A burst of regulatory and protein innovation at the origin of placental mammals drove the emergence of placenta and underpins divergent early pregnancy strategies in modern mammals. Summary paragraphThe origin of live birth in mammals [~]148 million years ago was a dramatic shift in reproductive strategy, yet the molecular changes that established mammal viviparity are largely unknown. Although progesterone receptor signalling predates the origin of mammals andis highly conserved in, and critical for, successful mammal pregnancy, it alone cannot explain the origin and subsequent diversity of implantation strategies throughout the placental mammal radiation. MiRNAs are known to be flexible and dynamic regulators with a well established role in the pathophysiology of mammal placenta. We propose that a dynamic core microRNA (miRNA) network originated early in placental mammal evolution, responds to conserved mammal pregnancy cues (e.g. progesterone), and facilitates species-specific responses. Here we identify 13 miRNAs that arose at the origin of placental mammals and were subsequently retained in all descendent lineages. The expression of these 13 miRNAs in response to early pregnancy molecules is regulated in a species-specific manner in endometrial epithelia of species with extremes of implantation strategies. Furthermore, these 13 miRNAs preferentially target 84 proteins under positive selective pressure on ancestral eutherian. Discovery of this core "live-birth" toolkit and specifically adapted proteins helps explain the origin and evolution of the placenta in mammals.
Ecological correlates of gene family size in a pine-feeding sawfly genome and across Hymenoptera A central goal in evolutionary biology is to determine the predictability of adaptive genetic changes. Despite many documented cases of convergent evolution at individual loci, little is known about the repeatability of gene family expansions and contractions. To address this void, we examined gene family evolution in the redheaded pine sawfly Neodiprion lecontei, a non-eusocial hymenopteran and exemplar of a pine-specialized lineage evolved from angiosperm-feeding ancestors. After assembling and annotating a draft genome, we manually annotated multiple gene families with chemosensory, detoxification, or immunity functions and characterized their genomic distributions and evolutionary history. Our results suggest that expansions of bitter gustatory receptor (GR), clan 3 cytochrome P450 (CYP3), and antimicrobial peptide (AMP) subfamilies may have contributed to pine adaptation. By contrast, there was no evidence of recent gene family contraction via pseudogenization. Next, we compared the number of genes in these same families across insect taxa that vary in diet, dietary specialization, and social behavior. In Hymenoptera, herbivory was associated with small GR and olfactory receptor (OR) families, eusociality was associated with large OR and small AMP families, and--unlike investigations in more closely related taxa--ecological specialization was not related to gene family size. Overall, our results suggest that gene families that mediate ecological interactions may expand and contract predictably in response to particular selection pressures, however, the ecological drivers and temporal pace of gene gain and loss likely varies considerably across gene families.
ZIKV disrupts placental ultrastructure and drug transporter expression in mice Congenital Zika virus (ZIKV) infection can induce fetal brain abnormalities. Here, we investigated whether maternal ZIKV infection affects placental physiology and metabolic transport potential and impacts the fetal outcome, regardless of viral presence in the fetus at term. Low (103 PFU-ZIKVPE243; low ZIKV) and high (5x107 PFU-ZIKVPE243; high ZIKV) virus titers were injected into immunocompetent (ICompetent C57BL/6) and immunocompromised (ICompromised A129) mice at gestational day (GD) 12.5 for tissue collection at GD18.5 (term). High ZIKV elicited fetal death rates of 66% and 100%, whereas low ZIKV induced fetal death rates of 0% and 60% in C57BL/6 and A129 dams, respectively. All surviving fetuses exhibited intrauterine growth restriction (IUGR) and decreased placental efficiency. High-ZIKV infection in C57BL/6 and A129 mice resulted in virus detection in maternal spleens and placenta, but only A129 fetuses presented virus RNA in the brain. Nevertheless, pregnancies in both strains produced fetuses with decreased head sizes (p<0.05). Low-ZIKV-A129 dams had higher IL-6 and CXCL1 levels (p<0.05), and their placentas showed increased CCL-2 and CXCL-1 contents (p<0.05). In contrast, low-ZIKV-C57BL/6 dams had an elevated CCL2 serum level and increased type I and II IFN expression in the placenta. Notably, less abundant microvilli and mitochondrial degeneration were evidenced in the placental labyrinth zone (Lz) of ICompromised and high-ZIKV-ICompetent mice but not in low-ZIKV-C57BL/6 mice. In addition, decreased placental expression of the drug transporters P-glycoprotein (P-gp) and breast cancer resistance protein (Bcrp) and the lipid transporter Abca1 was detected in all ZIKV-infected groups, but Bcrp and Abca1 were only reduced in ICompromised and high-ZIKV ICompetent mice. Our data indicate that gestational ZIKV infection triggers specific proinflammatory responses and affects placental turnover and transporter expression in a manner dependent on virus concentration and maternal immune status. Placental damage may impair proper fetal-maternal exchange function and fetal growth/survival, likely contributing to congenital Zika syndrome. Early functional mismatch between breast cancer cells and their tumour microenvironment suppresses long term growth Cancer cells thrive embedded in a fine-tuned cellular and extracellular environment or tumour microenvironment (TME). There is a general understanding of a co-evolution between cancer cells and their surrounding TME, pointing at a functional connection between cancer cells characteristics and the perturbations induced in their surrounding tissue. However, whether this functional connection needs to be set from the start or if aggressive cancer cells can always be dominating their microenvironment has never been formally proven with a dedicated experimental setting where malignant cells can be challenged to grow in a different TME from the one they would naturally create. Here we generated an experimental setting where we transiently perturb the secretory profile of aggressive breast cancer cells without affecting their intrinsic growth ability. This led to the initial establishment of an atypical TME. Interestingly, even if initially tumours are formed, this atypical TME evolves to impair long term in vivo cancer growth. Using a combination of in vivo transcriptomics, protein arrays and in vitro co-cultures, we found that the atypical TME culminates in the infiltration of macrophages with STAT1high activity. These macrophages show strong anti-tumoural functions which reduce long-term tumour growth, despite lacking canonical M1 markers. Importantly, gene signatures of the mesenchymal compartment of the TME, as well as the anti-tumoural macrophages show striking prognostic power-correlating with less aggressive human breast cancers. Game of theories: an agent-based model of how variation in contest cost-benefits determines the evolution of contest resolution rules Game-theory based models are used to understand rules that animals use to settle contests over indivisible resources. However, the empirical literature of contests indicates controversial support to models, with some species supporting different models and other species showing no support to any model. Since strategies used to resolve contests may have different associated costs, it is possible that different conditions have determined the evolution of distinct assessment strategies used by animals. We used an agent-based model to explore the importance of the following conditions: resource availability, probability of reproduction with resource, and damage costs on evolution of assessment strategies. We used self- and mutual-assessment models as a heurist framework to build agents with different assessment strategies. In our model, agents competed for resources in scenarios with different combinations of resource availability, probability of reproduction with resource, and damage costs. We found that agents following the self-assessment with damage strategy were prevalent in scenarios with no probability of reproduction without the resource, independently of other variables. We also found that agents following the non-aggressive strategy occurred in all scenarios. However, agents using the non-aggressive strategy were prevalent only in scenarios with probability of reproduction with the resource. Finally, we observed that agents using mutual-assessment occurred only in a scenario with high risk of damage, low availability of resources, and with probability of reproduction without the resource. These results indicate that agents following the self-assessment with damage and non-aggressive strategies may be able to stay at most scenarios. Morphology of immatures of the thelytokous ant, Monomorium triviale Wheeler (Formicidae: Myrmicinae: Solenopsidini) with descriptions of the extraordinary last-instar queen larvae The ant genus Monomorium is one of the most species-rich but taxonomically problematic groups in the hyperdiverse subfamily Myrmicinae. An East Asian species, M. triviale Wheeler, produces both reproductive queens and sterile workers via obligate thelytokous parthenogenesis. Here, we describe the immature forms of M. triviale based on light and scanning electron microscopy observations, with a note on the striking caste dimorphism in the last larval instar. The last-instar queen larvae were easily recognized by their large size, "aphaenogastroid" body shape, and rows of doorknob-like tubercles on the lateral and dorsal body surface. This type of queen-specific structure has not been found in ants in general, let alone congeneric species found in Japan. In stark contrast to the queen larvae, worker larvae showed a "pheidoloid" body shape and a body surface similar to other ants. The worker larvae were estimated to have three instars, consistent with previously described congeners. The pupae of both castes had no cocoon, a characteristic commonly described in other Myrmicinae species. In total, the developmental period from egg to adult worker averaged 59 days under 25{degrees}C. We discuss possible functions of the tubercles of queen larvae based on previous studies. mTORC2 contributes to murine systemic autoimmunity The development of many systemic autoimmune diseases, including systemic lupus erythematosus, is associated with overactivation of the type I interferon (IFN) pathway, lymphopenia, and increased follicular helper T (Tfh) cell differentiation. However, the cellular and molecular mechanisms underlying these immunological perturbations remain incompletely understood. Here we show that the mechanistic target of rapamycin complex 2 (mTORC2) promotes Tfh differentiation and disrupts Treg homeostasis. Inactivation of mTORC2 in total T cells, but not in Tregs, greatly ameliorated the immunopathology in a systemic autoimmunity mouse model. This was associated with reduced Tfh differentiation, B cell activation, and reduced T cell glucose metabolism. Finally, we show that type I IFN can synergize with TCR ligation to activate mTORC2 in T cells, which partially contributes to T cell lymphopenia. These data indicate that mTORC2 may act as downstream of type I IFN, TCR, and costimulatory receptor ICOS, to promote glucose metabolism, Tfh differentiation, and T cell lymphopenia, but not to suppress Treg function in systemic autoimmunity. Our results suggest that mTORC2 might be a rational target for systemic autoimmunity treatment. Streptococcus agalactiae MprF synthesizes a novel cationic glycolipid and contributes to brain entry and meningitis Bacterial membrane lipids are critical for membrane bilayer formation, cell division, protein localization, stress responses, and pathogenesis. Despite their critical roles, membrane lipids have not been fully elucidated for many pathogens. Here, we report the discovery of a novel cationic glycolipid, Lysyl-Glucosyl-Diacylglycerol (Lys-Glc-DAG) that is synthesized in high abundance by the bacterium Streptococcus agalactiae (Group B Streptococcus, GBS). To our knowledge, Lys-Glc-DAG is more positively charged than any other known lipids. Lys-Glc-DAG carries two positive net charges per molecule, distinct from the widely described lysylated phospholipid Lysyl-phosphatidylglycerol (Lys-PG) which carries one positive net charge due to the presence of a negatively charged phosphate moiety. We use normal phase liquid chromatography (NPLC) coupled with electrospray ionization (ESI) high-resolution tandem mass spectrometry (HRMS/MS) and genetic approaches to determine that Lys-Glc-DAG is synthesized by the enzyme MprF in GBS, which covalently modifies the neutral glycolipid Glc-DAG with the cationic amino acid lysine. GBS is a leading cause of neonatal meningitis, which requires traversal of the endothelial blood-brain barrier (BBB). We demonstrate that GBS strains lacking mprF exhibit a significant decrease in the ability to invade BBB endothelial cells. Further, mice challenged with a GBS{Delta}mprF mutant developed bacteremia comparably to Wild-Type infected mice yet had less recovered bacteria from brain tissue and a lower incidence of meningitis. Thus, our data suggest that Lys-Glc-DAG may contribute to bacterial uptake into host cells and disease progression. Importantly, our discovery provides a platform for further study of cationic lipids at the host-pathogen interface. Tetraspanin Cd9b and Cxcl12a/Cxcr4b have a synergistic effect on the control of collective cell migration Collective cell migration is essential for embryonic development and homeostatic processes. During zebrafish development, the posterior lateral line primordium (pLLP) navigates along the embryo flank by collective cell migration. The chemokine receptors, Cxcr4b and Cxcr7b, as well as their cognate ligand, Cxcl12a, are essential for this process. We corroborate that knockdown of the zebrafish cd9 tetraspanin orthologue, cd9b, results in mild pLL abnormalities. Through generation of CRISPR and TALEN mutants, we show that cd9a and cd9b function partially redundantly in pLLP migration, which is delayed in the cd9b single and cd9a; cd9b double mutants. This delay led to a transient reduction in neuromast numbers. Loss of both Cd9a and Cd9b sensitized embryos to reduced Cxcr4b and Cxcl12a levels. Together these results provide evidence that Cd9 modulates collective cell migration of the pLLP during zebrafish development. One interpretation of these observations is that Cd9 contributes to more effective chemokine signalling. SARS-CoV-2 infection induces soluble platelet activation markers and PAI-1 in the early moderate stage of COVID-19 IntroductionCoagulation dysfunction and thromboembolism emerge as strong comorbidity factors in severe COVID-19. However, it is unclear when particularly platelet activation markers and coagulation factors dysregulated during the pathogenesis of COVID-19. Here, we sought to assess the levels of coagulation and platelet activation markers at moderate and severe stages of COVID-19 to understand the pathogenesis.

MethodsTo understand this, hospitalized COVID-19 patients with (severe cases that required intensive care) or without pneumonia (moderate cases) were recruited. Phenotypic and molecular characterizations were performed employing basic coagulation tests including PT, APTT, D-Dimer and TFPI. The flow cytometry-based multiplex assays were performed to assess FXI, anti-thrombin, prothrombin, fibrinogen, FXIII, P-selectin, sCD40L, plasminogen, tissue-plasminogen activator (tPA), plasminogen activator inhibitor-1 (PAI-1) and D-Dimer.

ResultsThe investigations revealed induction of plasma P-selectin and CD40 ligand (sCD40L) in moderate COVID-19 cases which were significantly abolished with the progression of COVID-19 severity. Moreover, a profound reduction in plasma tissue factor pathway inhibitor (TFPI) and FXIII were identified particularly in the severe COVID-19. Further analysis revealed fibrinogen induction in both moderate and severe patients. Interestingly, an elevated PAI-1 more prominently in moderate, and tPA particularly in severe COVID-19 cases were observed. Particularly, the levels of fibrinogen and tPA directly correlated with the severity of the disease.

ConclusionsIn summary, induction of soluble P-selectin, sCD40L, fibrinogen and PAI-1 in moderate COVID-19 cases suggests the activation of platelets and coagulation system before patients require intensive care. These findings would help in designing better thromboprophylaxis to limit the COVID-19 severity. 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. Design, Mutate, Screen: High-throughput creation of genetic clocks with different period-amplitude characteristics Directed evolution has become an invaluable tool in protein engineering and has also greatly influenced the construction of synthetic gene circuits. The ability to generate diversity at precise targets for directed evolution approaches has improved vastly, allowing researchers to create large, specific mutant libraries with relative ease. Screening approaches for large mutant libraries have similarly come a long way, especially when the desired behavior can easily be tested for with static, single time-point assays. For more complex gene circuits with dynamic phenotypes that change over time, directed evolution approaches to controlling and tuning circuit behavior have been hindered by the lack of sufficiently high-throughput screening methods to isolate variants with desired characteristics. Here we utilize directed mutagenesis and multiplexed microfluidics to develop a workflow for creating, screening and tuning dynamic gene circuits that operate at the population level. Specifically, we create a mutant library of an existing oscillator, the synchronized lysis circuit, and tune its dynamics while uncovering principles regarding its behavior. Lastly, we utilize this directed evolution workflow to construct a new synchronized genetic oscillator that exhibits robust dynamics over long time scales. High performance single-cell gene regulatory network inference atscale: The Inferelator 3.0 MotivationGene regulatory networks define regulatory relationships between transcription factors and target genes within a biological system, and reconstructing them is essential for understanding cellular growth and function. Methods for inferring and reconstructing networks from genomics data have evolved rapidly over the last decade in response to advances in sequencing technology and machine learning. The scale of data collection has increased dramatically; the largest genome-wide gene expression datasets have grown from thousands of measurements to millions of single cells, and new technologies are on the horizon to increase to tens of millions of cells and above.

ResultsIn this work, we present the Inferelator 3.0, which has been significantly updated to integrate data from distinct cell types to learn context-specific regulatory networks and aggregate them into a shared regulatory network, while retaining the functionality of the previous versions. The Inferelator is able to integrate the largest single-cell datasets and learn cell-type specific gene regulatory networks. Compared to other network inference methods, the Inferelator learns new and informative Saccharomyces cerevisiae networks from single-cell gene expression data, measured by recovery of a known gold standard. We demonstrate its scaling capabilities by learning networks for multiple distinct neuronal and glial cell types in the developing Mus musculus brain at E18 from a large (1.3 million) single-cell gene expression dataset with paired single-cell chromatin accessibility data.

AvailabilityThe inferelator software is available on GitHub (https://github.com/flatironinstitute/inferelator) under the MIT license and has been released as python packages with associated documentation (https://inferelator.readthedocs.io/). A high throughput lipidomics method using scheduled multiple reaction monitoring Lipid compositions of cells, tissues and bio-fluids are complex, with varying concentrations and structural diversity, which makes their identification challenging. Newer methods for comprehensive analysis of lipids are thus necessary. Herein, we propose a targeted-mass spectrometry based method for large-scale lipidomics using a combination of variable retention time window and relative dwell time weightage. Using this, we detected more than 1000 lipid species, including structural isomers. The limit of detection varied from femtomolar to nanomolar range and the coefficient of variance <30% for 849 lipid species. We used this method to identify lipids altered due to Vitamin B12 deficiency and found that the levels of lipids with {omega}-3 fatty acid chains decreased while those with {omega}-6 increased. This method enables identification of by far the largest number of lipid species with structural isomers in a single experiment and would significantly advance our understanding of the role of lipids in biological processes. Comparative toxicogenomics of glyphosate and Roundup herbicides by mammalian stem cell-based genotoxicity assays and molecular profiling in Sprague-Dawley rats Whether glyphosate-based herbicides (GBHs) are more potent than glyphosate alone at activating cellular mechanisms, which drive carcinogenesis remains controversial. As GBHs are more cytotoxic that glyphosate, we reasoned they may also be more capable of activating carcinogenic pathways. We tested this hypothesis by comparing the effects of glyphosate with Roundup GBHs both in vitro and in vivo. First, glyphosate was compared with representative GBHs namely MON 52276 (EU), MON 76473 (UK) and MON 76207 (USA) using the mammalian stem cell-based ToxTracker system. Here, MON 52276 and MON 76473, but not glyphosate and MON 76207, activated oxidative stress and unfolded protein responses. Second, molecular profiling of liver was performed in female Sprague-Dawley rats exposed to glyphosate or MON 52276 (both at 0.5, 50, 175 mg/kg bw/day glyphosate) for 90 days. MON 52276 but not glyphosate increased hepatic steatosis and necrosis. MON 52276 and glyphosate altered the expression of genes in liver reflecting TP53 activation by DNA damage and circadian rhythm regulation. Genes most affected in liver were similarly altered in kidneys. Small RNA profiling in liver showed decreased amounts of miR-22 and miR-17 from MON 52276 ingestion. Glyphosate decreased mir-30 while miR-10 levels were increased. DNA methylation profiling of liver revealed 5,727 and 4,496 differentially methylated CpG sites between the control and glyphosate and MON 52276 exposed animals respectively. Apurinic/apyrimidinic DNA damage formation in liver was increased with glyphosate exposure. Altogether, our results show that Roundup formulations cause more biological changes linked with carcinogenesis than glyphosate. Embedded 3D printing in self-healing annealable composites for precise patterning of functionally mature human neural constructs Human in vitro models of neural tissue with controllable cellular identity, tunable microenvironment, and defined spatial arrangement are needed to facilitate studies of brain development and disease. Towards this end, embedded printing in jammed microgel supports (i.e., granular gels) holds great promise as it allows precise and programmable patterning of extremely soft and compliant tissue constructs. However, in contrast to the vast material landscape available for bulk hydrogels, granular printing support formulations are restricted to a handful of materials without the ability for facile adjustment of biofunctional properties of the cellular microenvironment. Therefore, there has been a need for novel materials that take advantage of versatile biomimicry of bulk hydrogels while providing high-fidelity support for embedded printing akin to granular gels. To address this need, we present a modular platform for bioengineering of neuronal networks via direct embedded 3D printing of human stem cells inside Self-Healing Annealable Particle-Extracellular matrix (SHAPE) composites. SHAPE composites consist of soft microgels immersed in viscous extracellular-matrix solution to enable precise freeform patterning of human stem cells and consequent generation and long-term maintenance of mature subtype-specific neurons that extend projections within the volume of the annealed support. The developed approach further allows multi-ink deposition, live spatial and temporal monitoring of oxygen levels, as well as creation of vascular channels. Due to its modularity, SHAPE biomanufacturing toolbox not only offers a solution for functional modeling of mechanically sensitive neural constructs, but also has potential to be applied to a wide range of biomaterials with different crosslinking mechanisms to model tissues and diseases where recapitulation of complex architectural features and topological cues is essential. HOW CONCERNING IS A SARS-COV-2 VARIANT OF CONCERN? COMPUTATIONAL PREDICTIONS AND THE VARIANTS LABELING SYSTEM We herein report a study to evaluate the use of computational prediction of SARS-CoV-2 genetic variations in improving the current variants labeling system. First, we reviewed the basis of the system developed by the World Health Organization (WHO) for the labeling of SARS-CoV-2 genetic variants and the adaptations made to it by the United States Center of Diseases Control (CDC). We observed that the labeling system is based upon the virus major attributes. However, we found that the labeling criteria of the SARS-CoV-2 variants derived from these attributes are not accurately defined and are used differently by the two health management agencies. Consequently, discrepancies exist between the labels given by WHO and CDC to same variants. Our observations suggest that giving the VOC label to a new variant is premature and might not be appropriate. Therefore, we carried out a comparative computational study to predict the effects of the mutations on the virus structure and functions of five VOCs. By linking these data to the criteria used by WHO and the CDC for variant labeling, we ascertained that comparative computational predictions of the impact of genetic variations are a better ground for rapid and more accurate labelling of SARS-CoV-2 variants. We propose to label all emergent variants VUM or VBM and to carry out computational predictive studies and thorough variants comparison, upon which more appropriate and informative labels can be attributed. Furthermore, harmonization of the variants labeling system would be globally beneficial to communicate about and fight COVID-19 pandemic. Tracheal motile cilia in mice require CAMSAP3 for formation of central microtubule pair and coordinated beating Motile cilia of multiciliated epithelial cells undergo synchronized beating to produce fluid flow along the luminal surface of various organs. Each motile cilium consists of an axoneme and a basal body, which are linked by a  transition zone. The axoneme exhibits a characteristic 9+2 microtubule arrangement important for ciliary motion, but how this microtubule system is generated is not yet fully understood. Here we show that CAMSAP3, a protein that can stabilize the minus end of a microtubule, concentrates at multiple sites of the cilium-basal body complex, including the upper region of the transition zone or the axonemal basal plate where the central pair of microtubules (CP) initiates. CAMSAP3 dysfunction resulted in loss of the CP and partial distortion of the basal plate, as well as the failure of multicilia to undergo synchronized beating. These findings suggest that CAMSAP3 plays pivotal roles in the formation or stabilization of the CP by localizing at the basal region of the axoneme, and thereby supports the coordinated motion of multicilia in airway epithelial cells. Presence of a SARS-COV-2 protein enhances Amyloid Formation of Serum Amyloid A A marker for the severeness and disease progress of COVID-19 is overexpression of serum amyloid A (SAA) to levels that in other diseases are associated with a risk for SAA amyloidosis. In order to understand whether SAA amyloidosis could also be a long-term risk of SARS-COV-2 infections we have used long all-atom molecular dynamic simulations to study the effect of a SARS-COV-2 protein segment on SAA amyloid formation. Sampling over 40 {micro}s we find that presence of the nine-residue segment SK9, located at the C-terminus of the Envelope protein, increases the propensity for SAA fibril formation by three mechanisms: it reduces the stability of the lipid-transporting hexamer shifting the equilibrium toward monomers, it increases the frequency of aggregation-prone configurations in the resulting chains, and it raises the stability of SAA fibrils. Our results therefore suggest that SAA amyloidosis and related pathologies may be a long-term risk of SARS-COV-2 infections. Vocal markers of autism: assessing the generalizability of machine learning models Machine learning (ML) approaches show increasing promise in their ability to identify vocal markers of autism. Nonetheless, it is unclear to what extent such markers generalize to new speech samples collected e.g., using a different speech task or in a different language. In this paper, we systematically assess the generalizability of ML findings across a variety of contexts.

We train promising published ML models of vocal markers of autism on novel cross-linguistic datasets following a rigorous pipeline to minimize overfitting, including cross-validated training and ensemble models. We test the generalizability of the models by testing them on i) different participants from the same study, performing the same task; ii) the same participants, performing a different (but similar) task; iii) a different study with participants speaking a different language, performing the same type of task.

While model performance is similar to previously published findings when trained and tested on data from the same study (out-of-sample performance), there is considerable variance between studies. Crucially, the models do not generalize well to different, though similar, tasks and not at all to new languages. The ML pipeline is openly shared.

Generalizability of ML models of vocal markers of autism is an issue. We outline three recommendations for strategies researchers could take to be more explicit about generalizability and improve it in future studies.

LAY SUMMARYMachine learning approaches promise to be able to identify autism from voice only. These models underestimate how diverse the contexts in which we speak are, how diverse the languages used are and how diverse autistic voices are. Machine learning approaches need to be more careful in defining their limits and generalizability. A method to estimate the cellular composition of the mouse brain from heterogeneous datasets The mouse brain contains a rich diversity of inhibitory interneuron types that have been characterized by their patterns of gene expression. However, it is still unclear how these cell types are distributed across the mouse brain. We developed a computational method to estimate the densities of different interneuron types across the mouse brain. Our method allows the unbiased integration of diverse and disparate datasets into one framework to predict interneuron densities for uncharted brain regions. We constrained our estimates based on previously computed brain-wide neuron densities, gene expression data from in situ hybridization image stacks together with a wide range of values reported in the literature. Using constrained optimization, we derived coherent estimates of cell densities for the different interneuron types. We estimate that 20.3% of all neurons in the mouse brain are inhibitory. Among all inhibitory neurons, 18% predominantly express parvalbumin (PV), 16% express somatostatin (SST), 3% express vasoactive intestinal peptide (VIP), and the remainder 63% belong to the residual GABAergic population. We find that our density estimations improve as more literature values are integrated. Our pipeline is extensible, allowing new cell types or data to be integrated as they become available. The data, algorithms, software, and results of our pipeline are publicly available and update the Blue Brain Cell Atlas. This work therefore leverages the research community to collectively converge on the numbers of each cell type in each brain region.

Author summaryObtaining a global understanding of the cellular composition of the brain is a very complex task, not only because of the great variability that exists between reports of similar counts but also because of the numerous brain regions and cell types that make up the brain. Previously, we presented a model of a cell atlas, which provided an estimate of the densities of neurons, glia and their subtypes for each region in the mouse brain. Here, we describe an extension of this model to include more inhibitory neuron types. We collected estimates of inhibitory neuron counts from literature and built a framework to combine them into a consistent cell atlas. Using brain slice images, we also estimated inhibitory neuron density in regions where no literature data are available. We estimated that in the mouse brain 20.3% of all neurons are inhibitory. Among all inhibitory neurons, 18% predominantly express parvalbumin (PV), 16% express somatostatin (SST), 3% express vasoactive intestinal peptide (VIP), and the remainder 63% belong to the residual GABAergic population Our approach can be further extended to any other cell type and provides a resource to build tissue-level models of the rodent brain. Revisiting regulatory decoherence and phenotypic integration: accounting for temporal bias in co-expression analyses Environment can alter the degree of phenotypic variation and covariation, potentially influencing evolutionary trajectories. However, environment-driven changes in phenotypic variation remain understudied. In an effort to exploit the abundance of RNASequencing data now available, an increasing number of ecological studies rely on population-level correlation to characterize the plastic response of the entire transcriptome and to identify environmentally responsive molecular pathways. These studies are fundamentally interested in identifying groups of genes that respond in concert to environmental shifts. We show that population-level differential co-expression exhibits biases when capturing changes of regulatory activity and strength in rice plants responding to elevated temperature. One possible cause of this bias is regulatory saturation, the observation that detectable co-variance between a regulator and its target may be low as their transcript abundances are induced. This phenomenon appears to be particularly acute for rapid-onset environmental stressors. However, our results suggest that temporal correlations may be a reliable means to detect transient regulatory activity following rapid onset environmental perturbations such as temperature stress. Such temporal bias is likely to confound the studies of phenotypic integration, where high-order organismal traits are hypothesized to be more integrated with strong correlation under stressful conditions, while recent transcriptome studies exhibited weaker coexpression between genes under stressful conditions. Collectively, our results point to the need to account for the nuances of molecular interactions and the possibly confounding effects that these can introduce into conventional approaches to study transcriptome datasets. The SLIM1 transcription factor is required for arsenic resistance in Arabidopsis thaliana The transcriptional regulators of arsenic-induced gene expression remain largely unknown. Sulfur assimilation is tightly linked with arsenic detoxification. Here we report that mutant alleles in the SLIM1 transcription factor are substantially more sensitive to arsenic than cadmium. Arsenic treatment caused high levels of oxidative stress in the slim1 mutants, and slim1 alleles were impaired in both thiol and sulfate accumulation. We further found enhanced arsenic accumulation in roots of slim1 mutants. Transcriptome analyses indicate an important role for SLIM1 in arsenic-induced tolerance mechanisms. The present study identifies the SLIM1 transcription factor as an essential component in arsenic tolerance and arsenic-induced gene expression. Our results suggest that the severe arsenic sensitivity of the slim1 mutants is caused by altered redox status. No evidence of human genome integration of SARS-CoV-2 found by long-read DNA sequencing A recent study proposed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) hijacks the LINE-1 (L1) retrotransposition machinery to integrate into the DNA of infected cells. If confirmed, this finding could have significant clinical implications. Here, we applied deep (>50x) long-read Oxford Nanopore Technologies (ONT) sequencing to HEK293T cells infected with SARS-CoV-2, and did not find the virus integrated into the genome. By examining ONT data from separate HEK293T cultivars, we completely resolved 78 L1 insertions arising in vitro in the absence of L1 overexpression systems. ONT sequencing applied to hepatitis B virus (HBV) positive liver cancer tissues located a single HBV insertion. These experiments demonstrate reliable resolution of retrotransposon and exogenous virus insertions via ONT sequencing. That we found no evidence of SARS-CoV-2 integration suggests such events are, at most, extremely rare in vivo, and therefore are unlikely to drive oncogenesis or explain post-recovery detection of the virus. A tool for assessing alignment of biomedical data repositories with open, FAIR, citation and trustworthy principles Increasing attention is being paid to the operation of biomedical data repositories in light of efforts to improve how scientific data is handled and made available for the long term. Multiple groups have produced recommendations for functions that biomedical repositories should support, with many using requirements of the FAIR data principles as guidelines. However, FAIR is but one set of principles that has arisen out of the open science community. They are joined by principles governing open science, data citation and trustworthiness, all of which are important aspects for biomedical data repositories to support. Together, these define a framework for data repositories that we call OFCT: Open, FAIR, Citable and Trustworthy. Here we developed an instrument using the open source PolicyModels toolkit that attempts to operationalize key aspects of OFCT principles and piloted the instrument by evaluating eight biomedical community repositories listed by the NIDDK Information Network (dkNET.org). Repositories included both specialist repositories that focused on a particular data type or domain, in this case diabetes and metabolomics, and generalist repositories that accept all data types and domains. The goal of this work was both to obtain a sense of how much the design of current biomedical data repositories align with these principles and to augment the dkNET listing with additional information that may be important to investigators trying to choose a repository, e.g., does the repository fully support data citation? The evaluation was performed from March to November 2020 through inspection of documentation and interaction with the sites by the authors. Overall, although there was little explicit acknowledgement of any of the OFCT principles in our sample, the majority of repositories provided at least some support for their tenets.