Ultra-deep through-skull mouse brain imaging via the combination of skull optical clearing and three-photon microscopy Optical microscopy has enabled in vivo monitoring of brain structures and functions with high spatial resolution. However, the strong optical scattering in turbid brain tissue and skull impedes the observation of microvasculature and neuronal structures at a large depth. Herein, we proposed a strategy to overcome the influence induced by the high scattering effect of both skull and brain tissue via the combination of skull optical clearing (SOC) technique and thee-photon fluorescence microscopy (3PM). The Visible-NIR-II compatible Skull Optical Clearing Agents (VNSOCA) we applied reduced the skull scattering and water absorption in long wavelength by refractive index matching and H2O replacement to D2O respectively. 3PM with the excitation in the 1300-nm window reached 1.5 mm cerebrovascular imaging depth in cranial window. Combining the two advanced technologies together, we achieved so far the largest cerebrovascular imaging depth of 1.0 mm and neuronal imaging depth of >700 m through intact mouse skull. Dual-channel through-skull imaging of both brain vessels and neurons was also successfully realized, giving an opportunity of non-invasively monitoring the deep brain structures and functions at single-cell level simultaneously.
A self-supervised domain-general learning framework for human ventral stream representation Anterior regions of the ventral visual stream encode substantial information about object categories. Are top-down category-level forces critical for arriving at this representation, or can this representation be formed purely through domain-general learning of natural image structure? Here we present a fully self-supervised model which learns to represent individual images, rather than categories, such that views of the same image are embedded nearby in a low-dimensional feature space, distinctly from other recently encountered views. We find (i) category information implicitly emerges in the local similarity structure of this feature space, and (ii) these models learn hierarchical features which capture the structure of brain responses across the human ventral visual stream, on par with category-supervised models. These results provide computational support for a domain-general framework guiding the formation of visual representation, where the proximate goal is not explicitly about category information, but is instead to learn unique, compressed descriptions of the visual world.
Cell trajectory modeling identifies a primitive trophoblast state defined by BCAM enrichment In early placental development, progenitor cytotrophoblasts (CTBs) differentiate along one of two cellular trajectories: the villous or extravillous pathways. CTBs committed to the villous pathway fuse with neighboring CTBs to form the outer multinucleated syncytiotrophoblast (SCT), while CTBs committed to the extravillous pathway differentiate into invasive extravillous trophoblasts (EVT). Unfortunately, little is known about the processes controlling human CTB progenitor maintenance and differentiation. To address this, we established a single cell RNA sequencing (scRNA-seq) dataset from first trimester placentas to identify cell states important in trophoblast progenitor establishment, renewal, and differentiation. Multiple distinct trophoblast states were identified, representing progenitor CTBs, column CTBs, SCT precursors, and EVT. Lineage trajectory analysis identified a progenitor origin that was reproduced in human trophoblast stem cell organoids. Heightened expression of basal cell adhesion molecule (BCAM) defined this primitive state, where BCAM enrichment or gene silencing resulted in enhanced or diminished organoid growth. Together, this work describes at high-resolution trophoblast heterogeneity within the first trimester, resolves gene networks within human CTB progenitors, and identifies BCAM as a primitive progenitor marker and possible regulator.

Summary StatementLineage trajectory modeling identifies multiple human progenitor trophoblast states and defines trophoblast differentiation kinetics, where BCAM-expressing progenitors demonstrate enhanced regenerative ability. Utility of SARS-CoV-2 infection models using in vitro and in vivo ACE2-lentivirus transduction SARS-CoV-2 uses the human ACE2 (hACE2) receptor for cell attachment and entry, with mouse ACE2 (mACE2) unable to support infection. Herein we describe an ACE2-lentivirus system and illustrate its utility for in vitro and in vivo SARS-CoV-2 infection models. Transduction of non-permissive cell lines with hACE2 imparted replication competence, and transduction with mACE2 containing N30D, N31K, F83Y and H353K substitutions, to match hACE2, rescued SARS-CoV-2 replication. Intranasal hACE2-lentivirus transduction of C57BL/6J mice permitted significant virus replication in lungs. RNA-Seq analyses illustrated that the model involves an acute inflammatory disease followed by resolution and tissue repair, with a transcriptomic profile similar to that seen in COVID-19 patients. Intranasal hACE2-lentivirus transduction of IFNAR-/- and IL-28RA-/- mice lungs was used to illustrate that loss of type I or III interferon responses have no significant effect on virus replication. However, their importance in driving inflammatory responses was illustrated by RNA-Seq analyses. We also demonstrate the utility of the hACE2-lentivirus transduction system for vaccine evaluation in C57BL/6J mice. The ACE2-lentivirus system thus has broad application in SARS-CoV-2 research, providing a tool for both mutagenesis studies and mouse model development.

AUTHOR SUMMARYSARS-CoV-2 uses the human ACE2 (hACE2) receptor to infect cells, but cannot infect mice because the virus cannot bind mouse ACE2 (mACE2). We use an ACE2-lentivirus system in vitro to identify four key amino acids in mACE2 that explain why SARS-CoV-2 cannot infect mice. hACE2-lentivirus was used to express hACE2 in mouse lungs in vivo, with the inflammatory responses after SARS-CoV-2 infection similar to those seen in human COVID-19. Genetically modified mice were used to show that type I and III interferon signaling is required for the inflammatory responses. We also show that the hACE2-lentivirus mouse model can be used to test vaccines. Overall this paper demonstrates that our hACE2-lentivirus system has multiple applications in SARS-CoV-2 and COVID-19 research. Maternal microbiota Bifidobacterium promotes placental morphogenesis, nutrient transport and fetal growth in mice The gut microbiota plays a central role in regulating host metabolism. However, while substantial progress has been made in discerning how the microbiota influences host functions post birth and beyond, little is known about how key members of the maternal gut microbiota can influence feto-placental growth. Here, using germ-free and specific-pathogen-free mice, we demonstrate that the bacterium Bifidobacterium breve UCC2003 modulates maternal body adaptations, placental structure and nutrient transporter capacity, with implications for fetal metabolism and growth. The effects of B. breve UCC2003 on feto-placental growth are mediated, in part, by changes in the maternal and placental metabolome (i.e. acetate and carnitine). Histological analysis of the placenta confirmed that Bifidobacterium modifies placental structure via changes in Igf2P0, Dlk1, Mapk1 and Mapk14 expression. Additionally, B. breve UCC2003, acting through Slc2a1 and Fatp1-4 transporters, was shown to restore fetal glycaemia and fetal growth in association with changes in the fetal hepatic transcriptome. This study provides knowledge towards a novel and safe therapeutic strategy for treating pregnancy disorders via modulation of the maternal gut microbiota. Fatal neuroinvasion and SARS-CoV-2 tropism in K18-hACE2 mice is partially independent on hACE2 expression Animal models recapitulating distinctive features of severe COVID-19 are critical to enhance our understanding of SARS-CoV-2 pathogenesis. Transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) under the cytokeratin 18 promoter (K18-hACE2) represent a lethal model of SARS-CoV-2 infection. The precise mechanisms of lethality in this mouse model remain unclear. Here, we evaluated the spatiotemporal dynamics of SARS-CoV-2 infection for up to 14 days post-infection. Despite infection and moderate pneumonia, rapid clinical decline or death of mice was invariably associated with viral neuroinvasion and direct neuronal injury (including brain and spinal neurons). Neuroinvasion was observed as early as 4 dpi, with virus initially restricted to the olfactory bulb supporting axonal transport via the olfactory neuroepithelium as the earliest portal of entry. No evidence of viremia was detected suggesting neuroinvasion occurs independently of entry across the blood brain barrier. SARS-CoV-2 tropism was not restricted to ACE2-expressing cells (e.g., AT1 pneumocytes), and some ACE2-positive lineages were not associated with the presence of viral antigen (e.g., bronchiolar epithelium and brain capillaries). Detectable ACE2 expression was not observed in neurons, supporting overexpression of ACE2 in the nasal passages and neuroepithelium as more likely determinants of neuroinvasion in the K18-hACE2 model. Although our work incites caution in the utility of the K18-hACE2 model to study global aspects of SARS-CoV-2 pathogenesis, it underscores this model as a unique platform for exploring the mechanisms of SARS-CoV-2 neuropathogenesis that may have clinical relevance acknowledging the growing body of evidence that suggests COVID-19 may result in long-standing neurologic consequences.

IMPORTANCECOVID-19 is predominantly a respiratory disease caused by SARS-CoV-2 that has infected more than 191 million people with over 4 million fatalities (2021-07-20). The development of animal models recapitulating distinctive features of severe COVID-19 is critical to enhancing our understanding of SARS-CoV-2 pathogenesis and in the evaluation of vaccine and therapeutic efficacy. Transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) under the cytokeratin 18 promoter (K18-hACE2) represent a lethal model of SARS-CoV-2 infection. Here, we show lethality of this model is invariably associated with viral neuroinvasion linked with viral replication and assembly. Importantly, pneumonia albeit invariably present was generally moderate with the absence of culturable infectious virus at peak neuroinvasion. The dynamics of viral neuroinvasion and pneumonia were only partially dependent on hACE2. Overall, this study provides an in-depth sequential characterization of the K18-hACE2 model following SARS-CoV-2 infection, highlighting its significance to further study the mechanisms of SARS-CoV-2 neuropathogenesis. The RAG1 Ubiquitin Ligase Domain Enhances Assembly and Selection of T Cell Receptor Genes to Restrain the Autoimmune Hazard of Generating T Cell Receptor Diversity RAG1/RAG2 (RAG) endonuclease-mediated assembly of diverse lymphocyte antigen receptor genes by V(D)J recombination is critical for the development and immune function of T and B cells. However, this process creates highly self-reactive cells that must be properly selected to suppress autoimmunity. The RAG1 protein contains a ubiquitin ligase domain that stabilizes RAG1 and stimulates RAG endonuclease activity in vitro. We report that mice with a mutation that inactivates the RAG1 ubiquitin ligase in vitro exhibit modestly reduced thymic cellularity, decreased assembly and altered repertoires of T cell receptor (TCR) {beta} and  genes in thymocytes, and impaired thymocyte developmental transitions that require the assembly of TCR{beta} or  genes and signaling by their proteins. These RAG1 mutant mice also exhibit less efficient positive selection and superantigen-mediated negative selection of conventional {beta} T cells, 2) impaired differentiation of iNKT lineage {beta} T cells, and 3) CD4+ {beta} T cells with elevated autoimmune potential. Our findings demonstrate that the RAG1 ubiquitin ligase domain functions in vivo to stimulate the assembly and selection of TCR{beta} and TCR genes, thereby establishing replete diversity of {beta} TCRs and {beta} T cell lineages while restraining the inherent autoimmune hazard of generating diverse antigen specificities. Sound localization in world and head-centered space in ferrets The location of sounds can be described in multiple coordinate systems that are defined relative to ourselves, or the world around us. Evidence from neural recordings in animals point towards the existence of both head-centered and world-centered representations of sound location in the brain; however, it is unclear whether such neural representations have perceptual correlates in the sound localization abilities of non-human listeners. Here, we establish novel behavioral tests to determine the coordinate systems in which ferrets can localize sounds. We found that ferrets could learn to discriminate between sound locations that were fixed in either world-centered or head-centered space, across wide variations in sound location in the alternative coordinate system. Using probe sounds to assess broader generalization of spatial hearing, we demonstrated that in both head and world-centered tasks, animals used continuous maps of auditory space to guide behavior. Single trial responses of individual animals were sufficiently informative that we could then model sound localization using speaker position in specific coordinate systems and accurately predict ferrets actions in held-out data. Our results indicate that an animal model in which neurons are known to be tuned to sound location in egocentric and allocentric reference frames can also localize sounds in multiple head and world-centered spaces.

Significance StatementHumans can describe the location of sounds either relative to themselves, or in the world, independent of their momentary position. These different spaces are also represented in the activity of neurons in animals, but its not clear whether non-human listeners also perceive both head and world-centered sound location. Here, we designed two behavioral tasks in which ferrets had to discriminate between two sounds using their position in the world, or relative to the head. Subjects learnt to solve both problems and showed the ability to generalize sound location in each space when presented with infrequent probe sounds. These findings reveal a perceptual correlate of neural sensitivity previously observed in the ferret brain and establish that, like humans, ferrets can access an auditory map of their local environment. Extent of Molecular Chaperone Association Might Determine Fates of Membraneless Organelles during Aging in C. elegans Proteome imbalance can lead to protein misfolding and aggregation which is associated with pathologies. Protein aggregation can also be an active, organized process and can be exploited by cells as a survival strategy. In adverse conditions, it is beneficial to deposit the proteins in a condensate rather degrading and resynthesizing. Membraneless organelles (MLOs) are biological condensates formed through liquid-liquid phase separation (LLPS), involving cellular components such as nucleic acids and proteins. LLPS is a regulated process, which when perturbed, can undergo a transition from a physiological liquid condensate to pathological solid-like protein aggregates.

To understand how the MLO-associated proteins (MLO-APs) behave during aging, we performed a comparative meta-analysis with age related proteome of C. elegans. We found that the MLO-APs are highly abundant throughout the lifespan. Interestingly, they are aggregating more in long-lived mutant worms compared to the age matched wildtype worms. GO term analysis revealed that the cell cycle and embryonic development are among the top enriched processes in addition to RNP components in insoluble proteome. Considering antagonistic pleotropic nature of these developmental genes and post mitotic status of C. elegans, we assume that these proteins phase transit during post development. As the organism ages, these MLO-APs either mature to become more insoluble or dissolve in uncontrolled manner. However, in the long-lived daf-2 mutant worms, the MLOs may attain protective states due to extended availability and association of molecular chaperones. 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. Dynamic Phosphorylation of RGS Provides Spatial Regulation of MAP Kinase And Promotes Completion of Cytokinesis during the Yeast Pheromone Response Yeast use a G-protein coupled receptor (GPCR) signaling pathway to detect mating pheromone, arrest in G1, and direct polarized growth towards the potential mating partner. The primary negative regulator of this pathway is the regulator of G-protein signaling (RGS), Sst2, which induces G GTPase activity and subsequent inactivation of all downstream signaling including a MAPK cascade. The MAPK Fus3 phosphorylates the RGS in response to pheromone, but the role of this modification is unknown. We set out to examine the role of RGS phosphorylation during the pheromone response. We found that RGS phosphorylation peaks early in the pheromone response and diminishes RGS localization to the polarity site and focuses MAPK complexes there. At later time points, RGS is predominantly unphosphorylated, which promotes RGS localization to the polar cap and broadens the distribution of MAPK complexes relative to the Cdc42 polarity machinery. Surprisingly, we found that phosphorylation of the RGS is required for the completion of cytokinesis prior to pheromone induced growth. The completion of cytokinesis in the presence of pheromone is promoted by the formin Bnr1 and the kelch-repeat protein, Kel1, both proteins previously found to interact with the RGS. Chromatin-contact atlas reveals disorder-mediated protein interactions RNA-binding proteins (RBPs) play diverse roles in regulating co-transcriptional RNA-processing and chromatin functions, but our knowledge of the repertoire of chromatin-associated RBPs (caRBPs) and their interactions with chromatin remains limited. Here, we developed SPACE (Silica Particle Assisted Chromatin Enrichment) to isolate global and regional chromatin components with high specificity and sensitivity, and SPACEmap to identify the chromatin-contact regions in proteins. Applied to mouse embryonic stem cells, SPACE identified 1,459 chromatin-associated proteins, [~]48% of which are annotated as RBPs, indicating their dual roles in chromatin and RNA-binding. Additionally, SPACEmap stringently verified chromatin-binding of 404 RBPs and identified their chromatin-contact regions. Notably, SPACEmap showed that about half of the caRBPs bind to chromatin by intrinsically disordered regions (IDRs). Studying SPACE and total proteome dynamics from mES cells grown in 2iL and serum medium indicates significant correlation (R = 0.62). One of the most dynamic caRBPs is Dazl, which we find co-localized with PRC2 at transcription start sites of genes that are distinct from Dazl mRNA binding. Dazl and other PRC2-colocalised caRBPs are rich in intrinsically disordered regions (IDRs), which could contribute to the formation and regulation of phase-separated PRC condensates. Together, our approach provides an unprecedented insight into IDR-mediated interactions and caRBPs with moonlighting functions in native chromatin. Naming of human diseases on the wrong side of history BackgroundIn the medical sphere, understanding naming conventions strengthen the integrity of naming human diseases remains nominal rather than substantial yet. Since the current nosology-based standard for human diseases could not offer a one-size-fits-all corrective mechanism, many idiomatic but flawed names frequently appear in scientific literature and news outlets at the cost of sociocultural impacts.

ObjectiveWe attempt to examine the ethical oversights of current naming practices and propose heuristic rationales and approaches to determine a pithy name instead of an inopportune nosology.

MethodsFirst, we examined the compiled global online news volumes and emotional tones on some inopportune nosology like German measles, Middle Eastern Respiratory Syndrome, Spanish flu, Hong Kong flu, and Huntingtons disease in the wake of COVID-19. Second, we prototypically scrutinize the lexical dynamics and pathological differentials of German measles and common synonyms by leveraging the capacity of the Google Books Ngram Corpus. Third, we demonstrated the empirical approaches to curate an exclusive substitute for an anachronistic nosology German measles based on deep learning models and post-hoc explanations.

ResultsThe infodemiological study shows that the public informed the offensive names with extremely negative tones in textual and visual narratives. The findings of the historiographical study indicate that many synonyms of German measles did not survive, while German measles became an anachronistic usage, and rubella has taken the dominant place since 1994. The PubMedBERT model could identify rubella as a potential substitution for German measles with the highest semantic similarity. The results of the semantic drift experiments further indicate that rubella tends to survive during the ebb and flow of semantic drift.

ConclusionsOur findings indicate that the nosological evolution of anachronistic names could result in sociocultural impacts without a corrective mechanism. To mitigate such impacts, we introduce some ethical principles for formulating an improved naming scheme. Based on deep learning models and post-hoc explanations, our illustrated experiments could provide hallmark references to the remedial mechanism of naming practices and pertinent credit allocations. An hidden Markov model to estimate homozygous-by-descent probabilities associated with nested layers of ancestors Inbreeding results from the mating of related individuals and has negative consequences because it brings together deleterious variants in one individual. Genomic estimates of the inbreeding coefficients are preferred to pedigree-based estimators as they measure the realized inbreeding levels and they are more robust to pedigree errors. Several methods identifying homozygous-by-descent (HBD) segments with hidden Markov models (HMM) have been recently developed and are particularly valuable when the information is degraded or heterogeneous (e.g., low-fold sequencing, low marker density, heterogeneous genotype quality or variable marker spacing). We previously developed a multiple HBD class HMM where HBD segments are classified in different groups based on their length (e.g., recent versus old HBD segments) but we recently observed that for high inbreeding levels with many HBD segments, the estimated contributions might be biased towards more recent classes (i.e., associated with large HBD segments) although the overall estimated level of inbreeding remained unbiased. We herein propose a new model in which the HBD classification is modeled in successive nested levels with decreasing expected HBD segment lengths, the underlying exponential rates being directly related to the number of generations to the common ancestor. The non-HBD classes are now modeled as a mixture of HBD segments from later generations and shorter non-HBD segments (i.e., both with higher rates). The new model has improved statistical properties and performs better on simulated data compared to our previous version. We also show that the parameters of the model are easier to interpret and that the model is more robust to the choice of the number of classes. Overall, the new model results in an improved partitioning of inbreeding in different HBD classes and should be preferred. The first multi-tissue diel genome-scale metabolic model of a woody plant highlights the suberin biosynthesis pathways in Quercus suber In the last decade, genome-scale metabolic models have been increasingly used to study plant metabolic behavior at the tissue and multi-tissue level under different environmental conditions. Quercus suber, also known as the cork oak tree, is one of the most important forest communities of the Mediterranean/Iberian region. In this work, we present the genome-scale metabolic model of the Q. suber (iEC7871), the first of a woody plant. The metabolic model comprises 7871 genes, 6231 reactions, and 6481 metabolites across eight compartments. Transcriptomics data was integrated into the model to obtain tissue-specific models for the leaf, inner bark, and phellogen, with specific biomass compositions. The tissue-specific models were merged into a diel multi-tissue metabolic model to predict interactions among the three tissues at the light and dark phases. The metabolic models were also used to analyze the pathways associated with the synthesis of suberin monomers. Nevertheless, the models developed in this work can provide insights into other aspects of the metabolism of Q. suber, such as its secondary metabolism and cork formation. 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. Distributed brain co-processor for tracking electrophysiology and behavior during electrical brain stimulation Early implantable epilepsy therapy devices provided open-loop electrical stimulation without brain sensing, computing, or an interface for synchronized behavioral inputs from patients. Recent epilepsy stimulation devices provide brain sensing but have not yet developed analytics for accurately tracking and quantifying behavior and seizures. Here we describe a distributed brain co-processor providing an intuitive bi-directional interface between patient, implanted neural stimulation and sensing device, and local and distributed computing resources. Automated analysis of continuous streaming electrophysiology is synchronized with patient reports using a hand-held device and integrated with distributed cloud computing resources for quantifying seizures, interictal epileptiform spikes, and patient symptoms during therapeutic electrical brain stimulation. The classification algorithms for interictal epileptiform spikes and seizures were developed and parameterized using long-term ambulatory data from 9 humans and 8 canines with epilepsy, and then implemented prospectively in out-of-sample testing in 2 pet canines and 4 humans with drug resistant epilepsy living in their natural environments. MetaTrass: High-quality metagenome assembly on the human gut microbiome by co-barcoding sequencing reads With the development of sequencing technologies and computational analysis in metagenomics, the genetic diversity of non-conserved regions has been receiving intensive attention to unravel the human gut microbial community. However, it remains a challenge to obtain enough microbial draft genomes at a high resolution from a single sample. In this work, we presented MetaTrass with a strategy of binning first and assembling later to assemble high-quality draft genomes based on metagenomics co-barcoding reads and the public reference genomes. We applied the tool to the single tube long fragment reads datasets for four human faecal samples, and generated more high-quality draft genomes with longer contiguity and higher resolution than the common combination strategies of genome assembling and binning. A total of 178 high-quality genomes was successfully assembled by MetaTrass, but the maximum of 58 was generated by the optimal common combination strategy in our tests. These high-quality genomes paved the way for genetic diversity and lineage analysis among different samples. With the high capability of assembling high-quality genomes of metagenomics datasets, MetaTrass will facilitate the study of spatial characters and dynamics of complex microbial communities at high resolution. The open-source code of MetaTrass is available at https://github.com/BGI-Qingdao/MetaTrass. RNA-binding protein Mub1 and the nuclear RNA exosome act to fine-tune environmental stress response The nuclear RNA exosome plays a key role in mediating degradation and processing of multiple cellular RNAs. Recognition of the specific RNA substrates by the exosome is mediated by the RNA-binding co-factors. Transient binding of co-factors either to the exosome or the substrate RNAs as well as their rapid decay make identification of the co-factors challenging. Here, we employ a comparative poly(A)+ RNA interactome capture approach in the fission yeast exosome mutants to identify proteins that interact with poly(A)+ RNA in an exosome-dependent manner. Our analyses identified multiple proteins whose occupancy on RNA is altered in the exosome mutants including zinc-finger protein Mub1. Mub1 is required to maintain the levels of a subset of the exosome RNA substrates including mRNAs encoding for stress-responsive proteins. Removal of the zinc finger domain leads to loss of RNA suppression under non-stressed conditions, altered expression of heat shock genes in response to stress, and reduced growth at elevated temperature. These findings highlight importance of exosome-dependent mRNA degradation in buffering gene expression networks to mediate cellular adaptation to stress. 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. Factors behind intraspecific competition during post-glacial recolonization: a Norway spruce case study O_LITo a large extent, the current distribution and population structure of many species were shaped by the cycles of isolation in glacial refugia and subsequent population expansions. Isolation in, and post-glacial expansion through, heterogeneous environments led to either neutral or adaptive divergence. Norway spruce is no exception, and its current distribution is the consequence of a complex interplay between evolutionary forces.
C_LIO_LIWe investigated population differentiation and adaptations of Norway spruce for juvenile growth, diameter of the trunk at breast height and its components: wood density and tracheid traits. Data from 4,461 phenotyped and genotyped Norway spruce from 396 half-sib families in two progeny tests were used to test for divergent selection in the framework of QST vs FST, and to carry out multiple Genome-Wide Association Studies.
C_LIO_LIWe show that (i) the macroscopic resultant trait (trunk diameter), unlike its microscopic components (tracheid dimensions) and juvenile growth, was under divergent selection, and (ii) adaptation predated the Last Glaciation Maximum.
C_LIO_LIAltogether, the current variation in these phenotypic traits in Norway spruce is better explained by local adaptation to ancestral environments than to current ones, where populations were partly pre-adapted mainly through growth-related traits.
C_LI Differential impact of mutations in cell cycle checkpoint kinases on breast cancer presentation and prognosis. Cell cycle checkpoint kinases ATM/Chk2 and ATR/Chk1 are important tumor suppressors that are activated by DNA damage and other stressors to arrest replication. Germline variants in ATM and CHEK2 associate with increased incidence of estrogen receptor positive (ER+)/HER2- breast cancer and some evidence suggests that somatic inactivation of ATM/Chk2 induces therapy resistance in ER+/HER2- breast cancer patients. However, the relative contributions of germline and somatic inactivation of each of the four cell cycle checkpoint kinases to ER+/HER2- and ER-/PR-/HER2- (or triple negative breast cancer; TNBC) breast cancer incidence and outcomes has not yet been systematically assessed. Here, we comprehensively analyze associations between mutations in each cell cycle checkpoint kinase gene with age at diagnosis, tumor characteristics, and patient survival outcomes using six breast cancer datasets. Overall, we find that of all the cell cycle checkpoint kinases, CHEK2 (p=0.001) is the only gene that is preferentially mutated in ER+/HER2- breast cancer samples relative to TNBCs. CHEK2 mutations also associate with younger age at diagnosis of metastatic ER+/HER2- breast cancer (median age 41.5 years compared to 50 years for CHEK2 wildtype patients, p=0.03) that is highly PR positive (10% increase in PR positivity in metastatic vs primary CHEK2 mutant tumors, as opposed to a 25% decrease in PR positivity in CHEK2 wildtype tumors, p=0.03). These associations appear to be driven by germline variants, rather than somatic mutations. Whether germline or somatic, deleterious (truncating, frameshift or splice site) mutations in CHEK2 associate with rapid disease progression in response to standard first line endocrine therapy when compared to tumors with wildtype CHEK2 in two independent datasets (HR=6.15, p=0.01). Conversely, neither ATM nor ATR mutations are enriched in ER+/HER2- breast cancers relative to TNBC. However, co-incident mutation of ATR and TP53 is 2-fold enriched in this subset (p=0.002), and further enriched in metastatic (3.3%) vs primary (1%) ER+/HER2- breast cancers (p=0.002). This co-incident mutation of ATR and TP53 associates with decreased PR positivity in primary ER+/HER2- breast cancer diagnoses (p<0.0001) and significantly worse metastasis-free survival than mutations in either ATR or TP53 alone in two independent datasets (HR=2.01, p=0.007). This association is not specific to ER+/HER2- breast cancer but is observable in ER- breast cancer patients as well. These results provide the first systematic analysis of the contribution of germline and somatic mutations in cell cycle checkpoint kinases to tumor characteristics affecting patient prognosis and treatment response. They demonstrate a unique role for CHK2 in ER signaling and response to endocrine therapy, and a more universal role for ATR in combination with TP53 in metastatic progression across breast cancer subtypes. These findings provide rationale for streamlined testing of checkpoint kinase mutations as prognostic markers of metastatic potential and/or predictive markers of responsiveness to endocrine treatment in breast cancer patients. Heterogeneous but not random: Cargo degradation in phagosomes is kinetically coupled to 1 their intracellular mobility Immune cells degrade internalized pathogens in phagosomes through sequential biochemical changes. The degradation must be fast enough for effective infection control. The presumption is that each phagosome degrades cargos autonomously with a distinct but stochastic kinetic rate. Here we report that the degradation kinetics of individual phagosomes is not stochastic but coupled to their intracellular motility. By engineering RotSensors that are optically anisotropic, magnetic responsive, and fluorogenic in response to degradation activities in phagosomes, we monitored cargo degradation kinetics in single phagosomes simultaneously with their translational and rotational dynamics. We show that phagosomes that move faster centripetally are more likely to encounter and fuse with lysosomes, thereby acidifying faster and degrading cargos more efficiently. The degradation rates increase nearly linearly with the translational and rotational velocities of phagosomes. Our results indicate that the centripetal motion of phagosomes functions as a clock for controlling the progression of cargo degradation. Data-Driven Network Models for Genetic Circuits From Time-Series Data with Incomplete Measurements Synthetic gene networks are frequently conceptualized and visualized as static graphs. This view of biological programming stands in stark contrast to the transient nature of biomolecular interaction, which is frequently enacted by labile molecules that are often unmeasured. Thus, the network topology and dynamics of synthetic gene networks can be difficult to verify in vivo or in vitro, due to the presence of unmeasured biological states. Here we introduce the dynamical structure function as a new mesoscopic, data-driven class of models to describe gene networks with incomplete measurements. We introduce a network reconstruction algorithm and a code base for reconstructing the dynamical structure function from data, to enable discovery and visualization of graphical relationships in a genetic circuit diagram as time-dependent functions rather than static, unknown weights. We prove a theorem, showing that dynamical structure functions can provide a data-driven estimate of the size of crosstalk fluctuations from an idealized model. We illustrate this idea with numerical examples. Finally, we show how data-driven estimation of dynamical structure functions can explain failure modes in two experimentally implemented genetic circuits, a historical genetic circuit and a new E. coli based transcriptional event detector. Host species identity shapes the diversity and structure of insect microbiota As for most of the life that inhabits our planet, microorganisms play an essential role in the fitness of insects, including nutrition, reproduction, defence, and many other functions. More recently, we assisted in an exponential growth of studies describing the taxonomical composition of bacterial communities across insects phylogeny. However, there is still an outstanding question that needs to be answered: which factors contribute most to shape insects microbiomes? This study tries to find an answer to this question by taking advantage of publicly available sequencing data and reanalysing over 4,000 samples of insect-associated bacterial communities under a common framework. Results suggest that insect taxonomy has a wider impact on the structure and diversity of their associated microbial communities than the other factors considered (diet, sex, life stage, sample origin, and treatment). However, when specifically testing for signatures of co-diversification of insect species and their microbiota, analyses found weak support for this, suggesting that while insect species strongly drive the structure and diversity of insect microbiota, the diversification of those microbial communities did not follow their hosts phylogeny. Furthermore, a parallel survey of the literature highlights several methodological limitations that need to be considered in future research endeavours. 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.