Genetic architecture of natural variation of cardiac performance in flies Deciphering the genetic architecture of human cardiac disorders is of fundamental importance but their underlying complexity is a major hurdle. We investigated the natural variation of cardiac performance in the sequenced inbred lines of the Drosophila Genetic Reference Panel (DGRP)1. Genome Wide Associations Studies (GWAS) identified genetic networks associated with natural variation of cardiac traits which were used to gain insights as to the molecular and cellular processes affected. Non-coding variants that we identified were used to map potential regulatory non-coding regions, which in turn were employed to predict Transcription Factors (TFs) binding sites. Cognate TFs, many of which themselves bear polymorphisms associated with variations of cardiac performance, were also validated by heart specific knockdown. Additionally, we showed that the natural variations associated with variability in cardiac performance affect a set of genes overlapping those associated with average traits but through different variants in the same genes. Furthermore, we showed that phenotypic variability was also associated with natural variation of gene regulatory networks. More importantly, we documented correlations between genes associated with cardiac phenotypes in both flies and humans, which supports a conserved genetic architecture regulating adult cardiac function from arthropods to mammals. Specifically, roles for PAX9 and EGR2 in the regulation of the cardiac rhythm were established in both models, illustrating that the characteristics of natural variations in cardiac function identified in Drosophila can accelerate discovery in humans.
The maize gene maternal derepression of r1 (mdr1) encodes a DNA glycosylase with maternal and paternal fertility functions Demethylation of transposons can activate expression of nearby genes and cause imprinted gene expression in endosperm, and it is hypothesized to lead to expression of transposon siRNAs that reinforce silencing in the next generation through transfer either into egg or embryo. Here we describe maternal derepression of r1 (mdr1), which encodes a DNA glycosylase with homology to Arabidopsis DEMETER and which is partially responsible for demethylation of thousands of regions in endosperm. Instead of promoting siRNA expression in endosperm, MDR1 activity inhibits it. Methylation of most repetitive DNA elements in endosperm is not significantly affected by MDR1, with an exception of Helitrons. While maternally-expressed imprinted genes preferentially overlap with MDR1 demethylated regions, the majority of genes that overlap demethylated regions are not imprinted. Double mutant megagametophytes lacking both MDR1 and its close homolog DNG102 result in early seed failure, and double mutant microgametophytes fail pre-fertilization. These data establish DNA demethylation by glycosylases as essential in maize endosperm and pollen and suggest that neither transposon repression nor genomic imprinting are its main function in endosperm.
Molecular diversity maintained by long-term balancing selection in mating loci defines multiple mating types in fungi Balancing selection, an evolutionary force that retains genetic diversity, has been detected in multiple genes and organisms, such as the sexual mating loci in fungi. However, to quantify the strength of balancing selection and define the mating-related genes require a large number of specimens. In tetrapolar basidiomycete fungi, sexual type is determined by two unlinked loci, MATA and MATB. Genes in both loci defines mating type identity, control successful mating and completion of the life cycle. These loci are usually highly diverse. Previous studies have speculated, based on culture crosses, that species of the non-model genus Trichaptum (Hymenochaetales, Basidiomycota) possess a tetrapolar mating system, with multiple alleles. Here, we sequenced a hundred and eighty specimens of three Trichaptum species. We characterized the chromosomal location of MATA and MATB, the molecular structure of MAT regions and their allelic richness. Our sequencing effort was sufficient to molecularly characterize multiple MAT alleles segregating before the speciation event of Trichaptum species. Our analyses suggested that long-term balancing selection has generated trans-species polymorphisms. Mating sequences were classified in different allelic classes based on an amino acid identity (AAI) threshold supported by phylogenetics. The inferred allelic information mirrored the outcome of in vitro crosses, thus allowing us to support the degree of allelic divergence needed for successful mating. Even with the high amount of divergence, key amino acids in functional domains are conserved. The observed allelic classes could potentially generate 14,560 different mating types. We conclude that the genetic diversity of mating in Trichaptum loci is due to long-term balancing selection, with limited recombination and duplication activity. Our large number of sequenced specimens highlighted the importance of sequencing multiple individuals from different species to detect the mating-related genes, the mechanisms generating diversity and the evolutionary forces maintaining them.

Author summaryFungi have complex mating systems, and basidiomycete fungi can encode thousands of mating types. Individuals with the same mating type cannot mate. This sexual system has evolved to facilitate sexual mating, increasing the chances to recombine into advantageous allelic combination and prune deleterious alleles. We explored the genomes of hundred and eighty specimens, combined with experimental mating studies of selected specimens, from a non-model organism (Trichaptum). We characterized the genomic regions controlling sex. The mating ability of the specimens confirmed the role of the mating alleles observed in the genomic data. The detailed analyses of many specimens allowed us to observe gene duplication and rearrangements within the mating loci, increasing the diversity within these loci. We supported previous suggestions of balancing selection in this region, an evolutionary force that maintains genomic diversity. These results supports that our fungal specimens are prone to outcross, which might facilitate the adaptation to new conditions. Are microbes growing on flowers evil? Effects of old flower microbes on fruit set in a wild ginger with one-day flowers, Alpinia japonica (Zingiberaceae) Flowers are colonized and inhabited by diverse microbes. Plants rapidly replace flowers with short lifespan, and old flowers senesce. This may contribute to avoiding adverse effects of the microbes. In this study, we investigate if the flower microbial community on old flowers impedes fruit and seed production in a wild ginger with one-day flowers. We inoculated newly opened flowers with old flower microbes, and monitored the effects on fruit and seed set. We also assessed prokaryotic communities on the flowers using amplicon sequencing. We found six bacterial amplicon sequence variants (ASVs) whose proportions were increased on the inoculated flowers. These ASVs were also found on flower buds and flowers that were bagged by net or paper during anthesis, suggesting that they had been present in small numbers prior to flowering. Fruit set was negatively associated with the proportions of these ASVs, while seed set was not. The results suggest that old flowers harbor microbial communities different from those at anthesis, and that the microbes abundant on old flowers negatively affect plant reproduction. Though the short lifespan of flowers has gotten little attention, it might be an essential defense mechanism to cope with antagonistic microbes that rapidly proliferate on the flowers. Rapid expansion of SARS-CoV-2 variants of concern is a result of adaptive epistasis The SARS-CoV-2 pandemic recently entered an alarming new phase with the emergence of the variants of concern (VOC) and understanding their biology is paramount to predicting future ones. Current efforts mainly focus on mutations in the spike glycoprotein (S), but changes in other regions of the viral proteome are likely key. We analyzed more than 900,000 SARS-CoV-2 genomes with a computational systems biology approach including a haplotype network and protein structural analyses to reveal lineage-defining mutations and their critical functional attributes. Our results indicate that increased transmission is promoted by epistasis, i.e., combinations of mutations in S and other viral proteins. Mutations in the non-S proteins involve immune-antagonism and replication performance, suggesting convergent evolution. Furthermore, adaptive mutations appear in geographically disparate locations, suggesting that either independent, repeat mutation events or recombination among different strains are generating VOC. We demonstrate that recombination is a stronger hypothesis, and may be accelerating the emergence of VOC by bringing together cooperative mutations. This emphasizes the importance of a global response to stop the COVID-19 pandemic. The functional role of episodic memory in spatial learning AO_SCPLOWBSTRACTC_SCPLOWEpisodic memory has been studied extensively in the past few decades, but so far little is understood about how it drives behavior. Here we propose that episodic memory can facilitate learning in two fundamentally different modes: retrieval and replay. We study their properties by comparing three learning paradigms using computational modeling based on visually-driven reinforcement learning. Firstly, episodic memory is retrieved to learn from single experiences (one-shot learning); secondly, episodic memory is replayed to facilitate learning of statistical regularities (replay learning); and, thirdly, learning occurs online as experiences arise with no access to past experiences (online learning). We found that episodic memory benefits spatial learning in a broad range of conditions, but the performance difference is meaningful only when the task is sufficiently complex and the number of learning trials is limited. Furthermore, the two modes of accessing episodic memory affect spatial learning distinctly. One-shot learning is initially faster than replay learning, but the latter reaches a better asymptotic performance. Our model accounts for experimental results where replay is inhibited, but the hippocampus, and hence episodic memory, is intact during learning. Understanding how episodic memory drives behavior will be an important step towards elucidating the nature of episodic memory. Innovative GenExpA software for selecting suitable reference genes for reliable normalization of gene expression in melanoma The algorithms commonly used to select the best stable reference gene in RT-qPCR data analysis have their limitations. We showed that simple selection of the reference gene or pair of genes with the lowest stability value from the pool of potential reference genes - a commonly used approach - is not sufficient to accurately and reliably normalize the target gene transcript and can lead to biologically incorrect conclusions. For reliable assessment of changes in a target gene expression level, we propose our innovative GenExpA software, which works in a manner independent of the experimental model and the normalizer used. GenExpA software selects the best reference by combining the NormFinder algorithm with progressive removal of the least stable gene from the candidate genes in a given experimental model and in the set of daughter models assigned to it. The reliability of references is validated based on the consistency of the statistical analyses of normalized target gene expression levels through all models, described by the coherence score (CS). The use of the CS value imparts a new quality to qPCR analysis because it clarifies how low the stability value of reference must be in order for biologically correct conclusions to be drawn. We tested our method on qPCR data for the B4GALT genes family in melanoma, which is characterized by a high mutation rate, and in melanocytes. GenExpA is available at https://github.com/DorotaHojaLukowicz/GenExpA or https://www.sciencemarket.pl/baza-programow-open-source#oferty.

HighlightsGenExpA - next-generation software for normalizer selection and validation

The GenExpA tool defines how low the stability value of the reference should be

The GenExpA tool determines the level of gene expression analysis robustness

The GenExpA tool increases the speed of analysis and reduces cost Aberrant induction of p19Arf-mediated cellular senescence contributes to neurodevelopmental defects Timely induction of cellular senescence is important during embryonic development and tissue repair, while aberrant activation contributes to many age-related diseases. However, whether abnormal induction of senescence in the embryo contributes to developmental defects remains unclear. To explore this, we investigated the clinically significant model of Valproic acid- (VPA) induced developmental defects. VPA is a widely prescribed drug to treat epilepsy, bipolar disorder and migraine. If taken during pregnancy however, exposure to the developing embryo can cause birth defects, cognitive impairment and Autism-Spectrum Disorder. How VPA causes these developmental defects remains unknown. We used embryonic mice and human organoids to model key features of drug exposure, including exencephaly, microcephaly and spinal defects. In the malformed tissues, in which neurogenesis is defective, we find pronounced induction of cellular senescence in the neuroepithelial cells. Critically, through genetic and functional studies, we identified p19Arf as the instrumental mediator of senescence and microcephaly, but surprisingly, not exencephaly and spinal defects. Together, these findings uncover how misregulated senescence in neuroepithelial cells can contribute to developmental defects. Game of theories: an agent-based model of how variation in contest cost-benefits determines the evolution of contest resolution rules Game-theory based models are used to understand rules that animals use to settle contests over indivisible resources. However, the empirical literature of contests indicates controversial support to models, with some species supporting different models and other species showing no support to any model. Since strategies used to resolve contests may have different associated costs, it is possible that different conditions have determined the evolution of distinct assessment strategies used by animals. We used an agent-based model to explore the importance of the following conditions: resource availability, probability of reproduction with resource, and damage costs on evolution of assessment strategies. We used self- and mutual-assessment models as a heurist framework to build agents with different assessment strategies. In our model, agents competed for resources in scenarios with different combinations of resource availability, probability of reproduction with resource, and damage costs. We found that agents following the self-assessment with damage strategy were prevalent in scenarios with no probability of reproduction without the resource, independently of other variables. We also found that agents following the non-aggressive strategy occurred in all scenarios. However, agents using the non-aggressive strategy were prevalent only in scenarios with probability of reproduction with the resource. Finally, we observed that agents using mutual-assessment occurred only in a scenario with high risk of damage, low availability of resources, and with probability of reproduction without the resource. These results indicate that agents following the self-assessment with damage and non-aggressive strategies may be able to stay at most scenarios. Hidden dynamics of human proteasome autoregulation during protein degradation The cellular functions are executed by macromolecular complexes in nonequilibrium dynamic processes, which exhibit a vast diversity of conformational states. Solving conformational continuum of important complexes at atomic level remains a key challenge in the methodology of computational biophysics. Here we introduce a deep-learning framework, named AlphaCryo4D, which enables atomic-level cryogenic electron microscopy reconstructions of nonequilibrium conformational continuum. AlphaCryo4D integrates 3D deep residual learning with manifold embedding of energy landscapes, which simultaneously improves 3D classification accuracy and reconstruction resolution via an energy-based particle-voting algorithm. Applications of this methodology to six experimental datasets demonstrated its generality in breaking resolution barrier of visualizing dynamic components of functional complexes, in choreographing continuous inter-subunit motions and in exploring their  hidden conformational space. Importantly, AlphaCryo4D identified 64 conformers of the substrate-bound human 26S proteasome and reconstituted single-nucleotide-exchange dynamics of proteasomal AAA-ATPase motor during translocation initiation, which together illuminates a grand hierarchical allostery for proteasome autoregulation. Embryonic exposure to cannabidiol disrupts active neural circuits, an effect increased by Δ-9-tetrahydrocannabinol and involving CB1R and CB2R in zebrafish In the light of legislative changes and the widespread use of cannabis as a recreational and medicinal drug, delayed effects of cannabis upon brief exposure during embryonic development are of high interest as early pregnancies often go undetected. Here, zebrafish embryos were exposed to cannabidiol (CBD) and {Delta}-9-tetrahydrocannabinol l (THC) until the end of gastrulation (1-10 hours post-fertilization) and analyzed later in development (4-5 days post-fertilization). In order to measure neural activity, we implemented CaMPARI (Calcium-Modulated Photoactivatable Ratiometric Integrator) and optimized the protocol for a 96-well format complemented by locomotor analysis. Our results revealed that neural activity was decreased by CBD more than THC. At higher doses, both cannabinoids could dramatically reduce neural activity and locomotor activity. Interestingly, the decrease was more pronounced when CBD and THC were combined. At the receptor level, CBD-mediated reduction of locomotor activity was partially prevented using cannabinoid type 1 and 2 receptor inhibitors. Overall, we report that CBD toxicity occurs via two cannabinoid receptors and is synergistically enhanced by THC exposure to negatively impact neural activity late in larval development. Future studies are warranted to reveal other cannabinoids and receptors involved in this pathway to understand the subsequent health implications of cannabis consumption on fetal development. Receptor-binding domain recombinant protein on alum-CpG induces broad protection against SARS-CoV-2 variants of concern We conducted preclinical studies in mice using a yeast-produced SARS-CoV-2 RBD subunit vaccine candidate formulated with aluminum hydroxide (alum) and CpG deoxynucleotides. This formulation is equivalent to the Corbevax vaccine that recently received emergency use authorization by the Drugs Controller General of India. We compared the immune response of mice vaccinated with RBD/alum to mice vaccinated with RBD/alum+CpG. We also evaluated mice immunized with RBD/alum+CpG and boosted with RBD/alum. Mice were immunized twice intramuscularly at a 21-day interval. Compared to two doses of the /alum formulation, the RBD/alum+CpG vaccine induced a stronger and more balanced Th1/Th2 cellular immune response, with high levels of neutralizing antibodies against the original Wuhan isolate of SARS-CoV-2 as well as the B.1.1.7 (Alpha), B. 1.351 (Beta), B. 1.617.2 and (Delta) variants. Neutralizing antibody titers against the B.1.1.529 (BA.1, Omicron) variant exceeded those in human convalescent plasma after Wuhan infection but were lower than against the other variants. Interestingly, the second dose did not benefit from the addition of CpG, possibly allowing dose-sparing of the adjuvant in the future. The data reported here reinforces that the RBD/alum+CpG vaccine formulation is suitable for inducing broadly neutralizing antibodies against SARS-CoV-2 including variants of concern. If Research is Not the Evidence, What is it? The Lack of Research Citations in Health Vlogs Doctor-influencers have the knowledge needed to understand scientific research, and they have the social media popularity to share it with large audiences. In this article, I explore the treatment of evidence in vlogs by Egyptian doctor-influencers: how they present it and what they use instead of it. I answer the following questions: 1) How do doctor-influencers present evidence on social media? 2) If evidence is not the research, then what is it? The data was collected through in-depth interviews with 12 Egyptian doctor-influencers from different specializations; two focus groups; and a critical discourse analysis of 48 of the influencers most popular and most engaging videos. I found that the doctor-influencers cited academic research only in the videos about medical controversies, new treatments, misinformation, or common medical mistakes. In most of their videos, the Egyptian doctor-influencers scarcely referred to medical research. This is because they believe that their audiences would not understand evidence due to their low educational attainment, weak research skills, and the language barrier (as most medical research is published in English rather than Arabic). These findings highlight the challenges of communicating science in societies with a low level of education. In these settings, communicators may need to move beyond mediating research studies on social media and instead focus on simplifying, translating, and connecting evidence-based information to the cultural context. One billion synthetic 3D-antibody-antigen complexes enable unconstrained machine-learning formalized investigation of antibody specificity prediction Machine learning (ML) is a key technology to enable accurate prediction of antibody-antigen binding, a prerequisite for in silico vaccine and antibody design. Two orthogonal problems hinder the current application of ML to antibody-specificity prediction and the benchmarking thereof: (i) The lack of a unified formalized mapping of immunological antibody specificity prediction problems into ML notation and (ii) the unavailability of large-scale training datasets. Here, we developed the Absolut! software suite that allows the parameter-based unconstrained generation of synthetic lattice-based 3D-antibody-antigen binding structures with ground-truth access to conformational paratope, epitope, and affinity. We show that Absolut!-generated datasets recapitulate critical biological sequence and structural features that render antibody-antigen binding prediction challenging. To demonstrate the immediate, high-throughput, and large-scale applicability of Absolut!, we have created an online database of 1 billion antibody-antigen structures, the extension of which is only constrained by moderate computational resources. We translated immunological antibody specificity prediction problems into ML tasks and used our database to investigate paratope-epitope binding prediction accuracy as a function of structural information encoding, dataset size, and ML method, which is unfeasible with existing experimental data. Furthermore, we found that in silico investigated conditions, predicted to increase antibody specificity prediction accuracy, align with and extend conclusions drawn from experimental antibody-antigen structural data. In summary, the Absolut! framework enables the development and benchmarking of ML strategies for biotherapeutics discovery and design.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=194 SRC="FIGDIR/small/451258v2_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@14295d2org.highwire.dtl.DTLVardef@7a12bdorg.highwire.dtl.DTLVardef@647102org.highwire.dtl.DTLVardef@375112_HPS_FORMAT_FIGEXP  M_FIG O_FLOATNOGraphical abstractC_FLOATNO The software framework Absolut! enables (A,B) the generation of virtually arbitrarily large numbers of in silico 3D-antibody-antigen structures, (C,D) the formalization of antibody specificity as machine learning (ML) tasks as well as the exploration of ML strategies for paratope-epitope prediction.

C_FIG Highlights- Software framework Absolut! to generate an arbitrarily large number of in silico 3D-antibody-antigen structures
- Generation of one billion in silico antigen-antibody structures reflecting biological layers of complexity that make ML predictions challenging
- Immunological antibody specificity prediction problems formalized as machine learning tasks for which the in silico complexes are immediately usable as benchmark.
- Exploration of machine learning architectures for paratope-epitope interaction prediction accuracy as a function of neural network depth, dataset size, and sequence-structure encoding Magnetic wire active microrheology of human respiratory mucus Mucus is a viscoelastic gel secreted by the pulmonary epithelium in the tracheobronchial region of the lungs. The coordinated beating of cilia in contact with the gel layer moves mucus upwards towards pharynx, removing inhaled pathogens and particles from the airways. The efficacy of this clearance mechanism depends primarily on the rheological properties of mucus. Here we use a magnetic wire based microrheology technique to study the viscoelastic properties of human mucus collected from human bronchus tubes. The response of wires between 5 and 80 {micro}m in length to a magnetic rotating field is monitored by optical time-lapse microscopy and analyzed using constitutive equation models of rheology, including Maxwell and Kelvin-Voigt. The static shear viscosity and elastic modulus can be inferred from low frequency (10-3 - 10 rad s-1) measurements, leading to the evaluation of the mucin network relaxation time. This relaxation time is found to be widely distributed, from one to several hundred seconds. Mucus is identified as a viscoelastic liquid with an elastic modulus of 2.5 {+/-} 0.5 Pa and a static viscosity of 100 {+/-} 40 Pa s. Our work shows that beyond the established spatial variations in rheological properties due to microcavities, mucus exhibits secondary inhomogeneities associated with the relaxation time of the mucin network that may be important for its flow properties. Recovery of high-quality assembled genomes via metagenome binning guided with single-cell amplified genomes BackgroundObtaining high-quality (HQ) reference genomes from microbial communities is crucial for understanding the phylogeny and function of uncultured microbes in complex microbial ecosystems. Despite the improved bioinformatic approaches to generate curated metagenome-assembled genomes (MAGs), existing metagenomic binners often fail to obtain reliable MAGs, and thus, they are nowhere comparable to genomes sequenced from isolates in terms of strain level resolution. Here, we present a single-cell genome-guided metagenome binning (MetaSAG) to reconstruct the strain-resolved genomes from microbial communities at once.

ResultsMetaSAG employs single-cell amplified genomes (SAGs) generated with microfluidic technology as binning guides to recover improved draft genomes with the metagenomic data. To assess the performance of reconstructing genomes from various microbial communities, we compared MetaSAG with four conventional metagenomic binners using a cell mock community, human gut microbiota, and skin microbiota samples. MetaSAG showed precise contig binning and higher recovery rates (>97%) of rRNA and plasmids compared to conventional binners in genome reconstruction from the cell mock community. In human microbiota samples, MetaSAG recovered the largest number of genomes with a total of 103 gut microbial genomes (21 HQ and 65 showed >90% completeness) and 45 skin microbial genomes (10 HQ and 40 showed >90% completeness), respectively. Conventional binners recovered one Staphylococcus hominis genome, whereas MetaSAG recovered two S. hominis genomes from the identical skin microbiota sample. Single-cell sequencing indicated that these S. hominis genomes clearly derived from two distinct strains harboring specifically different plasmids. We found that all conventional S. hominis MAGs had substantial lack or excess of the genome sequences and contamination of other Staphylococcus bacteria (S. epidermidis).

ConclusionsMetaSAG enabled us to obtain the strain-resolved genomes in the mock community and human microbiota samples by assigning metagenomic sequences correctly and covering both highly conserved genes such as rRNA genes and unique extrachromosomal elements, including plasmids. MetaSAG will provide HQ genomes that are difficult to obtain with metagenomic analyses alone and will facilitate the understanding of microbial ecosystems by elucidating detailed metabolic pathways and horizontal gene transfer networks through microbial genomes. MetaSAG is available at https://github.com/kojiari/metasag. LPS-TLR4 pathway exaggerates alcohol-induced acute-on-chronic liver failure via provoking NETs formation Backgrounds: Intrahepatic infiltration of neutrophils is a character of alcoholic acute-on-chronic liver failure (AACLF) and neutrophil extracellular traps (NETs) are an important strategy for neutrophils to fix and kill invading microorganisms. Intestinal bacteria and the gut-liver axis have been thought to play a key role in many liver diseases also including AACLF. However, whether NETs appear in AACLF and play a role in AACLF is still unsure. Methods: WT, NE KO, and TLR4 KO mice were used to build the AACLF model, and the intestinal bacteria were eliminated at the same time and LPS was given. Then the formation of NETs and AACLF related markers were detected. Results: The serum MPO-DNA and LPS concentration was increased in AACLF patients and a correlation was revealed between these two indexes. More intrahepatic NETs formed in AACLF mice by testing MPO-DNA, Cit H3, and NE. These markers decreased with gut detergent and restored markers with gut detergent plus LPS supplement. While NETs formation failed to change with gut microbiome or combine LPS supplement in TLR4 KO mice. As we tested AACLF related characters, liver injury, intrahepatic fat deposition, inflammation, and fibrosis alleviated with depletion of NE. These related marks were also attenuated with gut sterilization by antibiotics and recovered with combined treatment with antibiotics plus LPS. But the liver injury, intrahepatic fat, fibro deposition, and liver inflammation-related markers did show a significant difference in TLR4 KO mice when they received the same treatment. Conclusion: Intestinal-derived LPS promotes NETs formation in AACLF through the TLR4 pathway and further accelerates the AACLF process by NETs. Design, Mutate, Screen: High-throughput creation of genetic clocks with different period-amplitude characteristics Directed evolution has become an invaluable tool in protein engineering and has also greatly influenced the construction of synthetic gene circuits. The ability to generate diversity at precise targets for directed evolution approaches has improved vastly, allowing researchers to create large, specific mutant libraries with relative ease. Screening approaches for large mutant libraries have similarly come a long way, especially when the desired behavior can easily be tested for with static, single time-point assays. For more complex gene circuits with dynamic phenotypes that change over time, directed evolution approaches to controlling and tuning circuit behavior have been hindered by the lack of sufficiently high-throughput screening methods to isolate variants with desired characteristics. Here we utilize directed mutagenesis and multiplexed microfluidics to develop a workflow for creating, screening and tuning dynamic gene circuits that operate at the population level. Specifically, we create a mutant library of an existing oscillator, the synchronized lysis circuit, and tune its dynamics while uncovering principles regarding its behavior. Lastly, we utilize this directed evolution workflow to construct a new synchronized genetic oscillator that exhibits robust dynamics over long time scales. Changes in Behavior and Salivary Serum Amyloid A in cows with Subclinical Mastitis The aim of this study was to identify detailed changes in behavior, and in salivary serum amyloid A (SAA), associated with subclinical mastitis. This included standard sickness behaviors (which form part of an adaptive response to conserve energy, minimize heat loss and facilitate recovery following infection and inflammation) and lesser-studied behaviors, that are biologically predicted to change at low-level infection, and therefore particularly relevant for detecting subclinical mastitis (here labelled  luxury behaviors). SAA is a physiological marker of systemic inflammation, with levels in milk and serum already known to increase during subclinical mastitis. We investigated whether the same was true for SAA in cow saliva. Data were collected for n = 34 commercial barn-housed dairy cows, tested in 17 matched-pairs. Each pair comprised a cow with subclinical mastitis (SCM) and a healthy control (CTRL), identified using somatic cell count (SCC) (SCM: SCC >200 x1000 cells/ml; CTRL: SCC <100 x1000 cells/ml). SCM cows were selected for study ad-hoc, at which point they were paired with a CTRL cow, based upon parity and calving date; consequently, the full data set was accrued over several months. Data were collected for each pair over 3 days: SCC (l4:00-l5:00h) Day 1; behavior (24h from 00:00h) Day 2; salivary serum amyloid-A (SAA) Day 3. We report, for the first time, that an increase in salivary SAA occurs during subclinical mastitis; SAA was higher in SCM cows and demonstrated a positive (weak) correlation with SCC. The behavioral comparisons revealed that SCM cows had reductions in activity (behavioral transitions and distance moved), social exploration, social reactivity (here: likelihood to move away/be displaced following receipt of agonism), performance of social grooming and head butts, and the receipt of agonistic non-contact challenges. In addition, SCM cows received more head swipes, and spent a greater proportion of time lying with their head on their flank than CTRL cows. SCM cows also displayed an altered feeding pattern; they spent a greater proportion of feeding time in direct contact with two conspecifics, and a lower proportion of feeding time at self-locking feed barriers, than CTRL cows. Behavioral measures were found to correlate, albeit loosely, with serum SAA in a direction consistent with predictions for sickness behavior. These included positive correlations with both lying duration and the receipt of all agonistic behavior, and negative correlations with feeding, drinking, the performance of all social and all agonistic behavior, and social reactivity. We conclude that changes in salivary SAA, social behavior, and activity offer potential in the detection of subclinical mastitis and recommend further investigation to substantiate and refine our findings. Intron-mediated induction of phenotypic heterogeneity Introns are universally present in the nuclear genomes of eukaryotes1. The budding yeast, an otherwise intron-poor species, preserves two sets of ribosomal protein (RP) genes differing primarily in their introns2-4. Despite recent findings on the role of RP introns under stress and starvation5-7, understanding the contribution of introns to ribosome regulation remains challenging. Here, combining isogrowth profiling8 with single-cell protein measurements9, we found that introns can mediate inducible phenotypic heterogeneity conferring a clear fitness advantage. Osmotic stress leads to bimodal expression of the small ribosomal subunit protein Rps22B, mediated by an intron in the 5 untranslated region of its transcript. The two resulting yeast subpopulations differ in their ability to cope with starvation. Low Rps22B protein levels resulted in prolonged survival under sustained starvation, while high Rps22B levels enabled cells to grow faster after transient starvation. Further, yeast growing at high sugar concentrations - similar to those in ripe grapes - exhibit bimodal Rps22B expression when approaching stationary phase. Differential intron-mediated regulation of RP genes thus provides a way to diversify the population when starvation looms in natural environments. Our findings reveal a new role for introns in inducing phenotypic heterogeneity in changing environments and suggest that duplicated RP genes in yeast contribute to resolving the evolutionary conflict between precise expression control and environmental responsiveness10. Differences in gait stability and acceleration characteristics between healthy young and older females Our aim was to evaluate differences in gait acceleration intensity, variability and stability of feet and trunk between older females and young females using inertial sensors. Twenty older females (OF; mean age 68.4, SD 4.1 years) and eighteen young females (YF; mean age 22.3, SD 1.7 years) were asked to walk straight for 100 meters at their preferred speed, while wearing inertial sensors on heels and lower back. We calculated spatiotemporal measures, foot and trunk acceleration characteristics and their variability, as well as trunk stability using the local divergence exponent (LDE). Two-way analysis of variance (including the factors foot and age), Students t-test, and Mann-Whitney U test were used to compare statistical differences of measures between groups. Cohens d effects were calculated for each variable. Foot maximum vertical acceleration and amplitude, trunk-foot vertical acceleration attenuation, as well as their variability were significantly smaller in OF than in YF. In contrast, trunk mediolateral acceleration amplitude, maximum vertical acceleration, and amplitude, as well as their variability were significantly larger in OF than in YF. Moreover, OF showed lower stability (i.e., higher LDE values) in mediolateral acceleration, mediolateral and vertical angular velocity of the trunk. Even though we measured healthy older females, these participants showed lower vertical foot accelerations with higher vertical trunk acceleration, lower trunk-foot vertical acceleration attenuation, less gait stability, and more variability of the trunk, and hence, were more likely to fall. These findings suggest that instrumented gait measurements may help for early detection of changes or impairments in gait performance, even before this can be observed by clinical eye or gait speed. RASopathy Mutations Demonstrate the Critical Function of the Cysteine-rich Domain in Maintaining BRAF in an Autoinhibited State to Prevent Aberrant Signaling The RAF kinases are essential effectors of the RAS-GTPases, and germline mutations in BRAF or CRAF are disease drivers in the RASopathy developmental syndromes, with mutations in the cysteine-rich domain (CRD) often observed in BRAF but not CRAF. Although the CRD is known for roles in phosphatidylserine (PS) binding, the RAS-RAF interaction, and RAF autoinhibition, the interplay of these activities and their impact on BRAF function in normal and disease states is unclear. Here, we analyze a panel of BRAF-CRD RASopathy mutations and show that they all increase the biological activity of BRAF by relieving autoinhibition and/or enhancing PS/membrane binding. Strikingly, we find that relief of autoinhibition is the predominant factor determining the severity of the mutations. Comparison of the BRAF and CRAF CRDs further indicates that the BRAF-CRD is a stronger mediator of both autoinhibition and PS binding, and we identify residues contributing to these differences. Moreover, given the increased catalytic activity of BRAF versus CRAF, our studies reveal a more critical role for the CRD and autoinhibition in BRAF regulation and demonstrate that CRD-mediated autoinhibition is required to prevent aberrant BRAF signaling, a finding consistent with the high frequency of mutations that disrupt this function in the RASopathies. Multi-omic analysis of the Arabidopsis clock activator mutant rve 4 6 8 reveals connections to carbohydrate metabolism and proteasome regulation Plants are able to sense changes in their light environments, such as the onset of day and night, as well as anticipate these changes in order to adapt and survive. Central to this ability is the plant circadian clock, a molecular circuit that precisely orchestrates plant cell processes over the course of a day. REVEILLE proteins (RVEs) are recently discovered members of the plant circadian circuitry that activate the evening complex and PRR genes to maintain regular circadian oscillation. The RVE 8 protein and its two homologs, RVE 4 and 6, have been shown to limit the length of the circadian period, with rve 4 6 8 triple-knockout plants possessing an elongated period along with increased leaf surface area, biomass, cell size and delayed flowering relative to wild-type Col-0 plants. Here, using a multi-omics approach consisting of phenomics, transcriptomics, proteomics, and metabolomics we draw novel connections between RVE8-like proteins and a number of core plant cell processes. In particular, we reveal that loss of RVE8-like proteins results in altered carbohydrate, organic acid and lipid metabolism, including a starch excess phenotype at dawn. We further demonstrate that rve 4 6 8 plants have lower levels of 20S proteasome subunits and possess significantly reduced proteasome activity, potentially explaining the increase in cell-size observed in RVE8-like mutants. Overall, this robust, multi-omic dataset, provides substantial new insights into the far reaching impact RVE8-like proteins have on the diel plant cell environment. Intermittent compression increases flow through a gel: a mechanical model perhaps relevant to flow of cerebrospinal fluid Exchange of molecules between cerebrospinal fluid (CSF) and brain cells contributes to brain function and protection from dementia. Despite widespread acceptance of the  glymphatic theory, the route by which CSF is brought close enough to the neural tissue for solutes to be exchanged by extracellular diffusion is not entirely clear. Exogenous molecules injected into CSF are observed to reach the basement lamina that surrounds the dense capillary network. Transport of solutes by diffusion along the basement lamina, a gel of macromolcules about 100 nm thick, would be too slow; bulk flow in a static geometry would require unphysiologically high pressures. However, it is known that the pulsation of blood aids transport of CSF, and we hypothesized that this is because the pulsation intermittently squeezes the pericapillary lamina. In a primitive mimicry, we have tested whether intermittent squeezing increases flow through an agar gel. In all but one of 216 tests, pulsation caused a reversible increase, sometimes by a factor of 100 or more. The enhancement was greatest for frequencies 5-11 Hz and, over the tested range of pressure heads (20 - 50 cmH2O), was greatest for the lowest pressure. The results suggest a reason why exercise slows the aging of the brain. 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. Online single-cell data integration through projecting heterogeneous datasets into a common cell-embedding space Computational tools for integrative analyses of diverse single-cell experiments are facing formidable new challenges including dramatic increases in data scale, sample heterogeneity, and the need to informatively cross-reference new data with foundational datasets. Here, we present SCALEX, a deep-learning method that integrates single-cell data by projecting cells into a batch-invariant, common cell-embedding space in a truly online manner (i.e., without retraining the model). SCALEX substantially outperforms online iNMF and other state-of-the-art non-online integration methods on benchmark single-cell datasets of diverse modalities, (e.g., scRNA-seq, scATAC-seq), especially for datasets with partial overlaps, accurately aligning similar cell populations while retaining true biological differences. We showcase SCALEXs advantages by constructing continuously expandable single-cell atlases for human, mouse, and COVID-19 patients, each assembled from diverse data sources and growing with every new data. The online data integration capacity and superior performance makes SCALEX particularly appropriate for large-scale single-cell applications to build-upon previously hard-won scientific insights.