title: Genome-wide association, prediction and heritability in bacteria

abstract:
Advances in whole-genome genotyping and sequencing have allowed genome-wide analyses of association, prediction and heritability in many organisms. However, the application of such analyses to bacteria is still in its infancy, being limited by difficulties including the plasticity of bacterial genomes and their strong population structure. Here we propose, and validate using simulations, a suite of genome-wide analyses for bacteria. We combine methods from human genetics and previous bacterial studies, including linear mixed models, elastic net and LD-score regression, and introduce innovations such as frequency-based allele coding, testing for both insertion/deletion and nucleotide effects and partitioning heritability by genome region. We then analyse three phenotypes of a major human pathogen Streptococcus pneumoniae, including the first analyses of minimum inhibitory concentrations (MIC) for each of two antibiotics, penicillin and ceftriaxone. We show that these are highly heritable leading to high prediction accuracy, which is explained by many genetic associations identified under good control of population structure effects. In the case of ceftriaxone MIC, these results are surprising because none of the isolates was resistant according to the inhibition zone diameter threshold. We estimate that just over half of the heritability of penicillin MIC is explained by a known drug-resistance region, which also contributes around a quarter of the heritability of ceftriaxone MIC. For the within-host survival phenotype carriage duration, no reliable associations were found but we observed moderate heritability and prediction accuracy, indicating a polygenic trait. While generating important new results for S. pneumoniae, we have critically assessed existing methods and introduced innovations that will be useful for future large-scale population genomics studies to help decipher the genetic architecture of bacterial traits.

Author summaryGenome-wide association, prediction and heritability analyses in bacteria are beginning to help unravel the genetic underpinnings of traits such as antimicrobial resistance, virulence, within-host survival and transmissibility. Progress to date is limited by challenges including the effects of strong population structure and variable recombination, and the many gaps in sequence alignments including the absence of entire genes in many isolates. More work is required to critically asses and develop methods for bacterial genomics. We address this task here, using a range of existing methods from bacterial and human genetics, such as linear mixed models, elastic net and LD-score regression. Using simulations, we first validate and then adapt these methods to introduce new analyses, including separate assessment of gap and nucleotide effects, a new allele coding for association analyses and a method to partition heritability into genome regions. We analyse within-host survival and two antimicrobial response traits of Streptococcus pneumoniae, identifying many novel associations while demonstrating good control of population structure and accurate prediction. We present both new results for an important pathogen and methodological advances that will be useful in guiding future studies in bacterial population genomics.


title: Intrinsically disordered sequences in the Polycomb protein Polyhomeotic regulate condensate formation

abstract: The Polycomb group (PcG) complex PRC1 localizes in the nucleus in the form of condensed structures called Polycomb bodies. The PRC1 subunit Polyhomeotic (Ph) contains a polymerizing sterile alpha motif (SAM) that is implicated in both PcG body formation and chromatin organization in Drosophila and mammalian cells. A truncated version of Ph containing the SAM (mini-Ph), forms phase separated condensates with DNA or chromatin in vitro, suggesting PcG bodies may form by phase separation. In cells, Ph forms multiple condensates, while mini-Ph forms a single large nuclear condensate. We therefore hypothesize that sequences outside of mini-Ph are required for proper condensate formation. We identified three distinct Intrinsically Disordered Regions (IDRs) in Ph based on sequence composition and complexity. We tested the role of each IDR in Ph condensates using live imaging of transfected Drosophila S2 cells. We find that each IDR uniquely affects Ph SAM-dependent condensate size, number, and morphology.

category: biochemistry


title: Predicting the Activities of Drug Excipients on Biological Targets using One-Shot Learning

abstract: Excipients are a major component of drugs and are used to improve drugs attributes such as stability and appearance. Excipients approved by Food and Drug Administration (FDA) are regarded as safe for human in allowed concentration, but their potential interaction with drug targets have not been investigated systematically, which might influence drugs efficacy. Deep learning models have been used for identification of ligands that could bind to the drug targets. However, due to the limited available data, it is challenging to reliably estimate the likelihood of a ligand-protein interaction. One-shot learning techniques provide a potential approach to address this low-data problem as these techniques require only one or a few examples to classify the new data. In this study, we apply one-shot learning models on datasets that include ligands binding to G-Protein Coupled Receptors (GPCRs) and Kinases. The predicted results suggest that one-shot learning models could be used for predicting ligand-protein interaction and the models attain better performance when protein targets contain conserved binding pockets. The trained models are also used to predict interactions between excipients and drug targets, which provides a potential efficient strategy to explore the activities of drug excipients. We find that a large number of drug excipients could interact with biological targets and influence their function. The results demonstrate how one-shot learning models can be used to make accurate prediction for excipient-protein interactions and these methods could be used for selecting excipients with limited drug-protein interactions.


title: RecA and RecB: probing complexes of DNA repair proteins with mitomycin C in live Escherichia coli with single-molecule sensitivity

abstract: The RecA protein and RecBCD complex are key bacterial components for the maintenance and repair of DNA, RecBCD a helicase-nuclease that uses homologous recombination to resolve double-stranded DNA breaks and also facilitating decoration of single-stranded DNA with RecA to form RecA filaments, a vital step in the double-stranded break DNA repair pathway. However, questions remain about the mechanistic roles of RecA and RecBCD in live cells. Here, we use millisecond super-resolved fluorescence microscopy to pinpoint the spatial localization of fluorescent reporters of RecA and the RecB at physiological levels of expression in individual live Escherichia coli cells. By introducing the DNA crosslinker mitomycin C, we induce DNA damage and quantify the resulting changes in stoichiometry, copy number and molecular mobilities of RecA and RecB. We find that both proteins accumulate in molecular hotspots to effect repair, resulting in RecA filamental stoichiometries equivalent to several hundred molecules that act largely in RecA tetramers before DNA damage, but switch to approximately hexameric subunits when mature filaments are formed. Unexpectedly, we find that the physiologically predominant form of RecB is a dimer.

category: biophysics


title: A mechanistic model of malignant transformation in vestibular schwannoma

abstract: A vestibular schwannoma (VS) is a relatively rare, benign tumour of the eighth cranial nerve, often involving alterations to the gene NF2. Previous mathematical models of schwannoma incidence have not attempted to account for alterations in specific genes, and could not distinguish between point mutations and loss of heterozygosity (LOH). Here, we present a mechanistic approach to modelling initiation and malignant transformation in Schwannoma. Each parameter is associated with a specific gene or mechanism operative in Schwann cells, and can be determined by combining incidence data with empirical frequencies of pathogenic variants and LOH. This results in new estimates for the base pair mutation rate u = 4.48 x 10-10 and the rate of LOH = 2.03 x 10-6/yr in Schwann cells. In addition to new parameter estimates, we extend the approach to estimate the risk of both spontaneous and radiation-induced malignant transformation. We conclude that radiotherapy is likely to have a negligible excess risk of malignancy for sporadic VS, with a possible exception of rapidly growing tumours.

category: cancer biology


title: Proteome biology of primary colorectal carcinoma and corresponding liver metastases

abstract: Colorectal adenocarcinomas (CRC) are one of the most commonly diagnosed tumors worldwide. Colorectal adenocarcinomas primarily metastasize into the liver and (less often) into the peritoneum. Patients suffering from CRC-liver metastasis (CRC-LM) typically present with a dismal overall survival compared to non-metastasized CRC patients. The metastasis process and metastasis-promoting factors in patients with CRC are under intensive debate. However, CRC studies investigating the proteome biology are lacking. Formalin-fixed paraffin-embedded (FFPE) tissue specimens provide a valuable resource for comprehensive proteomic studies of a broad variety of clinical malignancies. The presented pilot study compares the proteome of primary CRC and patient-matched CRC-LM. The applied protocol allows a reproducible and straightforward identification and quantification of over 2,600 proteins within the dissected tumorous tissue. Subsequent unsupervised clustering reveals distinct proteome biologies of the primary CRC and the corresponding CRC-LM. Statistical analysis yields multiple differentially abundant proteins in either primary CRC or their corresponding liver metastases. A more detailed analysis of dysregulated biological processes suggests an active immune response in the liver metastases, including several proteins of the complement system. Proteins with structural roles, e.g. cytoskeleton organization or cell junction assembly appear to be less prominent in liver metastases as compared to primary CRC. Immunohistochemistry corroborates proteomic high expression levels of metabolic proteins in CRC-LM. We further assessed how the in vitro inhibition of two in CRC-LM enriched metabolic proteins affected cell proliferation and chemosensitivity. The presented proteomic investigation in a small clinical cohort promotes a more comprehensive understanding of the distinct proteome biology of primary CRC and their corresponding liver metastases.


title: Fluorescence Activation Mechanism and Imaging of Drug Permeation with New Sensors for Smoking-Cessation Ligands

abstract: Nicotinic partial agonists provide an accepted aid for smoking cessation and thus contribute to decreasing tobacco-related disease. Improved drugs constitute a continued area of study. However, there remains no reductionist method to examine the cellular and subcellular pharmacokinetic properties of these compounds in living cells. Here, we developed new intensity-based drug sensing fluorescent reporters ("iDrugSnFRs") for the nicotinic partial agonists dianicline, cytisine, and two cytisine derivatives - 10-fluorocytisine and 9-bromo-10-ethylcytisine. We report the first atomic-scale structures of liganded periplasmic binding protein-based biosensors, accelerating development of iDrugSnFRs and also explaining the activation mechanism. The nicotinic iDrugSnFRs detect their drug partners in solution, as well as at the plasma membrane (PM) and in the endoplasmic reticulum (ER) of cell lines and mouse hippocampal neurons. At the PM, the speed of solution changes limits the growth and decay rates of the fluorescence response in almost all cases. In contrast, we found that rates of membrane crossing differ among these nicotinic drugs by > 30 fold. The new nicotinic iDrugSnFRs provide insight into the real-time pharmacokinetic properties of nicotinic agonists and provide a methodology whereby iDrugSnFRs can inform both pharmaceutical neuroscience and addiction neuroscience.

category: pharmacology and toxicology


title: Protection against avian coronavirus conferred by oral vaccination with live bacteria secreting LTB-fused viral proteins

abstract:
The devastating impact of infectious bronchitis (IB) triggered by the IB virus (IBV), on poultry farms is generally curbed by livestock vaccination with live attenuated or inactivated vaccines. Yet, this approach is challenged by continuously emerging variants and by time limitations of vaccine preparation techniques. This work describes the design and evaluation of an anti-IBV vaccine comprised of E. coli expressing and secreting viral spike 1 subunit (S1) and nucleocapsid N-terminus and C-terminus polypeptides fused to heat-labile enterotoxin B (LTB) (LS1, LNN, LNC, respectively). Following chicken oral vaccination, anti-IBV IgY levels and cellular-mediated immunity as well as protection against virulent IBV challenge, were evaluated 14 days following the booster dose. Oral vaccination induced IgY levels that exceeded those measured following vaccination with each component separately. Following exposure to inactivated IBV, splenocytes isolated from chicks orally vaccinated with LNN or LNC -expressing bacteria, showed a higher percentage of CD8+ cells as compared to splenocytes isolated from chicks vaccinated with wild type or LTB-secreting E. coli and to chicks subcutaneously vaccinated. Significant reduction in viral load and percent of shedders in the vaccinated chicks was evident starting 3 days following challenge with 107.5 EID50/ml virulent IBV. Taken together, orally delivered LTB-fused IBV polypeptide-expressing bacteria induced virus-specific IgY antibody production and was associated with significantly shorter viral shedding on challenge with a live IBV. The proposed vaccine design and delivery route promise an effective and rapidly adaptable means of protecting poultry farms from devastating IB outbreaks.

HighlightsO_LIMucosal vaccination was shown particularly beneficial against respiratory viruses.
C_LIO_LIAn anti-IBV vaccine composed of three IBV polypeptides fused to LTB was designed.
C_LIO_LIVaccine composed of bacteria secreting polypeptides was orally delivered.
C_LIO_LIVaccine induced specific immune responses and shortened viral shedding duration.
C_LI

category: immunology


title: Detection of Cell-Cell Interactions via Photocatalytic Cell Tagging

abstract: Cell-cell interactions drive essential biological processes critical to cell and tissue development, function, pathology, and disease outcome. The growing appreciation of immune cell interactions within disease environments has led to significant efforts to develop protein- and cell-based therapeutic strategies. A better understanding of these cell-cell interactions will enable the development of effective immunotherapies. However, characterizing these complex cellular interactions at molecular resolution in their native biological contexts remains challenging. To address this, we introduce photocatalytic cell tagging (PhoTag), a modality agnostic platform for profiling cell-cell interactions. Using photoactivatable flavin-based cofactors, we generate phenoxy radical tags for targeted labeling at the cell surface. Through various targeting modalities (e.g. MHC-Multimer, antibody, single domain antibody (VHH)) we deliver a flavin photocatalyst for cell tagging within monoculture, co-culture, and peripheral blood mononuclear cells. PhoTag enables highly selective tagging of the immune synapse between an immune cell and an antigen-presenting cell through targeted labeling at the cell-cell junction. This allowed for the ability to profile gene expression-level differences between interacting and bystander cell populations. Given the modality agnostic and spatio-temporal nature of PhoTag, we envision its broad utilization to detect and profile intercellular interactions within an immune synapse and other confined cellular regions for any biological system.


title: Genome-wide mapping of 	Vibrio cholerae VpsT binding identifies a mechanism for c-di-GMP homeostasis

abstract: Many bacteria use cyclic dimeric guanosine monophosphate (c-di-GMP) to control changes in lifestyle. The molecule, synthesised by proteins having diguanylate cyclase activity, is often a signal to transition from motile to sedentary behaviour. In Vibrio cholerae, c-di-GMP can exert its effects via the transcription factors VpsT and VpsR. Together, these proteins activate genes needed for V. cholerae to form biofilms. In this work, we have mapped the genome-wide distribution of VpsT in a search for further regulatory roles. We show that VpsT binds 23 loci and recognises a degenerate DNA palindrome having the consensus 5-W-5R-4[CG]-3Y-2W-1W+1R+2[GC]+3Y+4W+5-3. Most genes targeted by VpsT encode functions related to motility, biofilm formation, or c-di-GMP metabolism. Most notably, VpsT activates expression of the vpvABC operon that encodes a diguanylate cyclase. This creates a positive feedback loop needed to maintain intracellular levels of c-di-GMP. Mutation of the key VpsT binding site, upstream of vpvABC, severs the loop and c-di-GMP levels fall accordingly. Hence, as well as relaying the c-di-GMP signal, VpsT impacts c-di-GMP homeostasis.

category: microbiology


title: A unique genomic island-governed cannibalism in Bacillus enhanced biofilm formation through a novel regulation mechanism

abstract: Cannibalism is a differentiation strategy and social multicellular behavior in biofilms. The novel factors and mechanisms to trigger the bacterial cannibalism remain scarce. Here, we report a novel bacillunoic acids-mediated strategy for manipulating cannibalism in Bacillus velezensis SQR9 biofilm formation. A subfraction of cells differentiate into cannibals that secrete toxic bacillunoic acids to lyse a fraction of their sensitive siblings, and the released nutrients enhance biofilm formation. Meanwhile, the self-immunity of cannibal cells was induced by bacillunoic acids. A two-component system, the OmpS-OmpR signal-transduction pathway, controls the expression of the ABC transporter BnaAB for self-immunity. Specifically, bacillunoic acids activate the autophosphorylation of OmpS, a transmembrane histidine kinase, which then transfers a phosphoryl group to its response regulator OmpR. The phosphorylation of OmpR activates the transcription of the transporter gene bnaAB by binding its promoter. Thus, bacillunoic acids are pumped out of cells by the ABC transporter BnaAB. Moreover, we discovered that strain SQR9 could use the bacillunoic acids-mediated cannibalism to optimize its community to produce more bacillunoic acids for bacterial competition. This study revealed that bacillunoic acids play a previously undiscovered dual role in both cannibalism during biofilm formation and interspecies competition, which has an important biological significance.


title: Disruption of metapopulation structure effectively reduces Tasmanian devil facial tumour disease spread at the expense of abundance and genetic diversity

abstract:
Metapopulation structure (i.e. the spatial arrangement of local populations and corridors between them) plays a fundamental role in the persistence of wildlife populations, but can also drive the spread of infectious diseases. While the disruption of metapopulation connectivity can reduce disease spread, it can also impair host resilience by disrupting gene flow and colonisation dynamics. Thus, a pressing challenge for many wildlife populations is to elucidate whether the benefits of disease management methods that reduce metapopulation connectivity outweigh the associated risks.

Directly transmissible cancers are clonal malignant cell lines capable to spread through host populations without immune recognition, when susceptible and infected hosts become in close contact. Using an individual-based metapopulation model we investigate the effects of the interplay between host dispersal, disease transmission rate and inter-individual contact distance for transmission (determining within-population mixing) on the spread and persistence of a transmissible cancer, Tasmanian devil facial tumour disease (DFTD), from local to regional scales. Further, we explore population isolation scenarios to devise management strategies to mitigate disease spread.

Disease spread, and the ensuing population declines, are synergistically determined by individuals dispersal, disease transmission rate and within-population mixing. Low to intermediate transmission rates can be magnified by high dispersal and inter-individual transmission distance. Once disease transmission rate is high, dispersal and inter-individual contact distance do not impact the outcome of the disease transmission dynamics.

Isolation of local populations effectively reduced metapopulation-level disease prevalence but caused severe declines in metapopulation size and genetic diversity. The relative position of managed (i.e. isolated) populations within the metapopulation had a significant effect on disease prevalence, highlighting the importance of considering metapopulation structure when implementing metapopulation-scale disease control measures. Our findings suggests that population isolation is not an ideal management method for preventing disease spread in species inhabiting already fragmented landscapes, where genetic diversity and extinction risk are already a concern, such as the Tasmanian devil.

category: ecology


title: De Novo Whole Genome Assembly of the Roborovski Dwarf Hamster (Phodopus roborovskii) Genome, an Animal Model for Severe/Critical COVID-19

abstract: The Roborovski dwarf hamster Phodopus roborovskii belongs to the Phodopus genus, one of seven within Cricetinae subfamily. Like other rodents such as mice, rats or ferrets, hamsters can be important animal models for a range of diseases. Whereas the Syrian hamster from the genus Mesocricetus is now widely used as a model for mild to moderate COVID-19, Roborovski dwarf hamster show a severe to lethal course of disease upon infection with the novel human coronavirus SARS-CoV-2.

category: genomics


title: Imputation-free reconstructions of three-dimensional chromosome architectures in human diploid single-cells using allele-specified contacts

abstract: The sparseness of chromosomal contact information and the presence of homologous chromosomes with very similar nucleotide sequences make Hi-C analysis difficult. We propose a new algorithm using allele-specific single-nucleotide variations (SNVs) to reconstruct the three-dimensional (3D) chromosomal architectures from the Hi-C dataset of single diploid cells. Our algorithm has a function to discriminate SNVs specifically found between homologous chromosomes to our "recurrence plot"-based algorithm to estimate the 3D chromosome structure, which does not require imputation for ambiguous segment information. The new algorithm can efficiently reconstruct 3D chromosomal structures in single human diploid cells by employing only Hi-C segment pairs containing allele-specific SNVs. The datasets of the remaining pairs of segments without allele-specific SNVs are used to validate the estimated chromosome structure. This approach was used to reconstruct the 3D structures of human chromosomes in single diploid cells at a 1-Mb resolution. Introducing a subsequent mathematical measure further improved the resolution to 40-kb or 100-kb. The reconstruction data reveals that human chromosomes form chromosomal territories and take fractal structures where the mean dimension is a non-integer value. We also validate our approach by estimating 3D protein/polymer structures.

category: bioinformatics


title: Pioglitazone administration restores a PPARG-dependent transcriptional network and ATP levels within skeletal muscles of mice implanted with patient-derived breast tumors

abstract:
BackgroundFatigue is common in patents with breast cancer (BC), and can occur in patients with early stage disease and in the absence of muscle wasting (i.e. cachexia). We have reported transcriptional and proteomic alterations in muscles from BC patients, which are associated with fatigue. Mice implanted with human BC xenografts recapitulate the muscle molecular composition changes seen in patients, coupled with a greater rate of contraction-induced fatigue. Multiple bioinformatics platforms in both human and mouse muscles have identified peroxisome proliferator activated receptor gamma (PPARG) as central to this phenotype, with multiple PPARG target genes downregulated in response to tumor growth. The current study tested the hypothesis that the PPARG agonist pioglitazone (pio), a commonly prescribed diabetes drug, would rescue the transcriptional alterations observed in muscles of tumor-bearing mice.

MethodsSixteen female NSG mice were implanted with breast cancer patient-derived orthotopic xenografts (BC-PDOX) via transplantation of Her2/neu+ human tumor fragments. BC-PDOX mice were randomly assigned to a treatment group that received daily oral pio at 30 mg.kg-1 (n=8), or a control group that received a similar volume of vehicle (n=8). Treatment was initiated when tumors reached a volume of 600mm3, and lasted for 2-weeks. Hindlimb muscles were isolated from BC-PDOX and non-tumor bearing mice for RNA-sequencing, gene expression validation, and ATP quantification. Differentially expressed genes (DEGs) in muscles from BC-PDOX mice relative to non-tumor bearing controls were identified using DESeq2, and multiple bioinformatics platforms were employed to contextualize the DEGs.

ResultsWe found that the administration of pio restored the muscle gene expression patterns of BC-PDOX mice to a profile resembling muscles of non-tumor bearing NSG control mice. Validation of skeletal muscle gene expression by qPCR confirmed pio increased the expression of PPARG target genes in skeletal muscles. Isolated mitochondria from muscles of BC-PDOX mice treated with pio contained greater levels of ATP. There were no differences in body weights, muscle weights, or tumor volumes in pio vs. vehicle treated BC-PDOX mice.

ConclusionsThese data demonstrate that oral pio supplementation rescues the BC-associated downregulation of PPARG target genes in skeletal muscle. Additionally, muscles from BC-PDOX mice treated with pio had greater levels of ATP, which would be associated a more fatigue-resistant muscle phenotype. Therefore, we propose that the FDA-approved and generic diabetes drug, pio, be considered as a supportive therapy for the treatment of BC-associated muscle fatigue.


title: Sweet revenge: AtSWEET12 in plant defense against bacterial pathogens by apoplastic sucrose limitation

abstract:
Depriving bacterial pathogens of sugars is a potential plant defense strategy. The relevance of SUGARS WILL EVENTUALLY BE EXPORTED TRANSPORTERS (SWEETs) in plant susceptibility to pathogens has been established, but their role in plant defense remains unknown. We identified Arabidopsis thaliana SWEETs (AtSWEETs) involved in defense against nonhost and host Pseudomonas syringae pathogens through reverse genetic screening of atsweet1-17 mutants. Double/triple mutant, complementation, and overexpression line analysis, and apoplastic sucrose estimation studies revealed that AtSWEET12 suppresses pathogen multiplication by limiting sucrose availability in the apoplast. Localization studies suggested that plant defense occurred via increased plasma membrane targeting of AtSWEET12 with concomitant AtSWEET11 protein reduction. Moreover, the heterooligomerization of AtSWEET11 and AtSWEET12 was involved in regulating sucrose transport. Our results highlight a PAMP-mediated defense strategy against foliar bacterial pathogens whereby plants control AtSWEET11-mediated sucrose efflux in the apoplast through AtSWEET12. We uncover a fascinating new mechanism of pathogen starvation as a broad-spectrum disease resistance mechanism in parallel with existing immune pathways.

One sentence summaryThe transporter AtSWEET12 restricts bacterial pathogen multiplication by regulating sucrose availability to pathogens in the apoplast.

category: plant biology


title: Time and spatial trends in landing per unit of effort as support to fisheries management in a multi-gear coastal fishery

abstract: Landings by the multi-gear coastal fleet operating off the Portuguese continental coast include near 300 species, from which only a few are the object of management plans. In this study, daily landings (kg trip_1) are used, along with an effort indicator, vessel length overall (LoA), to obtain landings per unit of effort (LPUE) as a proxy for the species relative abundance for a total of 48 species. LPUE indices were then used as a response variable in linear models where year (2012-2016), season, region (north and south) and NAO index were included as explanatory variables. Season and region effects were found to significantly affect species abundance for a total of 41 and 40 species respectively, while interannual effects were found to be significant for 19 species, and finally, the NAO index for 3 species. Global LPUE density maps are presented for a number of selected species and a subsample of trips where VMS records were available. For the species analysed, it is proposed that geographic and seasonal changes in LPUE indexes can be used to understand trends in abundance and obtain information that can be used in support of the definition of regional management plans.


title: Population ecology of seabirds in Mexican Islands at the California Current System

abstract: The Baja California Pacific Islands (BCPI) is a seabird hotspot in the southern California Current System supporting 129 seabird breeding populations of 23 species and over one million birds annually. These islands had a history of environmental degradation because of invasive alien species, human disturbance, and contaminants that caused the extirpation of 27 seabird populations. Most of the invasive mammals have been eradicated and breeding colonies have been restored with social attraction techniques. We have systematic information for most of the breeding populations since 2008. To assess population trends, we analyzed data and present results for 19 seabird species on ten island groups. The maximum number of breeding pairs for each nesting season was used to estimate the population growth rate ({lambda}) for each species at every island colony. We performed a nonparametric bootstrapping to assess whether seabird breeding populations are increasing or decreasing. San Benito, Natividad, and San Jeronimo are the top three islands in terms of abundance of breeding pairs. The most widespread species is Cassins Auklet with 14 colonies. Twenty-three populations of 13 species are significantly increasing while eight populations of six species are decreasing. We did not find statistical significance for 30 populations, however, 20 have {lambda}>1 which suggest they are growing. Seven of the 18 species for which we estimated a regional population trend are significantly increasing, including three surface-nesting species: Brown Pelican, Elegant Tern and Laysan Albatross, and four burrow-nesting species: Ainleys and Ashy Storm-Petrels, and Craveris and Guadalupe Murrelet. Our results suggest that the BCPI support healthy and growing populations of seabirds that have shown to be resilient to extreme environmental conditions such as the "Blob", and that such resilience has been strengthen from conservation and restoration actions such as the eradication of invasive mammals and social attraction techniques.


title: Low Temperatures Lead to Higher Toxicity of the Fungicide Folpet to Larval Stages of Rana temporaria and Bufotes viridis

abstract: Pesticides are one of the main drivers of the worldwide amphibian decline. Their actual toxicity depends on a number of factors, like the species in focus or the developmental stage of exposed individuals. As ectothermic species, the metabolism of amphibians is influenced by ambient temperature. Therefore, temperature also affects metabolic rates and thus processes that might enhance or reduce toxic effects. Studies about the interactive effect of temperature and toxicity on amphibians are rare and deliver contrasting results. To investigate the temperature-dependent pesticide sensitivity of larvae of two European species we conducted acute toxicity tests for the viticultural fungicide Folpan(R) 500 SC with the active ingredient folpet at different temperatures (6{degrees}C, 11{degrees}C, 16{degrees}C, 21{degrees}C, 26{degrees}C). Sensitivity of Rana temporaria and Bufotes viridis was highly affected by temperature: early larvae (Gosner stage 20) were about twice more sensitive to Folpan(R) 500 SC at 6{degrees}C compared to 21{degrees}C. Next to temperature, species and developmental stage of larvae had an effect on sensitivity. The most sensitive individuals (early stages of R. temporaria at 6{degrees}C) were 14.5 times more sensitive than the least sensitive ones (early stages of B. viridis at 26{degrees}C). Our results raise concerns about typical ecotoxicological studies with amphibians that are often conducted at temperatures between 15{degrees}C and 20{degrees}C. We suggest that future test designs should be performed at temperatures that reflect the temperature range amphibians are exposed to in their natural habitats. Variations in the sensitivity due to temperature should also be considered as an uncertainty factor in upcoming environmental risk assessments for amphibians.


title: Effect of cow's milk with different PUFA n-6: n-3 ratios on performance, serum lipid profile, and blood parameters of grower gilts.

abstract: The concern with human health has increased the interest in producing foods enriched with polyunsaturated fatty acids (PUFA), directly or naturally by inclusion in the animals diet. The positive effects such as antithrombotic, anti-inflammatory, and hypolipidemic have been observed in pigs and rats, used as human models for study. The present study evaluated the effect of cows milk with different lipid profiles on performance, serum fatty acid profile, biochemical analysis, and a complete blood count of gilts used as a human model. At 34 days, thirty gilts were equally distributed in three treatments. Experimental treatments were milk from cows without the oil supplementation (C), milk from cows fed an enriched diet with linseed oil (n-3), and milk from cows fed an enriched diet with soybean oil (n-6). Milk supplementation was performed until the age of 190 days, provided once in the morning. The n-3 and n-6 milk reduced the concentration of myristic acid in the blood and increased the leukocytes. Milk enriched with n-3 compared to n-6 reduced stearic acid. In conclusion, milk with a better PUFA profile can reduce saturated fatty acids in the blood and alter the concentration of cells in the defense system.

category: physiology


title: Metabolic Regulation of Mitochondrial Morphologies in Pancreatic Beta Cells: Bioenergetics-Mitochondrial Dynamics Coupling

abstract: Cellular bioenergetics and mitochondrial dynamics are crucial for the secretion of insulin by pancreatic beta cells in response to elevated blood glucose concentrations. To obtain better insights into the interactions between energy production and mitochondrial fission/fusion dynamics, we combine live-cell mitochondria imaging with biophysical-based modeling and network analysis to elucidate the principle regulating mitochondrial morphology to match metabolic demand in pancreatic beta cells. A minimalistic differential equation-based model for beta cells was constructed to include glycolysis, oxidative phosphorylation, simple calcium dynamics, and graph-based fission/fusion dynamics controlled by ATP synthase flux and proton leak flux. The model revealed that mitochondrial fission occurs in response to hyperglycemia, starvation, ATP synthase inhibition, uncoupling, and diabetic condition, in which the rate of proton leak exceeds the rate of mitochondrial ATP synthesis. Under these metabolic challenges, the propensities of tip-to-tip fusion events simulated from the microscopic images of the mitochondrial networks were lower than those in the control group and prevented mitochondrial network formation. The modeling and network analysis could serve as the basis for further detailed research on the mechanisms of bioenergetics and mitochondrial dynamics coupling.

category: systems biology


title: Predicting compound-protein interaction using hierarchical graph convolutional networks

abstract:
MotivationConvolutional neural networks have enabled unprecedented breakthroughs in a variety of computer vision tasks. They have also drawn much attention from other domains, including drug discovery and drug development. In this study, we develop a computational method based on convolutional neural networks to tackle a fundamental question in drug discovery and development, i.e. the prediction of compound-protein interactions based on compound structure and protein sequence. We propose a hierarchical graph convolutional network (HGCN) to encode small molecules. The HGCN aggregates a molecule embedding from substructure embeddings, which are synthesized from atom embeddings. As small molecules usually share substructures, computing a molecule embedding from those common substructures allows us to learn better generic models. We then combined the HGCN with a one-dimensional convolutional network to construct a complete model for predicting compound-protein interactions. Furthermore we apply an explanation technique, Grad-CAM, to visualize the contribution of each amino acid into the prediction.

ResultsExperiments using different datasets show the improvement of our model compared to other GCN-based methods and a sequence based method, DeepDTA, in predicting compound-protein interactions. Each prediction made by the model is also explainable and can be used to identify critical residues mediating the interaction.

Availability and implementationhttps://github.com/banhdzui/cpi_hgcn.git


title: AIM2 inflammasome activation in astrocytes occurs during the late phase of EAE

abstract:
Inflammasomes are a class of innate immune signaling platforms that activate in response to an array of cellular damage and pathogens. Inflammasomes promote inflammation under many circumstances to enhance immunity against pathogens and inflammatory responses through their effector cytokines, IL-1{beta} and IL-18. Multiple sclerosis and its animal model, experimental autoimmune encephalomyelitis (EAE), are such autoimmune conditions influenced by inflammasomes. Despite work investigating inflammasomes during EAE, little remains known concerning the role of inflammasomes in the central nervous system (CNS) during the disease. Here we use multiple genetically modified mouse models to monitor activated inflammasomes in situ based on ASC oligomerization in the spinal cord. Using inflammasome reporter mice, we found heightened inflammasome activation in astrocytes after the disease peak. In contrast, microglia and CNS-infiltrated myeloid cells had few activated inflammasomes in the CNS during EAE. Astrocyte inflammasome activation was dependent on AIM2, but low IL-1{beta} expression and no significant signs of cell death were found in astrocytes during EAE. Thus, the AIM2 inflammasome activation in astrocytes may have a distinct role from traditional inflammasome-mediated inflammation.

SIGNIFICANCE STATEMENTInflammasome activation in the peripheral immune system is pathogenic in multiple sclerosis (MS) and its animal model, experimental autoimmune encephalomyelitis (EAE). However, inflammasome activity in the central nervous system (CNS) is largely unexplored. Here, we used genetically modified mice to determine inflammasome activation in the CNS during EAE. Our data indicated heightened AIM2 inflammasome activation in astrocytes after the disease peak. Unexpectedly, neither CNS-infiltrated myeloid cells nor microglia were the primary cells with activated inflammasomes in SC during EAE. Despite AIM2 inflammasome activation, astrocytes did not undergo apparent cell death and produced little of the proinflammatory cytokine, IL-1{beta}, during EAE. This study showed that CNS inflammasome activation occurs during EAE without associating with IL-1{beta}-mediated inflammation.


title: A sensitized genetic screen to identify regulators of C. elegans germline stem cells

abstract: Germline stem cells (GSCs) in Caenorhabditis elegans are maintained by GLP-1/Notch signaling from the niche and by a downstream RNA regulatory network. Loss of the GLP-1 receptor causes GSCs to precociously undergo meiotic differentiation, the "Glp" phenotype, due to a failure to self-renew. lst-1 and sygl-1 are functionally redundant direct targets of GLP-1 signaling whose gene products work with PUF RNA binding proteins to promote GSC self-renewal. Whereas single loss-of-function mutants are fertile, lst-1 sygl-1 double mutants are sterile and Glp. We set out to identify genes that function redundantly with either lst-1 or sygl-1 to maintain GSCs. To this end, we conducted forward genetic screens for Glp mutants in genetic backgrounds lacking functional copies of either lst-1 or sygl-1. The screens generated nine glp-1 alleles, two lst-1 alleles, and one allele of pole-1, which encodes the catalytic subunit of DNA polymerase {varepsilon}. Three glp-1 alleles reside in Ankyrin (ANK) repeats not previously mutated. pole-1 single mutants have a low penetrance Glp that is enhanced by loss of either lst-1 or sygl-1. Thus, the screen uncovered one locus that interacts genetically with both lst-1 and sygl-1 and generated useful mutations for further studies of GSC regulation.

category: genetics


title: Polyvinyl Chloride Biodegradation Fuels Survival of Invasive Insect Larva and Intestinal Degrading Strain of Klebsiella

abstract: Microbial degradation of polyvinyl chloride (PVC) is eco-friendly and economically attractive but extremely challenging due to the lack of a molecular understanding of the degrading strains and enzymes. Motivated by the serendipitous discovery that the larva of an agricultural invasive insect pest, Spodoptera frugiperda, effectively survived PVC film alone, we profiled the intestinal microbiota of S. frugiperda larva and screened for PVC-degrading strains. Feeding on PVC film significantly changed the larval intestinal microbiota through selective enrichment of Enterococcus, Ochrobactrum, Falsochrobactrum, Microbaterium, Sphingobacterium and Klebsiella. From the larval intestine, we isolated the biofilm-forming Klebsiella sp. EMBL-1 and experimentally verified it as the first Klebsiella bacterium known to actively degrade and utilize PVC by various classic physicochemical and morphological analyses. We further used multiomic analyses, complementarily integrating genomic, transcriptomic, proteomic, and metabolomic insights, to identify enzyme-coding genes responsible for PVC degradation and proposed a biodegradation pathway for the bacterial strain. Overall, both S. frugiperda and strain EMBL-1 are first found to survive effectively on PVC film by using the polymer as the sole energy source. Moreover, this work exemplifying PVC biodegradation provides a reference for discovering more microbes and enzymatic resources for degrading other recalcitrant plastics.


title: Polyvinyl Chloride Degradation by Intestinal Klebsiella of Pest larvae


title: Using bootstrap procedures for testing the modular partition inferred via leading eigenvector community detection algorithm

abstract: Modularity and modular structures can be recognized at various levels of biological organization and in various domains of studies. Recently, algorithms based on network analysis came into focus. And while such a framework is a powerful tool in studying modular structure, those methods usually pose a problem of assessing statistical support for the obtained modular structures. One of the widely applied methods is the leading eigenvector, or Newmans spectral community detection algorithm. We conduct a brief overview of the method, including a comparison with some other community detection algorithms and explore a possible fine-tuning procedure. Finally, we propose an adapted bootstrap-based procedure based on Shimodairas multiscale bootstrap algorithm to derive approximately unbiased p-values for the module partitions of observations datasets. The proposed procedure also gives a lot of freedom to the researcher in constructing the network construction from the raw numeric data, and can be applied to various types of data and used in diverse problems concerning modular structure. We provide an R language code for all the calculations and the visualization of the obtained results for the researchers interested in using the procedure.

category: evolutionary biology


title: Direct carbon capture for production of high-performance biodegradable plastic by cyanobacterial cell factory

abstract: Plastic pollution has become one of the most pressing environmental issues today, leading to an urgent need to develop biodegradable plastics1-3. Polylactic acid (PLA) is one of the most promising biodegradable materials because of its potential applications in disposable packaging, agriculture, medicine, and printing filaments for 3D printers4-6. However, current biosynthesis of PLA entirely uses edible biomass as feedstock, which leads to competition for resources between material production and food supply7,8. Meanwhile, excessive emission of CO2 that is the most abundant carbon source aggravates global warming, and climate instability. Herein, we first developed a cyanobacterial cell factory for the de novo biosynthesis of PLA directly from CO2, using a combinational strategy of metabolic engineering and high-density cultivation (HDC). Firstly, the heterologous pathway for PLA production, which involves engineered D-lactic dehydrogenase (LDH), propionate CoA-transferase (PCT), and polyhydroxyalkanoate (PHA) synthase, was introduced into Synechococcus elongatus PCC7942. Subsequently, different metabolic engineering strategies, including pathway debottlenecking, acetyl-CoA self-circulation, and carbon-flux redirection, were systematically applied, resulting in approximately 19-fold increase to 15 mg/g dry cell weight (DCW) PLA compared to the control. In addition, HDC increased cell density by 10-fold. Finally, the PLA titer of 108 mg/L (corresponding to 23 mg/g DCW) was obtained, approximately 270 times higher than that obtained from the initially constructed strain. Moreover, molecular weight (Mw, 62.5 kDa; Mn, 32.8 kDa) of PLA produced by this strategy was among the highest reported levels. This study sheds a bright light on the prospects of plastic production from CO2 using cyanobacterial cell factories.

category: bioengineering


title: Evidence for the Emergence of β-Trefoils by 'Peptide Budding' from an IgG-like β-Sandwich

abstract: As sequence and structure comparison algorithms gain sensitivity, the intrinsic interconnectedness of the protein universe has become increasingly apparent. Despite this general trend, {beta}-trefoils have emerged as an uncommon counterexample: They are an isolated protein lineage for which few, if any, sequence or structure associations to other lineages have been identified. If {beta}-trefoils are, in fact, remote islands in sequence-structure space, it implies that the oligomerizing peptide that founded the {beta}-trefoil lineage itself arose de novo. To better understand {beta}-trefoil evolution, and to probe the limits of fragment sharing across the protein universe, we identified both  {beta}-trefoil bridging themes (evolutionarily-related sequence segments) and  {beta}-trefoil-like motifs (structure motifs with a hallmark feature of the {beta}-trefoil architecture) in multiple, ostensibly unrelated, protein lineages. The success of the present approach stems, in part, from considering {beta}-trefoil sequence segments or structure motifs rather than the {beta}-trefoil architecture as a whole, as has been done previously. The newly uncovered inter-lineage connections presented here suggest a novel hypothesis about the origins of the {beta}-trefoil fold itself - namely, that it is a derived fold formed by  budding from an Immunoglobulin-like {beta}-sandwich protein. These results demonstrate how the emergence of a folded domain from a peptide need not be a signature of antiquity and underpin an emerging truth: few protein lineages escape natures sewing table.


title: Stochastic variational variable selection for high-dimensional microbiome data

abstract:
BackgroundThe rapid and accurate identification of a minimal-size core set of representative microbial species plays an important role in the clustering of microbial community data and interpretation of clustering results. However, the huge dimensionality of microbial metagenomics datasets is a major challenge for the existing methods such as Dirichlet multinomial mixture (DMM) models. In the framework of the existing methods, the computational burden of identifying a small number of representative species from a large number of observed species remains a challenge.

ResultsWe proposed a novel framework to improve the performance of the widely used DMM approach by combining three ideas: (i) we extended the finite DMM model to an infinite case by considering Dirichlet process mixtures and estimating the number of clusters as a random variables; (ii) we proposed an indicator variable to identify representative operational taxonomic units that substantially contribute to the differentiation among clusters; and (iii) to address the computational burden of high-dimensional microbiome data, we proposed a stochastic variational inference, which approximates the posterior distribution using a controllable distribution called variational distribution, and stochastic optimization algorithms for fast computation. Using the proposed method, stochastic variational variable selection (SVVS), we analyzed the root microbiome data collected in our soybean field experiment, the human gut microbiome data from three published datasets of large-scale case-control studies and the healthy human microbiome data from the Human Microbiome Project.

ConclusionsSVVS demonstrated a better performance and significantly faster computation than those of the existing methods in all cases of testing datasets. In particular, SVVS is the only method that can analyze massive high-dimensional microbial data with more than 50,000 microbial species and 1,000 samples. Furthermore, recent microbiome studies have suggested that selection of the microbial species used as a core set is important.


title: In vitro Anti-Cancer Activity of Oliveria decumbens Vent. Extract, an Endemic Persian Medicinal Plant, on HT-29 Colorectal Cancer Cell Line

abstract:
IntroductionThe top 3 causes of death worldwide include heart disease, injury, and cancer; and cancer records the 2nd place as the leading cause of death in the United States of America after cardiovascular diseases and injuries. Cancer can begin and progress in a very highly twisted and complex pattern and follow the multifactorial route. There is only very few research on medicinal properties Oliveria decumbens rare and valuable plant specially on cancer. So, in this study we tried to cover all needs for future in vivo research.

MethodsMTT assay has been performed to estimate the cytotoxicity of the ethanolic extract of the plant. Its free radical capacity evaluation was done by DPPH assay. Furthermore, real-time PCR, the wound-healing assay along with a DNA damage test to study DNA fragmentation characteristics. The plants transcriptomic study was performed by NGS de Novo assembly.

ResultOliveria decumbens ethanolic extract showed an Ic50 of 14.39 g/ml. The real-time PCR showed that Oliveria decumbens ethanolic extract significantly induced apoptosis by upregulating the bax gene and slight downregulation of bcl2 an anti-apoptosis gene. The NGS de Novo transcriptome analysis discovered 38 genes responsible for secondary metabolite synthesis so far. The remaining genes and reconstruction of the co-expression network of the transcriptome are underway.

ConclusionThe outcome of the Scratch-test and DNA fragmentation confirmed the anti-metastatic and DNA damage properties respectively. Based on these findings; Oliveria decumbens ethanolic extract shall be considered as potential anticancer and chemotherapeutic agents which may elucidate in upcoming studies.


title: Circadian regulation of the transcriptome in a complex polyploid crop

abstract: The circadian clock is a finely balanced time-keeping mechanism that coordinates programmes of gene expression. It is currently unknown how the clock regulates expression of homoeologous genes in polyploids. Here, we generate a high-resolution time-course dataset to investigate the circadian balance between sets of three homoeologous genes (triads) from hexaploid bread wheat. We find a large proportion of circadian triads exhibit imbalanced rhythmic expression patterns, with no specific sub-genome favoured. In wheat, period lengths of rhythmic transcripts are found to be longer and have a higher level of variance than in other plant species. Expression of transcripts associated with circadian controlled biological processes are largely conserved between wheat and Arabidopsis, however striking differences are seen in agriculturally critical processes such as starch metabolism. Together, this work highlights the ongoing selection for balance versus diversification in circadian homoeologs, and identifies clock-controlled pathways that might provide important targets for future wheat breeding.


title: Postsynaptic synucleins mediate vesicular exocytosis of endocannabinoids

abstract: Two seemingly unrelated questions have long motivated studies in neuroscience: How are endocannabinoids, among the most powerful modulators of synaptic transmission, released from neurons? What are the physiological functions of synucleins, key contributors to Parkinsons Disease? Here, we report an unexpected convergence of these two questions: Endocannabinoids are released via vesicular exocytosis from postsynaptic neurons by a synuclein-dependent mechanism. Specifically, we find that deletion of all synucleins selectively blocks all endocannabinoid-dependent synaptic plasticity; this block is reversed by postsynaptic expression of wildtype but not of mutant -synuclein. Loading postsynaptic neurons with endocannabinoids via patch-pipette dialysis suppressed presynaptic neurotransmitter release in wildtype but not in synuclein-deficient neurons, suggesting that the synuclein deletion blocks endocannabinoid release. Direct optical monitoring of endocannabinoid release confirmed the requirement of synucleins. Given the role of synucleins in vesicular exocytosis, the requirement for synucleins in endocannabinoid release indicates that endocannabinoids are secreted via exocytosis. Consistent with this hypothesis, postsynaptic expression of tetanus-toxin light chain, which cleaves synaptobrevin SNAREs, also blocked endocannabinoid-dependent plasticity and release. The unexpected finding that endocannabinoids are released via synuclein-dependent exocytosis assigns a function to synucleins and resolves a longstanding puzzle of how neurons release endocannabinoids to induce synaptic plasticity.

category: neuroscience


title: Causal evidence for a domain-specific role of left superior frontal sulcus in human perceptual decision-making

abstract: Humans and animals can flexibly choose their actions based on different information, ranging from objective states of the environment (e.g., apples are bigger than cherries) to subjective preferences (e.g., cherries are tastier than apples). Whether the brain instantiates these different choices by recruiting either specialized or shared neural circuitry remains debated. Specifically, domain-general theories of prefrontal cortex (PFC) function propose that prefrontal areas flexibly process either perceptual or value-based evidence depending on what is required for the present choice, whereas domain-specific theories posit that PFC sub-areas, such as the left superior frontal sulcus (SFS), selectively integrate evidence relevant for perceptual decisions. Here we comprehensively test the functional role of the left SFS for choices based on perceptual and value-based evidence, by combining fMRI with a behavioural paradigm, computational modelling, and transcranial magnetic stimulation. Confirming predictions by a sequential sampling model, we show that TMS-induced excitability reduction of the left SFS selectively changes the processing of decision-relevant perceptual information and associated neural processes. In contrast, value-based decision making and associated neural processes remain unaffected. This specificity of SFS function is evident at all levels of analysis (behavioural, computational, and neural, including functional connectivity), demonstrating that the left SFS causally contributes to evidence integration for perceptual but not value-based decisions.


title: β-amyloid-driven synaptic depression requires PDZ protein interaction at AMPA-receptor subunit GluA3

abstract: Soluble oligomeric amyloid-{beta} (A{beta}) is a prime suspect to cause cognitive deficits in Alzheimers disease and weakens synapses by removing AMPA-type glutamate receptors (AMPARs). We show that synapses of CA1 pyramidal neurons become vulnerable to A{beta} when they express AMPAR subunit GluA3. We found that A{beta}-oligomers reduce the levels of GluA3 immobilized at spines, indicating they deplete GluA3-containing AMPARs from synapses. These A{beta}-driven effects critically depended on the PDZ-binding motif of GluA3. When GluA3 was expressed with a single amino acid mutation in its PDZ-binding motif that prevents GRIP binding, it did not end up at spines and A{beta} failed to trigger synaptic depression. GluA3 with a different point mutation in the PDZ-motif that leaves GRIP-binding intact but prevents its endocytosis, was present at spines in normal amounts but was fully resistant to effects of A{beta}. Our data indicate that A{beta}-mediated synaptic depression requires the removal of GluA3 from synapses. We propose that GRIP-detachment from GluA3 is a critical early step in the cascade of events through which A{beta} accumulation causes a loss of synapse.


title: A causality-inspired feature selection method for cancer imbalanced high-dimensional data

abstract:
It is significant but challenging to explore a subset of robust biomarkers to distinguish cancer from normal samples on high-dimensional imbalanced cancer biological omics data. Although many feature selection methods addressing high dimensionality and class imbalance have been proposed, they rarely pay attention to the fact that most classes will dominate the final decision-making when the dataset is imbalanced, leading to instability when it expands downstream tasks. Because of causality invariance, causal relationship inference is considered an effective way to improve machine learning performance and stability. This paper proposes a Causality-inspired Least Angle Nonlinear Distributed (CLAND) feature selection method, consisting of two branches with a class-wised branch and a sample-wised branch representing two deconfounder strategies, respectively. We compared the performance of CLAND with other advanced feature selection methods in transcriptional data of six cancer types with different imbalance ratios. The genes selected by CLAND have superior accuracy, stability, and generalization in the downstream classification tasks, indicating potential causality for identifying cancer samples. Furthermore, these genes have also been demonstrated to play an essential role in cancer initiation and progression through reviewing the literature.

Author SummarySelecting trustworthy biomarkers from high-dimensional data is an important step to help researchers and clinicians understand which genes play key roles in cancer development and progression. A large number of machine learning-based feature selection algorithms have been generated in recent years for biomarker discovery. However, these methods usually show unstable results in the face of class-imbalanced biological data, making it seem unreliable for researchers. Here we introduce the causal theory with the property of causal invariance to aid in the design of feature selection algorithms, analyze how imbalanced distributions affect feature selection methods, and propose a novel causality-based feature selection method. The method with bilateral structure adjusts the data distribution from both class-wise and sample-wise to eliminate the effect of imbalance on the results. Additionally, CLAND can simultaneously address the nonlinearity and high-dimensionality of cancer data, which broaden its application scope. We conducted extensive experiments on six real imbalance cancer datasets and obtained efficient and stable results, while the obtained biomarker has significant biological significance.


title: Efficient inference for agent-based models of real-world phenomena

abstract:
The modelling of many real-world problems relies on computationally heavy simulations. Since statistical inference rests on repeated simulations to sample the parameter space, the high computational expense of these simulations can become a stumbling block. In this paper, we compare two ways to mitigate this issue based on machine learning methods. One approach is to construct lightweight surrogate models to substitute the simulations used in inference. Alternatively, one might altogether circumnavigate the need for Bayesian sampling schemes and directly estimate the posterior distribution. We focus on stochastic simulations that track autonomous agents and present two case studies of real-world applications: tumour growths and the spread of infectious diseases. We demonstrate that good accuracy in inference can be achieved with a relatively small number of simulations, making our machine learning approaches orders of magnitude faster than classical simulation-based methods that rely on sampling the parameter space. However, we find that while some methods generally produce more robust results than others, no algorithm offers a one-size-fits-all solution when attempting to infer model parameters from observations. Instead, one must choose the inference technique with the specific real-world application in mind. The stochastic nature of the considered real-world phenomena poses an additional challenge that can become insurmountable for some approaches. Overall, we find machine learning approaches that create direct inference machines to be promising for real-world applications. We present our findings as general guidelines for modelling practitioners.

Author summaryComputer simulations play a vital role in modern science as they are commonly used to compare theory with observations. One can thus infer the properties of a observed system by comparing the data to the predicted behaviour in different scenarios. Each of these scenarios corresponds to a simulation with slightly different settings. However, since real-world problems are highly complex, the simulations often require extensive computational resources, making direct comparisons with data challenging, if not insurmountable. It is, therefore, necessary to resort to inference methods that mitigate this issue, but it is not clear-cut what path to choose for any specific research problem. In this paper, we provide general guidelines for how to make this choice. We do so by studying examples from oncology and epidemiology and by taking advantage of developments in machine learning. More specifically, we focus on simulations that track the behaviour of autonomous agents, such as single cells or individuals. We show that the best way forward is problem-dependent and highlight the methods that yield the most robust results across the different case studies. We demonstrate that these methods are highly promising and produce reliable results in a small fraction of the time required by classic approaches that rely on comparisons between data and individual simulations. Rather than relying on a single inference technique, we recommend employing several methods and selecting the most reliable based on predetermined criteria.


title: Models of the cardiac L-type calcium current: a quantitative comparison

abstract: The L-type calcium current (ICaL) plays a critical role in cardiac electrophysiology, and models of ICaL are vital tools to predict arrhythmogenicity of drugs and mutations. Five decades of measuring and modelling ICaL have resulted in several competing theories (encoded in mathematical equations). However, the introduction of new models has not typically been accompanied by a data-driven critical comparison with previous work, so that it is unclear where predictions overlap or conflict, or which model is best suited for any particular application. We gathered 71 mammalian ICaL models, compared their structure, and reproduced simulated experiments to show that there is a large variability in their predictions, which was not substantially diminished when grouping by species or other categories. By highlighting the differences in these competing theories, listing major data sources, and providing simulation code, we have laid strong foundations for the development of a consensus model of ICaL.

category: cell biology


title: Early diagnosis of Parkinson's disease: A cross-species biomarker

abstract:
BackgroundCare management of Parkinsons disease (PD) patients currently remains symptomatic, especially because diagnosis relying on the expression of the cardinal motor symptoms is made too late. Detecting PD earlier therefore represents a key step for developing therapies able to delay or slow down its progression.

MethodsWe investigated metabolic markers in three different animal models of PD, mimicking different phases of the disease assessed by behavioral and histological evaluation, and in 2 cohorts of de novo PD patients (n = 95). Serum and brain tissue samples were analyzed by nuclear magnetic resonance spectroscopy and data submitted to advanced multivariate statistics.

ResultsOur translational strategy reveals common metabolic dysregulations in serum of the different animal models and PD patients. Some of them were mirrored in the tissue samples, possibly reflecting pathophysiological mechanisms associated with PD development. Interestingly, some metabolic dysregulations appeared before motor symptom emergence, and could represent early biomarkers of PD.

Finally, we built a composite biomarker with a combination of 6 metabolites. This biomarker discriminated animals mimicking PD from controls, even from the first, non-motor signs and very interestingly, also discriminated PD patients from healthy subjects.

ConclusionFrom our translational study which included three animal models and two PD patient cohorts, we propose a promising composite biomarker exhibiting a high level of predictivity for PD diagnosis in its early phase, before motor symptoms appearance.

FundingsANR, DOPALCOMP, Institut National de la Sante et de la Recherche Medicale, Grenoble Alpes University.

category: pathology


title: Weight perturbation learning outperforms node perturbation on broad classes of temporally extended tasks

abstract:
Biological constraints often impose restrictions for plausible plasticity rules such as locality and reward-based rather than supervised learning. Two learning rules that comply with these restrictions are weight (WP) and node (NP) perturbation. NP is often used in learning studies, in particular as a benchmark; it is considered to be superior to WP and more likely neurobiologically realized, as the number of weights and therefore their perturbation dimension typically massively exceed the number of nodes. Here we show that this conclusion no longer holds when we take two biologically relevant properties into account: First, tasks extend in time. This increases the perturbation dimension of NP but not WP. Second, tasks are low dimensional, with many weight configurations providing solutions. We analytically delineate regimes where these properties let WP perform as well as or better than NP. Further we find qualitative features of the weight and error dynamics that allow to distinguish which of the rules underlie a learning process: in WP, but not NP, weights mediating zero input diffuse and gathering batches of subtasks in a trial decreases the number of trials required. The insights suggest new learning rules, which combine for specific task types the advantages of WP and NP. Using numerical simulations, we generalize the results to networks with various architectures solving biologically relevant and standard network learning tasks. Our findings suggest WP and NP as similarly plausible candidates for learning in the brain and as similarly important benchmarks.

Statement of significanceNeural networks can learn by first perturbing the network weights or the activity of neurons and thereafter consolidating perturbations that improve the network performance. Weight perturbation learning is considered less efficient, useful and biologically plausible, because there are many more connection weights than neurons, such that generating beneficial perturbations seems less likely. We show that the argument does no longer hold when accounting for two features common in biology: tasks extend in time and the neuronal dynamics are low dimensional. In particular, we find that perturbing the weights is comparably good or better in various biologically relevant and standard network learning applications. This indicates that weight perturbation learning is similarly useful and a plausible candidate for learning in the brain.


title: Inhibition of LRRK2 kinase activity promotes anterograde axonal transport and presynaptic targeting of α-synuclein

abstract: Pathologic inclusions composed of -synuclein called Lewy pathology are hallmarks of Parkinsons Disease (PD). Dominant inherited mutations in leucine rich repeat kinase 2 (LRRK2) are the most common genetic cause of PD. Lewy pathology is found in the majority of individuals with LRRK2-PD, particularly those with the G2019S-LRRK2 mutation. Lewy pathology in LRRK2-PD associates with increased non-motor symptoms such as cognitive deficits, anxiety, and orthostatic hypotension. Thus, understanding the relationship between LRRK2 and -synuclein could be important for determining the mechanisms of non-motor symptoms. In PD models, expression of mutant LRRK2 reduces membrane localization of - synuclein, and enhances formation of pathologic -synuclein, particularly when synaptic activity is increased. -Synuclein and LRRK2 both localize to the presynaptic terminal. LRRK2 plays a role in membrane traffic, including axonal transport, and therefore may influence -synuclein synaptic localization. This study shows that LRRK2 kinase activity influences -synuclein targeting to the presynaptic terminal. We used the selective LRRK2 kinase inhibitors, MLi-2 and PF-06685360 (PF-360) to determine the impact of reduced LRRK2 kinase activity on presynaptic localization of -synuclein. Expansion microscopy (ExM) in primary hippocampal cultures and the mouse striatum, in vivo, was used to more precisely resolve the presynaptic localization of -synuclein. Live imaging of axonal transport of -synuclein-GFP was used to investigate the impact of LRRK2 kinase inhibition on -synuclein axonal transport towards the presynaptic terminal. Reduced LRRK2 kinase activity increases -synuclein overlap with presynaptic markers in primary neurons, and increases anterograde axonal transport of - synuclein-GFP. In vivo, LRRK2 inhibition increases -synuclein overlap with glutamatergic, cortico-striatal terminals, and dopaminergic nigral-striatal presynaptic terminals. The findings suggest that LRRK2 kinase activity plays a role in axonal transport, and presynaptic targeting of -synuclein. These data provide potential mechanisms by which LRRK2-mediated perturbations of -synuclein localization could cause pathology in both LRRK2-PD, and idiopathic PD.


title: Ptbp1 deletion does not induce glia-to-neuron conversion in adult mouse retina and brain.

abstract: Direct reprogramming of glia into neurons is a potentially promising approach for the replacement of neurons lost to injury or neurodegenerative disorders. Knockdown of the polypyrimidine tract-binding protein Ptbp1 has been recently reported to induce efficient conversion of retinal Muller glia and brain astrocytes into functional neurons. However, genetic analysis of Ptbp1 function in adult glia has not been conducted. Here, we use a combination of genetic lineage tracing, scRNA-Seq, and electrophysiological analysis to show that specific deletion of Ptbp1 in adult retinal Muller glia and brain astrocytes does not lead to any detectable level of glia-to-neuron conversion. Only a few changes in gene expression are observed in glia following Ptbp1 deletion, and glial identity is maintained. These findings highlight the importance of using genetic manipulation and lineage tracing methods in studying cell type conversion.


title: Association Between Action Video Game Playing Experience and Visual Search in Real-life Multisensory scenes

abstract: Prior studies investigating the effects of playing action video games on attentional control have demonstrated improvements on a variety of basic psychophysical tasks. However, as of yet, there is little evidence indicating that the cognitive benefits of playing action video games generalize to naturalistic multisensory scenes - a fundamental characteristic of our natural, everyday life environments. The present study addressed the generalization of attentional control enhancement due to AVGP experience to real-life like scenarios by comparing the performance of action video-game players (AVGPs) with non-players (NVGPs) on a visual search task using naturalistic, dynamic audio-visual scenes. To this end, a questionnaire collecting data on gaming habits and sociodemographic data as well as a visual search task was administered online to a gender-balanced sample of 60 participants of age 18 to 30 years. According to the standard hypothesis, AVGPs outperformed NVGPs in the search task overall, showing faster reaction times without sacrificing accuracy. In addition, in replication of previous findings, semantically congruent cross-modal cues benefited performance overall. However, according to our results, despite the overall advantage in search, and the multisensory congruence benefit, AVGPs did not exploit multisensory cues more efficiently than NVGPs. Exploratory analyses with gender as a variable indicated that the advantage of AVG experience to both genders should be done with caution.


title: Spatial and temporal analysis of neutrophil trans-epithelial migration in response to RSV infection

abstract:
In the airways, recruitment and activation of neutrophils occurs early following respiratory virus (RSV) infection and is associated with the development of severe disease. We investigated whether activated neutrophils selectively migrate across virus infected airway epithelial cells, or whether trans-epithelial migration is sufficient and necessary for neutrophil activation. We profiled the movement and adherence of fluorescently labelled human neutrophils during migration across primary human airway epithelial cells (AECs) infected with RSV in vitro. In RSV infected AECs neutrophil adherence, with clustering occurs after 15-18 minutes. Using flow cytometry, we found that, when migration occurred, expression of CD11b, CD62L, CD64, NE and MPO were increased in all compartments of our system and RSV infection further increased CD11b and NE expression. We found evidence suggesting that migrated neutrophils can migrate in reverse to the basolateral membrane. Our study provides novel insights into how airway activated neutrophils mediate systemic disease in respiratory virus infection.

Graphical Abstract LegendAir-liquid interface (ALI) models for studying neutrophil trans-epithelial migration in response to RSV infection. Left panel shows primary airway epithelial cells cultured at ALI on membrane inserts with 3m pore size that permits neutrophils to migrate through. 1) unmigrated neutrophils expressing baseline levels of CD11b, 2) neutrophils migrate across infected AECs and some remain adherent to the infected AECs, 3) neutrophils are shown to increase expression of CD11b and other activation associated markers, 4) some  activated neutrophils undergo reverse migration as 5) neutrophils with the increased expression of CD11b are detected on the basolateral side of the insert. Right panel shows primary airway epithelial cells cultured at ALI on membrane inserts with 0.4m pore size that prevents neutrophils migration. Here, after 1h incubation with RSV infected AECs, neutrophils on the basolateral side 1) and 2) were shown to express the same level of CD11b markers, indicating that neutrophil migration is key process for increasing expression of these activation markers. Drawing created using BioRender.com.

O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY


title: Integrative analysis of scRNAs-seq and scATAC-seq revealed transit-amplifying thymic epithelial cells expressing autoimmune regulator

abstract: Medullary thymic epithelial cells (mTECs) are critical for self-tolerance induction in T cells via promiscuous expression of tissue-specific antigens (TSAs), which are controlled by transcriptional regulator AIRE. Whereas AIRE-expressing (Aire+) mTECs undergo constant turnover in the adult thymus, mechanisms underlying differentiation of postnatal mTECs remain to be discovered. Integrative analysis of single-cell assays for transposase accessible chromatin (scATAC-seq) and single-cell RNA sequencing (scRNA-seq) suggested the presence of proliferating mTECs with a specific chromatin structure, which express high levels of Aire and co-stimulatory molecules CD80 (Aire+CD80hi). Proliferating Aire+CD80hi mTECs detected by using Fucci technology express a minimal level of Aire-dependent TSAs and are converted into quiescent Aire+CD80hi mTECs expressing high levels of TSAs after a transit amplification. These data provide evidence for the existence of transit amplifying Aire+mTEC precursors during Aire+mTEC differentiation process of the postnatal thymus.


title: Aminoglycosides induce a bacterial senescent state that increases antibiotic tolerance in treatment-naïve cells

abstract: 1.Bacterial evolution of antibiotic resistance is facilitated by non-genetic resistance that increases drug tolerance, buying time for evolutionary innovation. Escherichia coli treated with aminoglycosides permanently lose the ability to divide within four hours, yet we discovered a majority of cells maintain membrane integrity and metabolic activity greater than two days post treatment - a bacterial senescent-like state. These cells, which we term zombies, exhibit dynamic gene expression and metabolomic profiles, even after irreversible exit from the cell cycle. Our data reveal zombies upregulate the phage shock protein pathway to maintain membrane integrity. Remarkably, though unable to form new colonies, zombies increase the antibiotic tolerance of treatment-naive cells, implying chemical communication. Chemical supplementation and genetic knockouts show that zombies communicate with treatment-naive cells by secreting indole. In summary, our study revealed a bacterial senescent-like state, induced by aminoglycosides, that decreases the antibiotic susceptibility of multiple bacterial species. Thus, E. coli zombies utilize paracrine signaling to promote non-genetic antibiotic tolerance.


title: T cell stimulation remodels the latently HIV-1 infected cell population by differential activation of proviral chromatin

abstract: The reservoir of latently HIV-1 infected cells is heterogeneous. To achieve an HIV-1 cure, the reservoir of activatable proviruses should be eliminated while permanently silenced proviruses may be tolerated. We have developed a method to assess the proviral nuclear microenvironment in single cells. In latently HIV-1 infected cells, a zinc finger protein tethered to the HIV-1 promoter produced a fluorescent signal as a protein of interest came in its proximity, such as the viral transactivator Tat when recruited to the nascent RNA. Tat is essential for viral replication. In these cells we assessed the proviral activation and chromatin composition. By linking Tat recruitment to proviral activity, we dissected the mechanisms of HIV-1 latency reversal and the consequences of HIV-1 production. A pulse of promoter-associated Tat was identified that contrasted to the continuous production of viral proteins. As expected, promoter H3K4me3 led to substantial expression of the provirus following T cell stimulation. However, the activation-induced cell cycle arrest and death led to a surviving cell fraction with proviruses encapsulated in repressive chromatin. Further, this cellular model was used to reveal mechanisms of action of small molecules. In a proof-of-concept study we determined the effect of an enhancer specific CBP/P300-inhibitor on HIV-1 latency reversal. Only proviruses resembling active enhancers, associated with H3K4me1 and H3K27ac, efficiently recruited Tat. Tat-independent HIV-1 latency reversal of unknown significance still occurred. We present a method for single cell assessment of the microenvironment of the latent HIV-1 proviruses, used here to reveal how T cell stimulation modulates the proviral activity and how the subsequent fate of the infected cell depends on the chromatin context.


title: Ancient and modern geochemical signatures in the 13,500-year sedimentary record of Lake Cadagno

abstract: Although lake sediments are globally important organic carbon sinks and therefore important habitats for deep microbial life, the deep lacustrine biosphere has thus far been little studied compared to its marine counterpart. To investigate the impact of the underexplored deep lacustrine biosphere on the sediment geochemical environment and vice versa, we performed a comprehensive microbiological and geochemical characterization of a sedimentary sequence from Lake Cadagno covering its entire environmental history since formation following glacial retreat. We found that both geochemical gradients and microbial community shifts across the [~]13.5 kyr subsurface sedimentary record reflect redox changes in the lake, going from oxic to anoxic and sulfidic. Most microbial activity occurs within the top 40 cm of sediment, where millimolar sulfate concentrations diffusing in from the bottom water are completely consumed. In deeper sediment layers, organic carbon remineralization is much slower but microorganisms nonetheless subsist on fermentation, sulfur cycling, metal reduction, and methanogenesis. The most surprising finding was the presence of a deep, oxidizing groundwater source. This water source generates an inverse redox gradient at the bottom of the sedimentary sequence and could contribute to the remineralization of organic matter sequestered in the energy-limited deep subsurface.


title: Coordination between metabolic transitions and gene expression by NAD+ availability during adipogenic differentiation in human cells.

abstract:
Adipocytes are the main cell type in adipose tissue, a critical regulator of metabolism, highly specialized in storing energy as fat. Adipocytes differentiate from multipotent mesenchymal stromal cells through adipogenesis, a tightly controlled differentiation process involving closely interplay between metabolic transitions and sequential programs of gene expression. However, the specific gears driving this interplay remain largely obscure. Additionally, the metabolite nicotinamide adenine dinucleotide (NAD+) is becoming increasingly recognized as a regulator of lipid metabolism, being postulated as promising therapeutic target for dyslipidemia and obesity. Here, we explored the effect of manipulating NAD+ bioavailability during adipogenic differentiation from human mesenchymal stem cells. We found a previously unappreciated strong repressive role for NAD+ on adipocyte commitment, while a functional NAD+-dependent deacetylase SIRT1 appeared crucial for terminal differentiation of pre-adipocytes. Remarkably, repressing the NAD+ biosynthetic salvage pathway during adipogenesis promoted the adipogenic transcriptional program, suggesting that SIRT1 activity during adipogenesis is independent from the NAD+ salvage pathway, while two photon microscopy and extracellular flux analyses suggest that its activation relies on the metabolic switch. Interestingly, SIRT1-directed control of subcellular compartmentalization of redox metabolism during adipogenesis was evidenced by two-photon fluorescence lifetime microscopy.

Significance StatementAdipocyte differentiation occurs from mesenchymal stem cells through the adipogenic process, involving sequential activation of both transcriptional and metabolic programs in a tightly coordinated manner. However, how transcriptional and metabolic transitions reciprocally interact during adipogenic differentiation remains largely obscure. Here we describe that the metabolite NAD+ is suppresses adipogenesis trough rewiring transcription, while a functional NAD+-dependent deacetylase SIRT1 is essential for terminal differentiation of pre-adipocytes. Using two-photon fluorescence lifetime microscopy, we created a metabolic map of NADH and lipid content simultaneously in live cells and described a new role for SIRT1 in the control of compartmentalization of redox metabolism during adipogenesis. These findings advance our understanding to improve therapeutical approaches targeting the NAD+-SIRT1 axis as treatment for obesity and dyslipemia.


title: Structure of an ant-myrmecophile-microbe community

abstract: Superorganismal ant colonies play host to a menagerie of symbiotic arthropods, termed myrmecophiles, which exhibit varying degrees of social integration into colony life. Such systems permit examination of how animal community interactions influence microbial assemblages. Here, we present an ecologically and phylogenetically comprehensive characterization of an ant-myrmecophile-microbe community in Southern California. Using 16S rRNA profiling, we find that microbiotas of the velvety tree ant (Liometopum occidentale) and its cohort of myrmecophiles are distinguished by species-specific characteristics but nevertheless bear signatures of their behavioral interactions. We found that the host ant microbiome was diverse at all taxonomic levels; that of a myrmecophilous cricket was moderately diverse, while microbiotas of three myrmecophilous rove beetles (Staphylinidae), which have convergently evolved symbiosis with Liometopum, were dominated by intracellular endosymbionts. Yet, despite these compositional differences, similarities between ant and myrmecophile microbiotas correlated with the nature and intimacy of their behavioral relationships. Physical interactions such as grooming and trophallaxis likely facilitate cross-species extracellular microbial sharing. Further, phylogenetic comparisons of microbiotas from myrmecophile rove beetles and outgroups revealed a lack of co-cladogenesis of beetles and intracellular endosymbionts, and limited evidence for convergence among the myrmecophiles intracellular microbiotas. Comparative genomic analyses of the dominant Rickettsia endosymbiont of the most highly socially integrated myrmecophile imply possible functions unrelated to nutrient-provisioning in the host beetles specialized lifestyle. Our findings indicate that myrmecophile microbiotas evolve largely independently of the constraints of deep evolutionary history, and that the transition to life inside colonies, including social interactions with hosts, plays a significant role in structuring bacterial assemblages of these symbiotic insects.


title: Projected dynamics of breeding habitat suitability for a steppe-land bird warrant anticipatory conservation actions

abstract:
Understanding spatial and temporal variations of habitat suitability is fundamental for species conservation under global change. Steppic species are particularly sensitive to anthropogenic change and have undergone large declines in the last decades. We aimed to describe current and future breeding habitat suitability for the Eurasian stone-curlew Burhinus oedicnemus, a steppic species of conservation concern, and to identify critical areas for its conservation. We collected 1628 presence records covering the period 1992-2016. We developed a species distribution model using a dynamic Maxent algorithm and a set of pseudo-absences with a spatial density weighted on a fixed kernel density estimated on the presences, to mitigate the potential sampling bias. We projected this model under a set of carbon emission, socioeconomic and land-use/land-cover scenarios for the years 2030, 2050, 2070 and 2090. Finally, we described the cell-wise and mean change of breeding habitat suitability through consecutive time intervals and identified the areas critical for the species conservation.

All scenarios predicted a short-term northward shift of suitable areas, followed by a period of stability. We found no consistent trends in the mean change of breeding habitat suitability, and similar extents of suitable areas under current and future scenarios. Critical areas for the conservation of the species are mainly located in Northern Europe, Israel and parts of North Africa, the Iberian Peninsula and Italy. According to our results, the Eurasian stone-curlew has the potential to maintain viable populations in the Western Palearctic, but dispersal limitations might hinder the colonization of shifted suitable areas. Targeted conservation interventions in the critical areas are therefore recommended to secure the future of the species under global change.


title: Bottom-up and top-down effects of temperature on body growth, population size spectra and yield in a size-structured food web

abstract: Resolving the combined effect of climate warming and exploitation in a food web context is key for predicting future biomass production, size-structure, and potential yields of marine fishes. Previous studies based on mechanistic size-based food web models have found that bottom-up processes are important drivers of size-structure and fisheries yield in changing climates. However, we know less about the joint effects of  bottom-up and  top-down effects of temperature: how do temperature effects propagate from individual-level physiology through food webs and alter the size-structure of exploited species in a community? Here we assess how a species-resolved size-based food web is affected by warming through both these pathways, and by exploitation. We parameterize a dynamic size spectrum food web model inspired by the offshore Baltic Sea food web, and investigate how individual growth rates, size-structure, relative abundances of species and yields are affected by warming. The magnitude of warming is based on projections by the regional coupled model system RCA4-NEMO and the RCP 8.5 emission scenario, and we evaluate different scenarios of temperature dependence on fish physiology and resource productivity. When accounting for temperature-effects on physiology in addition to on basal productivity, projected size-at-age in 2050 increases on average for all fish species, mainly for young fish, compared to scenarios without warming. In contrast, size-at-age decreases when temperature affects resource dynamics only, and the decline is largest for young fish. Faster growth rates due to warming, however, do not always translate to larger yields, as lower resource carrying capacities with increasing temperature tend to result in declines in the abundance of larger fish and hence spawning stock biomass - the part of the population exposed to fishing. These results show that to understand how global warming impacts the size structure of fish communities, both direct metabolic effects and indirect effects of temperature via basal resources must be accounted for.


title: Genomic architecture and sexually dimorphic expression underlying immunity in the red mason bee, Osmia bicornis

abstract: Insect pollinators provide crucial ecosystem services yet face increasing environmental pressures. The challenges posed by novel and reemerging pathogens on bee health means we need to improve our understanding of the immune system, an important barrier to infections and disease. Despite its importance, for certain ecologically important species, such as solitary bees, our understanding of the genomic basis and molecular mechanisms underlying immune potential, and how intrinsic and extrinsic factors may influence immune gene expression is lacking. Here, to improve our understanding of the genomic architecture underlying immunity of a key solitary bee pollinator, we characterised putative immune genes of the red mason bee, Osmia bicornis. In addition, we used publicly available RNA-seq datasets to determine how sexes differ in immune gene expression and splicing but also how pesticide exposure may affect immune gene expression in females. Through comparative genomics, we reveal an evolutionary conserved set of more than 500 putative immune-related genes. We found genome-wide patterns of sex-biased gene expression, including immune genes involved in antiviral-defence. Interestingly, the expression of certain immune genes were also affected by exposure to common neonicotinoids, particularly genes related to haemocyte proliferation. Collectively, our study provides important insights into the gene repertoire, regulation and expression differences in the sexes of O. bicornis, as well as providing additional support for how neonicotinoids can affect immune gene expression, which may affect the capacity of solitary bees to respond to pathogenic threats.


title: A class of identifiable birth-death models

abstract:
In a striking result, Louca and Pennell (2020) recently proved that a large class of phylogenetic birth-death models are statistically unidentifiable from lineage-through-time (LTT) data: any pair of sufficiently smooth birth and death rate functions is "congruent" to an infinite collection of other rate functions, all of which have the same likelihood for any LTT vector of any dimension. As Louca and Pennell argue, this fact has distressing implications for the thousands of studies that have utilized birth-death models to study evolution.

In this paper, we qualify their finding by proving that an alternative and widely used class of birth-death models is indeed identifiable. Specifically, we show that piecewise constant birth-death models can, in principle, be consistently estimated and distinguished from one another, given a sufficiently large extant time tree and some knowledge of the present-day population. Subject to mild regularity conditions, we further show that any unidentifiable birth-death model class can be arbitrarily closely approximated by a class of identifiable models. The sampling requirements needed for our results to hold are explicit, and are expected to be satisfied in many contexts such as the phylodynamic analysis of a global pandemic.


title: A class of identifiable phylogenetic birth-death models


title: Inference of cell-type specific imprinted regulatory elements and genes during human neuronal differentiation

abstract: Genomic imprinting results in gene expression biased by parental chromosome of origin and occurs in genes with important roles during human brain development. However, the cell-type and temporal specificity of imprinting during human neurogenesis is generally unknown. By detecting within-donor allelic biases in chromatin accessibility and gene expression that are unrelated to cross-donor genotype, we inferred imprinting in both primary human neural progenitor cells (phNPCs) and their differentiated neuronal progeny from up to 85 donors. We identified 43/20 putatively imprinted regulatory elements (IREs) in neurons/progenitors, and 133/79 putatively imprinted genes in neurons/progenitors. Though 10 IREs and 42 genes were shared between neurons and progenitors, most imprinting was only detected within specific cell types. In addition to well-known imprinted genes and their promoters, we inferred novel IREs and imprinted genes. We found IREs overlapped with CpG islands more than non-imprinted regulatory elements. Consistent with DNA methylation-based regulation of imprinted expression, some putatively imprinted regulatory elements also overlapped with differentially methylated regions on the maternal germline. Finally, we identified a progenitor-specific putatively imprinted gene overlap with copy number variation that is associated with uniparental disomy-like phenotypes. Our results can therefore be useful in interpreting the function of variants identified in future parent-of-origin association studies.


title: Archerfish number discrimination

abstract: Debates have arisen as to whether non-human animals actually can learn astract non-symbolic numerousness or whether they always rely on some continuous physical aspect of the stimuli covarying with number. Here we investigated archerfish (Toxotes jaculatrix) non-symbolic numerical discrimination with accurate control for co-varying continuous physical stimulus attributes. Archerfish were trained to select one of two groups of black dots (Exp. 1: 3 vs. 6 elements; Exp. 2: 2 vs. 3 elements); these were controlled for several combinations of physical variables (elements size, overall area, overall perimeter, density and sparsity), ensuring that only numerical information was available. Generalization tests with novel numerical comparisons (2 vs. 3, 5 vs. 8 and 6 vs. 9 in Exp. 1; 3 vs. 4, 3 vs. 6 in Exp. 2) revealed choice for the largest or smallest numerical group according to the relative number that was rewarded at training. None of the continuous physical variables, including spatial frequency, were affecting archerfish performance. Results provide evidence of the spontaneous use of abstract relative numerical information in archerfish for both small and large numbers.

category: animal behavior and cognition