Using machine learning to design adeno-associated virus capsids with high likelihood of viral assembly We study the application of machine learning in designing adeno-associated virus (AAV) capsid sequences with high likelihood of viral assembly, i.e. capsid viability. Specifically, we design and implement Origami, a model-based optimization algorithm, to identify highly viable capsid sequences within the vast space of 2033 possibilities. Our evaluation shows that Origami performs well in terms of optimality and diversity of model-designed sequences. Moreover, these sequences are ranked according to their viability score. This helps designing experiments given budget constraint.
Parameterized syncmer schemes improve long-read mapping MotivationSequencing long reads presents novel challenges to mapping. One such challenge is low sequence similarity between the reads and the reference, due to high sequencing error and mutation rates. This occurs, e.g., in a cancer tumor, or due to differences between strains of viruses or bacteria. A key idea in mapping algorithms is to sketch sequences with their minimizers. Recently, syncmers were introduced as an alternative sketching method that is more robust to mutations and sequencing errors.

ResultsWe introduce parameterized syncmer schemes, a generalization of syncmers, and provide a theoretical analysis for multi-parameter schemes. By combining these schemes with downsampling or minimizers we can achieve any desired compression and window guarantee. We implemented the use of parameterized syncmer schemes in the popular minimap2 and Winnowmap2 mappers. In tests on simulated and real long read data from a variety of genomes, the syncmer-based algorithms, with scheme parameters selected on the basis of the theoretical analysis, reduced unmapped reads by 20-60% at high compression while usually using less memory. The advantage was more pronounced at low sequence identity. At sequence identity of 75% and medium compression, syncmer-minimap had only 37% as many unmapped reads, and 8% fewer of the reads that did map were incorrectly mapped. Even at lower compression and error rates, parameterized syncmer based mapping mapped more reads than the original minimizer-based mappers as well as mappers using the original syncmer schemes. We conclude that using parameterized syncmer schemes can improve mapping of long reads in a wide range of settings.

Availabilityhttps://github.com/Shamir-Lab/syncmer_mapping

Supplementary informationSupplementary data are available at https://github.com/Shamir-Lab/syncmer_mapping.

Author summaryPopular long read mappers use minimizers, the minimal hashed k-mers from overlapping windows, as alignment seeds. Recent work showed that syncmers, which select a fixed set of k-mers as seeds, are more likely to be conserved under errors or mutations than minimizers, making them potentially useful for mapping error-prone long reads. We introduce a framework for creating syncmers, that we call parameterized syncmer schemes, which generalize those introduced so far, and provide a theoretical analysis of their properties. We implemented parameterized syncmer schemes in the minimap2 and Winnowmap2 long read mappers. Using parameters selected on the basis of our theoretical analysis we demonstrate improved mapping performance, with fewer unmapped and incorrectly mapped reads on a variety of simulated and real datasets. The improvements are consistent across a broad range of compression rates and sequence identities, with the most significant improvements for lower sequence identity (high error or mutation rates) and high compression.
Hidden dynamics of human proteasome autoregulation during protein degradation The cellular functions are executed by macromolecular complexes in nonequilibrium dynamic processes, which exhibit a vast diversity of conformational states. Solving conformational continuum of important complexes at atomic level remains a key challenge in the methodology of computational biophysics. Here we introduce a deep-learning framework, named AlphaCryo4D, which enables atomic-level cryogenic electron microscopy reconstructions of nonequilibrium conformational continuum. AlphaCryo4D integrates 3D deep residual learning with manifold embedding of energy landscapes, which simultaneously improves 3D classification accuracy and reconstruction resolution via an energy-based particle-voting algorithm. Applications of this methodology to six experimental datasets demonstrated its generality in breaking resolution barrier of visualizing dynamic components of functional complexes, in choreographing continuous inter-subunit motions and in exploring their  hidden conformational space. Importantly, AlphaCryo4D identified 64 conformers of the substrate-bound human 26S proteasome and reconstituted single-nucleotide-exchange dynamics of proteasomal AAA-ATPase motor during translocation initiation, which together illuminates a grand hierarchical allostery for proteasome autoregulation. A nickase Cas9 gene-drive system promotes super-Mendelian inheritance in Drosophila CRISPR-based gene-drive systems have been proposed for managing insect populations, including disease-transmitting mosquitoes, due to their ability to bias their inheritance towards super-Mendelian rates (>50%). Current technologies employ a Cas9 that introduces DNA double-strand breaks into the opposing wildtype allele to replace it with a copy of the gene drive allele via DNA homology-directed repair. Yet, the use of different Cas9s versions is unexplored, and alternative approaches could increase the available toolkit for gene-drive designs. Here, we report a novel gene-drive approach that relies on Cas9 nickases that generate staggered paired nicks in DNA to propagate the engineered gene-drive cassette. We show that generating 5 overhangs in the system yields efficient allelic conversion. The nickase gene-drive arrangement produces large, stereotyped deletions that are advantageous for targeting essential genes. Indeed, our nickase approach should expand the repertoire for gene-drive designs aimed at applications in mosquitoes and beyond. Microbial colonization of tannin-rich tropical plants: interplay between degradability, methane production and tannin disappearance in the rumen AO_SCPLOWBSTRACTC_SCPLOWCondensed tannins in plants are found free and attached to protein and fibre but it is not known whether these fractions influence rumen degradation and microbial colonization. This study explored the rumen degradation of tropical tannins-rich plants and the relationship between condensed tannins fractions disappearance and microbial communities colonising plant particles. Leaves from Calliandra calothyrsus, Gliricidia sepium, and Leucaena leucocephala, pods from Acacia nilotica and the leaves of two agricultural by-products: Manihot esculenta and Musa spp. were incubated in situ in the rumen of dairy cows. An in vitro approach was also used to assess the effects of these plants on rumen fermentation parameters. All plants contained more than 100 g/kg of condensed tannins with a large proportion (32 to 61%) bound to proteins. Calliandra calothyrsus had the highest concentration of condensed tannins at 361 g/kg, whereas Acacia nilotica was particularly rich in hydrolysable tannins (350 g/kg). Hydrolysable and free condensed tannins from all plants completely disappeared after 24 h incubation in the rumen. Disappearance of protein-bound condensed tannins was variable with values ranging from 93% for Gliricidia sepium to 21% for Acacia nilotica. In contrast, fibre-bound condensed tannins disappearance averaged ~82% and did not vary between plants. Disappearance of bound fractions of condensed tannins was not associated with degradability of plant fractions. The presence of tannins interfered with the microbial colonisation of plants. Each plant had distinct bacterial and archaeal communities after 3 and 12 h of incubation in the rumen and distinct protozoal communities at 3 h. Adherent communities in tannin-rich plants had a lower relative abundance of fibrolytic microbes, notably Fibrobacter spp. Whereas, archaea diversity was reduced in high tannin-containing Calliandra calothyrsus and Acacia nilotica at 12 h of incubation. Concurrently, in vitro methane production was lower for Calliandra calothyrsus, Acacia nilotica and Leucaena leucocephala although for the latter total volatile fatty acids production was not affected and was similar to control. Here we show that the total amount of hydrolysable and condensed tannins contained in a plant govern the interaction with rumen microbes affecting degradability and fermentation. The effect of protein- and fibre-bound condensed tannins on degradability is less important. The DEAD box RNA helicase DDX42 is an intrinsic inhibitor of positive-strand RNA viruses Genome-wide screens are powerful approaches to unravel new regulators of viral infections. Here, we used a CRISPR/Cas9 screen to reveal new HIV-1 inhibitors. This approach led us to identify the RNA helicase DDX42 as an intrinsic antiviral inhibitor. DDX42 was previously described as a non-processive helicase, able to bind RNA secondary structures such as G-quadruplexes, with no clearly defined function ascribed. Our data show that depletion of endogenous DDX42 significantly increased HIV-1 DNA accumulation and infection in cell lines and primary cells. DDX42 overexpression inhibited HIV-1, whereas a dominant-negative mutant increased infection. Importantly, DDX42 also restricted retrotransposition of LINE-1, infection with other retroviruses and positive-strand RNA viruses, including CHIKV and SARS-CoV-2. However, DDX42 did not inhibit infection with three negative-strand RNA viruses, arguing against a general, unspecific effect on target cells, which was confirmed by RNA-seq analysis. DDX42 was found in the vicinity of viral elements by proximity ligation assays, and cross-linking RNA immunoprecipitation confirmed a specific interaction of DDX42 with RNAs from sensitive viruses. This strongly suggested a direct mode of action of DDX42 on viral ribonucleoprotein complexes. Taken together, our results show for the first time a new and important role of DDX42 in intrinsic antiviral immunity. Nanoscale ligand density modulates gap junction intercellular communication of cell condensates during chondrogenesis To unveil the influence of cell-matrix adhesions in the establishment of gap junction intercellular communication (GJIC) during cell condensation in chondrogenesis.

Materials & MethodsPreviously developed nanopatterns of the cell adhesive ligand arginine-glycine-aspartic acid (RGD) were used as cell culture substrates to control cell adhesion at the nanoscale. We conducted in vitro chondrogenesis of mesenchymal stem cells on the nanopatterns. We evaluated cohesion and GJIC in cell condensates.

ResultsMechanical stability and GJIC are enhanced by a nanopattern configuration in which 90% of the surface area presents adhesion sites separated less than 70 nm, thus providing an onset for cell signaling.

ConclusionCell-matrix adhesions regulate GJIC of mesenchymal cell condensates during in vitro chondrogenesis from a threshold configuration at the nanoscale. TeamTree analysis: a new approach to evaluate scientific production Advances in science and technology depend on the work of research teams and the publication of results through peer-reviewed articles representing a growing socio-economic resource. Current methods to mine the scientific literature regarding a field of interest focus on content, but the workforce credited by authorship remains largely unexplored, and appropriate measures of scientific production are debated. Here, a new bibliometric approach named TeamTree analysis is introduced that visualizes the development and composition of the workforce driving a field. A new citation-independent measure that scales with the H index estimates impact based on publication record, genealogical ties and collaborative connections. This author-centered approach complements existing tools to mine the scientific literature and to evaluate research across disciplines. A Practical Alzheimer Disease Classifier via Brain Imaging-Based Deep Learning on 85,721 Samples Beyond detecting brain lesions or tumors, comparatively little success has been attained in identifying brain disorders such as Alzheimers disease (AD), based on magnetic resonance imaging (MRI). Many machine learning algorithms to detect AD have been trained using limited training data, meaning they often generalize poorly when applied to scans from previously unseen populations. Here we aimed to build a practical brain imaging-based AD diagnostic classifier using deep learning/transfer learning on dataset of unprecedented size and diversity. We pooled MRI data from more than 217 sites/scanners to constitute the largest brain MRI sample to date (85,721 scans from 50,876 participants). Next, we applied a state-of-the-art deep convolutional neural network, Inception-ResNet-V2, to build a sex classifier with high generalization capability. The sex classifier achieved 94.9% accuracy and served as a base model in transfer learning for the objective diagnosis of AD. After transfer learning, the model fine-tuned for AD classification achieved 91.3% accuracy in leave-sites-out cross-validation on the Alzheimers Disease Neuroimaging Initiative (ADNI) dataset and 94.2%/87.9% accuracy for direct tests on two unseen independent datasets (AIBL/OASIS). When this AD classifier was tested on brain images from unseen mild cognitive impairment (MCI) patients, MCI patients who finally converted to AD were 3 times more likely to be predicted as AD than MCI patients who did not convert (65.2% vs 20.6%). Predicted scores from the AD classifier showed significant correlations with illness severity. In sum, the proposed AD classifier could offer a medical-grade biomarker that could be integrated into AD diagnostic practice. Our trained model, code and preprocessed data are freely available to the research community. Biomechanical control of meiotic chromosomal bouquet and germ cell morphogenesis by the zygotene cilium The hallmark of meiosis is chromosomal pairing and synapsis via synaptonemal complexes, but chromosomal pairing also depends on cytoplasmic counterparts that tether and rotate telomeres on the nuclear envelope. Telomeres slide on perinuclear microtubules, shuffling chromosomes and mechanically driving their homology searches. Pull of telomeres towards the centrosome drives formation of the "zygotene chromosomal bouquet". These telomere dynamics are essential for pairing and fertility, and the bouquet, discovered in 1900, is universally conserved. Nevertheless, how cytoplasmic counterparts of bouquet formation are mechanically regulated has remained enigmatic. Here, we report the "zygotene cilium" - a previously unrecognized cilium, in oocytes. We show in zebrafish that this cilium specifically connects to the bouquet centrosome, constituting a cable system of the cytoplasmic bouquet machinery. Furthermore, zygotene cilia extend throughout the germline cyst, a conserved germ cell organization. Using multiple ciliary mutants and laser-induced excision, we demonstrate that the zygotene cilium is essential for chromosomal bouquet and synaptonemal complex formation, germ cell morphogenesis, ovarian development and fertility. Mechanistically, we provide evidence that the cilium functions at least partly via anchoring the bouquet centrosome in order to counterbalance telomere rotation and pulling. We also show that the zygotene cilium is conserved in both male and female meiosis in zebrafish, as well as in mammals. Our work uncovers the novel concept of a cilium as a critical player in meiosis and sheds new light on reproduction phenotypes in ciliopathies. We propose a cellular paradigm that cilia can control chromosomal dynamics. Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. Development and Characterization of PAR-Trackers: New Tools for Detecting Poly(ADP-ribose) In Vitro and In Vivo AO_SCPLOWBSTRACTC_SCPLOWADP-ribosylation (ADPRylation) is a reversible post-translation modification resulting in the covalent attachment of ADP-ribose (ADPR) moieties on substrate proteins. Naturally-occurring protein motifs and domains, including WWEs, PBZs, and macrodomains, act as "readers" for protein-linked ADPR. Although recombinant, antibody-like ADPR detection reagents containing these readers have facilitated the detection of ADPR, they are limited in their ability to capture the dynamic nature of ADPRylation. Herein, we describe and characterize a set of poly(ADP-ribose) (PAR) Trackers (PAR-Ts) - optimized dimerization-dependent or split-protein reassembly PAR sensors in which a naturally occurring PAR binding domain, WWE, was fused to both halves of dimerization-dependent GFP (ddGFP) or split Nano Luciferase (NanoLuc), respectively. We demonstrate that these new tools allow the detection and quantification of PAR levels in extracts, living cells, and living tissues with greater sensitivity, as well as temporal and spatial precision. Importantly, these sensors detect changes in cellular ADPR levels in response to physiological cues (e.g., hormone-dependent induction of adipogenesis without DNA damage), as well as xenograft tumor tissues in living mice. Our results indicate that PAR Trackers have broad utility for detecting ADPR in many different experimental and biological systems. Medium-throughput zebrafish optogenetic platform identifies deficits in subsequent neural activity following brief early exposure to cannabidiol and Δ-9-tetrahydrocannabinol In the light of legislative changes and the widespread use of cannabis as a recreational and medicinal drug, delayed effects of cannabis upon brief exposure during embryonic development are of high interest as early pregnancies often go undetected. Here, zebrafish embryos were exposed to cannabidiol (CBD) and {Delta}-9-tetrahydrocannabinol l (THC) until the end of gastrulation (1-10 hours post-fertilization) and analyzed later in development (4-5 days post-fertilization). In order to measure neural activity, we implemented CaMPARI (Calcium-Modulated Photoactivatable Ratiometric Integrator) and optimized the protocol for a 96-well format complemented by locomotor analysis. Our results revealed that neural activity was decreased by CBD more than THC. At higher doses, both cannabinoids could dramatically reduce neural activity and locomotor activity. Interestingly, the decrease was more pronounced when CBD and THC were combined. At the receptor level, CBD-mediated reduction of locomotor activity was partially prevented using cannabinoid type 1 and 2 receptor inhibitors. Overall, we report that CBD toxicity occurs via two cannabinoid receptors and is synergistically enhanced by THC exposure to negatively impact neural activity late in larval development. Future studies are warranted to reveal other cannabinoids and receptors involved in this pathway to understand the subsequent health implications of cannabis consumption on fetal development. Rapid evolution of seed dormancy during sunflower de-domestication Hybridization between crops and their wild relatives may promote the evolution of de-domesticated (feral) weeds. Wild sunflower (Helianthus annuus L.) is typically found in ruderal environments, but crop-wild hybridization may facilitate the evolution of weedy populations. Using one crop-specific mitochondrial marker (CMS-PET1) and 14 nuclear SSR markers, we studied the origin and genetic diversity of a recently discovered weedy population of sunflower (named BRW). Then, using a resurrection approach, we tested for rapid evolution of weedy traits (seed dormancy, herbicide resistance, and competitive ability) by sampling weedy and wild populations 10 years apart (2007 and 2017). All the weedy plants present the CMS-PET1 cytotype, confirming their feral origin. At the nuclear markers, BRW showed higher genetic diversity than the cultivated lines and low differentiation with one wild population, suggesting that wild hybridization increased their genetic diversity. We found support for rapid evolution towards higher seed dormancy, but not for higher competitive ability or herbicide resistance. Our results highlight the importance of seed dormancy during the earliest stages of adaptation and show that crop-wild hybrids can evolve quickly in agricultural environments. From fitting the average to fitting the individual: A cautionary tale for mathematicalmodelers An outstanding challenge in the clinical care of cancer is moving from a one-size-fits-all approach that relies on population-level statistics towards personalized therapeutic design. Mathematical modeling is a powerful tool in treatment personalization, as it allows for the incorporation of patient-specific data so that treatment can be tailor-designed to the individual. Herein, we work with a mathematical model of murine cancer immunotherapy that has been previously-validated against the average of an experimental dataset. We ask the question: what happens if we try to use this same model to perform personalized fits, and therefore make individualized treatment recommendations? Typically, this would be done by choosing a single fitting methodology, and a single cost function, identifying the individualized best-fit parameters, and extrapolating from there to make personalized treatment recommendations. Our analyses show the potentially problematic nature of this approach, as predicted personalized treatment response proved to be sensitive to the fitting methodology utilized. We also demonstrate how a small amount of the right additional experimental measurements could go a long way to improve consistency in personalized fits. Finally, we show how quantifying the robustness of the average response could also help improve confidence in personalized treatment recommendations.

Author summaryAs we enter the era of healthcare where personalized medicine becomes a more common approach to treating cancer patients, harnessing the power of mathematical models will only become more essential. Using a preclinical dataset on cancer immunotherapy, we explore the challenges and limitations that arise when trying to move from fitting and making predictions for the population-level average, to fitting and making predictions for an individual. We find that the standard of approach of picking a single fitting methodology and a single cost function may end up having limited predictive value when applied to individual data. We also show how having a small amount of the right additional experimental data, and establishing the robustness of average treatment response, can help improve confidence in personalized model predictions. Cooperation of two opposite flagella allows high-speed swimming and active turning in zoospores Phytophthora species cause diseases in a large variety of plants and represent a serious agricultural threat, leading, every year, to multibillion dollar losses. Infection occurs when these biflagellated zoospores move across the soil at their characteristic high speed and reach the roots of a host plant. Despite the relevance of zoospore spreading in the epidemics of plant diseases, characteristics of individual swimming of zoospores have not been fully investigated. It remains unknown about the characteristics of two opposite beating flagella during translation and turning, and the roles of each flagellum on zoospore swimming. Here, combining experiments and modeling, we show how these two flagella contribute to generate thrust when beating together, and identify the mastigonemes-attached anterior flagellum as the main source of thrust. Furthermore, we find that turning involves a complex active process, in which the posterior flagellum temporarily stops, while the anterior flagellum keeps on beating and changes its pattern from sinusoidal waves to power and recovery strokes, similar to Chlamydomonass breaststroke, to reorient its body to a new direction. Our study is a fundamental step towards a better understanding of the spreading of plant pathogens motile forms, and shows that the motility pattern of these biflagellated zoospores represents a distinct eukaryotic version of the celebrated "run-and-tumble" motility class exhibited by peritrichous bacteria. Effect of sublethal prenatal endotoxaemia on murine placental transport systems and lipid homeostasis Infection alters the expression of transporters that mediate the placental exchange of xenobiotics, lipids and cytokines. We hypothesized that lipopolysaccharide (LPS) modifies the expression of placental transport systems and lipid homeostasis. LPS (150 g/kg; i.p.) treatments were administered for 4 h or 24 h, animals were euthanized at gestational days (GD) 15.5 or 18.5, and maternal blood, foetuses and placentae were collected. Increased rates of foetal demise were observed at GD15.5 following LPS treatment, whereas at GD18.5, high rates of early labour occurred and were associated with distinct proinflammatory responses. LPS did not alter ABC transporter mRNA expression but decreased Fabppm at GD15.5 (LPS-4 h) and increased Fat/Cd36 lipid transporter mRNA at GD18.5 (LPS-4 h). At the protein level, breast cancer-related protein (BCRP) and Abcg1 levels were decreased in the placental labyrinth zone (Lz) at GD15.5, whereas P-glycoprotein (P-gp) and Bcrp Lz-immunostaining was decreased at GD18.5. In the placental junctional zone (Jz), P-gp, Bcrp and Abcg1 levels were higher at GD18.5. Specific maternal plasma and placental changes in triacylglycerol, free fatty acid, cholesterol, cholesterol ester and monoacylglycerol levels were detected in a gestational age-dependent manner. In conclusion, LPS-induced foetal death and early labour were associated with altered placental ABC and lipid transporter expression and deranged maternal plasma and placental lipid homeostasis. These changes likely modify foetal xenobiotic exposure and placental lipid exchange in cases of bacterial infection. Brain endothelial STING1 activation by Plasmodium-sequestered heme promotes cerebral malaria via type I IFN response. Cerebral malaria (CM) is a life-threatening form of Plasmodium falciparum infection caused by brain inflammation. Brain endothelium dysfunction is a hallmark of CM pathology, which is also associated with the activation of the type I interferon (IFN) inflammatory pathway. The molecular triggers and sensors eliciting brain type I IFN cellular responses during CM remain largely unknown. We herein identified the stimulator of interferon response cGAMP interactor 1 (STING1) as the key innate immune sensor that induces Ifn{beta}1 transcription in the brain of mice infected with Plasmodium berghei (Pba). This STING1/IFN{beta}-mediated response increases brain CXCL10 governing the extent of brain leucocyte infiltration and blood-brain barrier (BBB) breakdown, and determining CM lethality. The critical role of brain endothelial cells (BECs) in fueling type I IFN-driven brain inflammation was demonstrated in brain endothelial-specific IFN{beta}-reporter and STING1-deficient Pba-infected mice, which are significantly protected from CM lethality. Moreover, extracellular particles (EPs) released from Pba-infected erythrocytes activated STING1-dependent type I IFN response in BECs, a response requiring intracellular acidification. Fractionation of the EPs enabled us to identify a defined fraction carrying hemoglobin degradation remnants that activates STING1/IFN{beta} in the brain endothelium, a process correlated with heme content. Notably, stimulation of STING1-deficient BECs with heme, docking experiments and in vitro binding assays unveiled that heme is a putative STING1 ligand. This work shows that heme resultant from the parasite heterotrophic activity operates as an alarmin triggering brain endothelial inflammatory responses via STING1/IFN{beta}/CXCL10 axis crucial to CM pathogenesis and lethality.

SignificanceCM results from loss of blood-brain endothelial barrier function caused by unrestrained inflammatory response in the natural course of infection by Plasmodium parasites. However, the role of brain endothelium in triggering inflammatory mechanisms is still undetermined. We found that the innate immune sensor STING1 is crucial for production of IFN{beta} in brain endothelial cells in Plasmodium-infected mice. This in turn stimulates CXCL10-mediated recruitment of leukocytes and subsequent brain inflammation and tissue damage. We identified within extracellular particles released from Plasmodium-infected erythrocytes, a fraction containing products of hemoglobin degradation, namely heme, which we show can bind STING1. Our results unravel a new angle of CM pathogenesis: heme contained in particles triggers the STING/IFN{beta}/CXCL10 axis in brain endothelial cells. Predicting gene regulatory networks from multi-omics to link genetic risk variants and neuroimmunology to Alzheimers disease phenotypes BackgroundGenome-wide association studies have found many genetic risk variants associated with Alzheimers disease (AD). However, how these risk variants affect deeper phenotypes such as disease progression and immune response remains elusive. Also, our understanding of cellular and molecular mechanisms from disease risk variants to various phenotypes is still limited. To address these problems, we performed an integrative multi-omics analysis of genotype, transcriptomics, and epigenomics for revealing gene regulatory mechanisms from disease variants to AD phenotypes.

MethodFirst, given the population gene expression data of a cohort, we construct and cluster its gene co-expression network to identify gene co-expression modules for various AD phenotypes. Next, we predict transcription factors (TFs) regulating co-expressed genes and AD risk SNPs that interrupt TF binding sites on regulatory elements. Finally, we construct a gene regulatory network (GRN) linking SNPs, interrupted TFs, and regulatory elements to target genes and gene modules for each phenotype in the cohort. This network thus provides systematic insights into gene regulatory mechanisms from risk variants to AD phenotypes.

ResultsOur analysis predicted GRNs in three major AD-relevant regions: Hippocampus, Dorsolateral Prefrontal Cortex (DLPFC), Lateral Temporal Lobe (LTL). Comparative analyses revealed cross-region-conserved and region-specific GRNs, in which many immunological genes are present. For instance, SNPs rs13404184 and rs61068452 disrupt SPI1 binding and regulation of AD gene INPP5D in the Hippocampus and LTL. However, SNP rs117863556 interrupts bindings of REST to regulate GAB2 in DLPFC only. Driven by emerging neuroinflammation in AD, we used Covid-19 as a proxy to identify possible regulatory mechanisms for neuroimmunology in AD. To this end, we looked at the GRN subnetworks relating to genes from shared AD-Covid pathways. From those subnetworks, our machine learning analysis prioritized the AD-Covid genes for predicting Covid-19 severity. Decision Curve Analysis also validated our AD-Covid genes outperform known Covid-19 genes for classifying severe Covid-19 patients. This suggests AD-Covid genes along with linked SNPs can be potential novel biomarkers for neuroimmunology in AD. Finally, our results are open-source available as a comprehensive functional genomic map for AD, providing a deeper mechanistic understanding of the interplay among multi-omics, brain regions, gene functions like neuroimmunology, and phenotypes. Rho Kinase regulates neutrophil NET formation that is involved in UVB-induced skin inflammation ObjectiveUltraviolet B (UVB) is an important trigger of skin inflammation and lupus with leukocyte recruitment to inflamed skin. We recently reported the involvement of neutrophil NETosis in UVB-induced skin inflammation, and that NETotic nuclear envelope rupture is driven by PKC-mediated nuclear lamin B disassembly. To address the role of Actin cytoskeleton in NETosis, we investigated the effects of Rho kinase (ROCK) and its downstream actomyosin cytoskeletal networks on PKC nuclear translocation and NET formation, as well as their involvement in UVB-induced skin inflammation.

MethodsWe studied the dynamic changes of ROCK and actomyosin cytoskeletal networks during NETosis induction and their involvement in PKC nuclear translocation. Using mice with hematopoietic-specific ROCK1 deficiency, we investigated the effects of ROCK1 deficiency on NETosis, and its involvement in UVB-induced skin inflammation.

ResultsOur time course studies demonstrated the dynamic changes of actin polymerization and ROCK activation, support the role of actin cytoskeleton in nuclear translocation of cytosolic PKC in early stage of NETosis induction. Inhibition of actin polymerization or key molecules of the ROCK/MLCK/myosin pathway decreased PKC nuclear translocation and NET formation. Genetic deficiency of ROCK1, inhibited NETosis ex vivo and in vivo, decreased extracellular display of NET-associated IL-17A, TNF, IFN{gamma}, and IFN in inflamed skin, which were correlated with the ameliorated skin inflammation in UVB-irradiated mice with hematopoietic-specific ROCK1 deficiency.

ConclusionsROCK regulated NETosis through modulation of PKC nuclear translocation via actomyosin cytoskeletal networks in neutrophils. ROCK1 deficiency ameliorated UVB- induced skin inflammation by attenuation of NETosis and NET-associated cytokines. A variable-gain stochastic pooling motif mediates information transfer from receptor assemblies into NF-κB A myriad of inflammatory cytokines regulate signaling pathways to maintain cellular homeostasis. The IKK complex is an integration hub for cytokines that govern NF-{kappa}B signaling. In response to inflammation, IKK is activated through recruitment to receptor-associated protein assemblies. How and what information IKK complexes transmit about the milieu are open questions. Here we track dynamics of IKK complexes and nuclear NF-{kappa}B to identify upstream signaling features that determine same-cell responses. Experiments and modeling of single complexes reveals their size, number, and timing relays cytokine-specific information with feedback control that is independent of transcription. Our results provide evidence for variable-gain stochastic pooling, a noise-reducing motif that enables parsimonious and cytokine-specific information transfer. We propose that emergent properties of stochastic pooling are general principles of receptor signaling.

One Sentence SummaryA variable-gain stochastic pooling motif mediates robust and tunable information transmission from the extracellular milieu into the cell. "Neighbourhood watch" model: embryonic epiblast cells assess positional information in relation to their neighbours In many developing and regenerating systems, tissue pattern is established through gradients of informative morphogens, but we know little about how cells interpret these. Using experimental manipulation of early chick embryos including misexpression of an inducer (VG1 or ACTIVIN) and an inhibitor (BMP4), we test two alternative models for their ability to explain how the site of primitive streak formation is positioned relative to the rest of the embryo. In one model, cells read morphogen concentrations cell-autonomously. In the other, cells sense changes in morphogen status relative to their neighbourhood. We find that only the latter model can account for the experimental results, including some counter-intuitive predictions. This mechanism (which we name "neighbourhood watch" model) illuminates the classic "French Flag Problem" and how positional information is interpreted by a sheet of cells in a large developing system.

Summary statementIn a large developing system, the chick embryo before gastrulation, cells interpret gradients of positional signals relative to their neighbours to position the primitive streak, establishing bilateral symmetry. The Hippocampus uses cryptographic principles rather than plasticity to enable animals to secretly cache and retrieve their food For animals, the ability to hide and retrieve valuable information, such as the location of food, can mean the difference between life and death. Here, we propose that to achieve this, their brain uses spatial cells similarly to how we utilize encryption for data security. Some animals are able to cache hundreds of thousands of food items annually by each individual and later retrieve most of what they themselves stashed. Rather than memorizing their cache locations as previously suggested, we propose that they use a single cryptographic-like mechanism during both caching and retrieval. The model we developed is based on hippocampal spatial cells, which respond to an animals positional attention, such as when the animal enters a specific region (place-cells) or gazes at a particular location (spatial-view-cells). We know that the region that activates each spatial cell remains consistent across subsequent visits to the same area but not between areas. This remapping, combined with the uniqueness of cognitive maps, produces a persistent crypto-hash function for both food caching and retrieval. We also show that the model stores temporal information that helps animals in food caching order preference as previously observed. This behavior, which we refer to as crypto-taxis, might also explain consistent differences in decision-making when animals are faced with a large number of alternatives such as in foraging. Effects of fine-scale population structure on the distribution of heterozygosity in a long-term study of (Antirrhinum majus) Many studies have quantified the distribution of heterozygosity and relatedness in natural populations, but surprisingly few have examined the demographic processes driving these patterns. In this study we take a novel approach by studying how population structure affects both pairwise identity and the distribution of heterozygosity in a natural population of a self-incompatible plant Antirrhinum majus. We look at a measure of the variance in heterozygosity within a population, identity disequilibrium (g2), together with FST using a panel of 91 SNPs in 22,353 individuals collected over 11 years. We find that pairwise relatedness (FST) declines rapidly over short spatial scales, and the excess variance in heterozygosity between individuals (g2) reflects significant variation in inbreeding. Additionally, we detect an excess of individuals with around half the average heterozygosity, indicating that some are due to selfing or matings between close relatives. We use two types of simulation to ask whether variation in heterozygosity is consistent with fine-scale spatial population structure. First, by simulating offspring using parents drawn from a range of spatial scales, we show that the known pollen dispersal kernel explains g2. Second, we simulate a 1000-generation pedigree using the known dispersal and spatial distribution and find that the resulting g2 is consistent with that observed from the field data. In contrast, a simulated population with uniform density underestimates g2, indicating that heterogeneous density promotes identity disequilibrium. Our study shows that heterogeneous density and leptokurtic dispersal can together explain the distribution of heterozygosity. Furthermore, our study highlights the limitations of making theoretical predictions from simulations that only assume simple density and dispersal distributions. Damaraland mole-rats are not obligate cooperative breeders Damaraland mole-rats (Fukomys damarensis) are usually viewed as a eusocial or obligate cooperative breeder in which successful reproduction is dependent on help from closely related group members. However, because longitudinal studies of mole-rats in their natural environment are uncommon, the extent to which successful reproduction by breeders relies on assistance from other group members is unclear, and for non-breeders, the immediate and delayed fitness consequences of staying and helping are poorly understood. Using data from a 7-year field study of marked individuals, we investigate whether increasing group size confers reproductive and survival benefits to breeders and non-breeders, and explore the different routes through which individuals acquire breeding positions. We show that solitary natal dispersal was the most common route to breeding for both sexes and that the inheritance of dominant breeding positions was uncommon in both sexes. After dispersing, females typically settled alone in new burrow systems where they enjoyed high survival rates and remained in good body condition - often for several years - before being joined by males. In contrast to most obligately cooperative species, pairs of potential breeders reproduced successfully without helpers and experimentally formed pairs had the same reproductive success as larger established groups. Though larger breeding groups recruited slightly more pups on average, our data suggest that neither survival nor reproduction depend on the presence of non-breeding helpers, indicating that Damaraland mole-rats are not obligate cooperative breeders. We suggest that extended philopatry and group living in Damaraland mole-rats have evolved because of the high costs and constraints of dispersal rather than because of strong indirect benefits accrued through cooperative behaviour and that similarities between their breeding systems and those of obligatorily eusocial insects have been over-emphasized.

Significance StatementThe social mole-rats are often considered eusocial mammals in which successful reproduction depends on assistance from non-breeding helpers. In this study we show that in wild Damaraland mole-rats, the presence of non-breeders is associated with both costs and benefits and that nascent breeding pairs show high reproductive success despite the lack of non-breeding helpers. These findings indicate that Damaraland mole-rats are not obligate cooperative breeders and suggest that similarities between their breeding systems and those of obligatorily eusocial insects have been over-emphasized. Avian haemosporidians (Plasmodium and Haemoproteus) status in selected bird groups (Old world Flycatchers, Warblers, Babblers, and Thrushes) of India and their phylogenetic relationships with other lineages of the world The avian haemosporidians (Plasmodium and Haemoproteus) are widely distributed and may affect the host populations from body damage at individual level to the extinction of a population. The knowledge about their status may help in future avifauna conservation plans. Hence, we examined the avian haemosporidians status, in selected bird groups (Old world Flycatchers, Warblers, Babblers, and Thrushes) of India, and their phylogenetic relationships with other known lineages of the world. We used the common genetic marker (Cytochrome b gene fragment of 479 bp) with information on the geographic distribution of parasite and host species available at MalAvi database. The prevalence of avian haemosporidians, from northern, eastern, and southern parts of India and phylogenetic genetic analysis of lineages was carried out to know the genetic relatedness among them at local and world level. The MCC tree revealed six Haemosporidian lineages in which one was common (H_MSP01) and five were unique (H_CYOPOL01, H_CHD01, H_CYORUB01, H_EUMTHA01, and P_GEOCIT01). The avian host richness Index was 2.0852. 9.9%, prevalence of Haemosporidian infection was found in 111 DNA samples belonging to 6 host species. The Haemoproteus prevalence was found to be 9.0 % across five host species (Phylloscopus trochiloides, Cyornis poliogenys, C. hainanus dialilaemus, C. rubeculoides, Eumiyas thalassinus) and Plasmodium prevalence was 0.9% in Geokichla citrina. Spatial phylogeny at global level showed H_MSP01 lineage, found in different host species in India, was genetically related to H. pallidus lineages (COLL2 and PFC1) in parts of Africa, Europe, North America, Malaysia, and Philippines. The Plasmodium lineage (P_GEOCIT01) was related to PADOM16 in Egypt with poor sequence similarity (93.89%). The statistical analysis suggested that the haemosporidians host species distribution range was directly and significantly associated with the altitude, minimum temperature, and relative humidity. H_MSP01 distribution was in accordance with H. pallidus having a wide geographic and host range.