Imbalanced segregation of recombinant haplotypes in hybrid populations reveals inter- and intrachromosomal Dobzhansky-Muller incompatibilities Dobzhansky-Muller incompatibilities (DMIs) are a major component of reproductive isolation between species. DMIs imply negative epistasis, and are exposed when two diverged populations hybridize. Mapping the locations of DMIs has largely relied on classical genetic mapping. Approaches to date are hampered by low power and the challenge of identifying DMI loci on the same chromosome, because strong initial linkage of parental haplotypes weakens statistical tests. Here, we propose new statistics to infer negative epistasis from haplotype frequencies in hybrid populations. When two divergent populations hybridize, the variance in heterozygosity at two loci decreases faster with time at DMI loci than at random pairs of loci. When two populations hybridize at near-even admixture proportions, the deviation of the observed variance from its expectation becomes negative for the DMI pair. This negative deviation enables us to detect intermediate to strong negative epistasis both within and between chromosomes. In practice, the detection window in hybrid populations depends on the demographic scenario, the recombination rate, and the strength of epistasis. When the initial proportion of the two parental populations is uneven, only strong DMIs can be detected with our method unless migration prevents parental haplotypes from being lost. We use the new statistics to infer candidate DMIs from three hybrid populations of swordtail fish. We identify numerous new DMI candidates, some of which are inferred to interact with several loci within and between chromosomes. Moreover, we discuss our results in the context of an expected enrichment in intrachromosomal over interchromosomal DMIs.

Author SummaryGenetic incompatibility in the form of (Bateson-)Dobzhansky-Muller incompatibilities (DMIs) is an important component of reproductive isolation between species. However, the evolutionary role of DMIs during the process of speciation is contentious. DMIs occur when two or more genetic variants interact to reduce their carriers fitness. Once recombination combines incompatible variants in hybrids, selection acts to remove these variants from the population. One step towards addressing the evolutionary role of DMIs is to quantify the prevalence of DMIs in incipient and hybridizing species. Here, we present statistics that are sensitive to the resulting recombinant imbalance and that can indicate the location of DMIs in hybrid genomes in various demographic scenarios. We use simulations to show that the time window during which a DMI is detectable depends on its genomic location, the severity of the DMI, and the populations demography. Importantly, our statistic distinguishes genetic associations arising due to physical linkage from those arising due to gene interactions, which allows for the inference of both inter- and intrachromosomal DMIs. Applying our statistics to three hybrid populations of swordtail fish, we confirm previously known DMIs and identify new candidate incompatibilities.
Seed banks alter the molecular evolutionarily dynamics of Bacillus subtilis Fluctuations in the availability of resources constrains the growth and reproduction of individuals, which subsequently effects the evolution of their respective populations. Many organisms contend with such fluctuations by entering a reversible state of reduced metabolic activity, a phenomenon known as dormancy. This pool of dormant individuals (i.e., a seed bank) does not reproduce and is expected to act as an evolutionary buffer, though it is difficult to observe this effect directly over an extended evolutionary timescale. Through genetic manipulation, we analyze the molecular evolutionary dynamics of Bacillus subtilis populations in the presence and absence of a seed bank over 700 days. The ability of these bacteria to enter a dormant state increased the accumulation of genetic diversity over time and altered the trajectory of mutations, findings that were recapitulated using simulations based on a mathematical model of evolutionary dynamics. While the ability to form a seed bank did not alter the degree of negative selection, we found that it consistently altered the direction of molecular evolution across genes. Together, these results show that the ability to form a seed bank can affect the direction and rate of molecular evolution over an extended evolutionary timescale.
Juvenile Gouldian Finches (Erythrura gouldiae) form sibling sub-groups during social integration The formation of social relationships in complex groups is critical in shaping patterns of social organization and behavioral development. In many birds, young individuals remain dependent on their parents for extended periods but must abruptly transition to navigating interactions in the wider group after independence. While lack of social relationships during this period is detrimental in the development of later social skills, little is known about the social relationships juveniles form after independence in many bird species. In this study we describe patterns of social interactions in juvenile Gouldian Finches (Erythrura gouldiae) during transitions from family groups into flocks of unfamiliar individuals. A group of 20 juveniles from 4 families were introduced into two flocks. After introductions juveniles showed a gradient of approach rates with most approaches directed towards siblings, followed by juvenile peers, adult females, and lastly adult males. Significant preferences for siblings resulted in the emergence of sibling subgroups within the larger social network. This active self-assortment of siblings suggests that sibling sub-groups are an important bridge linking social connections within the family and the wider group. Such findings suggests that sibling relationships have a critical role in the socialization after independence, as well as structuring the social organization of Gouldian finch flocks. 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. A network approach to genetic circuit designs As genetic circuits become more sophisticated, the size and complexity of data about their designs increases. This data captured goes beyond monolithic genetic sequences and towards circuit modularity and functional details, which are beneficial for analyzing circuit performance and establishing design automation techniques. However, the accessibility, visualisation and usability of design data (and metadata) have received relatively little attention to date. Here, we present a method to turn circuit designs into networks and showcase its potential to enhance the utility of design data. Since networks are dynamic structures, initial graphs can be interactively shaped into sub-networks of relevant information based on requirements such as abstraction, hierarchy and protein interactions. Additionally, several visual changes can be applied, such as colouring or clustering nodes based on types (e.g., genes or promoters), resulting in easier comprehension from a user perspective. This approach allows circuit designs to be coupled to other networks, such as metabolic pathways or implementation protocols captured in graph-like formats. Therefore, we advocate using networks to structure, access and improve synthetic biology information. Bispecific antibody neutralizes circulating SARS-CoV-2 variants, prevents escape and protects mice from disease Neutralizing antibodies targeting the receptor binding domain (RBD) of the SARS-CoV-2 Spike (S) are among the most promising approaches against coronavirus disease 2019 (COVID-19)1,2. We developed a bispecific, IgG1-like molecule (CoV-X2) based on two antibodies derived from COVID-19 convalescent donors, C121 and C1353. CoV-X2 simultaneously binds two independent sites on the RBD and, unlike its parental antibodies, prevents detectable S binding to Angiotensin-Converting Enzyme 2 (ACE2), the virus cellular receptor. Furthermore, CoV-X2 neutralizes SARS-CoV-2 and its variants of concern, as well as the escape mutants generated by the parental monoclonals. In a novel animal model of SARS-CoV-2 infection with lung inflammation, CoV-X2 protects mice from disease and suppresses viral escape. Thus, simultaneous targeting of non-overlapping RBD epitopes by IgG-like bispecific antibodies is feasible and effective, combining into a single molecule the advantages of antibody cocktails. Characterization of methylation profiles in spontaneous preterm birth placental villous tissue Preterm birth is a global public health crisis which results in significant neonatal and maternal mortality. Yet little is known regarding the molecular mechanisms of idiopathic spontaneous preterm birth, and we have few diagnostic markers for adequate assessment of placental development and function. Previous studies of placental pathology and our transcriptomics studies suggest a role for placental maturity in idiopathic spontaneous preterm birth. It is known that placental DNA methylation changes over gestation. We hypothesized that if placental hypermaturity is present in our samples, we would observe a unique idiopathic spontaneous preterm birth DNA methylation profile potentially driving the gene expression differences we previously identified in our placental samples. Our results indicate the idiopathic spontaneous preterm birth DNA methylation pattern mimics the term birth methylation pattern suggesting hypermaturity. Only seven significant differentially methylated regions fitting the idiopathic spontaneous preterm birth specific (relative to the controls) profile were identified, indicating unusually high similarity in DNA methylation between idiopathic spontaneous preterm birth and term birth samples. We identified an additional 1,718 significantly methylated regions in our gestational age matched controls were the idiopathic spontaneous preterm birth DNA methylation pattern mimics the term birth methylation pattern, again indicating a striking level of similarity between the idiopathic spontaneous preterm birth and term birth samples. Pathway analysis of these regions revealed differences in genes within the WNT and Cadherin signaling pathways, both of which are essential in placental development and maturation. Taken together, these data demonstrate that the idiopathic spontaneous preterm birth samples are molecularly more mature than expected given their respective gestational age which likely impacts birth timing. Comprehensive-immunopeptidomics analysis reveals presentation of potential neoantigens carrying cancer driver mutations Understanding the properties of human leukocyte antigen (HLA) peptides (HLAp) is essential for cancer precision medicine, while the direct identification of HLAp from a tiny piece of clinical tissues by mass spectrometry (MS) is still confronted with technical challenges. Here, to overcome that hindrances, high-field asymmetric waveform ion mobility spectrometry (FAIMS) is introduced to conduct differential ion mobility (DIM)-MS by seamless gas-phase fractionation optimal for scarce samples. The global-immunopeptidomics analysis enables in-depth identification of 44,785 HLAp, including 2 neoantigens with KRAS-G12V and CPPED1-R228Q from stage IV colorectal cancer (CRC) tissues obtained from 17 subjects. Comparison of tissue-based personal immunopeptidome disclosed cancer-specific processing of HLAp. Since the direct identification of neoantigens from CRC tissues suggests more potential neoantigens have yet to been identified, the targeted-immunopeptidomics by screening-oriented parallel reaction monitoring (PRM) has been established and identified two more neoantigens with oncogenic KRAS. The targeted-immunopeptidomics analysis clarifies the presentation of aimed neoantigens, including neoantigens that are unpredictable by computational algorithms. The comprehensive-immunopeptidomics approach combining the FAIMS-assisted DIM-MS and the screening-oriented PRM contributes the direct and effective identification of HLAp and emerging neoantigens from clinical tissue samples, as an advanced strategy to identify the authentic and recurrent neoantigens for cancer immunotherapy. Evidence that faecal carriage of resistant Escherichia coli by 16-week-old dogs in the United Kingdom is associated with raw feeding We report a survey (August 2017 to March 2018) and risk factor analysis of faecal carriage of antibacterial-resistant (ABR) Escherichia coli in 223 sixteen-week-old dogs in the United Kingdom. Raw feeding was associated with the presence of E. coli resistant to fluoroquinolones, tetracycline, amoxicillin, and streptomycin, but not to cefalexin or cefotaxime. Whole genome sequencing of 30 fluoroquinolone-resistant (FQ-R), 22 cefotaxime-resistant (CTX-R) and seven dual FQ-R/CTX-R E. coli isolates showed a wide range of sequence types (STs), an approximately 50:50 split of CTX-M:AmpC-mediated CTX-R, and almost exclusively mutational FQ-R dominated by ST744 and ST162. Comparisons between E. coli isolates from puppies known to be located within a 50 x 50 km region with those isolated from human urinary tract and bloodstream infections (isolated in parallel in the same region) identified a clone of ST963 E. coli carrying chromosomal blaCMY.2 in two puppies and causing two urinary tract infections and one bloodstream infection. Furthermore, an ST744 FQ-R clone was carried by one puppy and caused one urinary tract infection. Accordingly, we conclude that raw feeding is associated with carriage of ABR E. coli in dogs even at sixteen weeks of age and that bacteria carried by dogs are shared with humans. Dynamic interplay between a TonB dependent heme transporter and a TonB protein in a membrane environment The envelope of Gram-negative bacteria is composed of a double membrane separated by the periplasmic space. This organization imposes geometrical and distance constraints that are key for the mechanism of action of multicomponent systems spanning the envelope. However, consideration of all three compartments by experimental approaches is still elusive. Here we used the state-of-the-art molecular dynamics simulation in an Escherichia coli envelope model to obtain a dynamic view of molecular interactions between the outer membrane heme transporter HasR and the inner membrane TonB-like protein HasB. Their interaction allows the transfer of the inner membrane proton motive force derived energy to the transporter for heme internalization. The simulations which incorporate both membranes show the key role of periplasmic domains of both proteins, and their dynamics in the complex formation and stability. They revealed a previously unidentified atomic network of interactions, as well as the sequences of the interactions and their variations with the presence of external substrates. Experimental validation (mutations, phenotypic and in vitro assays) confirms the robustness of our approach and provides verification of the simulation-predicted interactions. Based on structural and sequence conservation, the network of interaction revealed in this study is expected to occur in other nutrient import systems. The integrative approach presented here is highly useful to study the dynamic interplay between components of any other bacterial transmembrane systems. Sablefish (Anoplopoma fimbria Pallas, 1814) plasma biochemistry and hematology reference intervals including blood cell morphology Plasma biochemistry and hematology reference intervals are integral health assessment tools in all medical fields, including aquatic animal health. As sablefish (Anoplopoma fimbria) are becoming aquaculturally and economically more important, this manuscript provides essential reference intervals (RI) for their plasma biochemistry and hematology along with reference photomicrographs of blood cells in healthy, fasted sablefish. Blood cell morphology can differ between fish species. In addition, blood cell counts and blood chemistry can vary between fish species, demographics, water conditions, seasons, diets, and culture systems, which precludes the use of RIs from other fish species. For this study, blood was collected for plasma biochemistry and hematology analysis between June 20 and July 18, 2019, from healthy, yearling sablefish, hatched and reared in captivity on a commercial diet. Overnight fast of 16-18 hours did not sufficiently reduce lipids in the blood, which led to visible lipemia and frequent rupture of blood cells during analysis. Therefore, sablefish should be fasted for 24 to 36 hours before blood is collected to reduce hematology artifacts or possible reagent interference in plasma biochemistry analysis. Lymphocytes were the most dominant leukocytes (98%), while eosinophils were rare, and basophils were not detected in sablefish. Neutrophils were very large cells with Dohle bodies. In mammals and avian species, Dohle bodies are usually signs of toxic change from inflammation, but no such association was found in these fish. In conclusion, lipemia can interfere with sablefish blood analysis, and available removal methods should be evaluated as fasting for up to 36 h might not always be feasible. Also, more studies are required to establish RI for different developmental stages and rearing conditions. Reuse of a wing venation gene-regulatory network in patterning the eyespot rings of butterflies Novel organismal traits might reuse ancestral gene-regulatory networks (GRNs) in their development, but data supporting this mechanism are still sparse. Here we propose that a conserved venation gene network, used in patterning insect wings, has been recruited to pattern the sharp and distinct rings of color in butterfly eyespot development. This network involves Decapentaplegic (Dpp), acting as a central morphogen, activating optix and spalt at different concentration thresholds. It also involves Spalt cross-regulating optix resulting in the formation of a sharp boundary between the two genes. First, using in situ hybridizations, we show that dpp is expressed in the eyespot centers during the early pupal stage and that CRISPR-Cas9 embryonic knockouts of dpp, optix, and spalt result in the loss of eyespots, loss of the orange ring, and loss of the black scales, respectively. Furthermore, using RNAi during the pupal stage, we show that dpp down-regulation results in the complete or partial loss of eyespots. Using CRISPR disruptions of optix or spalt, followed by immunostainings, we show that Spalt represses optix in the central region of the eyespot, limiting optix expression to a more peripheral ring. We further illustrate that optix disruptions alter scale pigmentation and scale ultrastructure as they transform orange to brown scales. Altogether, the regulatory interactions between dpp, spalt and optix mimic those found in earlier larval developmental stages, in the anterior compartment of an insects wing, where these genes play a role in venation patterning. The network similarities suggest that the venation GRN was co-opted to aid in the differentiation of the eyespot rings. TAS-Seq: a robust and sensitive amplification method for bead-based scRNA-seq Single-cell RNA-sequencing (scRNA-seq) is valuable for analyzing cellular heterogeneity. Cell composition accuracy is critical for analyzing cell-cell interaction networks from scRNA-seq data. We developed terminator-assisted solid-phase cDNA amplification and sequencing (TAS-Seq) for scRNA-seq based on a terminator, terminal transferase, and nanowell/bead-based scRNA-seq platform; TAS-Seq showed high tolerance to variations in the terminal transferase reaction, which complicate the handling of existing terminal transferase-based scRNA-seq methods. In murine and human lung samples, TAS-Seq yielded scRNA-seq data that were highly correlated with flow-cytometric data, showing higher gene-detection sensitivity and more robust detection of important cell-cell interactions and expression of growth factors/interleukins in cell subsets than 10X Chromium v2 and Smart-seq2. Expanding TAS-Seq application will improve understanding and atlas construction of lung biology at the single-cell level. Advancing motion denoising of multiband resting-state functional connectivity fMRI data Simultaneous multi-slice (multiband) accelerated functional magnetic resonance imaging (fMRI) provides dramatically improved temporal and spatial resolution for resting-state functional connectivity (RSFC) studies of the human brain in health and disease. However, multiband acceleration also poses unique challenges for denoising of subject motion induced data artifacts, the presence of which is a major confound in RSFC research that substantively diminishes reliability and reproducibility. We comprehensively evaluated existing and novel approaches to volume censoring-based motion denoising in the Human Connectome Project (HCP) dataset. We show that assumptions underlying common metrics for evaluating motion denoising pipelines, especially those based on quality control-functional connectivity (QC-FC) correlations and differences between high- and low-motion participants, are problematic, and appear to be inappropriate in their current widespread use as indicators of comparative pipeline performance and as targets for investigators to use when tuning pipelines for their own datasets. We further develop two new quantitative metrics that are instead agnostic to QC-FC correlations and other measures that rely upon the null assumption that no true relationships exist between trait measures of subject motion and functional connectivity, and demonstrate their use as benchmarks for comparing volume censoring methods. Finally, we develop and validate quantitative methods for determining dataset-specific optimal volume censoring parameters prior to the final analysis of a dataset, and provide straightforward recommendations and code for all investigators to apply this optimized approach to their own RSFC datasets. Multiple molecular events underlie stochastic switching between two heritable cell states in a eukaryotic system Eukaryotic transcriptional networks are often large and contain several levels of feedback regulation. Many of these networks have the ability to generate and maintain several distinct transcriptional states across multiple cell divisions and to switch between them. In certain instances, switching between cell states is stochastic, occurring in a small subset of cells of an isogenic population in a seemingly homogenous environment. Given the scarcity and unpredictability of switching in these cases, investigating the determining molecular events is challenging. White-opaque switching in the fungal species Candida albicans is an example of stably inherited cell states that are determined by a complex transcriptional network and can serve as an experimentally accessible model system to study characteristics important for stochastic cell fate switching in eukaryotes. In standard lab media, genetically identical cells maintain their cellular identity (either "white" or "opaque") through thousands of cell divisions and switching between the states is rare. By isolating populations of white or opaque cells, previous studies have elucidated the many differences between the two stable cell states and identified a set of transcriptional regulators needed for cell type switching. Yet little is known about the molecular events that determine the rare, stochastic switching events that occur in single cells. We use microfluidics combined with fluorescent reporters to directly observe rare switching events between the white and opaque states. We investigate the stochastic nature of switching by beginning with white cells and monitoring the activation of Wor1, a master regulator and marker for the opaque state, in single cells and throughout cell pedigrees. Our results indicate that switching requires two stochastic steps; first an event occurs that predisposes a lineage of cells to switch. In the second step, some but not all, of those predisposed cells rapidly express high levels of Wor1 and commit to the opaque state. To further understand the rapid rise in Wor1, we used a synthetic inducible system in Saccharomyces cerevisiae into which a controllable C. albicans Wor1 and a reporter for its transcriptional control region have been introduced. We document that Wor1 positive autoregulation is highly cooperative (Hill coefficient > 3), leading to rapid activation and producing an "all or none" rather than a graded response. Taken together, our results suggest that reaching a threshold level of a master regulator is sufficient to drive cell type switching in single cells and that an earlier molecular event increases the probability of reaching that threshold in certain small lineages of cells. Quantitative molecular analysis of the white-opaque circuit can serve as a model for the general understanding of complex circuits. AFFORDABLE, REPLICABLE ROBOTIC MINIRHIZOTRON SAMPLING FOR ROOT DYNAMICS STUDIES O_LIMinirhizotrons (paired camera systems and buried observatories) are the best current method to make repeatable measurements of fine root dynamics in the field. Automating data collection is the only way to assess fine-scale temporal changes in fine roots in natural systems. When paired with above-ground proximal remote sensing, automatic minirhizotron data could reveal coordination between above and below ground phenology, supporting both plant allocation and carbon exchange understanding. However, there are many challenges to automating minirhizotrons for field experiments. First, instruments must be cheap enough to replicate given shallow field of view and variable natural environments. Second, automated analysis must be robust to changeable soil and root conditions because image properties extracted must have biological meaning.
C_LIO_LIHere, we demonstrate an automatic minirhizotron scheme, built with off-the-shelf parts and capable to sample at sub-daily resolution paired with a neural network-based image analysis method. As a proof of concept, we tested the instruments and the methodology in a mesocosm study and in two short real-world field trials alongside datasets from other instruments (e.g. proximal remote sensed leaf dynamics).
C_LIO_LIWe show that the method produces robust daily time-series of root dynamics in the mesocosm and the field. We applied the same model across multiple instruments, demonstrating good reproducibility of measurements. Temporal variations of root cover were a strong driver of soil CO2 efflux in mesocosm, and vegetation dynamics from above ground proximal remote sensing and minirhizotron data differed both in mesocosm and field. We found sensitivity of root cover extracted to soil moisture and sometimes time of day (potentially relating to soil moisture), which may only affect high frequency imagery and not commonly reported as encountered when training neural networks on traditional, time-distinct minirhizotron studies.
C_LIO_LIWe discuss avenues for dealing with such issues in future field applications of minirhizotrons. If such issues are dealt with to a satisfactory manner in the field, timeseries of root biomass and traits from replicated instruments can add a new dimension to phenology studies at the ecosystem level by understanding the dynamics of root properties and traits.
C_LI Basal Gp78 mitophagy promotes mitochondrial health and limits mitochondrial ROS production Mitochondria are major sources of cytotoxic reactive oxygen species (ROS) that contribute to cancer progression. Mitophagy, the selective elimination of mitochondria by autophagy, monitors and maintains mitochondrial health and integrity, eliminating ROS-producing mitochondria. However, mechanisms underlying mitophagic control of mitochondrial homeostasis under basal conditions remain poorly understood. Gp78 E3 ubiquitin ligase is an endoplasmic reticulum membrane protein that induces mitochondrial fission and mitophagy of depolarized mitochondria. Here, we report that CRISPR/Cas9 knockout of Gp78 in HT-1080 fibrosarcoma cells increased mitochondrial volume and rendered cells resistant to carbonyl cyanide m-chlorophenyl hydrazone (CCCP)-induced mitophagy. These effects were phenocopied by knockdown of the essential autophagy protein ATG5 in wild-type HT-1080 cells. Use of the mito-Keima mitophagy probe confirmed that Gp78 promoted both basal and damage-induced mitophagy. Application of a spot detection algorithm (SPECHT) to GFP-mRFP tandem fluorescent-tagged LC3 (tfLC3)-positive autophagosomes reported elevated autophagosomal maturation in wild-type HT-1080 cells relative to Gp78 knockout cells, predominantly in proximity to mitochondria. Mitophagy inhibition by either Gp78 knockout or ATG5 knockdown reduced mitochondrial potential and increased mitochondrial ROS. Live cell analysis of tfLC3 in HT-1080 cells showed the preferential association of autophagosomes with mitochondria of reduced potential. Basal Gp78-dependent mitophagic flux is therefore selectively associated with reduced potential mitochondria promoting maintenance of a healthy mitochondrial population and limiting ROS production. NOMA: a high-throughput microchip for robust, sequential measurements of secretions from the same single-cells Despite recent advances in single-cell analysis technologies, lacking simple methods to keep the live single-cells traceable for longitudinal detection reliably poses a significant obstacle in single-cell secretion analysis. Here we reported the high-density NOMA (narrow-opening microwell array) microchip that realized the retention of[&ge;] 97% of trapped single cells in dedicated spatial locations during repetitive detection procedures, verified with both adherent and suspension cells by two researchers independently. We applied it in monitoring single-cell protein secretions sequentially from the same single cells, and we found the digital protein secretion patterns dominate the protein secretion. We also demonstrated the microchip for longitudinally tracking IL-8 and the CD81+EV secretions from the same single-cells over days, which revealed the presence of "super secretors" within the cell population be more persistent to secrete protein or extracellular vesicle for an extended period. The NOMA platform reported here is simple, robust, and easy to operate for tracking sequential measurements from the same single cells, representing a novel and informative tool to inspire new observations in biomedical research.

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org.highwire.dtl.DTLVardef@aa69c7org.highwire.dtl.DTLVardef@6bc79org.highwire.dtl.DTLVardef@3fcbbforg.highwire.dtl.DTLVardef@597f4b_HPS_FORMAT_FIGEXP  M_FIG C_FIG High school science fair: Experiences of two groups of undergraduate bioscience students Science fairs offer potential opportunities for students to learn first-hand about the practices of science. Over the past six years we have been carrying out voluntary and anonymous surveys with regional and national groups of high school and post high school students to learn about their high school science fair experiences regarding help received, obstacles encountered, and opinions about the value and impact of science fair. Understanding what students think about science fairs will help educators make science fairs more effective learning opportunities. In this paper, we focus on the findings with two national groups of post high school students - undergraduate research fellows (SURF students) who did research at UT Southwestern Medical Center during 2014-2019 and undergraduates biology students attending the 2019 Howard Hughes Medical Institute Science Education Alliance (SEA) summer symposium. About 25% of the students who completed surveys indicated that they had participated in high school science fair, but more than half attended high schools where science fairs were unavailable. Effectively, 6 out of every 10 students participated in science fair if available. Students who could have participated in high school science fair but chose not to do so identified not enough time and coming up with their project idea as major reasons why not. About half the SURF students favored requiring non-competitive science fair regardless whether they themselves had participated in science fair. On the other hand, less than 1 in 5 thought that competitive science fair should be required. Introduction to the scientific process and general learning were mentioned most frequently as the reasons to require non-competitive science fair; these reasons were mentioned rarely in connection with competitive science fair. Unlike the national cohort of high school students we surveyed previously, who mostly did science fair in 9th and 10th grades, SURF students participated in science fair throughout high school and were twice as likely as high school students to have carried out science fair more than once. In conclusion, our findings suggest that participation of the undergraduate bioscience majors in high school science fairs occurs far more frequently than recognized previously. The findings emphasize further the importance of incentivizing rather than requiring science fair participation, especially in 9th and 10th grades, and the potential value of developing non-competitive science fairs. Selective Src-Family B Kinase Inhibition Promotes Pulmonary Artery Endothelial Cell Dysfunction. Protein tyrosine kinases (PTKs) are essential for eukaryotic signaling. By targeting select PTKs, the group of drugs known as Tyrosine kinase inhibitors (TKIs) have proven to be effective for treating multiple diseases ranging from cancer to pulmonary fibrosis. However, some TKIs also paradoxically lead to the development of adverse conditions such as pulmonary arterial hypertension (PAH) by promoting endothelial cell dysfunction (ECD). We hypothesize that (1) subsets of PTKs may disproportionately modulate signaling pathways critical for endothelial homeostasis, such as BMPR2 signaling, and (2) inhibiting those pro-endothelial PTKs can promote the development of ECD. Herein we use an agnostic high-throughput siRNA screen to investigate how PTKs affect the canonical BMPR2 signaling pathway. Our major finding is that within the Src-family of non-receptor PTKs, the Src-B family promotes canonical BMPR2 signaling while the Src-A family suppresses it. We focus on two representative members of each family, Lck (for Src-B) and Fyn (for Src-A) that are the strongest activators or inhibitors of BMPR2 signaling in the screen. We confirm that Lck is expressed in the endothelium of pulmonary arteries and show that Lck knockout (termed si-Lck) in pulmonary artery endothelial cells (PAECs) suppresses canonical BMPR2 signaling while Fyn knockout (termed si-Fyn) promotes canonical BMPR2 signaling. Furthermore, Lck and Fyn are responsible for opposing functional behaviors in PAECs: si-Lck promotes apoptosis and interferes with tube formation while si-Fyn suppresses apoptosis and promotes tube formation. After analyzing the whole-transcriptome signature of si-Lck and si-Fyn PAECs we find that in addition to BMPR2 signaling suppression, si-Lck (and not si-Fyn) increases a broad number of ECD markers and increases canonical NF-{kappa}{beta} signaling. In summary, for the first time we show that Src-A and B Family of PTKs exert differential control over key endothelial cell signaling pathways resulting in direct phenotypic consequences. This knowledge may help to guide the design of more precise TKIs which avoid adverse drug reactions brought about through endothelial cell dysfunction. Flexibility of Short-chain dehydrogenase is interconnected to its promiscuity for the reduction of multiple ketone intermediates Short-chain dehydrogenases/reductases (SDRs) are a convenient class of enzymes used to synthesize enantiopure alcohols. Several studies describe native or engineered SDRs for converting substrates of interest using cost and time-intensive high-throughput approaches. The classification of SDRs is based on chain length and cofactor binding site. Of these, the shorter  Classical and the longer  Extended enzymes participate in ketoreduction. However, comparative analysis of various modelled SDRs reveals a length independent conserved N-terminal Rossmann fold and a variable C-terminus region for both types. The general hypothesis is that the latter domain influences the enzymes flexibility that may affect the observed promiscuity of the enzyme. We have used a machine learning algorithm on this flexible domain to build a rationale to screen promiscuous candidates. We have built a data set consisting of physicochemical properties derived from the amino-acid composition of enzymes to select closely associated promiscuous mesophilic enzymes. The resulting in vitro studies on pro-pharmaceutical substrates illustrate a direct correlation between the C-terminal lid-loop structure, enzyme melting temperature and the turnover number. We present a walkthrough for exploring promiscuous SDRs for catalyzing enantiopure alcohols of industrial importance. PIN-FORMED1 polarity in the shoot is insensitive to the polarity of neighbouring cells In plants, epidermal cells are planar-polarized along an axis marked by the asymmetric localization patterns of several proteins including PIN-FORMED1 (PIN1), which facilitates the directional efflux of the plant hormone auxin to pattern phyllotaxis (Heisler et al., 2010; Mansfield et al., 2018; Reinhardt et al., 2003). While PIN1 polarity is known to be regulated non-cell autonomously via the MONOPTEROS (MP) transcription factor, how this occurs has not been determined (Bhatia et al., 2016). Here we use mosaic expression of the serine threonine kinase PINOID (PID) to test whether PIN1 polarizes according to the polarity of neighbouring cells. Our findings reveal that PIN1 is insensitive to the polarity of PIN1 in neighbouring cells arguing against auxin flux or extracellular auxin concentrations acting as a polarity cue, in contrast to previous model proposals (Abley et al., 2016; Stoma et al., 2008). AlphaFold2-aware protein-DNA binding site prediction using graph transformer Protein-DNA interactions play crucial roles in the biological systems, and identifying protein-DNA binding sites is the first step for mechanistic understanding of various biological activities (such as transcription and repair) and designing novel drugs. How to accurately identify DNA-binding residues from only protein sequence remains a challenging task. Currently, most existing sequence-based methods only consider contextual features of the sequential neighbors, which are limited to capture spatial information. Based on the recent breakthrough in protein structure prediction by AlphaFold2, we propose an accurate predictor, GraphSite, for identifying DNA-binding residues based on the structural models predicted by AlphaFold2. Here, we convert the binding site prediction problem into a graph node classification task and employ a transformer-based variant model to take the protein structural information into account. By leveraging predicted protein structures and graph transformer, GraphSite substantially improves over the latest sequence-based and structure-based methods. The algorithm is further confirmed on the independent test set of 181 proteins, where GraphSite surpasses the state-of-the-art structure-based method by 16.4% in AUPR and 11.2% in MCC, respectively. We provide the datasets, the predicted structures, and the source codes along with the pre-trained models of GraphSite at https://github.com/biomed-AI/GraphSite. The GraphSite web server is freely available at https://biomed.nscc-gz.cn/apps/GraphSite. The 55K SNP-Based Exploration of QTL for Spikelet Number Per Spike in a Tetraploid Wheat (Triticum turgidum L.) Population: Chinese Landrace Ailanmai X Wild Emmer The spikelet number per spike (SNS) is a primary factor determining wheat yield. Common wheat breeding reduces the genetic diversity among elite germplasm resources, leading to a detrimental effect on future wheat production. It is, therefore, necessary to explore new genetic resources for SNS to increase wheat yield. A tetraploid landrace  Ailanmai x wild emmer wheat recombinant inbred line (RIL) population was used to construct a genetic map using the wheat 55K single nucleotide polymorphism (SNP) array. The linkage map containing 1150 bin markers with a total genetic distance of 2411.8 cM was obtained. Based on phenotypic data from eight environments and best linear unbiased prediction (BLUP) values, five quantitative trait loci (QTL) for SNS were identified, explaining 6.71-29.40% of the phenotypic variation. Two of them, QSns.sau-AM-2B.3 and QSns.sau-AM-3B.2, were detected as the major and novel QTL. Their effects were further validated in two additional F2 populations using tightly linked Kompetitive Allele-Specific PCR (KASP) markers. Potential candidate genes within the physical intervals of corresponding QTL were predicted to participate in inflorescence development and spikelet formation. Genetic associations between SNS and other agronomic traits were also detected and analyzed. This study demonstrates the feasibility of wheat 55K SNP array developed for common wheat in genetic mapping of tetraploid population and shows the potential application of wheat related species in wheat improvement programs. 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. Critical re-evaluation of the slope factor of the operational model of agonism Background and PurposeAlthough being a relative term, agonist efficacy is a cornerstone in the proper assessment of agonist selectivity and signalling bias. The operational model of agonism (OMA) has become successful in the determination of agonist efficacies and ranking them. In 1985, Black et al. introduced the slope factor to the OMA to make it more flexible and allow for fitting steep as well as flat concentration-response curves.

Experimental ApproachFunctional analysis of OMA demonstrates that the slope factor implemented by Black et al. affects relationships among parameters of the OMA, leading to wrong estimates of operational efficacy and affinity of an agonist. In contrast, functional analysis of OMA with Hill coefficient as a slope factor has not this flaw.

Key ResultsFitting of the OMA with Black et al. slope factor to concentration-response curves of several models (homotropic allosteric modulation, substrate inhibition and non-competitive auto-inhibition) gives wrong estimates of operational efficacy and affinity. In contrast, fitting of the OMA modified by the Hill coefficient to concentration-response curves of these several models gives correct estimates of operational efficacy and affinity.

Conclusion and ImplicationsThe OMA modified by the Hill coefficient can be used for correct ranking of agonism and subsequent analysis, like quantification of signalling bias.