Omicron BA.1 and BA.2 Variants Increase the Interactions of SARS-CoV-2 Spike Glycoprotein with ACE2 SARS-CoV-2 infection is initiated by binding of the receptor-binding domain (RBD) of its spike glycoprotein to the peptidase domain (PD) of angiotensin-converting enzyme 2 (ACE2) receptors in host cells. Recently detected Omicron variant of SARS-CoV-2 (B.1.1.529) is heavily mutated on RBD. Currently, the most common Omicron variants are the original BA.1 Omicron strain and the BA.2 variant, which became more prevalent since it first appeared. To investigate how these mutations affect RBD-PD interactions, we performed all-atom molecular dynamics simulations of the BA.1 and BA.2 RBD-PD in the presence of full-length glycans, explicit water and ions. Simulations revealed that RBDs of BA.1 and BA.2 variants exhibit a more dispersed interaction network and make an increased number of salt bridges and hydrophobic interactions with PD compared to wild-type RBD. Although BA.1 and BA.2 differ in two residues at the RBD-ACE2 interface, no major difference in RBD-PD interactions and binding strengths were observed between these variants. Using the conformations sampled in each trajectory, the Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) method estimated ~34% and ~51% stronger binding free energies for BA.1 and BA.2 RBD, respectively, than wild-type RBD, which may result in higher binding efficiency of the Omicron variant to infect host cells.
Metabolic regulation of ILC2 differentiation into ILC1-like cells during Mycobacterium tuberculosis infection Tissue-resident innate lymphoid cells (ILCs) regulate tissue homeostasis, protect against pathogens at mucosal surfaces and are key players at the interface of innate and adaptive immunity. How ILCs adapt their phenotype and function to environmental cues within tissues remains to be fully understood. Here, we show that Mycobacterium tuberculosis infection alters the phenotype and function of immature lung ILC2 toward a protective interferon-{gamma}-producing ILC1-like population. This differentiation is controlled by type 1 cytokines and is associated with a glycolytic program involving the transcription factor HIF1. Collectively, our data reveal how tissue-resident ILCs adapt to type 1 inflammation toward a pathogen tailored immune response.
Balancing sensitivity and specificity in preclinical research The success of scientific discovery in preclinical drug development is based on the different roles of exploration and confirmation. Exploration requires sensitivity while confirmation needs to be specific. Based on published empirical data, we simulated two preclinical research trajectories to examine their effectiveness to detect true effects while keeping animal numbers low. We compare a conventional p-value based approach with a method based on an a priori determined smallest effect size of interest (SESOI). Using a SESOI increases transition rates from exploration to confirmation and results in higher detection rates across the trajectory. Specificity in the SESOI trajectory increases if the prior probability of true effects is low. We conclude that employing a SESOI is superior to a p-value based approach. Based on our findings, we propose a reconsideration of planning and conducting preclinical experiments, especially when the prior probability of true hypotheses is low. Deep learning: step forward to high-resolution in vivo shortwave infrared imaging Shortwave infrared window (SWIR: 1000-1700 nm) represents a major improvement compared to the NIR-I region (700-900 nm) in terms of temporal and spatial resolutions in depths down to 4 mm. SWIR is a fast and cheap alternative to more precise methods such as X-ray and opto-acoustic imaging. Main obstacles in SWIR imaging are the noise and scattering from tissues and skin that reduce the precision of the method. We demonstrate that the combination of SWIR in vivo imaging in the NIRIIb region (1500-1700 nm) with advanced deep learning image analysis allows to overcome these obstacles and making a large step forward to high resolution imaging: it allows to precisely segment vessels from tissues and noise, provides morphological structure of the vessels network, with learned pseudo-3D shape, their relative position, dynamic information of blood vascularization in depth in small animals and distinguish the vessels types: artieries and veins. For demonstration we use neural network IterNet that exploits structural redundancy of the blood vessels, which provides a useful analysis tool for raw SWIR images. Serological fingerprints link antiviral activity of therapeutic antibodies to affinity and concentration We assessed the affinities of the therapeutic monoclonal antibodies (mAbs) cilgavimab, tixagevimab, sotrovimab, casirivimab, and imdevimab to the receptor binding domain (RBD) of wild type, Delta, and Omicron spike. The Omicron RBD affinities of cilgavimab, tixagevimab, casirivimab, and imdevimab decreased by at least two orders of magnitude relative to their wild type equivalents, whereas sotrovimab binding was less severely impacted. These affinity reductions correlate with reduced antiviral activities of these antibodies, suggesting that simple affinity measurements can serve as an indicator for activity before challenging and time-consuming virus neutralization assays are performed. We also compared the properties of these antibodies to serological fingerprints (affinities and concentrations) of wild type RBD specific antibodies in 74 convalescent sera. The affinities of the therapeutic mAbs to wild type and Delta RBD were in the same range as the polyclonal response in the convalescent sera indicative of their high antiviral activities against these variants. However, for Omicron RBD, only sotrovimab retained affinities that were within the range of the polyclonal response, in agreement with its high activity against Omicron. Serological fingerprints thus provide important context to affinities and antiviral activity of mAb drugs and could guide the development of new therapeutics. bulkAnalyseR: An accessible, interactive pipeline for analysing and sharing bulk multi-modal sequencing data Bulk sequencing experiments (single- and multi-omics) are essential for exploring wide-ranging biological questions. To facilitate interactive, exploratory tasks, coupled with the sharing of easily accessible information, we present bulkAnalyseR, a package integrating state-of-the-art approaches using an expression matrix as the starting point (pre-processing functions are available as part of the package). Static summary images are replaced with interactive panels illustrating quality-checking, differential expression analysis (with noise detection) and biological interpretation (enrichment analyses, identification expression patterns, followed by inference and comparison of regulatory interactions). bulkAnalyseR can handle different modalities, facilitating robust integration and comparison of cis-, trans- and customised regulatory networks.

bulkAnalyseR is available on CRAN and GitHub, with extensive documentation and usage examples (https://github.com/Core-Bioinformatics/bulkAnalyseR, https://cran.r-project.org/web/packages/bulkAnalyseR/)

ContactIrina Mohorianu iim22@cam.ac.uk 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. Intramolecular carbon isotope signals reflect metabolite allocation in plants Stable isotopes at natural abundance are key tools to study physiological processes occurring outside the temporal scope of manipulation and monitoring experiments. Whole-molecule carbon isotope ratios (13C/12C) enable assessments of plant carbon uptake yet conceal information about carbon allocation. Here, we identify an intramolecular 13C/12C signal at treering glucose C-5 and C-6 and develop experimentally testable theories on its origin. More specifically, we assess the potential of processes within C3 metabolism for signal introduction based (inter alia) on constraints on signal propagation posed by metabolic networks. We propose that the intramolecular signal reports carbon allocation into major metabolic pathways in actively photosynthesising leaf cells including the anaplerotic, shikimate, and non-mevalonate pathway. We support our theoretical framework by linking it to previously reported whole-molecule 13C/12C increases in cellulose of ozone-treated Betula pendula and a highly significant relationship between the intramolecular signal and tropospheric ozone concentration. Our theory postulates a pronounced preference of leaf-cytosolic triose-phosphate isomerase to catalyse the forward reaction in vivo (dihydroxyacetone phosphate to glyceraldehyde 3-phosphate). In conclusion, intramolecular 13C/12C analysis resolves information about carbon uptake and allocation enabling more comprehensive assessments of carbon metabolism than whole-molecule 13C/12C analysis.

HighlightIntramolecular 13C/12C analysis resolves information about carbon uptake and allocation (and associated environmental controls) enabling more comprehensive assessments of carbon metabolism, plant-environment interactions, and environmental variability than whole-molecule 13C/12C analysis. Chromosomal rearrangements with stable repertoires of genes and transposable elements in an invasive forest-pathogenic fungus AO_SCPLOWBSTRACTC_SCPLOWChromosomal rearrangements have been largely described among eukaryotes, and may have important consequences on evolution of species. High genome plasticity has been often reported in Fungi, which may explain their apparent ability to quickly adapt to new environments. Cryphonectria parasitica, causing the Chestnut blight disease, is an invasive fungal pathogen species associated with several recent host shifts during its successive introductions from Asia to North America and Europe. Previous cytological karyotyping and genomic studies suggested several chromosomal rearrangements which remains to be described in detail for this species. A serious limitation for valid genome comparisons is the access to robust genome assemblies that usually contain genomic regions of low complexity. We present a new de novo whole-genome assembly obtained from a new method of DNA extraction and long-reads sequencing Nanopore technology obtained from a Japanese isolate sampled in the native area of the species. The comparison with a recently published reference genome revealed stable gene and transposable elements (TEs) repertoires. We also showed that the C. parasitica genome is lowly compartmentalized, with a poor association between TEs and genes, such as those potentially involved in host interactions (i.e., genes coding for small secreted proteins or for secondary metabolites). This genome comparison, however, detected several large chromosomal rearrangements that may have important consequences in gene regulations and sexual mating in this invasive species. This study opens the way for more comparisons of high-quality assembled genomes, and questions the role of structural variations in the invasive success of this fungal pathogen species. A nontoxic tetrodotoxin analog, 5,6,11-trideoxytetrodotoxin, as an olfactory chemoattractant for the grass puffer Toxic puffers contain the potent neurotoxin, tetrodotoxin (TTX). Although TTX is considered to serve as a defense substance, previous behavioral studies have demonstrated that TTX acts as an attractive pheromone for some toxic puffers. To elucidate the physiological mechanism of putative pheromonal action of TTX, we examined whether grass puffers Takifugu alboplumbeus can detect TTX. Electroolfactogram (EOG) results suggest that the olfactory epithelium (OE) of grass puffers responded to a type of TTX analog (5,6,11-trideoxyTTX), although it did not respond to TTX. We also examined the attractive action of 5,6,11-trideoxyTTX on grass puffers by recording their swimming behavior under dark conditions. Grass puffers preferred to stay on the side of the aquarium where 5,6,11-trideoxyTTX was administered, and their swimming speed decreased. Additionally, odorant-induced labeling of olfactory sensory neurons by immunohistochemistry against neural activity marker (phosphorylated extracellular signal regulated kinase; pERK) revealed that labeled olfactory sensory neurons were localized in the region surrounding "islets" where there was considered as nonsensory epithelium. 5,6,11-trideoxyTTX has been known to accumulate in grass puffers, but its toxicity is much lower (almost nontoxic) than TTX. Our results suggest that toxic puffers may positively use this unknown function TTX analog as an olfactory chemoattractant. Dramatic differences in male and female mortality trends for selected European cohorts over ~20 years. Longevity is of considerable interest. Collation of recent data after World War II by the Human Mortality Database allowed analyses, previously unattainable, of modal death-ages for sufficient numbers of selected European cohorts. The aim was to track modes and medians/means ([&ge;]60 years old (y)) of all-cause mortality for both sexes. The only highest-quality, large-number Lexis data available were analyzed: from nine countries: Denmark, Finland, France, Iceland, Italy, Netherlands, Norway, Sweden and Switzerland; raw-data modes (and medians/means [&ge;]60y, plus thin-plate-spline averages), were analyzed, plus pooled data. Here we show that for cohorts 1880-[~]1900 dramatic sex differences existed between death-age changes with all countries except Iceland showing male modal negative trends lasting [~]10-20 years and medians in all countries near-constant or negative lasting [~]10-20 years; whereas females from most countries showed fairly constant positive trends (except Finnish modes and Norwegian medians). For cohorts [~]1900-1919 male and female modal trends were positive (except Dutch and Icelandic cohorts and Finnish females). The net results were that male mortality modes for Danish, Icelandic, Italian, Dutch, Swedish and Norwegian 1919 cohorts were roughly the same as for 1880 cohorts, whereas female death-age modes increased. Results clarify previously knowledge concerning sex differences during this period. Despite improved environment in late adulthood over this period, this did not translate into increased male longevity and earlier events might have sealed their fate, especially in Denmark, Italy, Netherlands, Norway, aand Sweden (and, later, Iceland). Tracheal tube fusion in Drosophila involves release of extracellular vesicles from multivesicular bodies Extracellular vesicles (EVs) comprise diverse types of cell-released membranous structures that are thought to play important roles in intercellular communication. Despite extensive work on the formation and functions of EVs in cultured cells, studies of EVs in vivo have remained scarce. We report here that EVs are present in the developing lumen of tracheal tubes in Drosophila embryos. We defined two distinct EV subpopulations, one of which contains the Munc13-4 homologue Staccato (Stac) and is spatially and temporally associated with tracheal tube fusion events. The formation of Stac-positive luminal EVs depends on the tip-cell-specific GTPase Arl3, which is also required for the formation of Stac-positive multivesicular bodies, suggesting that Stac-EVs derive from fusion of Stac-MVBs with the luminal membrane in tip cells during anastomosis formation. The GTPases Rab27 and Rab35 cooperate downstream of Arl3 to promote Stac-MVB formation and tube fusion. We propose that Stac-MVBs act as membrane reservoirs that facilitate tracheal lumen fusion in a process regulated by Arl3, Rab27, Rab35, and Stac/Munc13-4. Mathematical Modeling and Analysis of Mitochondrial Retrograde Signaling Dynamics Mitochondria, semi-autonomous eukaryotic organelles, participate in energy production and metabolism, making mitochondrial quality control crucial. As most mitochondrial proteins are encoded by nuclear genes, quality control depends on proper mitochondria-nucleus communication, designated mitochondrial retrograde signaling. Early studies focused on retrograde signaling participants and specific gene knockouts. However, mitochondrial signal modulation remains elusive. Using yeast, we simulated signal propagation following mitochondrial damage and proposed a mathematical model based ordinary differential equations. Mitochondrial retrograde signaling decisions were described using a Boolean model. Dynamics were analyzed through an ordinary differential equation-based model and extended to evaluate the model response to noisy damage signals. Simulation revealed localized protein concentration dynamics, including waveforms, frequency response, and robustness under noise. Retrograde signaling is bistable with three localized steady states, and increased damage compromises robustness. We elucidated mitochondrial retrograde signaling, thus providing a basis for drug design against yeast and fungi.

Author SummaryThe yeast RTG pathway regulates mitochondrial metabolism and mitochondrial quality through passing mitochondrial signal to the nucleus to modulate gene expressions. Using microscopic data of RTG proteins translocation from cytosol to nucleus, the parameters were found by fitting 16 knockout conditions simulated from the proposed differential equation-based model. Further, through dose response, ultrasensitivity, frequency response and noise interference, we demonstrated a switch-like property of RTG pathway activation, a capacity charging property of RTG protein translocation, a low pass filter property of signals in different frequencies, and noise amplification due to mitochondrial signal. The proposed mathematical model enables us to understand the dynamics and mechanisms in mitochondrial retrograde signaling in yeast and provides potential antifungal treatment strategies. The Rab GTPase activating protein TBC-2 regulates endosomal localization of DAF-16 FOXO and lifespan FOXO transcription factors have been shown to regulate longevity in model organisms and are associated with longevity in humans. To gain insight into how FOXO functions to increase lifespan, we examined the subcellular localization of DAF-16 in C. elegans. We show that DAF-16 is localized to endosomes and that this endosomal localization is increased by the insulin-IGF signaling (IIS) pathway. Endosomal localization of DAF-16 is modulated by endosomal trafficking proteins. Disruption of the Rab GTPase activating protein TBC-2 increases endosomal localization of DAF-16, while inhibition of TBC-2 targets, RAB-5 or RAB-7 GTPases, decreases endosomal localization of DAF-16. Importantly, the amount of DAF-16 that is localized to endosomes has functional consequences as increasing endosomal localization through mutations in tbc-2 reduced the lifespan of long-lived daf-2 IGFR mutants, depleted their fat stores, and DAF-16 target gene expression. Overall, this work identifies endosomal localization as a mechanism regulating DAF-16 FOXO, which is important for its functions in metabolism and aging. Immunomodulatory Contribution of Mast Cells to the Regenerative Biomaterial Microenvironment Bioactive immunomodulatory biomaterials have shown promise for influencing the immune response to promote tissue repair and regeneration. Macrophages and T cells have been associated with this response; however, other immune cell types have been traditionally overlooked. In this study, we investigated the role of mast cells in the regulation of the immune response to decellularized biomaterial scaffolds using a subcutaneous implant model. In mast cell-deficient mice, there was dysregulation of the expected M1 to M2 macrophage transition typically induced by the biomaterial scaffold. Polarization progression deviated in a sex specific manner with an early transition to an M2 profile in female mice, while the male response was unable to properly transition past a pro-inflammatory M1 state. Both were reversed with adoptive mast cell transfer. Further investigation of the later stage immune response in male mice determined a greater sustained pro-inflammatory gene expression profile including the IL-1 cytokine family, IL-6, alarmins, and chemokines. These results highlight mast cells as another important cell type that influences the immune response to pro-regenerative biomaterials. Embracing imperfection: machine-assisted invertebrate classification in difficult datasets O_LIDespite growing concerns over the health of global invertebrate diversity, terrestrial invertebrate monitoring efforts remain poorly geographically distributed. Machine-assisted classification has been proposed as a potential solution to quickly gather large amounts of data; however, previous studies have often used unrealistic or idealized datasets to train their models.
C_LIO_LIIn this study, we describe a practical methodology for including machine learning in ecological data acquisition pipelines. Here we train and test machine learning algorithms to classify over 56,000 bulk terrestrial invertebrate specimens from morphometric data and contextual metadata. All vouchered specimens were collected in pitfall traps by the National Ecological Observatory Network (NEON) at 27 locations across the United States in 2016. Specimens were photographed, and morphometric data was extracted as feature vectors using ImageJ. Issues stemming from inconsistent taxonomic label specificity were resolved by making classifications at the lowest identified taxonomic level (LITL). Taxa with too few specimens to be included in the training dataset were classified by the model using zero-shot classification.
C_LIO_LIWhen classifying specimens that were known and seen by our models, we reached an accuracy of 72.7% using extreme gradient boosting (XGBoost) at the LITL. Models that were trained without contextual metadata underperformed models with contextual metadata by an average of 7.2%. We also classified invertebrate taxa that were unknown to the model using zero-shot classification, with an accuracy of 39.4%, resulting in an overall accuracy of 71.5% across the entire NEON dataset.
C_LIO_LIThe general methodology outlined here represents a realistic application of machine learning as a tool for ecological studies. Hierarchical and LITL classifications allow for flexible taxonomic specificity at the input and output layers. These methods also help address the  long tail problem of underrepresented taxa missed by machine learning models. Finally, we encourage researchers to consider more than just morphometric data when training their models, as we have shown that the inclusion of contextual metadata can provide significant improvements to accuracy.
C_LI Re-convolving the compositional landscape of primary and recurrent glioblastoma reveals prognostic andtargetable tissue states Glioblastoma is an aggressive diffusely infiltrating neoplasm that spreads beyond surgical resection margins, where it intermingles with non-neoplastic brain cells. This complex microenvironment harbouring infiltrating glioma and non-neoplastic brain cells is the origin of tumor recurrence. Thus, understanding the cellular and molecular features of the glioma microenvironment is therapeutically and prognostically important. Here, we used single-nucleus RNA sequencing (snRNAseq) of primary and recurrent glioma to define three compositional  tissue-states rooted in cohabitation of cell-types and transcriptional states. These comprise a state featuring A) abundant normal brain microenvironment cells, B) reactive/inflamed brain microenvironment, and C) cellular/proliferative tumor. All these states exhibited variable degrees of infiltration by glioma cells. Spatial transcriptomics confirmed that the cell-types and transcriptomics states which compositionally cohabitate tissue states also colocalize in space. Tissue states are clinically significant because they correlate with radiographic, histopathologic, and prognostic features. We found that enrichment of tissue state B signature correlated with shorter survival. Importantly, we found that our compositionally defined tissue states are enriched in distinct metabolic pathways. One such pathway is fatty acid biosynthesis, which was enriched in tissue state B - a state enriched in recurrent glioblastoma and composed of astrocyte-like/mesenchymal glioma cells, reactive astrocytes resembling those seen in neurodegeneration, and monocyte-like myeloid cells. We showed that treating acute slices of GBM with a fatty acid synthesis inhibitor is sufficient to deplete the transcriptional signature of tissue state B. Our findings define a novel compositional approach to the glioma-infiltrated tissue which allows us to discover prognostic and targetable features, paving the way to new mechanistic and therapeutic discoveries. Host cell membrane capture by the SARS CoV-2 spike protein fusion intermediate Cell entry by SARS-CoV-2 is accomplished by the S2 subunit of the spike S protein on the virion surface by capture of the host cell membrane and fusion with the viral envelope. Capture and fusion require the prefusion S2 to transit to its potent, fusogenic form, the fusion intermediate (FI). However, the FI structure is unknown, detailed computational models of the FI are unavailable, and the mechanisms and timing of membrane capture and fusion are not established. Here, we constructed a full-length model of the CoV-2 FI by extrapolating from known CoV-2 pre- and postfusion structures. In atomistic and coarse-grained molecular dynamics simulations the FI was remarkably flexible and executed large bending and extensional fluctuations due to three hinges in the C-terminal base. Simulations suggested a host cell membrane capture time of [~] 2 ms. Isolated fusion peptide simulations identified an N-terminal helix that directed and maintained binding to the membrane but grossly underestimated the binding time, showing that the fusion peptide environment is radically altered when attached to its host fusion protein. The large configurational fluctuations of the FI generated a substantial exploration volume that aided capture of the target membrane, and may set the waiting time for fluctuation-triggered refolding of the FI that draws the viral envelope and host cell membrane together for fusion. These results describe the FI as a machinery designed for efficient membrane capture and suggest novel potential drug targets.



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org.highwire.dtl.DTLVardef@1374b59org.highwire.dtl.DTLVardef@133d21forg.highwire.dtl.DTLVardef@127f2ddorg.highwire.dtl.DTLVardef@1b9ab8f_HPS_FORMAT_FIGEXP  M_FIG C_FIG CEP162 deficiency causes human retinal degeneration and reveals a dual role inciliogenesis and neurogenesis Defects in primary or motile cilia result in a variety of human pathologies, and retinal degeneration is frequently associated with these so-called ciliopathies. We show that homozygosity for a truncating variant in CEP162, a centrosome and microtubule-associated protein required for transition zone (TZ) assembly during ciliogenesis and neuronal differentiation in the retina, causes late-onset retinitis pigmentosa in 2 unrelated families. The mutant CEP162-E646R*5 protein is expressed and properly localized to the mitotic spindle but missing from the basal body in primary and photoreceptor cilia. This impairs recruitment of TZ components to the basal body and corresponds to complete loss of CEP162 function at the ciliary compartment, reflected by delayed formation of dysmorphic cilia. In contrast, rescue of increased cell death in the developing mouse retina after shRNA knockdown of Cep162 by expression of CEP162-E646R*5 indicates that the mutant retains its role for retinal neurogenesis. Human retinal degeneration thus results from specific loss of ciliary CEP162 function.

Graphical abstract

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org.highwire.dtl.DTLVardef@83457eorg.highwire.dtl.DTLVardef@47775corg.highwire.dtl.DTLVardef@1ed643eorg.highwire.dtl.DTLVardef@5032d2_HPS_FORMAT_FIGEXP  M_FIG C_FIG Robust retrieval of data stored in DNA by de Bruijn graph-based de novo strand assembly DNA data storage is a rapidly developing technology with great potential due to its high density, long-term durability, and low maintenance cost. The major technical challenges include various errors, such as the strand breaks, rearrangements, and indels that frequently arise during DNA synthesis, amplification, sequencing, and preservation. Through a de novo assembly strategy, we developed an algorithm based on the de Bruijn graph and greedy path search (DBGPS) to address these issues. DBGPS shows distinct advantages in handling DNA breaks, rearrangements, and indels. The robustness of DBGPS is demonstrated by accelerated aging, multiple independent data retrievals, deep error-prone PCR, and large data scale simulations. Remarkably, 6.8 MB of data can be retrieved accurately from a seriously corrupted sample that has been treated at 70 {degrees}C for 70 days. With DBGPS, we were able to achieve a logical density of 1.30 bits/cycle and a physical density of 295 PB/g.

One-Sentence SummaryA de Bruijn graph-based de novo assembly algorithm for DNA data storage enables fast and robust data readouts even with DNA samples that have been severely corrupted. Metabolic reconstitution by a gnotobiotic microbiota varies over the circadian cycle The capacity of the intestinal microbiota to degrade otherwise indigestible diet components is known to greatly improve the recovery of energy from food. This has led to the hypothesis that increased digestive efficiency may underlie the contribution of the microbiome to obesity. OligoMM12-colonized gnotobiotic mice have a consistently higher fat-mass than germ-free or fully colonized counterparts. We therefore investigated their food intake, digestion efficiency, energy expenditure and respiratory quotient using a novel isolator-housed metabolic cage system which allows long-term measurements without contamination risk. This demonstrated that microbiota- released calories are perfectly balanced by decreased food intake in fully colonized versus gnotobiotic OligoMM12 and germ-free mice fed a standard chow diet, i.e., microbiota-released calories can in fact be well-integrated into appetite control. We also observed no significant difference in energy expenditure per gram lean mass between the different microbiota groups, suggesting that cumulative very small differences in energy balance, or altered energy storage must underlie fat accumulation in OligoMM12 mice. Consistent with altered energy storage, major differences were observed in the type of respiratory substrates used in metabolism over the circadian cycle: in germ-free mice the respiratory exchange ratio was consistently lower than that of fully colonized mice at all times of day, indicative of more reliance on fat and less on glucose metabolism. Intriguingly the RER of OligoMM12-colonized gnotobiotic mice phenocopied fully colonized mice during the dark (active/eating) phase but phenocopied germ-free mice during the light (fasting/resting) phase. Further, OligoMM12-colonized mice showed a germ-free-like drop in liver glycogen storage during the light cycle and both liver and plasma metabolomes of OligoMM12 mice clustered closely with germ-free mice. This implies the existence of microbiota functions that are required to maintain normal host metabolism during the resting/fasting phase of circadian cycle, and which are absent in the OligoMM12 consortium. Chromatin remodelling by INO80 at promoter proximal pause sites promotes premature termination of mRNA synthesis How co-transcriptional RNA quality control is regulated remains poorly understood. Here, we report that in S. cerevisiae premature transcription termination of mRNAs is regulated by the evolutionarily conserved ATP-dependent chromatin remodeling INO80 complex. Loss of INO80 leads to an increase in promoter-proximally paused RNA Polymerase II and defective progression into the gene body. We show that promoter-proximal transcriptional pausing correlates with loading of RNA surveillance and transcription termination factors to mRNA transcripts. Cells lacking INO80 are defective for the Nrd1-Nab3-Sen1 (NNS)-dependent pathway for transcription termination at snRNA genes and promoter-proximally sites of mRNA genes. We demonstrate that INO80 promotes the association of the RNA surveillance and termination factor Nab2 with short promoter-proximal mRNA transcripts. We provide evidence that co-transcriptional recruitment of Nab2 to chromatin is regulated by INO80, which enables the interaction of Nab2 with the histone variant H2A.Z. Our work suggests a chromatin mechanism for premature transcription termination at promoter-proximally pausing sites, linking RNA quality control to the transcriptional process. Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: the Multi-Targeting Drug DREAM Challenge A continuing challenge in modern medicine is the identification of safer and more efficacious drugs. Precision therapeutics, which have one molecular target, have been long promised to be safer and more effective than traditional therapies. This approach has proven to be challenging for multiple reasons including lack of efficacy, rapidly acquired drug resistance, and narrow patient eligibility criteria. An alternative approach is the development of drugs that address the overall disease network by targeting multiple biological targets ( polypharmacology). Rational development of these molecules will require improved methods for predicting single chemical structures that target multiple drug targets. To address this need, we developed the Multi-Targeting Drug DREAM Challenge, in which we challenged participants to predict single chemical entities that target pro-targets but avoid anti-targets for two unrelated diseases: RET-based tumors and a common form of inherited Tauopathy. Here, we report the results of this DREAM Challenge and the development of two neural network-based machine learning approaches that were applied to the challenge of rational polypharmacology. Together, these platforms provide a potentially useful first step towards developing lead therapeutic compounds that address disease complexity through rational polypharmacology.

Author SummaryMany modern drugs are developed with the goal of modulating a single cellular pathway or target. However, many drugs are, in fact,  dirty; they target multiple cellular pathways or targets. This phenomenon is known as multi-targeting or polypharmacology. While some strive to develop  cleaner therapeutics that eliminate secondary targets, recent work has shown that multi-targeting therapeutics have key advantages for a variety of diseases. However, while multi-targeting drugs that affect a precisely-defined profile of targets may be more effective, it is difficult to computationally predict which molecules have desirable target profiles. Here, we report the results of a competitive crowdsourcing project (the Multi-Targeting Drug DREAM Challenge), where we challenged participants to predict chemicals that have desired target profiles for cancer and neurodegenerative disease. Mapping the signatures of inflammatory pain and its relief Ongoing pain is often driven by direct activation of pain-sensing neurons and neuroimmune mediated sensitization. These heightened states of pain alter physiology, reduce motor function, and alter motivation to engage in normal behaviors. The complexity of the pain state has evaded a comprehensive definition, especially in nonverbal animals. Here in mice, we capture the physiological state of sensitized pain neurons at different time points post-inflammation and used computational tools to automatically map behavioral signatures of evoked and spontaneous displays of pain. First, retrograde labeling coupled with electrophysiology of neurons innervating the site of localized inflammation defined critical time points of pain sensitization. Next, we used high-speed videography combined with supervised and unsupervised machine learning tools and uncovered sensory-evoked defensive coping postures to pain. Using 3D pose analytics inspired by natural language processing, we identify movement sequences that correspond to robust representations of ongoing pain states. Surprisingly, with this analytical framework, we find that a commonly used anti-inflammatory painkiller does not return an animals behavior back to a pre-injury state. Together, these findings reveal the previously unidentified signatures of pain and analgesia at timescales when inflammation induces heightened pain states. Bacterial glycyl tRNA synthetase offers glimpses of ancestral protein topologies Aminoacyl tRNA synthetases (aaRSs) are among the proposed proteins present in the Last Universal Common Ancestor (LUCA). There are two types of glycyl tRNA synthetases (GlyRSs), from which the archaeal-eukaryal type is the one suggested to be present in LUCA. Here we solved the crystal structure of a complete bacterial glycyl tRNA synthetase (bacGlyRS) and show that indeed, bacGlyRS carries several structural signals that point it at the origin of all aaRSs. Furthermore, if bacGlyRS is ancestral, it should help to build a reliable Tree of Life (ToL). Given the modular nature of protein evolution, we used only two sub-domain segments with duplicated ancestral topologies, no detected orthologs and an assumed limited horizontal gene transfer (HGT). These motifs correspond to the non-specific RNA binding regions of contemporary bacGlyRS, archaeal CCA-adding enzyme (arch-CCAadd), and eukaryotic rRNA processing enzyme (euk-rRNA). The calculated, rooted bacterial ToL agrees with several phyla relationships unaccounted by the available trees. Deficits in seizure threshold and other behaviors in adult mice without gross neuroanatomic injury after late gestation transient prenatal hypoxia Intrauterine hypoxia is a common cause of brain injury in children resulting in a broad spectrum of long-term neurodevelopmental sequela, including life-long disabilities that can occur even in the absence of severe neuroanatomic damage. Postnatal hypoxia-ischemia rodent models are commonly used to understand the effects of ischemia and transient hypoxia on the developing brain. Postnatal models, however, have some limitations. First, they do not test the impact of placental pathologies on outcomes from hypoxia. Second, they primarily recapitulate severe injury because they provoke substantial cell death, which is not seen in children with mild hypoxic injury. Lastly, they do not model preterm hypoxic injury. Prenatal models of hypoxia in mice may allow us to address some of these limitations to expand our understanding of developmental brain injury. The published rodent models of prenatal hypoxia employ multiple days of hypoxic exposure or complicated surgical procedures, making these models challenging to perform consistently in mice. Furthermore, large animal models suggest that transient prenatal hypoxia without ischemia is sufficient to lead to significant functional impairment to the developing brain. However, these large animal studies are resource-intensive and not readily amenable to mechanistic molecular studies. Therefore, here we characterized the effect of late gestation (embryonic day 17.5) transient prenatal hypoxia (5% inspired oxygen) on long-term anatomical and neurodevelopmental outcomes in mice. Late gestation transient prenatal hypoxia increased hypoxia-inducible factor 1 alpha protein levels (a marker of hypoxic exposure) in the fetal brain. Hypoxia exposure predisposed animals to decreased weight at postnatal day 2, which normalized by day 8. However, hypoxia did not affect gestational age at birth, litter size at birth, or pup survival. No differences in fetal brain cell death or long-term gray or white matter changes resulted from hypoxia. Animals exposed to prenatal hypoxia did have several long-term functional consequences, including sex-dichotomous changes. Hypoxia exposure was associated with a decreased seizure threshold and abnormalities in hindlimb strength and repetitive behaviors in males and females. Males exposed to hypoxia had increased anxiety-related deficits, whereas females had deficits in social interaction. Neither sex developed any motor or visual learning deficits. This study demonstrates that late gestation transient prenatal hypoxia in mice is a simple, clinically relevant paradigm for studying putative environmental and genetic modulators of the long-term effects of hypoxia on the developing brain.