title: Accelerated Predictive Healthcare Analytics with Pumas, A High Performance Pharmaceutical Modeling and Simulation Platform

abstract:
Pharmacometric modeling establishes causal quantitative relationships between administered dose, tissue exposures, desired and undesired effects and patients risk factors. These models are employed to de-risk drug development and guide precision medicine decisions. However, pharmacometric tools have not been designed to handle todays heterogeneous big data and complex models. We set out to design a platform that facilitates domain-specific modeling and its integration with modern analytics to foster innovation and readiness in healthcare.

Pumas demonstrates estimation methodologies with dramatic performance advances. New ODE solver algorithms, such as coeficient-optimized higher order integrators and new automatic stiffness detecting algorithms which are robust to frequent discontinuities, give rise to a median 4x performance improvement across a wide range of stiff and non-stiff systems seen in pharmacometric applications. These methods combine with JIT compiler techniques, such as statically-sized optimizations and discrete sensitivity analysis via forward-mode automatic differentiation, to further enhance the accuracy and performance of the solving and parameter estimation process. We demonstrate that when all of these techniques are combined with a validated clinical trial dosing mechanism and non-compartmental analysis (NCA) suite, real applications like NLME fitting see a median 81x acceleration while retaining the same accuracy. Meanwhile in areas with less prior software optimization, like optimal experimental design, we see orders of magnitude performance enhancements over competitors. Further, Pumas combines these technical advances with several workflows that are automated and designed to boost productivity of the day-to-day user activity. Together we show a fast pharmacometric modeling framework for next-generation precision analytics.


title: The disproportionate effect of drift on a hypervariable master regulator of density

abstract: Symbiosis is a continuum of long-term interactions ranging from mutualism to parasitism, according to the balance between costs and benefits for the protagonists. The density of endosymbionts is, in both cases, a key factor that determines both the transmission of symbionts and the host extended phenotype, and is thus tightly regulated within hosts. However, the evolutionary and molecular mechanisms underlying bacterial density regulation are currently poorly understood. In this context, the symbiosis between the fruit fly and its intracellular bacteria Wolbachia (wMelPop strain) is particularly interesting to study. Although vertically transmitted, the symbiont is pathogenic, and a positive correlation between virulence and wMelPop density is observed. In addition, the number of repeats of a bacterial genomic region -Octomom-is positively correlated with Wolbachia density, underlying a potential genetic mechanism that controls bacterial density. Interestingly, the number of repeats varies between host individuals, but most likely also within them. Such genetic heterogeneity within the host could promote conflicts between bacteria themselves and with the host, notably by increasing within-host competition between symbiont genotypes through a process analogous to the tragedy of the commons. To characterize the determinisms at play in the regulation of bacterial density, we first introgressed wMelPop in different genetic backgrounds of D. melanogaster, and found different density levels and Octomom copy numbers in each host lineage. To determine whether such variations reflect a host genetic determinism on density regulation through Octomom copy number selection, we replicated the introgressions and performed reciprocal crosses on the two Drosophila populations with the most extreme density levels. In both experiments, we detected an absence of directionality in the patterns of infection, associated with a strong instability of these patterns across generations. Given that bacterial density was highly correlated with Octomom copy numbers in all experiments, these results rather suggest a strong influence of drift and a random increase in the frequency of certain bacterial variants. We then discuss how drift, both on the symbiont population during transmission and on the host population, could limit the efficiency of selection in such a symbiotic system, and the consequences of drift on the regulation of density and composition of bacterial populations.

category: evolutionary biology


title: Wolbachia load variation in Drosophila is more likely caused by drift than by host genetic factors


title: CoxBase: an online platform for epidemiological surveillance, visualization, analysis and typing of Coxiella burnetii genomic sequence

abstract: Q (query) fever is an infectious zoonotic disease caused by the Gram-negative bacteria Coxiella burnetii. Although the disease has been studied since decades, it still represents a threat due to sporadic outbreaks across farms in Europe. The absence of a central platform for Coxiella typing data management in an important epidemiological gap which is relevant in the case of an outbreak. To fill this gap, we have designed and implemented an online, open-source, and, web-based platform called CoxBase (https://coxbase.q-gaps.de). This platform includes a database that holds genotyping information of more than 400 Coxiella isolates alongside metadata that annotates them. We have also implemented features for in silico genotyping of completely or minimally assembled Coxiella sequences using five different typing methods, querying existing isolates, visualization of isolates geodata via aggregation on a world map and submission of new isolates. We tested our in silico typing method on 50 Coxiella genomes downloaded from the RefSeq database and we successfully genotyped all except for cases where the sequence quality was poor. We identified new spacer sequences using our implementation of the MST in silico typing method, and established adaA gene phenotypes for all 50 genomes as well as their plasmid types.

category: bioinformatics


title: Nonsense correlations in neuroscience

abstract: Many neurophysiological signals exhibit slow continuous trends over time. Because standard correlation analyses assume that all samples are independent, they can yield apparently significant "nonsense correlations" even for signals that are completely unrelated. Here we compare the performance of several methods for assessing correlations between timeseries, using simulated slowly drifting signals with and without genuine correlations. The best performance was obtained from a "pseudosession method", which relies on one of the signals being randomly generated by the experimenter, or a "session perturbation" method which requires multiple recordings under the same conditions. If neither of these is applicable, a "linear shift" method can be used when one of the signals is stationary. Methods based on cross-validation, circular shifting, phase randomization, or detrending gave up to 100% false positive rates in our simulations. We conclude that analysis of neural timeseries is best performed when stationarity and randomization is built into the experimental design.

category: neuroscience


title: Pan-primate DNA methylation clocks

abstract: DNA methylation data have been successfully used to develop highly accurate estimators of age ("epigenetic clocks") in many mammalian species. With a view of extending such epigenetic clocks to all primate species, we analyzed DNA methylation profiles of 2400 tissues derived from 37 primate species including 11 haplorhine species (baboons, marmosets, vervets, rhesus macaque, chimpanzees, gorillas, orangutan, humans) and 26 strepsirrhine species (suborders Lemuriformes and Lorisiformes). From these we present here, pan-primate epigenetic clocks which are highly accurate for all primates including humans (age correlation R=0.98). We also carried out in-depth analysis of baboon DNA methylation profiles and generated five epigenetic clocks for baboons (Olive-yellow baboon hybrid), one of which, the pan-tissue epigenetic clock, was trained on seven tissue types (fetal cerebral cortex, adult cerebral cortex, cerebellum, adipose, heart, liver, and skeletal muscle) with ages ranging from late fetal life to 22.8 years of age. To facilitate translation of findings in baboons to humans, we further constructed two dual-species, human-baboon clocks. We also identified and present here, epigenetic predictors of sex that apply to all primate species. Low overlap can be observed between age- and sex-related CpGs. Overall, this study advances our understanding of conserved age- and sex-related epigenetic changes in primates, and provides biomarkers to study the aging of all primate species with the facility to readily translate any findings between primate species.

category: developmental biology


title: Molecular basis for gating and regulation of cardiac ryanodine receptor: underlying mechanisms for gain- and loss-of function mutations

abstract: Cardiac ryanodine receptor (RyR2) is a large Ca2+ release channel in the sarcoplasmic reticulum and indispensable for excitation-contraction coupling in the heart. RyR2 is activated by Ca2+ and RyR2 mutations are implicated in severe arrhythmogenic diseases. Yet, the structural basis underlying channel opening and how mutations affect the channel remain unknown. Here, we addressed gating mechanism of RyR2 by combining high-resolution structures determined by cryo-electron microscopy with quantitative functional analysis of channels carrying various mutations in specific residues. We demonstrated two fundamental mechanisms for channel gating: interactions close to the channel pore stabilize the channel to prevent hyperactivity and a series of interactions in the surrounding regions is necessary for channel opening upon Ca2+ binding. Mutations at the residues involved in the former and the latter mechanisms cause gain-of-function and loss-of-function, respectively. Our results reveal gating mechanisms of the RyR2 channel and alterations by pathogenic mutations at the atomic level.

category: biochemistry


title: Molecular basis for gating of cardiac ryanodine receptor: underlying mechanisms for gain- and loss-of function mutations


title: A Novel SARS-CoV-2 Multitope Protein/Peptide Vaccine Candidate is Highly Immunogenic and Prevents Lung Infection in an AAV hACE2 Mouse Model and non-human primates

abstract:
A novel multitope protein-peptide vaccine against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and disease is described in this report. The initial development and characterization experiments are presented along with proof-of-concept studies for the vaccine candidate UB-612. UB-612 consists of eight components rationally designed for induction of potently neutralizing antibodies and broad T cell responses against SARS-CoV-2: the S1-RBD-sFc fusion protein, six synthetic peptides (one universal peptide and five SARS-CoV-2-derived peptides), a proprietary CpG TLR-9 agonist at low concentration as an excipient, and aluminum phosphate adjuvant. Through immunogenicity studies in Guinea pigs and rats, we optimized the design of protein/peptide immunogens and selected an adjuvant system, yielding a vaccine that provides excellent S1-RBD binding and high neutralizing antibody responses, robust cellular responses, and a Th1-oriented response at low doses. In challenge studies, UB- 612 vaccination reduced viral load and prevented development of disease in mouse and non-human primate challenge models. With a Phase 1 trial completed, a Phase 2 trial ongoing in Taiwan, and additional trials planned to support global authorizations, UB-612 is a highly promising and differentiated vaccine candidate for prevention of SARS-CoV-2 infection and COVID-19 disease.

Author SummarySARS-CoV-2 virus, the causative agent of Coronavirus Disease 2019 (COVID-19), has spread globally since its origin in 2019, causing an unprecedented public health crisis that has resulted in greater than 4.7 million deaths worldwide. Many vaccines are under development to limit disease spread and reduce the number of cases, but additional candidates that promote a robust immune response are needed. Here, we describe a multitope protein-peptide vaccine platform that is unique among COVID-19 vaccines. The advantages of our approach are induction of both high levels of neutralizing antibodies as well as a Th/CTL response in the vaccinated host, which mimics the immune response that occurs after natural infection with SARS-CoV-2. We demonstrate that our vaccine is immunogenic and effective in preventing disease in several animal models, including AAV- hACE-2 transduced mice, and both rhesus and cynomolgus macaques. Importantly, no immunopathology was observed in the lungs of immunized animals, therefore showing that antibody-dependent enhancement (ADE) does not occur. Our study provides an additional, novel vaccine candidate for advancement in clinical trials to treat and prevent SARS-CoV-2 infection and COVID-19 disease.

category: immunology


title: Detection of plasmid contigs in draft genome assemblies using customized Kraken databases

abstract:
Plasmids play an important role in bacterial evolution and mediate horizontal transfer of genes including virulence and antimicrobial resistance genes. Although short-read sequencing technologies have enabled large-scale bacterial genomics, the resulting draft genome assemblies are often fragmented into hundreds of discrete contigs. Several tools and approaches have been developed to identify plasmid sequences in such assemblies, but require trade-off between sensitivity and specificity. Here we propose using the Kraken classifier, together with a custom Kraken database comprising known chromosomal and plasmid sequences of Klebsiella pneumoniae species complex (KpSC), to identify plasmid-derived contigs in draft assemblies. We assessed performance using Illumina-based draft genome assemblies for 82 KpSC isolates, for which complete genomes were available to supply ground truth. When benchmarked against five other classifiers (Centrifuge, RFPlasmid, mlplasmids, PlaScope, and Platon), Kraken showed balanced performance in terms of overall sensitivity and specificity (90.8% and 99.4%, respectively for contig count; 96.5% and >99.9%, respectively for cumulative contig length), and the highest accuracy (96.8% vs 91.8%-96.6% for contig count; 99.8% vs 99.0%-99.7% for cumulative contig length), and F1-score (94.5% vs 84.5%-94.1%, for contig count; 98.0% vs 88.9%-96.7% for cumulative contig length). Kraken also achieved consistent performance across our genome collection. Furthermore, we demonstrate that expanding the Kraken database with additional known chromosomal and plasmid sequences can further improve classification performance. Although we have focused here on the KpSC, this methodology could easily be applied to other species with a sufficient number of completed genomes.

IMPACT STATEMENTThe assembly of bacterial genomes using short-read data often results in hundreds of discrete contigs due to the presence of repeat sequences in those genomes. Separating plasmid contigs from chromosomal contigs in such assemblies is required, e.g., to assess the mobility of antimicrobial resistance genes. Although several tools have been developed for that purpose, they often suffer from low sensitivity or specificity. Here, we propose that the Kraken classifier coupled with a custom Kraken database comprising plasmid-free chromosomal sequences and complete plasmid sequences can be used for detection of plasmid contigs in draft genome assemblies. We showed that Kraken achieved balanced and higher performance compared with other methods (Centrifuge, RFPlasmid, mlplasmids, PlaScope, and Platon). We therefore consider that the Kraken classifier can be the best option for predicting the origin of contigs for species with a suitable number of completed chromosomal and plasmid sequences.

DATA SUMMARYTable S1: Complete chromosomes used for creating the base Kraken database. Plasmid-free chromosomal sequences and complete plasmid sequences used for creating the base Kraken database are also available via Figshare at https://doi.org/10.6084/m9.figshare.13289564.

Table S2: Sequence data used for benchmarking. Draft assemblies of these 82 KpSC strains are available via Figshare at https://doi.org/10.6084/m9.figshare.13553432. The corresponding sequence read files and complete genomes were deposited in the NCBI SRA and GenBank under BioProjects PRJEB6891, PRJNA351909, PRJNA486877, and PRJNA646837 (individual BioSample IDs listed in Table S2).

Kraken output files are available via Figshare at https://doi.org/10.6084/m9.figshare.13553789.

category: microbiology


title: Virophages and retrotransposons colonize the genomes of a heterotrophic flagellate

abstract: Virophages can parasitize giant DNA viruses and may provide adaptive anti-giant-virus defense in unicellular eukaryotes. Under laboratory conditions, the virophage mavirus integrates into the nuclear genome of the marine flagellate Cafeteria burkhardae and reactivates upon superinfection with the giant virus CroV. In natural systems, however, the prevalence and diversity of host-virophage associations has not been systematically explored. Here, we report dozens of integrated virophages in four globally sampled C. burkhardae strains that constitute up to 2% of their host genomes. These endogenous mavirus-like elements (EMALEs) separated into eight types based on GC-content, nucleotide similarity, and coding potential and carried diverse promoter motifs implicating interactions with different giant viruses. Between host strains, some EMALE insertion loci were conserved indicating ancient integration events, whereas the majority of insertion sites were unique to a given host strain suggesting that EMALEs are active and mobile. Furthermore, we uncovered a unique association between EMALEs and a group of tyrosine recombinase retrotransposons, revealing yet another layer of parasitism in this nested microbial system. Our findings show that virophages are widespread and dynamic in wild Cafeteria populations, supporting their potential role in antiviral defense in protists.


title: Remodeling and activation mechanisms of outer arm dyneins revealed by cryo-electron microscopy

abstract: Cilia are thin microtubule-based protrusions of eukaryotic cells. The swimming of ciliated protists and sperm cells is propelled by the beating of cilia. Cilia propagate the flow of mucus in the trachea and protect the human body from viral infections. The main force generators of ciliary beating are the outer dynein arms (ODAs) which attach to the doublet microtubules. The bending of cilia is driven by the ODAs conformational changes caused by ATP hydrolysis. Here, we report the native ODA complex structure attaching to the doublet microtubule by cryoelectron microscopy. The structure reveals how the ODA complex is attached to the doublet microtubule via the docking complex in its native state. Combined with molecular dynamics simulations, we present a model of how the attachment of the ODA to the doublet microtubule induces remodeling and activation of the ODA complex.

category: cell biology


title: Cross-tissue eQTL mapping in the presence of missing data via surrogate outcome analysis

abstract: Sample sizes vary substantially across tissues in the Genotype-Tissue Expression (GTEx) project, where considerably fewer samples are available from certain inaccessible tissues, such as the substantia nigra (SSN), than from accessible tissues, such as blood. This severely limits power for identifying tissue-specific expression quantitative trait loci (eQTL) in undersampled tissues. Here we propose Surrogate Phenotype Regression Analysis (SO_SCPLOWPRAYC_SCPLOW) for leveraging information from a correlated surrogate outcome (e.g. expression in blood) to improve inference on a partially missing target outcome (e.g. expression in SSN). Rather than regarding the surrogate outcome as a proxy for the target outcome, SO_SCPLOWPRAYC_SCPLOW jointly models the target and surrogate outcomes within a bivariate regression framework. Unobserved values of either outcome are treated as missing data. We describe and implement an expectation conditional maximization algorithm for performing estimation in the presence of bilateral outcome missingness. SO_SCPLOWPRAYC_SCPLOW estimates the same association parameter estimated by standard eQTL mapping and controls the type I error even when the target and surrogate outcomes are truly uncorrelated. We demonstrate analytically and empirically, using simulations and GTEx data, that in comparison with marginally modeling the target outcome, jointly modeling the target and surrogate outcomes increases estimation precision and improves power.

category: genetics


title: Leveraging a surrogate outcome to improve inference on a partially missing target outcome


title: SPICEMIX: Integrative single-cell spatial modeling for inferring cell identity

abstract: Spatial transcriptomics technologies promise to reveal spatial relationships of cell-type composition in complex tissues. However, the development of computational methods that can utilize the unique properties of spatial transcriptome data to unveil cell identities remains a challenge. Here, we introduce SO_SCPLOWPICEC_SCPLOWMO_SCPLOWIXC_SCPLOW, a new interpretable method based on probabilistic, latent variable modeling for effective joint analysis of spatial information and gene expression from spatial transcriptome data. Both simulation and real data evaluations demonstrate that SO_SCPLOWPICEC_SCPLOWMO_SCPLOWIXC_SCPLOW markedly improves upon the inference of cell types and their spatial patterns compared with existing approaches. By applying to spatial transcriptome data of brain regions in human and mouse acquired by seqFISH+, STARmap, and Visium, we show that SO_SCPLOWPICEC_SCPLOWMO_SCPLOWIXC_SCPLOW can enhance the inference of complex cell identities, reveal interpretable spatial metagenes, and uncover differentiation trajectories. SO_SCPLOWPICEC_SCPLOWMO_SCPLOWIXC_SCPLOW is a generalizable framework for analyzing spatial transcriptome data to provide critical insights into the cell type composition and spatial organization of cells in complex tissues.


title: SPICEMIX: Integrative single-cell spatial modeling of cell identity


title: A dynamic spike threshold with correlated noise predicts observed patterns of negative interval correlations in neuronal spike trains

abstract: Negative correlations in the sequential evolution of interspike intervals (ISIs) are a signature of memory in neuronal spike-trains. They provide coding benefits including firing-rate stabilization, improved detectability of weak sensory signals, and enhanced transmission of information by improving signal-to-noise ratio. Primary electrosensory afferent spike-trains in weakly electric fish fall into two categories based on the pattern of SCCs: non-bursting units have negative SCCs which remain negative but decay to zero with increasing lags (Type I SCCs), and bursting units have oscillatory (alternating sign) SCCs which damp to zero with increasing lags (Type II SCCs). Here, we predict and match observed ISI serial correlations in these afferents using a stochastic dynamic threshold model. We determine SCCs as a function of an arbitrary discrete noise correlation function Rk, where k is a multiple of the mean ISI. The function permits forward and inverse calculations of SCCs. Both types of SCCs can be generated by adding colored noise to the spike threshold with Type I SCCs generated with slow noise and Type II SCCs generated with fast noise. We show that a first-order autoregressive (AR) process with a single parameter is sufficient to predict and accurately match both types of afferent SCCs, the type being determined by the sign of the AR parameter. The predicted and experimentally observed SCCs are in geometric progression. The theory predicts that the limiting sum of SCCs is -0.5 yielding a perfect DC-block in the power spectrum of the spike train. Observed SCCs from afferents have a limiting sum that is slightly larger at -0.475 {+/-} 0.04 (mean {+/-} s.d.). We conclude that the underlying process for generating ISIs may be a simple combination of low-order autoregressive (AR) processes, and discuss the results from the perspective of optimal coding.


title: Activity-mediated accumulation of potassium induces a switch in firing pattern and neuronal excitability type

abstract:
During normal neuronal activity, ionic concentration gradients across a neurons membrane are often assumed to be stable. Prolonged spiking activity, however, can reduce transmembrane gradients and affect voltage dynamics. Based on mathematical modeling, we investigated the impact of neuronal activity on ionic concentrations and, consequently, the dynamics of action potential generation. We find that intense spiking activity on the order of a second suffices to induce changes in ionic reversal potentials and to consistently induce a switch from a regular to an intermittent firing mode. This transition is caused by a qualitative alteration in the systems voltage dynamics, mathematically corresponding to a co-dimension-two bifurcation from a saddle-node on invariant cycle (SNIC) to a homoclinic orbit bifurcation (HOM). Our electrophysiological recordings in mouse cortical pyramidal neurons confirm the changes in action potential dynamics predicted by the models: (i) activity-dependent increases in intracellular sodium concentration directly reduce action potential amplitudes, an effect typically attributed solely to sodium channel inactivation; (ii) extracellular potassium accumulation switches action potential generation from tonic firing to intermittently interrupted output. Thus, individual neurons may respond very differently to the same input stimuli, depending on their recent patterns of activity and/or the current brain-state.

Author summaryIonic concentrations in the brain are not constant. We show that during intense neuronal activity, they can change on the order of seconds and even switch neuronal spiking patterns under identical stimulation from a regular firing mode to an intermittently interrupted one. Triggered by an accumulation of extracellular potassium, such a transition is caused by a specific, qualitative change in of the neuronal voltage dynamics - a so-called bifurcation - which affects crucial features of action-potential generation and bears consequences for how information is encoded and how neurons behave together in the network. Also, changes in intracellular sodium can induce measurable effects, like a shrinkage of spike amplitude that occurs independently of the fast amplitude-effects attributed to sodium channel inactivation. Taken together, our results demonstrate that a neuron can respond very differently to the same stimulus, depending on its previous activity or the current brain state. This finding may be particularly relevant when other regulatory mechanisms of ionic homeostasis are challenged, for example, during pathological states of glial impairment or oxygen deprivation. Finally, Categorization of cortical neurons as intrinsically bursting or regular spiking may be biased by the ionic concentrations at the time of the observation, highlighting the non-static nature of neuronal dynamics.


title: Neural Flip-Flops III: Stomatogastric Ganglion

abstract:
The stomatogastric ganglion (STG) is a group of about 30 neurons that resides on the stomach in decapod crustaceans. Its two central pattern generators (CPGs) control the chewing action of the gastric mill and the peristaltic movement of food through the pylorus to the gut. The STG has been studied extensively because it has properties that are common to all nervous systems and because of the small number of neurons and other features that make it convenient to study. So many details are known that the STG is considered a classic test case in neuroscience for the reductionist strategy of explaining the emergence of macro-level phenomena from micro-level data. In spite of the intense scrutiny the STG has received, how it generates its rhythmic patterns of bursts remains unknown.

The explicit neural networks proposed here model the pyloric CPG of the American lobster (Homarus americanus). The models share enough significant features with the lobsters CPG that they may be considered first approximations, or perhaps simplified versions, of STG architecture. The similarities include 1) mostly inhibitory synapses; 2) pairs of cells with reciprocal inhibitory inputs, complementary outputs that are approximately 180 degrees out of phase, and state changes occurring with the high output changing first; 3) cells that have reciprocal, inhibitory inputs with more than one other cell; and 4) six cells that produce coordinated oscillations with the same period, four phases distributed approximately uniformly over the period, and half of the burst durations approximately 1/4 of the period and the other half 3/8.

Each models connectivity is explicit, and its operation depends only on minimal neuron capabilities of excitation and inhibition. One model performs a function that fills a gap in standard ring oscillators. It is apparently new to engineering, making it an example of neuroscience and logic circuit design informing each other.

Some models are derived from standard circuit designs by moving each negation symbol from one end of a connection to the other. This does not change the logic of the network, but it changes each logic gate to one that can be implemented with a single neuron.


title: Can citizen science analysis of camera trap data be used to study reproduction? Lessons from Snapshot Serengeti program

abstract:
Ecologists increasingly rely on camera-trap data to estimate biological parameters such as population abundance. Because of the huge amount of data, the assistance of non-scientists is often sought after, but an assessment of the data quality is necessary. We tested whether volunteers data from one of the largest citizen science projects - Snapshot Serengeti - could be used to study breeding phenology. We tested whether the presence of juveniles (less than one or 12 months old) of species in the Serengeti: topi, kongoni, Grants gazelle, could be reliably detected by the "naive" volunteers vs. trained observers. We expected a positive correlation between the proportion of volunteers identifying juveniles and their effective presence within photographs, assessed by the trained observers.

The agreement between the trained observers was good (Fleiss {kappa} > 0.61 for juveniles of less than one and 12 month(s) old), suggesting that morphological criteria can be used to determine age. The relationship between the proportion of volunteers detecting juveniles less than a month old and their actual presence plateaued at 0.45 for Grants gazelle, reached 0.70 for topi and 0.56 for kongoni. The same relationships were much stronger for juveniles younger than 12 months, reaching 1 for topi and kongoni. The absence of individuals < one month and the presence of juveniles < 12 months could be reliably assumed, respectively, when no volunteer and when all volunteers reported a presence of a young. In contrast, the presence of very young individuals and the absence of juveniles appeared more difficult to ascertain from volunteers classification, given how the classification task was presented to them.

Volunteers classification allows a moderately accurate but quick sorting of photograph with/without juveniles. We discuss the limitations of using citizen science camera-traps data to study breeding phenology, and the options to improve the detection of juveniles.

category: ecology


title: Isolation of Cell cycle delay, Pro-metaphase arrest, and c-metaphase inducing agents from leaf aqueous extract of Clerodendrum viscosum Vent.

abstract: Clerodendrum viscosum is a traditionally used medicinal plant. The present study aimed to analyze cell cycle delay, pro-metaphase arrest, and c-metaphase inducing effects of the petroleum ether fraction (AQPEF) of leaf aqueous extract of C. Viscosum (LAECV). The LAECV was fractionated with petroleum ether and its metaphase arrest, cell cycle delay, and c-metaphase inducing activities were tested on A. cepa root tip cells. The AQPEF induced cell cycle delay, and colchicine like metaphase, c-metaphase, in A. cepa root tip cells. Thus, the present study explores AQPEF as an active fraction of LAECV having metaphase arresting, cell cycle delay, and c-metaphase inducing potentials.

category: pharmacology and toxicology


title: Cell Cycle Delay, Pro-metaphase Arrest and C-metaphase Inducing Effects of Petroleum Ether Fraction of Leaf Aqueous Extract of Clerodendrum viscosum Vent.


title: Optimized cryo-EM data acquisition workflow by sample thickness determination

abstract:
Sample thickness is a known key parameter in cryo-electron microscopy (cryo-EM) and can affect the amount of high-resolution information retained in the image. Yet, common data acquisition approaches in single particle cryo-EM do not take it into account. Here, we demonstrate how the sample thickness can be determined before data acquisition, allowing to identify optimal regions and restrict automated data collection to images with preserved high-resolution details. This quality over quantity approach, almost entirely eliminates the time- and storage-consuming collection of suboptimal images, which are discarded after a recorded session or during early image processing due to lack of high-resolution information. It maximizes data collection efficiency and lowers the electron microscopy time required per dataset. This strategy is especially useful, if the speed of data collection is restricted by the microscope hardware and software, or if microscope access time, data transfer, data storage and computational power are a bottleneck.

SynopsisSample thickness is a key parameter in single particle cryo-electron microscopy. Determining sample thickness before data acquisition allows to target optimal areas and maximize data output quality of single particle cryo-electron microscopy sessions. Scripts and optimized workflows for EPU and SerialEM are presented and available as open-source.

category: biophysics


title: Oct1 recruits the histone lysine demethylase Utx to canalize lineage specification

abstract: The pathways used by cells to transition between undifferentiated, pluripotent state and tissue-specific states are incompletely understood. Here we show that the widely-expressed transcription factor Oct1/Pou2f1 activates silent, developmental lineage-appropriate genes to "canalize" developmental progression. Using Oct1 inducible knockout embryonic stem cells, we show that that Oct1 deficiency impairs mesodermal and terminal muscle differentiation in a manner that can be rescued by Oct1 retroviral expression. Using bulk RNA-seq, we show that mesoderm-specific genes are not correctly induced early in the differentiation timecourse. Single-cell gene expression profiling reveals that Oct1-deficient cells lose coherence in temporal induction of lineage programs, and show inappropriate developmental lineage branching resulting in poorly differentiated cells state with epithelial characteristics and hallmarks of oxidative stress. In embryonic stem cells, Oct1 co-binds with Oct4 to genes critical for mesoderm induction. The Utx/Kdm6a histone lysine demethylase also binds to many of these genes, and using a prototypic Pax3 gene we show that Oct1 recruits Utx to remove inhibitory H3K27me3 marks and activate expression. The specificity of the ubiquitous Oct1 protein for mesodermal genes can be explained by cooperative interactions with lineage-driving Smad transcription factors, as we show that Smad and Oct binding sites frequently coexist mesoderm-specific genes, that Oct1 and Smad3 interact, and that the sites and factors act cooperatively at the Myog enhancer. Overall, these results identify Oct1 as a key mediator of the induction of mesoderm lineage-specific genes.


title: Oct1 recruits the histone lysine demethylase Utx to promote lineage specification


title: Host-pathogen genetic interactions underlie tuberculosis susceptibility

abstract: The outcome of an encounter with Mycobacterium tuberculosis depends on the pathogens ability to adapt to the variable immune pressures exerted by the host. Understanding this interplay has proven difficult, largely because experimentally tractable animal models do not recapitulate the heterogeneity of tuberculosis disease. We leveraged the genetically diverse Collaborative Cross (CC) mouse panel in conjunction with a library of Mtb mutants to associate bacterial genetic requirements with host genetics and immunity. We report that CC strains vary dramatically in their susceptibility to infection and produce qualitatively distinct immune states. Global analysis of Mtb mutant fitness across the CC panel revealed that many virulence pathways are only in specific host microenvironments, identifying the large fraction of the pathogens genome that has been maintained to ensure fitness in a diverse population. Both immunological and bacterial traits were associated with genetic variants distributed across the mouse genome, identifying the specific host-pathogen genetic interactions that influence pathogenesis.


title: Bacillus subtilis YngB contributes to wall teichoic acid glucosylation and glycolipid formation during anaerobic growth

abstract: UTP-glucose-1-phosphate uridylyltransferases (UGPases) are enzymes that produce UDP-glucose from UTP and glucose-1-phosphate. In Bacillus subtilis 168, UDP-glucose is required for the decoration of wall teichoic acid (WTA) with glucose residues and the formation of glucolipids. The B. subtilis UGPase GtaB is essential for UDP-glucose production under standard aerobic growth conditions, and gtaB mutants display severe growth and morphological defects. However, bioinformatics predictions indicate that two other UGPases, are present in B. subtilis. Here, we investigated the function of one of them named YngB. The crystal structure of YngB revealed that the protein has the typical fold and all necessary active site features of a functional UGPase. Furthermore, UGPase activity could be demonstrated in vitro using UTP and glucose-1-phosphate as substrates. Expression of YngB from a synthetic promoter in a B. subtilis gtaB mutant resulted in the reintroduction of glucose residues on WTA and production of glycolipids, demonstrating that the enzyme can function as UGPase in vivo. When wild-type and mutant B. subtilis strains were grown under anaerobic conditions, YngB-dependent glycolipid production and glucose decorations on WTA could be detected, revealing that YngB is expressed from its native promoter under anaerobic condition. Based on these findings, along with the structure of the operon containing yngB and the transcription factor thought to be required for its expression, we propose that besides WTA, potentially other cell wall components might be decorated with glucose residues during oxygen limited growth condition.


title: Streptococcus agalactiae MprF synthesizes a novel cationic glycolipid and plays a role in brain entry and meningitis

abstract: Bacterial membrane lipids are critical for membrane bilayer formation, cell division, protein localization, stress responses, and pathogenesis. Despite their critical roles, membrane lipids have not been fully elucidated for many pathogens. Here, we report the discovery of a novel cationic glycolipid, Lysyl-Glucosyl-Diacylglycerol (Lys-Glc-DAG) that is synthesized in high abundance by the bacterium Streptococcus agalactiae (Group B Streptococcus, GBS). To our knowledge, Lys-Glc-DAG is more positively charged than any other known lipids. Lys-Glc-DAG carries two positive net charges per molecule, distinct from the widely described lysylated phospholipid Lysyl-phosphatidylglycerol (Lys-PG) which carries one positive net charge due to the presence of a negatively charged phosphate moiety. We use normal phase liquid chromatography (NPLC) coupled with electrospray ionization (ESI) high-resolution tandem mass spectrometry (HRMS/MS) and genetic approaches to determine that Lys-Glc-DAG is synthesized by the enzyme MprF in GBS, which covalently modifies the neutral glycolipid Glc-DAG with the cationic amino acid lysine. GBS is a leading cause of neonatal meningitis, which requires traversal of the endothelial blood-brain barrier (BBB). We demonstrate that GBS strains lacking mprF exhibit a significant decrease in the ability to invade BBB endothelial cells. Further, mice challenged with a GBS{Delta}mprF mutant developed bacteremia comparably to Wild-Type infected mice yet had less recovered bacteria from brain tissue and a lower incidence of meningitis. Thus, our data suggest that Lys-Glc-DAG may contribute to bacterial uptake into host cells and disease progression. Importantly, our discovery provides a platform for further study of cationic lipids at the host-pathogen interface.


title: Streptococcus agalactiae MprF synthesizes a novel cationic glycolipid and contributes to brain entry and meningitis


title: Identification of a novel cationic glycolipid in Streptococcus agalactiae that contributes to brain entry and meningitis


title: Reproductive proteins evolve faster than non-reproductive proteins among Solanum species

abstract: Elevated rates of evolution in reproductive proteins are commonly observed in animal species, and are thought to be driven by the action of sexual selection and sexual conflict acting specifically on reproductive traits. Whether similar patterns are broadly observed in other biological groups is equivocal. Here we examine patterns of protein divergence among wild tomato species (Solanum section Lycopersicon), to understand forces shaping the evolution of reproductive genes in this diverse, rapidly evolving plant clade. By comparing rates of molecular evolution among loci expressed in reproductive and non-reproductive tissues, our aims were to test if: a) reproductive-specific loci evolve more rapidly, on average, than non-reproductive loci;  male-specific loci evolve at different rates than  female-specific loci; c) genes expressed exclusively in gametophytic (haploid) tissue evolve differently from genes expressed in sporophytic (diploid) tissue or in both tissue types; and d) mating system variation (a potential proxy for the expected strength of sexual selection and/or sexual conflict) affects patterns of protein evolution. We observed elevated evolutionary rates in reproductive proteins. However this pattern was most evident for female- rather than male-specific loci, both broadly and for individual loci inferred to be positively selected. These elevated rates might be facilitated by greater tissue-specificity of reproductive proteins, as faster rates were also associated with more narrow expression domains. In contrast we found little evidence that evolutionary rates are consistently different in loci experiencing haploid selection (gametophytic-exclusive loci), or in lineages with quantitatively different mating systems. Overall while reproductive protein evolution is generally elevated in this diverse plant group, some specific patterns of evolution are more complex than those reported in other (largely animal) systems, and include a more prominent role for female-specific loci among adaptively evolving genes.


title: Large uncertainty in individual PRS estimation impacts PRS-based risk stratification

abstract: Large-scale genome-wide association studies have enabled polygenic risk scores (PRS), which estimate the genetic value of an individual for a given trait. Since PRS accuracy is typically assessed using cohort-level metrics (e.g., R2), uncertainty in PRS estimates at individual level remains underexplored. Here we show that Bayesian PRS methods can estimate the variance of an individuals PRS and can yield well-calibrated credible intervals for the genetic value of a single individual. For real traits in the UK Biobank (N=291,273 unrelated "white British") we observe large variance in individual PRS estimates which impacts interpretation of PRS-based stratification; for example, averaging across 13 traits, only 0.8% (s.d. 1.6%) of individuals with PRS point estimates in the top decile have their entire 95% credible intervals fully contained in the top decile. We provide an analytical estimator for individual PRS variance--a function of SNP-heritability, number of causal SNPs, and sample size--and observe high concordance with individual variances estimated via posterior sampling. Finally as an example of the utility of individual PRS uncertainties, we explore a probabilistic approach to PRS-based stratification that estimates the probability of an individuals genetic value to be above a prespecified threshold. Our results showcase the importance of incorporating uncertainty in individual PRS estimates into subsequent analyses.

category: genomics


title: Redistribution of centrosomal proteins by centromeres and Polo kinase controls partial nuclear envelope breakdown in fission yeast

abstract: Proper mitotic progression in Schizosaccharomyces pombe requires partial nuclear envelope breakdown (NEBD) and insertion of the spindle pole body (SPB - yeast centrosome) to build the mitotic spindle. Linkage of the centromere to the SPB is vital to this process, but why that linkage is important is not well understood. Utilizing high- resolution structured illumination microscopy (SIM), we show that the conserved SUN- domain protein Sad1 and other SPB proteins redistribute during mitosis to form a ring complex around SPBs, which is a precursor for localized NEBD and spindle formation. Although the Polo kinase Plo1 is not necessary for Sad1 redistribution, it localizes to the SPB region connected to the centromere, and its activity is vital for redistribution of other SPB ring proteins and for complete NEBD at the SPB to allow for SPB insertion. Our results lead to a model in which centromere linkage to the SPB drives redistribution of Sad1 and Plo1 activation that in turn facilitate partial NEBD and spindle formation through building of a SPB ring structure.


title: A comprehensive catalogue of regulatory variants in the cattle transcriptome

abstract: Characterization of genetic regulatory variants acting on the transcriptome of livestock is essential for interpreting the molecular mechanisms underlying traits of economic value and for increasing the rate of genetic gain through artificial selection. Here, we build a cattle Genotype-Tissue Expression atlas (cattle GTEx, http://cgtex.roslin.ed.ac.uk/) as part of the pilot phase of Farm animal GTEx (FarmGTEx) project for the research community based on publicly available 11,642 RNA-Seq datasets. We describe the landscape of the transcriptome across over 100 tissues and report hundreds of thousands of genetic associations with gene expression and alternative splicing for 24 major tissues. We evaluate the tissue-sharing patterns of these genetic regulatory effects, and functionally annotate them using multi-omics data. Finally, we link gene expression in different tissues to 43 economically important traits using both transcriptome-wide association study (TWAS) and colocalization analyses to decipher the molecular regulatory mechanisms underpinning such agronomic traits in cattle.


title: The structural dynamics of macropinosome formation and PI3-kinase-mediated sealing revealed by lattice lightsheet microscopy

abstract: Macropinosomes are formed by shaping actin-rich plasma membrane ruffles into large intracellular organelles in a phosphatidylinositol 3-kinase (PI3K)-coordinated manner. Here, we utilize lattice lightsheet microscopy and image visualization methods to map the three-dimensional structure and dynamics of macropinosome formation relative to PI3K activity. We show that multiple ruffling morphologies produce macropinosomes and that the majority form through collisions of adjacent PI3K-rich ruffles. By combining multiple volumetric representations of the plasma membrane structure and PI3K products, we show that PI3K activity begins early throughout the entire ruffle volume and continues to increase until peak activity concentrates at the base of the ruffle after the macropinosome closes. Additionally, areas of the plasma membrane rich in ruffling had increased PI3K activity and produced many macropinosomes of various sizes. Pharmacologic inhibition of PI3K activity had little effect on the rate and morphology of membrane ruffling, demonstrating that early production of 3-phosphoinositides within ruffles plays a minor role in regulating their morphology. However, 3-phosphoinositides are critical for the fusogenic activity that seals ruffles into macropinosomes. Taken together, these data indicate that local PI3K activity is amplified in ruffles and serves as a priming mechanism for closure and sealing of ruffles into macropinosomes.


title: A hydro-osmotic coarsening theory of biological cavity formation

abstract:
Fluid-filled biological cavities are ubiquitous, but their collective dynamics has remained largely unexplored from a physical perspective. Based on experimental observations in early embryos, we propose a model where a cavity forms through the coarsening of myriad of pressurized micrometric lumens, that interact by ion and fluid exchanges through the intercellular space. Performing extensive numerical simulations, we find that hydraulic fluxes lead to a self-similar coarsening of lumens in time, characterized by a robust dynamic scaling exponent. The collective dynamics is primarily controlled by hydraulic fluxes, which stem from lumen pressures differences and are dampened by water permeation through the membrane. Passive osmotic heterogeneities play, on the contrary, a minor role on cavity formation but active ion pumping can largely modify the coarsening dynamics: it prevents the lumen network from a collective collapse and gives rise to a novel coalescence-dominated regime exhibiting a distinct scaling law. Interestingly, we prove numerically that spatially biasing ion pumping may be sufficient to position the cavity, suggesting a novel mode of symmetry breaking to control tissue patterning. Providing generic testable predictions, our model forms a comprehensive theoretical basis for hydro-osmotic interaction between biological cavities, that shall find wide applications in embryo and tissue morphogenesis.

Author summaryThe formation of a single biological cavity, or lumen, in tissues and embryos has been widely studied experimentally but the collective dynamics of multiple lumens has received much less attention. Here, we focus on a particular type of lumens, which are located at the adhesive side of cells and can therefore interact directly through the intercellular space, as recently observed in the very first stages of embryogenesis. We propose a generic model to describe the hydraulic and osmotic exchanges between lumens themselves, and with the surrounding cellular medium. Lumens are pressurized by a surface tension, which leads naturally to their coarsening into a single final cavity through hydraulic exchanges. With extensive numerical simulations and mean-field theory we predict that such coarsening dynamics follows a robust scaling law, that barely depends on concentration heterogeneities between lumens. On the contrary, active osmotic pumping largely influences the collective dynamics by favoring lumen coalescence and by biasing the position of the final cavity. Our theoretical work highlights the essential role of hydraulic and osmotic flows in morphogenesis.


title: Multigenerational exposure to heat stress induces phenotypic resilience, and genetic and epigenetic variations in Arabidopsis thaliana offspring

abstract: Plants are sedentary organisms that constantly sense changes in their environment and react to various environmental cues. On a short-time scale, plants respond through alterations in their physiology, and on a long-time scale, plants alter their development and pass on the memory of stress to the progeny. The latter is controlled genetically and epigenetically and allows the progeny to be primed for future stress encounters, thus increasing the likelihood of survival. The current study intended to explore the effects of multigenerational heat stress in Arabidopsis thaliana. 25 generations of Arabidopsis thaliana were propagated in the presence of heat stress. The multigenerational stressed lineage F25H exhibited a higher tolerance to heat stress and elevated frequency of homologous recombination, as compared to the parallel control progeny F25C. A comparison of genomic sequences revealed that the F25H lineage had a three-fold higher number of mutations (SNPs and INDELs) as compared control lineages, suggesting that heat stress induced genetic variations in the heat-stressed progeny. The F25H stressed progeny showed a 7-fold higher number of non-synonymous mutations than the F25C line. Methylome analysis revealed that the F25H stressed progeny showed a lower global methylation level in the CHH context than the control progeny. The F25H and F25C lineages were different from the parental control lineage F2C by 66,491 and 80,464 differentially methylated positions (DMPs), respectively. F25H stressed progeny displayed higher frequency of methylation changes in the gene body and lower in the body of transposable elements (TEs). Gene Ontology analysis revealed that CG-DMRs were enriched in processes such as response to abiotic and biotic stimulus, cell organizations and biogenesis, and DNA or RNA metabolism. Hierarchical clustering of these epimutations separated the heat stressed and control parental progenies into distinct groups which revealed the non-random nature of epimutations. We observed an overall higher number of epigenetic variations than genetic variations in all comparison groups, indicating that epigenetic variations are more prevalent than genetic variations. The largest difference in epigenetic and genetic variations was observed between control plants comparison (F25C vs F2C), which clearly indicated that the spontaneous nature of epigenetic variations and heat-inducible nature of genetic variations. Overall, our study showed that progenies derived from multigenerational heat stress displayed a notable adaption in context of phenotypic, genotypic and epigenotypic resilience.

category: plant biology


title: Inferring system-level brain communication through multi-scale neural activity

abstract: Fundamental principles underlying computation in multi-scale brain networks illustrate how multiple brain areas and their coordinated activity give rise to complex cognitive functions. Whereas the population brain activity has been studied in the micro-to meso-scale in building the connections between the dynamical patterns and the behaviors, such studies were often done at a single length scale and lacked an explanatory theory that identifies the neuronal origin across multiple scales. Here we introduce the NeuroBondGraph Network, a dynamical system incorporating both biological-inspired components and deep learning techniques to capture cross-scale dynamics that can infer and map the neural data from multiple scales. We demonstrated our model is not only 3.5 times more accurate than the popular sphere head model but also able to predict synchronous neural activity and extract correlated low-dimensional latent dynamics. We also showed that we can extend our methods to robustly predict held-out data across several weeks. The extracted effective connectivity agreed with the neuroanatomical hierarchy of motor control. Accordingly, the NeuroBondGraph Network opens the door to revealing comprehensive understanding of the brain computation, where network mechanisms of multi-scale communications are critical.


title: Enhancing daily light exposure increases the antibody response to influenza vaccination in patients with dementia

abstract: Enhancing lighting conditions in institutions for individuals with dementia improves their sleep, circadian rhythms and well-being. Here, we tested whether a greater long-term daily light exposure supports the immune response to the annual influenza vaccination. Eighty older institutionalised patients suffering from dementia (54 women and 26 men) continuously wore an activity tracker for 8 weeks to assess individual light exposure and rest-activity cycles. The patients immune response was analysed from two blood samples taken before and 4 - 5 weeks after the annual influenza vaccination. Individual antibody concentrations to three influenza virus strains (H3N2, H1N1, IB) were quantified via hemagglutination inhibition assays. By quantifying individual light exposure profiles (including daylight), we classified the patients into a low and a high light exposure group based on a median illuminance of 392.6 lux. The two light exposure groups did not differ in cognitive impairment severity, age or gender distribution. However, patients in the high light exposure group showed a significantly greater circadian rest-activity amplitude (i.e., more daytime activity and less nighttime activity) along with a significantly greater antibody titer increase to the H3N2 vaccine than patients in the low light exposure group, despite similar pre-vaccination concentrations. Sufficient seroprotective responses to all three influenza virus strains were attained for [≥] 75% of participants. These data provide first evidence for a potentially enhanced immune response in patients with dementia when they received more daily light. Increasing daily light exposure may have beneficial effects on the human immune system, either directly or via circadian rhythm stabilisation.


title: Regulation of REM Sleep by Inhibitory Neurons in the Dorsomedial Medulla

abstract: The two major stages of mammalian sleep - rapid eye movement sleep (REMs) and non-REM sleep (NREMs) - are characterized by distinct brain rhythms ranging from millisecond to minute-long (infraslow) oscillations. The mechanisms controlling transitions between sleep stages and how they are synchronized with infraslow rhythms remain poorly understood. Using opto- and chemogenetic manipulation, we show that GABAergic neurons in the dorsomedial medulla (dmM) promote the initiation and maintenance of REMs, in part through their projections to the dorsal and median raphe nuclei. Fiber photometry revealed that dmM GABAergic neurons are strongly activated during REMs. During NREMs, their activity fluctuated in close synchrony with infraslow oscillations in the spindle band of the electroencephalogram, and the phase of this rhythm modulated the latency of optogenetically induced REMs episodes. Thus, dmM inhibitory neurons powerfully promote REMs, and their slow activity fluctuations may coordinate transitions from NREMs to REMs with infraslow brain rhythms.


title: Membrane cholesterol regulates TRPV4 function, cytoskeletal expression and the cellular response to tension

abstract: Despite the association of cholesterol with debilitating pressure-related diseases, its role in mechanotransduction is not well understood. We investigated the relationship between mechanical strain, free membrane cholesterol, actin cytoskeleton, and activation of stretch- activated TRPV4 (transient receptor potential vanilloid isoform 4) channel in human trabecular meshwork (TM) cells. Physiological levels of cyclic stretch resulted in time- dependent decreases in membrane cholesterol/phosphatidylcholine ratio and upregulation of stress fibers. Depletion of free membrane cholesterol with m-{beta}-cyclodextrin (M{beta}CD) augmented TRPV4 activation by the agonist GSK1016790A, swelling and strain, with the effects reversed by cholesterol supplementation. M{beta}CD increased membrane expression of TRPV4, caveolin-1 and flotillin. Caveolin-1 antibody partially precipitated a truncated [~]75 kDa variant whereas the majority of TRPV4 did not colocalize or interact with caveolae or lipid rafts, indicating that TRPV4 is mainly localized outside of cholesterol-enrichedmembrane domains. M{beta}CD induced currents in TRPV4-expressing Xenopus laevis oocytes. Thus, while the membrane C/P ratio reflects the biomechanical milieu, trabecular transduction of mechanical information is modulated by the membrane cholesterol content. Diet, cholesterol metabolism and mechanical stress might modulate the conventional outflow pathway and intraocular pressure in glaucoma and diabetes.


title: Lysosomal positioning regulates Rab10 phosphorylation at LRRK2-positive lysosomes

abstract: Genetic variation at the Leucine-rich repeat kinase 2 (LRRK2) locus contributes to enhanced lifetime risk of familial and sporadic Parkinsons disease. Previous data have demonstrated that recruitment to various membranes of the endolysosomal system results in LRRK2 activation. However, the mechanism(s) underlying LRRK2 activation at endolysosomal membranes and the cellular consequences of these events are still poorly understood. Here, we directed LRRK2 to lysosomes and early endosomes, triggering both LRRK2 autophosphorylation and phosphorylation of the direct LRRK2 substrates Rab10 and Rab12. However, when directed to the lysosomal membrane, pRab10 was restricted to perinuclear lysosomes, whereas pRab12 was visualized on both peripheral and perinuclear LRRK2-positive lysosomes, suggesting that lysosomal positioning provides additional regulation of LRRK2-dependent Rab phosphorylation. Anterograde transport of lysosomes to the cell periphery by increasing expression of ARL8B and SKIP or by knockdown of the motor adaptor protein JIP4 blocked recruitment and phosphorylation of Rab10 by LRRK2. Conversely, overexpression of the Rab7 effector protein RILP resulted in lysosomal clustering within the perinuclear area and increased LRRK2-dependent Rab10 recruitment and phosphorylation. The regulation of Rab10 phosphorylation in the perinuclear area depends on counteracting phosphatases, as knockdown of phosphatase PPM1H significantly increased pRab10 signal and lysosomal tubulation in the perinuclear region. Our novel findings suggest LRRK2 can be activated at multiple cellular membranes including lysosomes, and that lysosomal positioning further provides regulation of some Rab substrates likely via differential phosphatase activity in nearby cellular compartments.


title: eSCAN: Scan Regulatory Regions for Aggregate Association Testing using Whole Genome Sequencing Data

abstract: Multiple statistical methods for aggregate association testing have been developed for whole genome sequencing (WGS) data. Many aggregate variants in a given genomic window and ignore existing knowledge to define test regions, resulting in many identified regions not clearly linked to genes and thus limiting biological understanding. Functional information from new technologies (such as Hi-C and its derivatives), which can help link enhancers to their effector genes, can be leveraged to predefine variant sets for aggregate testing in WGS data. Here we propose the eSCAN (Scan the Enhancers) method for genome-wide assessment of enhancer regions in sequencing studies, combining the advantages of dynamic window selection in SCANG, a previously developed method, with the advantages of incorporating putative regulatory regions from annotation. eSCAN, by searching in putative enhancer, increases statistical power and aids mechanistic interpretation, as demonstrated by extensive simulation studies. We also apply eSCAN for blood cell traits using TOPMed WGS data. Results from real data analysis show that eSCAN is able to capture more significant signals, and these signals are of shorter length (indicating higher resolution fine-mapping capability) and drive association of larger regions detected by other methods.


title: CellKb Immune: a manually curated database of mouse hematopoietic marker gene sets optimized for rapid cell type identification

abstract: Using single-cell RNA sequencing, it is now possible to get the detailed gene expression pattern in each cell for millions of cells in a single experiment under varying conditions. Annotating cells by assigning a type or state to them is important for correct interpretation of results. In spite of current advances in technology, assigning cell types in single-cell datasets remains a bottleneck due to the lack of a comprehensive reference database and an accurate search method in a single tool. CellKb Immune is a knowledgebase of manually collected, curated and annotated marker gene sets representing cell types in the immune response in mouse. It allows users to find matching cell types in literature given a list of genes. We evaluated the contents and search methodology of CellKb Immune using a leave-one-out approach. We further used CellKb Immune to annotate previously defined marker gene sets from a bulk RNA-seq dataset to confirm its accuracy and coverage. CellKb Immune provides an easy-to-use online tool with a reliable method to find matching cell types and annotate cells in single-cell experiments. It is available at https://www.cellkb.com/immune.


title: CellKb Immune: a manually curated database of hematopoietic marker gene sets from 7 species for rapid cell type identification


title: CellKb Immune: a manually curated database of mammalian hematopoietic marker gene sets for rapid cell type identification


title: Integrated multi-omics analysis reveals common and distinct dysregulated pathways for genetic subtypes of Frontotemporal Dementia

abstract: Understanding the molecular mechanisms underlying frontotemporal dementia (FTD) is essential for the development of successful therapies. Here we integrated transcriptomic and epigenomic analyses of postmortem human brains of FTD patients with mutations in MAPT, GRN and C9orf72 and detected common and distinct dysregulated cellular pathways between patient groups. Our results highlight that excitatory neurons are the most vulnerable neuronal cell type and that vascular aberrations are a common hallmark in FTD. Via integration of multi-omics data, we detected several transcription factors and pathways which regulate the strong neuroinflammation observed in FTD-GRN. Small RNA-seq data and verification experiments in cellular models identified up-regulated miRNAs that inhibit cellular trafficking pathways in FTD and lead to microglial activation. These findings shed light on novel mechanistic and pathophysiological hallmarks of FTD. The data represent the 1st phase of a multi-omics, multi-model data resource for FTD research which allows in-depth molecular research into disease mechanisms that will further mechanistic FTD research.


title: Biliverdin reductase bridges focal adhesion kinase to Src to modulate synaptic signaling

abstract: Synapses are complex bridges that connect discrete neurons into vast networks that send, receive, and encode diverse forms of information. However, they must remain dynamic in order to adapt to changing inputs. Here, we report that the enzyme biliverdin reductase (BVR) physically links together key molecules in focal adhesion signaling at the synapse. In challenging mice with a battery of neurocognitive tasks, we first discover that BVR null (BVR-/-) mice exhibit profound deficits in learning and memory. We uncover that these deficits may be explained by a loss of focal adhesion signaling that is both transcriptionally and biochemically disrupted in BVR-/- hippocampi. We learn that BVR mediates focal adhesion signaling by physically bridging the initiatory kinases FAK/Pyk2 to the effector kinase Src. Activated Src normally promotes synaptic plasticity by phosphorylating the N-methyl-D-aspartate (NMDA) receptor, but FAK/Pyk2 are unable to bind and stimulate Src without BVR. Src itself is a molecular hub upon which many signaling pathways converge in order to stimulate NMDA neurotransmission, positioning BVR at a prominent intersection of synaptic signaling.


title: Estimating population size when individuals are asynchronous: a model illustrated with northern elephant seal breeding colonies

abstract: Our aim was to develop a method for estimating the number of animals using a single site in an asynchronous species, meaning that not all animals are present at once so that no one count captures the entire population. This is a common problem in seasonal breeders, and in northern elephant seals, we have a model for quantifying asynchrony at the Ano Nuevo colony. Here we test the model at several additional colonies having many years of observations and demonstrate how it can account for animals not present on any one day. This leads to correction factors that yield total population from any single count throughout a season. At seven colonies in California for which we had many years of counts of northern elephant seals, we found that female arrival date varied < 2 days between years within sites and by < 5 days between sites. As a result, the correction factor for any one day was consistent, and at each colony, multiplying a female count between 26 and 30 Jan by 1.15 yielded an estimate of total population size that minimized error. This provides a method for estimating the female population size at colonies not yet studied. Our method can produce population estimates with minimal expenditure of time and resources and will be applicable to many seasonal species with asynchronous breeding phenology, particularly colonial birds and other pinnipeds. In elephant seals, it will facilitate monitoring the population over its entire range.


title: Strong selective environments determine evolutionary outcome in time-dependent fitness seascapes

abstract: The impact of fitness landscape features on evolutionary outcomes has attracted considerable interest in recent decades. However, evolution often occurs under time-dependent selection in so-called fitness seascapes where the landscape is under flux. Fitness seascapes are an inherent feature of natural environments, where the landscape changes owing both to the intrinsic fitness consequences of previous adaptations and extrinsic changes in selected traits caused by new environments. The complexity of such seascapes may curb the predictability of evolution. However, empirical efforts to test this question utilising a comprehensive set of regimes are lacking. Here we employed an in vitro microbial model system to investigate differences in evolutionary outcomes between time-invariant and -dependent environments, including all possible temporal permutations, with three subinhibitory antimicrobials and a viral parasite (phage) as selective agents. Expectedly, time-invariant environments caused stronger directional selection for resistances compared to time-dependent environments. Intriguingly, however, multidrug resistance outcomes in both cases were largely driven by two strong selective agents (rifampicin and phage) out of four agents in total. These agents either caused cross-resistance or obscured the phenotypic effect of other resistance mutations, modulating the evolutionary outcome overall in time-invariant environments and as a function of exposure epoch in time-dependent environments. This suggests that identifying strong selective agents and their pleiotropic effects is critical for predicting evolution in fitness seascapes, with ramifications for evolutionarily informed strategies to mitigate drug resistance evolution.


title: Spatial population genomics of a recent mosquito invasion

abstract: Population genomic approaches can characterise dispersal across a single generation through to many generations in the past, bridging the gap between individual movement and intergenerational gene flow. These approaches are particularly useful when investigating dispersal in recently altered systems, where they provide a way of inferring long-distance dispersal between newly established populations and their interactions with existing populations. Human-mediated biological invasions represent such altered systems which can be investigated with appropriate study designs and analyses. Here we apply temporally-restricted sampling and a range of population genomic approaches to investigate dispersal in a 2004 invasion of Aedes albopictus (the Asian tiger mosquito) in the Torres Strait Islands (TSI) of Australia. We sampled mosquitoes from 13 TSI villages simultaneously and genotyped 373 mosquitoes at genome-wide single nucleotide polymorphisms (SNPs): 331 from the TSI, 36 from Papua New Guinea (PNG), and 4 incursive mosquitoes detected in uninvaded regions. Within villages, spatial genetic structure varied substantially but overall displayed isolation by distance and a neighbourhood size of 232-577. Close kin dyads revealed recent movement between islands 31-203 km apart, and deep learning inferences showed incursive Ae. albopictus had travelled to uninvaded regions from both adjacent and non-adjacent islands. Private alleles and a coancestry matrix indicated direct gene flow from PNG into nearby islands. Outlier analyses also detected four linked alleles introgressed from PNG, with the alleles surrounding 12 resistance-associated cytochrome P450 genes. By treating dispersal as both an intergenerational process and a set of discrete events, we describe a highly interconnected invasive system.


title: Analytic Pearson residuals for normalization of single-cell RNA-seq UMI data

abstract:
BackgroundStandard preprocessing of single-cell RNA-seq UMI data includes normalization by sequencing depth to remove this technical variability, and nonlinear transformation to stabilize the variance across genes with different expression levels. Instead, two recent papers propose to use statistical count models for these tasks: Hafemeister & Satija [1] recommend using Pearson residuals from negative binomial regression, while Townes et al. [2] recommend fitting a generalized PCA model. Here, we investigate the connection between these approaches theoretically and empirically, and compare their effects on downstream processing.

ResultsWe show that the model of Hafemeister and Satija produces noisy parameter estimates because it is overspecified, which is why the original paper employs post-hoc smoothing. When specified more parsimoniously, it has a simple analytic solution equivalent to the rank-one Poisson GLM-PCA of Townes et al. Further, our analysis indicates that per-gene overdispersion estimates in Hafemeister and Satija are biased, and that the data are in fact consistent with the overdispersion parameter being independent of gene expression. We then use negative control data without biological variability to estimate the technical overdispersion of UMI counts, and find that across several different experimental protocols, the data are close to Poisson and suggest very moderate overdispersion. Finally, we perform a benchmark to compare the performance of Pearson residuals, variance-stabilizing transformations, and GLM-PCA on scRNA-seq datasets with known ground truth.

ConclusionsWe demonstrate that analytic Pearson residuals strongly outperform other methods for identifying biologically variable genes, and capture more of the biologically meaningful variation when used for dimensionality reduction.


title: A fast and robust Bayesian nonparametric method for prediction of complex traits using summary statistics

abstract: Genetic prediction of complex traits has great promise for disease prevention, monitoring, and treatment. The development of accurate risk prediction models is hindered by the wide diversity of genetic architecture across different traits, limited access to individual level data for training and parameter tuning, and the demand for computational resources. To overcome the limitations of the most existing methods that make explicit assumptions on the underlying genetic architecture and need a separate validation data set for parameter tuning, we develop a summary statistics-based nonparametric method that does not rely on validation datasets to tune parameters. In our implementation, we refine the commonly used likelihood assumption to deal with the discrepancy between summary statistics and external reference panel. We also leverage the block structure of the reference linkage disequilibrium matrix for implementation of a parallel algorithm. Through simulations and applications to twelve traits, we show that our method is adaptive to different genetic architectures, statistically robust, and computationally efficient. Our method is available at https://github.com/eldronzhou/SDPR.


title: Razor: annotation of signal peptides from toxins

abstract:
MotivationSignal peptides are responsible for protein transport and secretion and are ubiquitous to all forms of life. The annotation of signal peptides is important for understanding protein translocation and toxin secretion and evolution.

ResultsHere we explore the features of these signal sequences from eukaryotic proteins. Strikingly, we find that the signal peptides from secretory toxins have common features across kingdoms, supporting the idea of horizontal gene transfer or convergence of toxin genes across kingdoms. We leverage these features to build Razor, a simple yet powerful tool specialised in identifying signal peptides from toxins using the first 23 N-terminal residues. We demonstrate the usability of Razor by analysing all the sequences reviewed by UniProt. Indeed, Razor is able to identify toxins using their N-terminal sequences only. Strikingly, we also discover that many defensive proteins across kingdoms harbour a toxin-like signal peptide; some of these defensive proteins have emerged through convergent evolution, e.g. defensin and defensin-like protein families, and phospholipase families. In sum, Razor uses an approach independent of homology search to identify novel and known toxin classes across species using N-terminal residues.

Availability and implementationRazor is available as a web application (https://tisigner.com/razor) and a command-line tool (https://github.com/Gardner-BinfLab/Razor).


title: A Non-Negative Tensor Factorization Approach to Deconvolute Epigenetic Microenvironment in Breast Cancer

abstract:
An in-depth understanding of epithelial breast cell response to growth-promoting ligands is required to elucidate how signals from the microenvironment affect cell-intrinsic regulatory networks and their resultant cellular phenotypes, such as cell growth, progression, and differentiation. Understanding the cellular response to these signals is particularly important in understanding the mechanisms of breast cancer initiation and progression. There is increasing evidence that aberrant epigenetic marks are present in cells of the breast tumor microenvironment and are known to affect primary cellular processes like proliferation, differentiation, and apoptosis. However, the current mechanisms by which epigenetic microenvironment signals influence these cellular phenotypes are not well established. We developed a high-order correlation method using proteomics data to reveal the regulatory dynamics among signaling proteins, histones, and growth-promoting ligands in the breast epithelial cells. In the proposed method, the protein-ligand and histone-ligand correlations at multiple time points are first encoded in two three-way tensors. Then, a non-negative tensor factorization (NTF) model is used to capture and quantify the protein-ligand and histone-ligand correlations spanning all time points, followed by a correlation analysis to reveal the pairwise correlations between histones and proteins. Our method revealed the onset of specific protein-histone signatures in response to growth ligands contributing to distinct cellular phenotypes that are indicative of breast cancer initiation and progression. Furthermore, the differential and enrichment analyses of transcriptomic data corroborated with the correlations found between ligands and signaling proteins by the NTF-based model.

Author summaryBreast cancer is the most common malignancy, which has become the dominant cause of cancer-relevant death in women worldwide. Breast cancer comprises not only tumor cells but also epigenetic alterations in the surrounding microenvironment (ME). Increasing evidence shows that aberrant epigenetic marks are present in cells of the ME, contributing to cancer initiation, growth, progression, invasion, and metastasis. As a result, epigenetic ME responses are key indicators of the therapeutic efficacy of various clinical treatments. Due to the importance of epigenetic ME responses in various cancer cellular activities, recent years have seen an increasing interest in developing therapies targeting specific epigenetic biomarkers in the tumor microenvironment (TME).

However, communications among different biomolecules such as growth-promoting ligands, signaling proteins, and epigenetic marks in TME are complex. How their interactions affect various cellular behaviors causing cancer initiation, growth and progression are not well understood. In this study, we focus on the interaction mechanisms among ligands, proteins, and histone modifications, aiming to identify likely biomarkers and the onset of tumorigenesis through computational modeling. The findings from our study will help identify potential biomarkers for developing epigenetic-directed breast cancer therapies in the future.

category: cancer biology


title: Neuroprotective mechanisms of red clover and soy isoflavones in Parkinson's disease models

abstract:
Parkinsons disease (PD) is a neurodegenerative disorder characterized by nigrostriatal degeneration and the spreading of aggregated forms of the presynaptic protein -synuclein (aSyn) throughout the brain. PD patients are currently only treated with symptomatic therapies, and strategies to slow or stop the progressive neurodegeneration underlying the diseases motor and cognitive symptoms are greatly needed. The time between the first neurobiochemical alterations and the initial presentation of symptoms is thought to span several years, and early neuroprotective dietary interventions could delay the disease onset or slow PD progression. In this study, we characterized the neuroprotective effects of isoflavones, a class of dietary polyphenols found in soy products and in the medicinal plant red clover (Trifolium pratense). We found that isoflavone-rich extracts and individual isoflavones rescued the loss of dopaminergic neurons and the shortening of neurites in primary mesencephalic cultures exposed to two PD-related insults, the environmental toxin rotenone and an adenovirus encoding the A53T aSyn mutant. The extracts and individual isoflavones also activated the Nrf2-mediated antioxidant response in astrocytes via a mechanism involving inhibition of the ubiquitin-proteasome system, and they alleviated deficits in mitochondrial respiration. Furthermore, an isoflavone-enriched soy extract reduced motor dysfunction exhibited by rats lesioned with the PD-related neurotoxin 6-OHDA. These findings suggest that plant-derived isoflavones could serve as dietary supplements to delay PD onset in at-risk individuals and mitigate neurodegeneration in the brains of patients.

Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=167 HEIGHT=200 SRC="FIGDIR/small/391268v3_ufig1.gif" ALT="Figure 1">
View larger version (40K):
org.highwire.dtl.DTLVardef@14446dcorg.highwire.dtl.DTLVardef@1884a7borg.highwire.dtl.DTLVardef@d1ebaborg.highwire.dtl.DTLVardef@1c744b1_HPS_FORMAT_FIGEXP  M_FIG The isoflavone-rich extracts red clover and soy and the individual isoflavones daidzein and equol protect neuronal cultures against environmental and genetic triggers of Parkinsons disease, and rescue motor deficits in rats exposed to the neurotoxin 6-OHDA.

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title: Humans optimally anticipate and compensate for an uneven step during walking

abstract: The simple task of walking up a sidewalk curb is actually a dynamic prediction task. The curb is a disturbance that causes a loss of momentum, to be anticipated and compensated for. For example, the compensation might regain momentum and ensure undisturbed time of arrival. But without a selection criterion, there are infinite possible strategies. Here we show that humans compensate with an anticipatory pattern of forward speed adjustments, with a criterion of minimizing mechanical energy input. This is predicted by optimal control for a simple model of walking dynamics, with each legs push-off work as input. Optimization predicts a tri-phasic trajectory of speed (and thus momentum) adjustments, including an anticipatory, feedforward phase. In experiment, human subjects successfully regain time relative to undisturbed walking, with the predicted tri-phasic trajectory. They also scale the pattern with up- or down-steps, and inversely with average speed, as also predicted by model. Humans can reason about the dynamics of walking to plan anticipatory and economical control, even with a sidewalk curb in the way.

category: bioengineering


title: Spatiotemporal analysis of glioma heterogeneity reveals Col1A1 as an actionable 1 target to disrupt tumor mesenchymal differentiation, invasion and malignancy

abstract: Intra-tumoral heterogeneity and diffuse infiltration are hallmarks of glioblastoma that challenge treatment efficacy. However, the mechanisms that set up both tumor heterogeneity and invasion remain poorly understood. Herein, we present a comprehensive spatiotemporal study that aligns distinctive intra-tumoral histopathological structures, oncostreams, with dynamic properties and a unique, actionable, spatial transcriptomic signature. Oncostreams are dynamic multicellular fascicles of spindle-like and aligned cells with mesenchymal properties, detected using ex vivo explants and in vivo intravital imaging. Their density correlates with tumor aggressiveness in genetically engineered mouse glioma models, and high-grade human gliomas. Oncostreams facilitate the intra-tumoral distribution of tumoral and non-tumoral cells, and the invasion of the normal brain. These fascicles are defined by a specific molecular signature that regulates their organization and function. Oncostreams structure and function depend on overexpression of COL1A1. COL1A1 is a central gene in the dynamic organization of glioma mesenchymal transformation, and a powerful regulator of glioma malignant behavior. Inhibition of COL1A1 eliminated oncostreams, reprogramed the malignant histopathological phenotype, reduced expression of the mesenchymal associated genes, induced changes in the tumor microenvironment and prolonged animal survival. Oncostreams represent a novel pathological marker of potential value for diagnosis, prognosis, and treatment.


title: RUNX1 controls the dynamics of cell cycle entry of naive resting B cells by regulating expression of cell cycle and immunomodulatory genes in response to BCR stimulation

abstract: RUNX1 is a transcription factor that plays key roles in haematopoietic development and in adult haematopoiesis and lymphopoiesis. Here we report that RUNX1 is also involved in controlling the dynamics of cell cycle entry of naive resting B cells in response to stimulation of the B cell receptor (BCR). Conditional knockout of Runx1 in mouse resting B cells resulted in accelerated entry of the cells into S-phase following BCR engagement. Our results indicate that Runx1 regulates the cyclin D2 (Ccnd2) gene, the immediate early genes, Fosl2, Atf3 and Egr2, and the Notch effector Rbpj, in B cells, reducing the rate at which transcription of these genes increases following BCR stimulation. RUNX1 interacts with the chromatin remodeller SRCAP, recruiting it to promoter and enhancer regions of the Ccnd2 gene. BCR-mediated activation triggers switching between binding of RUNX1 and its paralog RUNX3 and between SRCAP and the SWI/SNF remodelling complex member BRG1. We also find that RUNX1 regulates expression of a number of immunomodulatory genes in resting B cells. These include the interferon receptor subunit gene Ifnar1, which is upregulated in B cells from lupus patients, the Ptpn22 gene, which has been identified as a major lupus risk allele, and the Lrrk2 gene, which is mutated in familial Parkinsons disease. The hyperresponsiveness of the Runx1 knockout B cells to antigen stimulation and its role in regulating a suite of genes that are known to be associated with autoimmune disease suggest that RUNX1 is a major regulator of B cell tolerance and autoimmunity.


title: Decision value signals in the ventromedial prefrontal cortex andmotivational and hedonic symptoms across mood and psychotic disorders

abstract: Deficits in motivation and pleasure are common across many psychiatric disorders, and manifest as symptoms of amotivation and anhedonia, which are prominent features of both mood and psychotic disorders. Here we provide evidence for a shared transdiagnostic mechanism underlying impairments in motivation and pleasure across major depression, bipolar disorder, and schizophrenia. We found that value signals in the ventromedial prefrontal cortex (vmPFC) during decision-making were dampened in individuals with greater motivational and hedonic deficits, regardless of the primary diagnosis. This relationship remained significant while controlling for diagnosis-specific symptoms of mood and psychosis, such as depression as well as positive and negative symptoms. Our results demonstrate that dysfunction in the vmPFC during value-based decision-making is specifically linked to motivational and hedonic impairments across various psychiatric conditions. These findings provide a quantitative neural target for the potential development of novel treatments for amotivation and anhedonia.


title: Coherent natural scene structure facilitates the extraction of task-relevant object information in visual cortex

abstract: Looking for objects within complex natural environments is a task everybody performs multiple times each day. In this study, we explore how the brain uses the typical composition of real-world environments to efficiently solve this task. We recorded fMRI activity while participants performed two different categorization tasks on natural scenes. In the object task, they indicated whether the scene contained a person or a car, while in the scene task, they indicated whether the scene depicted an urban or a rural environment. Critically, each scene was presented in an "intact" way, preserving its coherent structure, or in a "jumbled" way, with information swapped across quadrants. In both tasks, participants categorization was more accurate and faster for intact scenes. These behavioral benefits were accompanied by stronger responses to intact than to jumbled scenes across high-level visual cortex. To track the amount of object information in visual cortex, we correlated multi-voxel response patterns during the two categorization tasks with response patterns evoked by people and cars in isolation. We found that object information in object- and body-selective cortex was enhanced when the object was embedded in an intact, rather than a jumbled scene. However, this enhancement was only found in the object task: When participants instead categorized the scenes, object information did not differ between intact and jumbled scenes. Together, these results indicate that coherent scene structure facilitates the extraction of object information in a task-dependent way, suggesting that interactions between the object and scene processing pathways adaptively support behavioral goals.


title: Experimental evolution-driven identification of Arabidopsis rhizosphere competence genes in Pseudomonas protegens

abstract:
Beneficial plant root-associated microorganisms carry out a range of functions that are essential for plant performance. Establishment of a bacterium on plant roots, however, requires overcoming several challenges, including competition with neighboring microorganisms and host immunity. Forward and reverse genetics has led to the identification of mechanisms that are used by beneficial microorganisms to overcome these challenges such as the production of iron-chelating compounds, the formation of strong biofilms, or the concealment of characteristic microbial molecular patterns that trigger the host immune system. However, how such mechanisms arose from an evolutionary perspective is much less understood. To study bacterial adaptation in the rhizosphere, we employed experimental evolution to track the physiological and genetic dynamics of root-dwelling Pseudomonas protegens in the Arabidopsis thaliana rhizosphere under axenic conditions. This simplified binary one plant-one bacterium system allows for the amplification of key adaptive mechanisms for bacterial rhizosphere colonization. We identified 35 mutations, including single-nucleotide polymorphisms, insertions, and deletions, distributed over 28 genes. We found that mutations in genes encoding global regulators, and in genes for siderophore production, cell surface decoration, attachment, and motility accumulated in parallel, underlining that bacterial adaptation to the rhizosphere follows multiple strategies. Notably, we observed that motility increased in parallel across multiple independent evolutionary lines. Altogether these results underscore the strength of experimental evolution to identify key genes, pathways, and processes for bacterial rhizosphere colonization, and a methodology for the development of elite beneficial microorganisms with enhanced root-colonizing capacities that can support sustainable agriculture in the future.

ImportanceBeneficial root-associated microorganisms carry out many functions that are essential for plant performance. Establishment of a bacterium on plant roots, however, requires overcoming many challenges. Previously, diverse mechanisms that are used by beneficial microorganisms to overcome these challenges were identified. However, how such mechanisms have developed from an evolutionary perspective is much less understood. Here, we employed experimental evolution to track the evolutionary dynamics of a root-dwelling pseudomonad on the root of Arabidopsis. We find that mutations in global regulators, as well as in genes for siderophore production, cell surface decoration, attachment, and motility accumulate in parallel, underlining these strategies for bacterial adaptation to the rhizosphere. We identified 35 mutations distributed over 28 genes. Altogether our results demonstrate the power of experimental evolution to identify key pathways for rhizosphere colonization and a methodology for the development of elite beneficial microorganisms that can support sustainable agriculture.


title: Temperature effects on individual-level parasitism translate into predictable effects on parasitism in populations

abstract: Parasitism is expected to change in a warmer future, but whether warming leads to substantial increases in parasitism remains unclear. Understanding how warming effects on parasitism in individual hosts (e.g., parasite load) translate to effects on population-level parasitism (e.g., prevalence, R0) remains a major knowledge gap. We analyzed the temperature dependence of parasitism at both host and population levels in thirteen empirical vector-borne host-parasite systems and found a strong, significant positive correlation between the thermal optima of individual- and population-level parasitism. We also found a significant, positive correlation in eleven environmentally-transmitted parasite systems, though several of these systems exhibited thermal optima >5{o}C apart between individual and population levels. Similarly, parasitism thermal optima were close to host performance thermal optima in vector-borne systems but not in environmentally-transmitted systems. We then adapted and simulated simple models for both transmission modes and found a similar pattern to the empirical systems: thermal optima in vector-borne systems were more strongly correlated across scales compared to environmentally-transmitted systems. Generally, our results suggest that information on the temperature-dependence, and specifically the thermal optimum, at either the individual- or population-level should provide a useful--though not quantitatively exact--baseline for predicting temperature dependence at the other level, especially in vector-borne parasite systems. Environmentally-transmitted parasitism may operate by a different set of rules, in which temperature-dependence is decoupled in some systems, requiring the need for trait-based studies of temperature-dependence at individual and population levels.


title: Scaling effects of temperature on parasitism from individuals to host-parasite systems


title: Epigenetic scores for the circulating proteome replicate protein-disease predictions as tools for biomarker discovery

abstract: Protein biomarkers have been identified across many age-related morbidities. However, characterising epigenetic influences could further inform disease predictions. Here, we leverage epigenome-wide data to study links between the DNAm signatures of the circulating proteome and incident diseases. Using data from four cohorts, we trained and tested epigenetic scores (EpiScores) for 953 plasma proteins, identifying 109 scores that explained between 1% and 58% of the variance in protein levels after adjusting for known protein quantitative trait loci (pQTL) genetic effects. By projecting these EpiScores into an independent sample, (Generation Scotland; n=9,537) and relating them to incident morbidities over a follow-up of 14 years, we uncovered 137 EpiScore - disease associations. These associations were largely independent of immune cell proportions, common lifestyle and health factors and biological aging. Notably, we found that our diabetes-associated EpiScores highlighted previous top biomarker associations from proteome-wide assessments of diabetes. These EpiScores for protein levels can therefore be a valuable resource for disease prediction and risk stratification.


title: Epigenetic scores for the circulating proteome as tools for disease prediction