrAn was effective in discriminating the normal fish from ca the 70% of lordotic fish. Our results suggest the PrAn as a valuable scale of quality, which quantifies the lordosis effects on fish external morphology, both at the juvenile stage and at harvest. Depending on the lordosis rates, and the hatchery strategy on the maximum allowed abnormality rates, this scale can cull out different rates of lordotic fish, without affecting the fish with normal phenotype or the lordotic fish with high recovery potential.

category: zoology


title: In Poetry, if Meter has to Help Memory, it Takes its Time

abstract: To test the idea that poetic meter emerged as a cognitive schema to aid verbal memory, we have focused on classical Italian poetry and on its three basic components of meter: rhyme, accent and verse length. Meaningless poems were generated by introducing prosody-invariant non-words into passages from Dantes Divina Commedia and Ariostos Orlando Furioso, which were then further manipulated by selectively ablating rhymes, modifying accent patterns or altering the number of syllables. The resulting four versions of each non-poem were presented in a fully balanced design to cohorts of high school educated Italian native speakers, who were then asked to retrieve 3 target non-words. Surprisingly, we found that the integrity of Dantes meter has no significant effect on memory performance. With passages derived from Ariosto, instead, removing each component downgrades memory by an amount proportional to its contribution to perceived metric plausibility, with rhymes having the strongest effects, followed by accents and then by verse length. Counterintuitively, the fully metric versions required longer reaction times, implying that activating metric schemata involves a cognitive cost. Within schema theories, this finding provides evidence for high-level interactions between procedural and episodic memory.


title: α-lipoic acid has the potential to normalize copper metabolism, which is dysregulated in Alzheimer's disease

abstract:
Alzheimers disease (AD) is an age-dependent progressive neurodegenerative disorder and the most common cause of dementia. The treatment and prevention of AD present immense yet unmet needs. One of the hallmarks of AD is the formation of extracellular amyloid plaques in the brain, composed of amyloid-beta (A{beta}) peptides. Multiple amyloid-targeting drug candidates have recently failed in clinical trials, which creates the necessity to focus also on alternative therapeutic strategies. One factor contributing to the development of AD is dysregulated copper metabolism, reflected in the intracellular copper deficit and excess extracellular copper levels. In the current study, we follow the widely accepted hypothesis that the normalization of copper metabolism leads to the prevention or slowing of the disease and searched for new copper-regulating ligands. We demonstrate that the natural intracellular copper chelator, -lipoic acid (LA) translocates copper from extracellular to intracellular space in a SH-SY5Y-based neuronal cell model, and is thus suitable to alleviate the intracellular copper deficit characteristic of AD neurons. Furthermore, we show that supplementation with LA protects the Drosophila melanogaster model of AD from developing AD phenotype, reflecting in decreased locomotor activity. Collectively, these results provide evidence that LA has the potential to normalize copper metabolism in AD and supports the hypothesis that LA supplementation may serve as a promising cost-effective method for the prevention and/or treatment of AD.

Significance statementAlzheimers disease (AD) is a major biomedical concern that requires novel effective prevention and treatment approaches. An early determinant of AD pathology is dysregulated copper metabolism, which initiates the amyloid cascade, induces oxidative stress and impairs the functioning of cellular copper proteins, all contributing to the development of neurodegeneration. We suggest that the natural copper chelator -lipoic acid (LA) can normalize impaired copper metabolism in AD. We demonstrate that LA promotes the influx of copper into SH-SY5Y cells in a dose-dependent manner. Moreover, we show that LA alleviates the disease phenotype in a Drosophila melanogaster model of AD. Together with previously published data, these results support the hypothesis that LA has the potential for the prevention and treatment of AD.


title: Elicitation of broadly protective sarbecovirus immunity by receptor-binding domain nanoparticle vaccines

abstract: Understanding the ability of SARS-CoV-2 vaccine-elicited antibodies to neutralize and protect against emerging variants of concern and other sarbecoviruses is key for guiding vaccine development decisions and public health policies. We show that a clinical stage multivalent SARS-CoV-2 receptor-binding domain nanoparticle vaccine (SARS-CoV-2 RBD-NP) protects mice from SARS-CoV-2-induced disease after a single shot, indicating that the vaccine could allow dose-sparing. SARS-CoV-2 RBD-NP elicits high antibody titers in two non-human primate (NHP) models against multiple distinct RBD antigenic sites known to be recognized by neutralizing antibodies. We benchmarked NHP serum neutralizing activity elicited by RBD-NP against a lead prefusion-stabilized SARS-CoV-2 spike immunogen using a panel of single-residue spike mutants detected in clinical isolates as well as the B.1.1.7 and B.1.351 variants of concern. Polyclonal antibodies elicited by both vaccines are resilient to most RBD mutations tested, but the E484K substitution has similar negative consequences for neutralization, and exhibit modest but comparable neutralization breadth against distantly related sarbecoviruses. We demonstrate that mosaic and cocktail sarbecovirus RBD-NPs elicit broad sarbecovirus neutralizing activity, including against the SARS-CoV-2 B.1.351 variant, and protect mice against severe SARS-CoV challenge even in the absence of the SARS-CoV RBD in the vaccine. This study provides proof of principle that sarbecovirus RBD-NPs induce heterotypic protection and enables advancement of broadly protective sarbecovirus vaccines to the clinic.


title: Cluster Analysis of SARS-CoV-2 Gene using Deep Learning Autoencoder: Gene Profiling for Mutations and Transitions

abstract: We report on a method for analyzing the variant of coronavirus genes using autoencoder. Since coronaviruses have mutated rapidly and generated a large number of genotypes, an appropriate method for understanding the entire population is required. The method using autoencoder meets this requirement and is suitable for understanding how and when the variants emarge and disappear. For the over 30,000 SARS-CoV-2 ORF1ab gene sequences sampled globally from December 2019 to February 2021, we were able to represent a summary of their characteristics in a 3D plot and show the expansion, decline, and transformation of the virus types over time and by region. Based on ORF1ab genes, the SARS-CoV-2 viruses were classified into five major types (A, B, C, D, and E in the order of appearance): the virus type that originated in China at the end of 2019 (type A) practically disappeared in June 2020; two virus types (types B and C) have emerged in the United States and Europe since February 2020, and type B has become a global phenomenon. Type C is only prevalent in the U.S. and is suspected to be associated with high mortality, but this type also disappeared at the end of June. Type D is only found in Australia. Currently, the epidemic is dominated by types B and E.


title: Design and proof-of-concept for targeted phage-based COVID-19 vaccination strategies with a streamlined cold-free supply chain

abstract:
Development of effective vaccines against Coronavirus Disease 2019 (COVID-19) is a global imperative. Rapid immunization of the world human population against a widespread, continually evolving, and highly pathogenic virus is an unprecedented challenge, and many different vaccine approaches are being pursued to meet this task. Engineered filamentous bacteriophage (phage) have unique potential in vaccine development due to their inherent immunogenicity, genetic plasticity, stability, cost-effectiveness for large-scale production, and proven safety profile in humans. Herein we report the design, development, and initial evaluation of targeted phage-based vaccination approaches against Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) by using dual ligand peptide-targeted phage and adeno-associated virus/phage (AAVP) particles. Towards a unique phage- and AAVP-based dual-display candidate approach, we first performed structure-guided antigen design to select six solvent-exposed epitopes of the SARS-CoV-2 spike (S) protein for display on the recombinant major capsid coat protein pVIII. Targeted phage particles carrying one of these epitopes induced a strong and specific humoral response. In an initial experimental approach, when these targeted phage particles were further genetically engineered to simultaneously display a ligand peptide (CAKSMGDIVC) on the minor capsid protein pIII, which enables receptor-mediated transport of phage particles from the lung epithelium into the systemic circulation (termed "dual-display"), they enhanced a systemic and specific spike (S) protein-specific antibody response upon aerosolization into the lungs of mice. In a second line of investigation, we engineered targeted AAVP particles to deliver the entire S protein gene under the control of a constitutive cytomegalovirus (CMV) promoter, which induced tissue-specific transgene expression stimulating a systemic S protein-specific antibody response. As proof-of-concept preclinical experiments, we show that targeted phage- and AAVP-based particles serve as robust yet versatile enabling platforms for ligand-directed immunization and promptly yield COVID-19 vaccine prototypes for further translational development.

SignificanceThe ongoing COVID-19 global pandemic has accounted for over 2.5 million deaths and an unprecedented impact on the health of mankind worldwide. Over the past several months, while a few COVID-19 vaccines have received Emergency Use Authorization and are currently being administered to the entire human population, the demand for prompt global immunization has created enormous logistical challenges--including but not limited to supply, access, and distribution--that justify and reinforce the research for additional strategic alternatives. Phage are viruses that only infect bacteria and have been safely administered to humans as antibiotics for decades. As experimental proof-of-concept, we demonstrated that aerosol pulmonary vaccination with lung-targeted phage particles that display short epitopes of the S protein on the capsid as well as preclinical vaccination with targeted AAVP particles carrying the S protein gene elicit a systemic and specific immune response against SARS-CoV-2 in immunocompetent mice. Given that targeted phage- and AAVP-based viral particles are sturdy yet simple to genetically engineer, cost-effective for rapid large-scale production in clinical grade, and relatively stable at room temperature, such unique attributes might perhaps become additional tools towards COVID-19 vaccine design and development for immediate and future unmet needs.


title: Overexpression of the RNA-binding protein NrdA affects global gene expression and secondary metabolism in Aspergillus species

abstract:
RNA-binding protein Nrd1 plays a role in RNA polymerase II transcription termination. In this study, we showed that the orthologous NrdA is important in global mRNA expression and secondary metabolism in Aspergillus species. We constructed an nrdA conditional expression strain using the Tet-On system in Aspergillus luchuenesis mut. kawachii. Downregulation of nrdA caused a severe growth defect, indicating that NrdA is essential for the proliferation of A. kawachii. Parallel RNA-sequencing and RNA immunoprecipitation-sequencing analysis identified potential NrdA-interacting transcripts, corresponding to 32% of the predicted protein coding genes of A. kawachii. Subsequent gene ontology analysis suggested that overexpression of NrdA affects the production of secondary metabolites. To clarify this, we constructed NrdA-overexpressing strains of Aspergillus nidulans, Aspergillus fumigatus, and Aspergillus oryzae. Overexpression of NrdA reduced the production of sterigmatocystin and penicillin in A. nidulans, as well as that of helvolic acid and pyripyropene A in A. fumigatus. Moreover, it increased the production of kojic acid and reduced production of penicillin in A. oryzae. These effects were accompanied by almost consistent transcriptional changes in the relevant genes. Collectively, these results suggest that NrdA is the essential RNA-binding protein, which plays a significant role in global gene expression and secondary metabolism in Aspergillus species.

IMPORTANCENrd1, a component of the Nrd1-Nab3-Sen1 complex, is an essential RNA-binding protein involved in transcriptional termination in yeast. However, its role in filamentous fungi has not been studied. In this study, we characterized an orthologous NrdA in the Aspergillus species, identified potential NrdA-interacting mRNA, and investigated the effect of overexpression of NrdA on mRNA expression in Aspergillus luchuensis mut. kawachii. The results indicated that NrdA controls global gene expression involved in versatile metabolic pathways, including the secondary metabolic process. We demonstrated that NrdA overexpression significantly affected the production of secondary metabolites in Aspergillus nidulans, Aspergillus oryzae, and Aspergillus fumigatus. Our findings are of importance to the fungal research community because the secondary metabolism is an industrially and clinically important aspect for the Aspergillus species.


title: Pyrolyzed substrates induce aromatic compound metabolism in the post-fire fungus, Pyronema domesticum

abstract:
Wildfires represent a fundamental and profound disturbance in many ecosystems, and their frequency and severity are increasing in many regions of the world. Fire affects soil by removing carbon in the form of CO2 and transforming remaining surface carbon into pyrolyzed organic material (PyOM). Fires also generate substantial necromass at depths where the heat kills soil organisms but does not catalyze the formation of PyOM. Pyronema species strongly dominate soil fungal communities within weeks to months after fire. However, the carbon pool (i.e. necromass or PyOM) that fuels their rise in abundance is unknown. We used a Pyronema domesticum isolate from the catastrophic 2013 Rim Fire (CA, USA) to ask if P. domesticum is capable of metabolizing PyOM. P. domesticum grew readily on agar media where the sole carbon source was PyOM (specifically, pine wood PyOM produced at 750 {degrees}C). Using RNAseq, we investigated the response of P. domesticum to PyOM and observed a comprehensive induction of genes involved in the metabolism and mineralization of aromatic compounds, typical of those found in PyOM. Lastly, we used 13C-labeled 750 {degrees}C PyOM to demonstrate that P. domesticum is capable of mineralizing PyOM to CO2. Collectively, our results indicate a robust potential for P. domesticum to liberate carbon from PyOM in post-fire ecosystems and return it to the bioavailable carbon pool.

IMPORTANCEFires are increasing in frequency and severity in many regions across the world. Thus, its critically important to understand how our ecosystems respond to inform restoration and recovery efforts. Fire transforms the soil, removing many nutrients while leaving behind both nutritious necromass and complex pyrolyzed organic matter, which is often recalcitrant. Filamentous fungi of the genus Pyronema strongly dominate soil fungal communities soon after fire. While Pyronema are key pioneer species in post-fire environments, the nutrient source that fuels their rise in abundance is unknown. In this manuscript, we used a P. domesticum isolate from the catastrophic 2013 Rim Fire (CA, USA) to demonstrate that P. domesticum metabolizes pyrolyzed organic material, effectively liberating this complex pyrolyzed carbon and returning it to the bioavailable carbon pool. The success of Pyronema in post-fire ecosystems has the potential to kick-start growth of other organisms and influence the entire trajectory of post-fire recovery.


title: DNA spike-ins enable confident interpretation of SARS-CoV-2 genomic data from amplicon-based sequencing

abstract: The rapid global spread and continued evolution of SARS-CoV-2 has highlighted an unprecedented need for viral genomic surveillance and clinical viral sequencing. Amplicon-based sequencing methods provide a sensitive, low-cost and rapid approach but suffer a high potential for contamination, which can undermine lab processes and results. This challenge will only increase with expanding global production of sequences by diverse research groups for epidemiological and clinical interpretation. We present an approach which uses synthetic DNA spike-ins (SDSIs) to track samples and detect inter-sample contamination through a sequencing workflow. Applying this approach to the ARTIC Consortiums amplicon design, we define a series of best practices for Illumina-based sequencing and provide a detailed characterization of approaches to increase sensitivity for low-viral load samples incorporating the SDSIs. We demonstrate the utility and efficiency of the SDSI method amidst a real-time investigation of a suspected hospital cluster of SARS-CoV-2 cases.

category: molecular biology


title: Single cell RNA sequencing of the Strongylocentrotus purpuratus larva reveals the blueprint of major cell types and nervous system of a non-chordate deuterostome

abstract: Identifying the molecular fingerprint of organismal cell types is key for understanding their function and evolution. Here, we use single cell RNA sequencing (scRNA-seq) to survey the cell types of the sea urchin early pluteus larva, representing an important developmental transition from non-feeding to feeding larva. We identify 21 distinct cell clusters, representing cells of the digestive, skeletal, immune, and nervous systems. Further subclustering of these reveal a highly detailed portrait of cell diversity across the larva, including the identification of neuronal cell types. We then validate important gene regulatory networks driving sea urchin development and reveal new domains of activity within the larval body. Focusing on neurons that co-express Pdx-1 and Brn1/2/4, we identify an unprecedented number of genes shared by this population of neurons in sea urchin and vertebrate endocrine pancreatic cells. Using differential expression results from Pdx-1 knockdown experiments, we show that Pdx1 is necessary for the acquisition of the neuronal identity of these cells. We hypothesize that a network similar to the one orchestrated by Pdx1 in the sea urchin neurons was active in an ancestral cell type and then inherited by neuronal and pancreatic developmental lineages in sea urchins and vertebrates.

category: developmental biology