Striatin 3 and MAP4K4 cooperate towards oncogenic growth and tissue invasion in medulloblastoma MAP4K4 has been correlated with increased cell motility and reduced proliferation in mammalian cells. Consequences and regulation of this dichotomous functionality of MAP4K4 in tumor cells remained elusive. We find that MAP4K4 interacts with the STRN3 protein in medulloblastoma and that STRN3 and MAP4K4 exert opposing functions in Hippo tumor suppressor signaling and clonal growth. However, depletion of either STRN3 or MAP4K4 reduces migration and tissue invasion, and concomitant loss of both proteins halts tumor cell growth in the cerebellar tissue. Mechanistically, STRN3 couples MAP4K4 to the protein phosphatase 2A, which inactivates growth repressing activities of MAP4K4. In parallel, STRN3 enables growth factor-induced PKC{theta} activation and the direct phosphorylation of VASPS157 by MAP4K4, which are necessary for efficient migration and tissue invasion. Thus, STRN3 controls MAP4K4 functionality in growth factor-activated tumor cells, and the cooperation of the two proteins promotes invasiveness through nPKCs and VASP and increases proliferation via inactivation of Hippo signaling. Targeting of the STRN3-MAP4K4 cooperation could reactivate Hippo signaling and repress invasiveness in growth factor-driven tumors.

Graphical abstract

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Combined epigenetic and metabolic inhibition blocks platinum-induced ovarian cancer stem cell enrichment High grade serous ovarian cancer (HGSOC) is the most common and aggressive type of ovarian cancer. Platinum resistance is a common occurrence in HGSOC and a main cause of tumor relapse resulting in high patient mortality rates. Recurrent OC is enriched in aldehyde dehydrogenase (ALDH)+ ovarian cancer stem cells (OCSCs), which are resistant to platinum agents. We demonstrated that acute platinum treatment induced a DNA damage-dependent decrease in BRCA1 levels. In a parallel response associated with G2/M arrest, platinum treatment also induced an increase in expression of NAMPT, the rate limiting regulator of NAD+ production from the salvage pathway, and levels of NAD+, the cofactor required for ALDH activity. Concurrent inhibition of DNA methyltransferases (DNMTs) and NAMPT synergistically abrogated the platinum-induced increase in OCSCs. Combining pharmacological inhibitors of DNMT and NAMPT with carboplatin reduced tumorigenesis and OCSC percentage in vivo. We conclude that both epigenetic and metabolic alterations lead to platinum induced OCSC enrichment, providing preclinical evidence that in the neoadjuvant setting, combining DNMT and NAMPT inhibitors with platinum has the potential to reduce OC recurrence and avert the development of platinum resistance.
A bacterial extracellular vesicle-based intranasal vaccine against SARS-CoV-2 protects against disease and elicits neutralizing antibodies to wild-type virus and Delta variant Several vaccines have been introduced to combat the coronavirus infectious disease-2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Current SARS-CoV-2 vaccines include mRNA-containing lipid nanoparticles or adenoviral vectors that encode the SARS-CoV-2 Spike (S) protein of SARS-CoV-2, inactivated virus, or protein subunits. Despite growing success in worldwide vaccination efforts, additional capabilities may be needed in the future to address issues such as stability and storage requirements, need for vaccine boosters, desirability of different routes of administration, and emergence of SARS-CoV-2 variants such as the Delta variant. Here, we present a novel, well-characterized SARS-CoV-2 vaccine candidate based on extracellular vesicles (EVs) of Salmonella typhimurium that are decorated with the mammalian cell culture-derived Spike receptor-binding domain (RBD). RBD-conjugated outer membrane vesicles (RBD-OMVs) were used to immunize the golden Syrian hamster (Mesocricetus auratus) model of COVID-19. Intranasal immunization resulted in high titers of blood anti-RBD IgG as well as detectable mucosal responses. Neutralizing antibody activity against wild-type and Delta variants was evident in all vaccinated subjects. Upon challenge with live virus, hamsters immunized with RBD-OMV, but not animals immunized with unconjugated OMVs or a vehicle control, avoided body mass loss, had lower virus titers in bronchoalveolar lavage fluid, and experienced less severe lung pathology. Our results emphasize the value and versatility of OMV-based vaccine approaches. Trade-offs in biosensor optimization for dynamic pathway engineering Recent progress in synthetic biology allows the construction of dynamic control circuits for metabolic engineering. This technology promises to overcome many challenges encountered in traditional pathway engineering, thanks to their ability to self-regulate gene expression in response to bioreactor perturbations. The central components in these control circuits are metabolite biosensors that read out pathway signals and actuate enzyme expression. However, the construction of metabolite biosensors is a major bottleneck for strain design, and a key challenge is to understand the relation between biosensor dose-response curves and pathway performance. Here we employ multiobjective optimization to quantify performance trade-offs that arise in the design and calibration of metabolite biosensors. Our approach reveals strategies for tuning dose-response curves along an optimal trade-off between production flux and the cost of an increased expression burden on the host. We explore properties of control architectures built in the literature, and identify their advantages and caveats in terms of performance and robustness to growth conditions and leaky promoters. We demonstrate the optimality of a control circuit for glucaric acid production in Escherichia coli, which has been shown to increase titer by 2.5-fold as compared to static designs. Our results lay the groundwork for the automated design of control circuits for pathway engineering, with applications in the food, energy and pharmaceutical sectors. Continental generalization of an AI system for clinical seizure recognition BackgroundElectroencephalogram (EEG) monitoring and objective seizure identification is an essential clinical investigation for some patients with epilepsy. Accurate annotation is done through a time-consuming process by EEG specialists. Computer-assisted systems for seizure detection currently lack extensive clinical utility due to retrospective, patient-specific, and/or irreproducible studies that result in low sensitivity or high false positives in clinical tests. We aim to significantly reduce the time and resources on data annotation by demonstrating a continental generalization of seizure detection that balances sensitivity and specificity.

MethodsThis is a prospective inference test of artificial intelligence on nearly 14,590 hours of adult EEG data from patients with epilepsy between 2011 and 2019 in a hospital in Sydney, Australia. The inference set includes patients with different types and frequencies of seizures across a wide range of ages and EEG recording hours. The artificial intelligence (AI) is a convolutional long short-term memory network that is trained on a USA-based dataset. The Australian set is about 16 times larger than the US training dataset with very long interictal periods (between seizures), which is way more realistic than the training set and makes our false positives highly reliable. We validated our inference model in an AI-assisted mode with a human expert arbiter and a result review panel of expert neurologists and EEG specialists on 66 sessions to demonstrate achievement of the same performance with over an order-of-magnitude reduction in time.

FindingsOur inference on 1,006 EEG recording sessions on the Australian dataset achieved 76.68% with nearly 56 [0, 115] false alarms per 24 hours on average, against legacy ground-truth annotations by human experts, conducted independently over nine years. Our pilot test of 66 sessions with a human arbiter, and reviewed ground truth by a panel of experts, confirmed an identical human performance of 92.19% with an AI-assisted system, while the time requirements reduce significantly from 90 to 7.62 minutes on average.

InterpretationAccurate and objective seizure counting is an important factor in epilepsy. An AI-assisted system can help improve efficiency and accuracy alongside human experts, particularly in low and middle-income countries with limited expert human resources.

FundingsSOAR Fellowship from The University of Sydney, a Microsoft AI for Accessibility grant, and a Research Training Program (RTP) support provided by the Australian Government.

Research in contextO_ST_ABSEvidence before this studyC_ST_ABSDuring the development of our artificial intelligence (AI) system, we did a systematic review of the scientific literature with search via PubMed for research articles published on seizure detection with the following inclusion criteria: (1) Tests or inference evaluation is conducted on large-scale clinical EEG data; (2) Generalization is attempted or potentials for generalization is considered, e.g., in commercialized tools; (3) Seizure detection delay and real-time (aka. online) operation were not considered critical in this context as long as the test was conducted on raw EEG data. Note that ICU seizure detection or portable seizure alert systems are relying on detection delay and real-time needs. Our keywords include "prospective seizure detection", "automated seizure detection", "non-patient specific seizure detection", "seizure detection on continuous EEG", and "deep learning-based seizure detection" and "machine learning-based seizure detection". We found that the only two categories of works meet our criteria: two research papers published in 2020 and works published by commercial tools developers. We cited a recent review of 89 deep learning-based seizure detection, all of which are retrospective. One work from Stanford reported seizure detection on all ages (pediatric to adult ages) using post-acquisition EEG recordings and provided an avenue for independent evaluation by providing a test on a publicly available Temple University Hospital (TUH) EEG dataset. The other work pivoted on algorithmic-assisted real-time seizure risk monitoring in continuous EEG in neonatal intensive care unit (NICU) with 128 neonates (32 with seizures) showing about 20% improvement in seizure identification over 130 neonates (38 with seizures) with no algorithmic assistance.

Commercial tools we studied are Encevis (EpiScan), Besa, and Persyst. There is a recent comparative study on these tools on 81 patients. Encevis is reported as the best performing tool, and hence we provided a comparative study with Encevis ver. 1.9.2. Encevis is also the only tool that provided an avenue for comparative study on publicly available EEG data. The Stanford work, published in 2020, confirms many false positives with Persyst 13. We excluded our tests on Persyst 14 as it highly under-performed relative to Encevis. Only Stanfords work provides code availability. We compared our results with Stanfords work outcome and provided pilot test results with the Encevis (EpiScan) tool on the Australian dataset, which shows a considerably lower sensitivity.

Added value of this studyTo the best of our knowledge, the current study is the first continental generalization that demonstrates the potential to achieve an expert human-level seizure recognition rate in a clinical setting and in just a fraction of time. The two datasets used in this study are recorded with different infrastructure, which adds to the independence of inference from hardware types and improves clinical utility. This is particularly important as 80% of patients with epilepsy live in low and middle-income countries with limited resources, particularly EEG specialists and neurologists.

Implications of all the available evidenceOur results support the potential benefits of deep learning AI in clinical settings for seizure recognition and its contribution to significant sensitivity over available solutions. Our AI-assisted system achieves more than a ten-fold increase in time efficiency and reports identical performance to human experts for EEG interpretation with access to great neurophysiology support and auxiliary data. Our findings, particularly our tests on an available commercial tool, recommend that the evaluation, test, or inference in AI systems be performed on different datasets, with diverse infrastructures, and on large-scale and realistic sets with long interictal periods. Cellular feedback to organotelluranes displays modulation of antioxidant proteins gene expression Organotelluranes RT3 and RT4 are thiol reagents that induce mitochondrial transition pore (MTP) opening in a sensitive and insensitive manner to cyclosporin A. Although RT3 and RT4 promote glutathione depletion, paradoxically, they are also an efficient antioxidant for membrane lipids. These compounds antagonistic effects elicited the challenging question of how the gene expression of antioxidant enzymes would respond to treatment with these compounds. The influence of RT3 and RT4 on antioxidant enzyme expression was investigated in cultured aortic smooth muscle cells (ASMC). RT3 and RT4 promoted disruption of ionic calcium homeostasis, mitochondrial transmembrane potential ({Delta}{Psi}), and cell death in a dose-dependent manner. The cell death mechanisms responded qualitatively to the increase of the organotellurane concentration and changed from apoptosis to necrosis. RT3 and RT4 increased the expression of thioredoxin significantly. RT3 also increased the expression of glutaredoxin and glutathione peroxidase, slightly the catalase expression without significant effects on SOD expression. The results are consistent with GSH and protein thiol depletion and discussed based on the cell toxicity mechanism exhibited by these compounds.



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org.highwire.dtl.DTLVardef@52bb82org.highwire.dtl.DTLVardef@19476d9org.highwire.dtl.DTLVardef@6aa99org.highwire.dtl.DTLVardef@1aa605e_HPS_FORMAT_FIGEXP  M_FIG C_FIG Human inhalable antibody fragments neutralizing SARS-CoV-2 variants for COVID-19 therapy As of October 2021, coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains a global emergency, and novel therapeutics are urgently needed. Here we describe human single chain variable fragment (scFv) antibodies (76clAbs) that block an epitope of the SARS-CoV-2 spike protein essential for ACE2-mediated entry into cells. 76clAbs neutralize the delta variant and other variants being monitored (VBMs) and inhibit spike-mediated pulmonary cell-cell fusion, a critical feature of COVID-19 pathology. In two independent animal models, intranasal administration counteracted the infection. Due to high efficiency, remarkable stability, resilience to nebulization and low production cost, 76clAbs may become a relevant tool for rapid, self-administrable early intervention in SARS-CoV-2-infected subjects independently of their immune status. Genomics-based deconvolution of multiplexed transcriptional responses to wood smoke particles defines rapid AHR signaling dynamics. Heterogeneity of respirable particulates and compounds complicates understanding transcriptional responses to air pollution. Here, we address this problem through applying precision nuclear run-on sequencing (PRO-seq) to measure nascent transcription and the assay for transposase-accessible chromatin using sequencing (ATAC-seq) to airway epithelial cells after wood smoke particle (WSP) exposure. We used transcription factor enrichment analysis to agnostically identify temporally distinct roles for the TCF/SRF family, the aryl hydrocarbon receptor (AHR), and NFkB in regulating transcriptional changes induced by WSP. Transcription of canonical targets of the AHR, such as CYP1A1 and AHRR, was robustly increased after just 30 minutes of WSP exposure, and we discovered novel AHR-regulated pathways and targets including the DNA methyltransferase, DNMT3L. Transcription of these genes and associated enhancers rapidly returned to near baseline by 120 minutes. The kinetics of AHR- and NFkB-regulated responses to WSP were distinguishable based on the timing of both transcriptional responses and chromatin remodeling, with induction of several cytokines implicated in maintaining NFkB responses through 120 minutes of exposure. In aggregate, our data establish a direct and primary role for AHR in mediating airway epithelial responses to WSP and identify crosstalk between AHR and NFkB signaling in controlling pro-inflammatory gene expression. This work also defines an integrated genomics-based strategy for deconvoluting multiplexed transcriptional responses to heterogeneous environmental exposures. Localization of signaling receptors maximizes cellular informationacquisition in spatially-structured natural environments Cells in natural environments like tissue or soil sense and respond to extracellular ligands with intricately structured and non-monotonic spatial distributions, sculpted by processes such as fluid flow and substrate adhesion. In this work, we show that spatial sensing and navigation can be optimized by adapting the spatial organization of signaling pathways to the spatial structure of the environment. We develop an information-theoretic framework for computing the optimal spatial organization of a sensing system for a given signaling environment. We find that receptor localization maximizes information acquisition in simulated natural contexts, including tissue and soil. Receptor localization extends naturally to produce a dynamic protocol for continuously redistributing signaling receptors, which when implemented using simple feedback, boosts cell navigation efficiency by 30-fold. Broadly, our work shows how cells can maximize the fidelity of information transfer by adapting the spatial organization of signaling molecules to the spatial structure of the environment. 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. We get by with a little help from our friends: shared adaptive variation provides a bridge to novel ecological specialists during adaptive radiation Adaptive radiations involve astounding bursts of phenotypic, ecological, and species diversity. However, the microevolutionary processes that underlie the origins of these bursts are still poorly understood. We report the discovery of an intermediate  wide-mouth scale-eating ecomorph in a sympatric radiation of Cyprinodon pupfishes, illuminating the transition from a widespread algae-eating generalist to a novel microendemic scale-eating specialist. We first show that this ecomorph occurs in sympatry with generalist C. variegatus and scale-eating specialist C. desquamator on San Salvador Island, Bahamas, but is genetically differentiated, morphologically distinct, and often consumes scales. We then compared the timing of selective sweeps on shared and unique adaptive variants in trophic specialists to characterize their adaptive walk. Shared adaptive regions swept first in both the specialist desquamator and the intermediate  wide-mouth ecomorph, followed by unique sweeps of introgressed variation in  wide-mouth and de novo variation in desquamator. The two scale-eating populations additionally shared 9% of their hard selective sweeps with molluscivores C. brontotheroides, despite no single common ancestor among specialists. Our work provides a new microevolutionary framework for investigating how major ecological transitions occur and illustrates how both shared and unique genetic variation can provide a bridge for multiple species to access novel ecological niches. The Skeletal Muscle Circadian Clock Regulates Titin Splicing Through RBM20 Circadian rhythms are maintained by a cell autonomous, transcriptional-translational feedback loop known as the molecular clock. While previous research suggests a role of the molecular clock in regulating skeletal muscle structure and function, no mechanisms have connected the molecular clock to sarcomere filaments. Utilizing inducible, skeletal muscle specific, Bmal1 knockout (iMSBmal1-/-) mice, we showed that knocking out skeletal muscle clock function alters titin isoform expression through both RNAseq and LC-MS. This alteration in titins spring length resulted in sarcomere length heterogeneity. We demonstrate the direct link between altered titin splicing and sarcomere length in vitro using U7 snRNPs that truncate the region of titin altered in iMSBmal1-/- muscle. Finally, we identified a mechanism whereby the skeletal muscle clock regulates titin isoform expression through transcriptional regulation of Rbm20, a potent splicing regulator of titin. Our findings demonstrate the importance of the skeletal muscle circadian clock in maintaining titin isoform through regulation of RBM20 expression. Because circadian rhythm disruption is a feature of many chronic diseases, our results highlight a novel pathway that could be targeted to maintain skeletal muscle structure and function in a range of pathologies. Comparison of hybrid learning and remote education in the implementation of the 'Adopt a Microorganism' methodology The Internet has changed the way teachers and students access information and build knowledge. The recent COVID-19 pandemic has created challenges for both teachers and students and a demand for new methodologies of remote learning. In the life sciences, mixing online content with practical activities represents an even greater challenge. In microbiology, the implementation of an active teaching methodology, the #Adopt project, based on the social network Facebook(R), represents an excellent option for connecting remote education with classroom activities. In 2020, the version applied in high school, "Adopt a Microorganism", was adapted to meet the demands of emergency remote education owing to the suppression of face-to-face activities caused by the pandemic. In the present study, we assessed how the change in methodology impacted the discourse richness of students from high school integrated with technical education in the Business Administration program of the Federal Institute of Sao Paulo, Sorocaba Campus. Three questionnaires related to the groups of microorganisms (Archaea, Bacteria, Virus, Fungi, and Protozoan) were applied. The students responses in the 2019 and 2020 classes were compared concerning content richness and multiplicity of concepts through the application of the Shannon diversity index, an approach that is generally used to assess biodiversity in different environments. The observed results suggest that remote learning provided students with a conceptual basis and richness of content equivalent to that achieved by students subjected to the hybrid teaching model. In conclusion, this study suggests that the #Adopt project methodology increases students discourse richness in microbiology even without face-to-face traditional classes. 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. Multiple brace root phenotypes promote anchorage and limit root lodging in maize Plant mechanical failure (lodging) causes global yield losses of 7-66% in cereal crops. We have previously shown that the above-ground nodal roots (brace roots) in maize are critical for anchorage. However, it is unknown how brace root phenotypes vary across genotypes and the functional consequence of this variation. This study quantifies the contribution of brace roots to anchorage, brace root traits, plant height, and root lodging susceptibility in 52 maize inbred lines. We show that the contribution of brace roots to anchorage and root lodging susceptibility varies among genotypes and this contribution can be explained by plant architectural variation. Additionally, supervised machine learning models were developed and show that multiple plant architectural phenotypes can predict the contribution of brace roots to anchorage and root lodging susceptibility. Together these data define the plant architectures that are important in lodging resistance and show that the contribution of brace roots to anchorage is a good proxy for root lodging susceptibility. Herbivore life histories are altered by drought stress in their hosts plants Drought associated with climate change can stress plants, altering their interactions with phytophagous arthropods. Dryness not only impacts cultivated plants but also their parasites, which in some cases are favoured by drought. Herbivorous arthropods feeding on drought-stressed plants typically produce bigger offspring and develop faster. However, how much responses to abiotic factors differ among populations of a species remains poorly documented. Here, we evaluate variability among populations of a major agricultural pest, the two spotted spider mite, Tetranychus urticae, in response to drought-stress. We compare key life-history parameters of twelve populations that originate from climates ranging from wet and cool Atlantic locations to medium to dry hot Mediterranean locations. We evaluated how plant drought stress affects four life history traits: development time, fecundity, sex-ratio and emigration rate in an experiment comparing well-watered and drought-stressed bean plants. Mites feeding on drought-stressed plants developed faster and attempted to leave leaves less often, and young females were more fecund. The mites from wet temperate climates exhibited greater plasticity between the two water regimes than mites originating from dryer and hot climates. Thus, climate in the area of origin influences mite response to drought. Anisotropic expansion of hepatocyte lumina enforced by apical bulkheads Lumen morphogenesis is key to the function of organs and results from the integration of molecular pathways and mechanical forces1-3. The mechanisms governing anisotropic lumen expansion remain elusive4-6. In contrast to epithelial cells which have simple apico-basal polarity and form tubes, hepatocytes are multi-polar and form narrow lumina that grow anisotropically between adjacent cells, collectively generating a complex 3D network of bile canaliculi (BC)7,8. Here, we studied lumen elongation and BC morphogenesis in differentiating primary mouse hepatoblasts in vitro. Remarkably, we discovered a pattern of specific extensions of the apical membrane traversing the lumen between adjacent hepatocytes and sealed by tight junctions, reminiscent of the bulkheads of boats. These structures were also present in the developing liver. A targeted screen revealed that silencing of Rab35 caused loss of the bulkheads, conversion of hepatocyte into simple epithelial polarity and formation of spherical lumina in vitro. Strikingly, we could re-engineer hepatocyte polarity and tissue morphogenesis in vivo in the embryonic liver, converting BC into simple epithelial tubes. Our results suggest that the apical bulkheads of hepatocytes are cell-intrinsic anisotropic mechanical elements that ensure stability of the elongating lumen between two cells, thus determining the structure of BC during liver tissue morphogenesis. Directed evolution of angiotensin-converting enzyme 2 (ACE2) peptidase activity profiles for therapeutic applications Angiotensin Converting-Enzyme 2 (ACE2) is currently being investigated for its ability to beneficially modulate the Angiotensin receptor (ATR) therapeutic axis to treat multiple human diseases, but its broad substrate scope and diverse physiological roles limit its potential as a therapeutic agent. In this work we engineer ACE2 variants with enhanced hydrolytic activity and specificity toward Angiotensin-II (Ang-II) that may lead to new therapeutic candidates with improved efficacy and reduced off-target side effects. We established a yeast display-based liquid chromatography screen that enabled use of directed evolution to discover ACE2 variants with improved Ang-II activity and specificity relative to the off-target peptide substrates Apelin-13 and Angiotensin-I (Ang-I). We screened ACE2 active site libraries to reveal three substitution-tolerant positions (M360, T371 and Y510) that can be mutated to enhance ACE2s activity profile and followed up on these hits with focused double mutant libraries to further improve the enzyme. Relative to wildtype ACE2, our top variant (T371L/Y510Ile) displayed a sevenfold increase in Ang-II turnover number (kcat), a sixfold diminished catalytic efficiency (kcat/Km) on Apelin-13, and an overall decreased activity on other ACE2 substrates that were not directly assayed in directed evolution screen. At physiologically relevant substrate concentrations, T371L/Y510Ile hydrolyzes more Ang-II than wildtype ACE2 with concomitant Ang-II:Apelin-13 specificity improvements reaching 30-fold. Our efforts have delivered ATR axis-acting therapeutic candidates with relevance to both established and unexplored ACE2 therapeutic applications and provide a foundation for further ACE2 engineering efforts. Cryptic pathogen-sugar interactions revealed by universal saturation transfer analysis Many host pathogen interactions such as human viruses (including non-SARS-coronaviruses) rely on attachment to host cell-surface glycans. There are conflicting reports about whether the Spike protein of SARS-CoV-2 binds to sialic acid commonly found on host cell-surface N-linked glycans. In the absence of a biochemical assay, the ability to analyze the binding of glycans to heavily- modified proteins and resolve this issue is limited. Classical Saturation Transfer Difference (STD) NMR can be confounded by overlapping sugar resonances that compound with known experimental constraints. Here we present  universal saturation transfer analysis (uSTA), an NMR method that builds on existing approaches to provide a general and automated workflow for studying protein-ligand interactions. uSTA reveals that B-origin-lineage-SARS-CoV-2 spike trimer binds sialoside sugars in an  end on manner and modelling guided by uSTA localises binding to the spike N-terminal domain (NTD). The sialylated-polylactosamine motif is found on tetraantennary human N-linked-glycoproteins in deeper lung and may have played a role in zoonosis. Provocatively, sialic acid binding is abolished by mutations in some subsequent SARS- CoV-2 variants-of-concern. A very high resolution cryo-EM structure confirms the NTD location and  end on mode; it rationalises the effect of NTD mutations and the structure-activity relationship of sialic acid analogues. uSTA is demonstrated to be a robust, rapid and quantitative tool for analysis of binding, even in the most demanding systems.

Extended AbstractThe surface proteins found on both pathogens and host cells mediate entry (and exit) and influence disease progression and transmission. Both types can bear host-generated post- translational modifications such as glycosylation that are essential for function but can confound biophysical methods used for dissecting key interactions. Several human viruses (including non- SARS-coronaviruses) attach to host cell-surface N-linked glycans that include forms of sialic acid (sialosides). There remains, however, conflicting evidence as to if or how SARS-associated coronaviruses might use such a mechanism. Here, we demonstrate quantitative extension of  saturation transfer protein NMR methods to a complete mathematical model of the magnetization transfer caused by interactions between protein and ligand. The method couples objective resonance-identification via a deconvolution algorithm with Bloch-McConnell analysis to enable a structural, kinetic and thermodynamic analysis of ligand binding beyond previously-perceived limits of exchange rates, concentration or system. Using an automated and openly available workflow this  universal saturation transfer analysis (uSTA) can be readily-applied in a range of even heavily-modified systems in a general manner to now obtain quantitative binding interaction parameters (KD, kEx). uSTA proved critical in mapping direct interactions between natural sialoside sugar ligands and relevant virus-surface attachment glycoproteins - SARS-CoV-2-spike and influenza-H1N1-haemagglutinin variants - by quantitating ligand signal in spectral regions otherwise occluded by resonances from mobile protein glycans (that also include sialosides). In B- origin-lineage-SARS-CoV-2 spike trimer  end on-binding to sialoside sugars was revealed contrasting with  extended surface-binding for heparin sugar ligands; uSTA-derived constraints used in structural modelling suggested sialoside-glycan binding sites in a beta-sheet-rich region of spike N-terminal domain (NTD). Consistent with this, uSTA-glycan binding was minimally- perturbed by antibodies that neutralize the ACE2-binding domain (RBD) but strongly disrupted in spike from the B1.1.7/alpha and B1.351/beta variants-of-concern, which possess hotspot mutations in the NTD. Sialoside binding in B-origin-lineage-NTD was unequivocally pinpointed by cryo-EM to a site that is created from residues that are notably deleted in variants (e.g. H69,V70,Y145 in alpha). An analysis of beneficial genetic variances in cohorts of patients from early 2020 suggests a model in which this site in the NTD of B-origin-lineage-SARS-CoV-2 (but not in alpha/beta-variants) may have exploited a specific sialylated-polylactosamine motif found on tetraantennary human N-linked-glycoproteins in deeper lung. Together these confirm a novel binding mode mediated by the unusual NTD of SARS-CoV-2 and suggest how it may drive virulence and/or zoonosis via modulation of glycan attachment. Since cell-surface glycans are widely relevant to biology and pathology, uSTA can now provide ready, quantitative, widespread analysis of complex, host-derived and post-translationally modified proteins with putative ligands relevant to disease even in previously confounding complex systems. Cytosolic aggregation of mitochondrial proteins disrupts cellular homeostasis by stimulating the aggregation of other proteins Mitochondria are organelles with their own genomes, but they rely on the import of nuclear-encoded proteins that are translated by cytosolic ribosomes. Therefore, it is important to understand whether failures in the mitochondrial uptake of these nuclear-encoded proteins can cause proteotoxic stress and identify response mechanisms that may counteract it. Here, we report that upon impairments in mitochondrial protein import, high-risk precursor and immature forms of mitochondrial proteins form aberrant deposits in the cytosol. These deposits then cause further cytosolic accumulation and consequently aggregation of other mitochondrial proteins and disease-related proteins, including -synuclein and amyloid {beta}. This aggregation triggers a cytosolic protein homeostasis imbalance that is accompanied by specific molecular chaperone responses at both the transcriptomic and protein levels. Altogether, our results provide evidence that mitochondrial dysfunction, specifically protein import defects, contributes to impairments in protein homeostasis, thus revealing a possible molecular mechanism by which mitochondria are involved in neurodegenerative diseases. Protein contact map prediction using multiple sequence alignment dropout and consistency learning for sequences with fewer homologs The prediction of protein contact map needs enough normalized number of effective sequence (Nf) in multiple sequence alignment (MSA). When Nf is small, the predicted contact maps are often not satisfactory. To solve this problem, we randomly selected a small part of sequence homologs for proteins with large Nf to generate MSAs with small Nf. From these MSAs, input features were generated and were passed through a consistency learning network, aiming to get the same results when using the features generated from the MSA with large Nf. The results showed that this method effectively improves the prediction accuracy of protein contact maps with small Nf. Prevalence, complete genome and metabolic potentials of a phylogenetically novel cyanobacterial symbiont in the coral-killing sponge, Terpios hoshinota Terpios hoshinota is a ferocious, space-competing sponge that kills a variety of stony corals by overgrowth. Outbreaks of this species have led to intense coral reef damage and declines in living corals on the square kilometer scale in many geographical locations. Our large-scale 16S rRNA gene survey across three oceans revealed that the core microbiome of T. hoshinota included operational taxonomic units (OTUs) related to Prochloron, Endozoicomonas, Pseudospirillum, SAR116, Magnetospira, and Ruegeria. A Prochloron- related OTU was the most dominant cyanobacterium in T. hoshinota in the western Pacific Ocean, South China Sea, and Indian Ocean. The complete metagenome-assembled genome of the Prochloron-related cyanobacterium and our pigment analysis revealed that this bacterium had phycobiliproteins and phycobilins and lacked chlorophyll b, inconsistent with the iconic definition of Prochloron. Furthermore, the phylogenetic analyses based on 16S rRNA genes and 120 single-copy genes demonstrated that the bacterium was phylogenetically distinct to Prochloron, strongly suggesting that it should be a sister taxon to Prochloron; we therefore proposed this symbiotic cyanobacterium as a novel species under a new genus: Candidatus Paraprochloron terpiosii. With the recovery of the complete genome, we characterized the metabolic potentials of the novel cyanobacterium in carbon and nitrogen cycling and proposed a model for the interaction between Ca. Pp. terpiosi LD05 and T. hoshinota. In addition, comparative genomics analysis revealed that Ca. Paraprochloron and Prochloron showed distinct features in transporter systems and DNA replication.

ImportanceThe finding that one species predominates cyanobacteria in T. hoshinota from different geographic locations indicates that this sponge and Ca. Pp. terpiosi LD05 share a tight relationship. This study builds the foundation for T. hoshinotas microbiome and paves a way for understanding the ecosystem, invasion mechanism, and causes of outbreak of this coral-killing sponge. Also, the first Prochloron-related complete genome enables us to study this bacterium with molecular approaches in the future and broadens our knowledge of the evolution of symbiotic cyanobacteria. Parent-offspring inference in inbred populations Genealogical relationships are fundamental components of genetic studies. However, it is often challenging to infer correct and complete pedigrees even when genome-wide information is available. For example, inbreeding can obfuscate genetic differences between individuals, making it difficult to even distinguish first-degree relatives such as parent-offspring from full siblings. Similarly, genotyping errors can interfere with the detection of genetic similarity between parents and their offspring. Inbreeding is common in natural, domesticated, and experimental populations and genotyping of these populations often has more errors than in human datasets, so efficient methods for building pedigrees under these conditions are necessary. Here, we present a new method for parent-offspring inference in inbred pedigrees called SPORE (Specific Parent-Offspring Relationship Estimation). SPORE is vastly superior to existing pedigree-inference methods at detecting parent-offspring relationships, in particular when inbreeding is high or in the presence of genotyping errors, or both. SPORE therefore fills an important void in the arsenal of pedigree inference tools.

Author SummaryKnowing the genealogical relationships among individuals is critical for genetic analyses, such as for identifying the mutations that cause diseases or that contribute to valuable agricultural traits such as milk production. Although many tools exist for establishing pedigrees using genetic information, these tools fail when individuals are highly inbred, such as in domesticated animals, or in groups of people in which consanguineous matings are common. Furthermore, existing tools do not work well when genetic information has errors at levels observed in modern datasets. Here, we present a novel approach to solve these problems. Our method is significantly more accurate than existing tools and more tolerant of errors in the genetic data. We expect that our method, which is simple to use and computationally efficient, will be a useful tool in a diversity of settings, from the studies of human and natural populations, to agricultural and experimental settings. The Temporal Statistics of Musical Rhythm across Western Genres: An Amplitude Modulation Phase Hierarchy Model Statistical learning by the human brain plays a core role in the development of cognitive systems like language and music. Both music and speech have structured inherent rhythms, however the acoustic sources of these rhythms are debated. Theoretically, rhythm structures in both systems may be related to a novel set of acoustic statistics embedded in the amplitude envelope, statistics originally revealed by modelling childrens nursery rhymes. Here we apply similar modelling to explore whether the amplitude modulation (AM) timescales underlying rhythm in music match those in child-directed speech (CDS). Utilising AM-driven phase hierarchy modelling previously applied to infant-directed speech (IDS), adult-directed speech (ADS) and CDS, we test whether the physical stimulus characteristics that yield speech rhythm in IDS and CDS describe rhythm in music. Two models were applied. One utilized a low-dimensional representation of the auditory signal adjusted for known mechanisms of the human cochlear, and the second utilized probabilistic amplitude demodulation, estimating the modulator (envelope) and carriers using Bayesian inference. Both models revealed a similar hierarchically-nested temporal modulation structure across Western musical genres and instruments. Core bands of AM and spectral patterning matched prior analyses of IDS and CDS, and music showed strong phase dependence between slower bands of AMs, again matching IDS and CDS. This phase dependence is critical to the perception of rhythm. Control analyses modelling other natural sounds (wind, rain, storms, rivers) did not show similar temporal modulation structures and phase dependencies. We conclude that acoustic rhythm in language and music has a shared statistical basis. A diagnostic primer pair to distinguish between wMel and wAlbB Wolbachia infection - A simplified real-time PCR approach for use in field collected Aedes aegypti in dengue reduction trials Detection of the Wolbachia endosymbiont in Aedes aegypti mosquitoes through real-time PCR assays is widely used during and after Wolbachia releases in dengue reduction trials involving the wMel and wAlbB strains. However, primers applied in current successful Wolbachia releases cannot be used in a single assay to distinguish between these strains. Here, we developed a new diagnostic primer pair wMA which can detect wMel or wAlbB infection in the same assay. We also tested current Wolbachia primers and show that there is variation in their performance when they are used to assess the relative density of Wolbachia. The new wMA primers provide an accurate and efficient estimate of the presence and density of both Wolbachia infections. Once-daily feeding is associated with better health in companion dogs: Results from the Dog Aging Project A variety of diets have been studied for possible anti-aging effects. In particular, studies of intermittent fasting and time-restricted feeding in laboratory rodents have found evidence of beneficial health outcomes. Companion dogs represent a unique opportunity to study diet in a large mammal that shares human environments. The Dog Aging Project has been collecting data on thousands of companion dogs of all different ages, sizes, and breeds since 2019. We leveraged this diverse cross-sectional dataset to investigate associations between feeding frequency and cognitive function (n = 10,474) as well as nine broad categories of health conditions (n = 24,238). Controlling for sex, age, breed, and other potential confounders, we found that dogs fed once daily rather than more frequently had lower mean scores on a cognitive dysfunction scale, and lower odds of having gastrointestinal, dental, orthopedic, kidney/urinary, and liver/pancreas disorders. Therefore, we find that once-daily feeding is associated with better health in multiple domains. Future research with longitudinal data can provide stronger evidence for a possible causal effect of feeding frequency on health in companion dogs.