On the incongruence of genotype-phenotype and fitness landscapes The mapping from genotype to phenotype to fitness typically involves multiple nonlinearities that can transform the effects of mutations. For example, mutations may contribute additively to a phenotype, but their effects on fitness may combine non-additively because selection favors a low or intermediate value of that phenotype. This can cause incongruence between the topographical properties of a fitness landscape and its underlying genotype-phenotype landscape. Yet, genotype-phenotype landscapes are often used as a proxy for fitness landscapes to study the dynamics and predictability of evolution. Here, we use theoretical models and empirical data on transcription factor-DNA interactions to systematically study the incongruence of genotype-phenotype and fitness landscapes when selection favors a low or intermediate phenotypic value. Using the theoretical models, we prove a number of fundamental results. For example, selection for low or intermediate phenotypic values does not change simple sign epistasis into reciprocal sign epistasis, yet it changes reciprocal sign epistasis into simple sign epistasis and no sign epistasis with equal probability. More broadly, we show that such selection tends to create fitness landscapes that are more rugged than the underlying genotype-phenotype landscape, but this increased ruggedness typically does not frustrate adaptive evolution because the local adaptive peaks in the fitness landscape tend to be nearly as tall as the global peak. Many of these results carry forward to the empirical genotype-phenotype landscapes, which may help to explain why low- and intermediate-affinity transcription factor-DNA interactions are so prevalent in eukaryotic gene regulation.

AUTHOR SUMMARYHow do mutations change phenotypic traits and organismal fitness? This question is often addressed in the context of a classic metaphor of evolutionary theory -- the fitness landscape. A fitness landscape is akin to a physical landscape, in which genotypes define spatial coordinates, and fitness defines the elevation of each coordinate. Evolution then acts like a hill-climbing process, in which populations ascend fitness peaks as a consequence of mutation and selection. It is becoming increasingly common to construct such landscapes using experimental data from high-throughput sequencing technologies and phenotypic assays, in systems such as macromolecules and gene regulatory circuits. Although these landscapes are typically defined by molecular phenotypes, and are therefore more appropriately referred to as genotype-phenotype landscapes, they are often used to study evolutionary dynamics. This requires the assumption that the molecular phenotype is a reasonable proxy for fitness, which need not be the case. For example, selection may favor a low or intermediate phenotypic value, causing incongruence between a fitness landscape and its underlying genotype-phenotype landscape. Here, we study such incongruence using a diversity of theoretical models and experimental data from gene regulatory systems. We regularly find incongruence, in that fitness landscapes tend to comprise more peaks than their underlying genotype-phenotype landscapes. However, using evolutionary simulations, we show that this increased ruggedness need not impede adaptation.
An orthologous gene coevolution network provides insight into eukaryotic cellular and genomic structure and function Orthologous gene coevolution--which refers to gene pairs whose evolutionary rates covary across speciation events--is often observed among functionally related genes. We present a comprehensive gene coevolution network inferred from the examination of nearly three million orthologous gene pairs from 332 budding yeast species spanning [~]400 million years of eukaryotic evolution. Modules within the network provide insight into cellular and genomic structure and function, such as genes functioning in distinct cellular compartments and DNA replication. Examination of the phenotypic impact of network perturbation across 14 environmental conditions using deletion mutant data from the bakers yeast Saccharomyces cerevisiae suggests that fitness in diverse environments is impacted by orthologous gene neighborhood and connectivity. By mapping the network onto the chromosomes of S. cerevisiae and the opportunistic human pathogen Candida albicans, which diverged [~]235 million years ago, we discovered that coevolving orthologous genes are not clustered in either species; rather, they are most often located on different chromosomes or far apart on the same chromosome. The budding yeast coevolution network captures the hierarchy of eukaryotic cellular structure and function, provides a roadmap for genotype-to-phenotype discovery, and portrays the genome as an extensively linked ensemble of genes.
Advanced Functional Biotextiles for a Circular Materials Economy A circular materials economy can disrupt linear production models and mitigate its environmental threats. We harness extracellular biosynthesis of microbial nanocellulose (MC), coupled to a protocol that represents a serendipitous intersection between ancient textile techniques and green processing as a route to high-performance bioleather with a circular life cycle. Specifically, a plant-based lecithin phosphocholine treatment modulates cellulose cross-linking through phosphate and methylene groups, to yield a biodegradable material with superior mechanical and flame-retardant properties. A broad color palette and controlled color modulation was achieved with cultural heritage dyes and waste-to-resource strategies. Life cycle impact assessment shows up to an order of magnitude reduction in environmental impacts relative to conventional textiles, making MC relevant for widespread application in fashion, interiors, construction and insulating materials. The translational potential of this approach is tremendous, as use of microbes and green chemistry to engineer regenerative, high-performance products can accelerate a paradigm shift to a circular bioeconomy. Discovery of a pre-mRNA structural scaffold as a contributor to the mammalian splicing code The specific recognition of splice signals at or near exon-intron junctions is not explained by their weak conservation and instead is postulated to require a multitude of features embedded in the pre-mRNA strand. We explored the possibility of three-dimensional structural scaffold of AdML - a model pre-mRNA substrate - guiding early spliceosomal components to the splice signal sequences. We find that mutations in the non-cognate splice signal sequences impede recruitment of early spliceosomal components due to disruption of the global structure of the pre-mRNA. We further find that the pre-mRNA segments potentially interacting with the early spliceosomal component U1 snRNP are distributed across the intron, that there is a spatial proximity of 5' and 3' splice sites within the pre-mRNA scaffold, and that an interplay exists between the structural scaffold and splicing regulatory elements in recruiting early spliceosomal components. These results suggest that early spliceosomal components can recognize a three-dimensional structural scaffold beyond the short splice signal sequences, and that in our model pre-mRNA, this scaffold is formed across the intron involving the major splice signals. This provides a conceptual basis to analyze the contribution of recognizable three-dimensional structural scaffolds to the splicing code across the mammalian transcriptome. Metacommunity dynamics and the detection of species associations in co-occurrence analyses: why patch disturbance matters O_LI1: Many statistical methods attempt to detect species associations - and so infer inter-specific interactions - from species co-occurrence patterns. Habitat heterogeneity and out-of-equilibrium colonization histories are well recognized as potentially causing species associations, even when interactions are absent. The potential for patch disturbance, a classical component of metacommunity dynamics, to also drive spurious species associations has however been over-looked.
C_LIO_LI2: Using a new general metacommunity model, we derive mathematical predictions regarding how patch disturbance would affect the patterns of species associations detected in "null" co-occurrence matrices. We also conduct numerical simulations to test our predictions and to compare the performance of several widespread statistical methods, including direct tests of pairwise independence, matrix permutation approaches and joint species distribution modelling.
C_LIO_LI3: We show how classical metacommunity dynamics can produce statistical associations, both positive and negative, even when species do not interact, when there is no habitat heterogeneity, and at equilibrium. This occurs as soon as there is some rate of patch disturbance (i.e. simultaneous extinction of several species in a patch) and/or a finite life-span of patches, a common feature of a broad range of plant, animal or microbial systems.
C_LIO_LI4: Patch disturbance can compromise species co-occurrence analyses and cause the artefactual detection of species associations if not taken into account. Including patch age (i.e. the time since the last patch disturbance event) as a covariate in a joint species distribution model can resolve the artefact. However, this requires additional data that often are not available in practice. We argue that the consequences of patch disturbance should not be underestimated when analysing species distribution patterns in metacommunity-like systems.
C_LI Living with high potassium: a balance between nutrient acquisition and stress signaling during K-induced salt stress O_LIHigh potassium (K) in the growth medium is more toxic to plants than Na at similar concentrations. However, the molecular mechanisms underlying plant responses to K-induced salt stress are virtually unknown.
C_LIO_LIWe examined Arabidopsis thaliana and its extremophyte relative Schrenkiella parvula, using a comparative multi-omics approach to identify cellular processes affected by excess K and understand which deterministic regulatory pathways are active to avoid tissue damage while sustaining growth.
C_LIO_LIA. thaliana showed limited capacity to curb excess K accumulation and prevent nutrient depletion contrasting to S. parvula which could limit excess K accumulation without restricting nutrient uptake. Facilitated by a targeted transcriptomic response, promoting nitrogen uptake along with other key nutrients and uninterrupted N assimilation into primary metabolites during excess K-stress allowed S. parvula to boost its antioxidant and osmolyte pools concurrently leading to sustained growth. Antithetically, A. thaliana showed transcriptional responses indicative of a poor balance between stress signaling, increased ROS levels, and reduced photosynthesis, subsequently leading to inhibited growth.
C_LIO_LIThe ability to regulate independent nutrient uptake and a coordinated transcriptomic response to avoid non-specific stress signaling are two main deterministic steps towards building stress resilience to excess K+-induced salt stress.
C_LI Modular Dynamic Biomolecular Modelling with Bond Graphs: The Unification of Stoichiometry, Thermodynamics, Kinetics and Data. Renewed interest in dynamic simulation models of biomolecular systems has arisen from advances in genome-wide measurement and applications of such models in biotechnology and synthetic biology. In particular, genome-scale models of cellular metabolism beyond the steady state are required in order to represent transient and dynamic regulatory properties of the system. Development of such whole-cell models requires new modelling approaches. Here we propose the energy-based bond graph methodology, which integrates stoichiometric models with thermo-dynamic principles and kinetic modelling. We demonstrate how the bond graph approach intrinsically enforces thermodynamic constraints, provides a modular approach to modelling, and gives a basis for estimation of model parameters leading to dynamic models of biomolecular systems. The approach is illustrated using a well-established stoichiometric model of Escherichia coli (E. coli) and published experimental data. Staphylococcus aureus prophages are gatekeepers of lipid utilization to control membrane flexibility, bacterial fitness, and antibiotic adaptation Lipids are essential components of bacterial membranes and phages are quasi-ubiquitous in bacteria. Both are crucial mediators of bacteria-host interactions. In the major pathogen Staphylococcus aureus, two common prophages, {phi}11.1 and {phi}13, are preferentially integrated in lipase genes, respectively encoding Geh, a triglyceride lipase, and Hlb, a sphingomyelinase. Here we report how prophage status, and consequently lipase availability, impacts S. aureus metabolism of environmental lipids, and overall bacterial fitness. The fatty acid kinase subunit FakB1, known to promote saturated fatty acid incorporation, also facilitates incorporation of unsaturated fatty acids released from triglycerides by Geh; this process occurs only when {phi}11.1 is absent. Geh and Hlb lipase products compete for FakB1, and interference by prophage integration changes the outcome of this competition. Our findings could explain the selective advantage of prophage conservation, as a means of modulating bacterial membrane composition and preventing toxicity of environmental lipids. {phi}13 lysogeny also impaired the bacterial capacity to escape antibiotic inhibitors of FASII (fatty acid synthesis). We suggest that testing new therapeutics against S. aureus should consider prophage status and environmental lipids for accurate prediction of efficiency.

ImportanceStaphylococcus aureus is a major human health challenge. Its lipases are crucial for virulence and immune response escape. Prophages inserted in lipases are common in S. aureus but the selective benefits of their maintenance is little understood. We demonstrate that two prophages, inserted in triglyceride and sphingomyelin lipase genes, interactively modulate fatty acid incorporation into bacterial membranes. The presence or absence of prophage determine how bacteria respond to a complex lipid environment such as the host, by affecting membrane properties, fitness, and adaptation to antibiotics inhibiting fatty acid synthesis. Our findings highlight the importance of assessing prophage status and lipid environments when evaluating infection risk and therapy efficiency. ZIKV disrupts placental ultrastructure and drug transporter expression in mice Congenital Zika virus (ZIKV) infection can induce fetal brain abnormalities. Here, we investigated whether maternal ZIKV infection affects placental physiology and metabolic transport potential and impacts the fetal outcome, regardless of viral presence in the fetus at term. Low (103 PFU-ZIKVPE243; low ZIKV) and high (5x107 PFU-ZIKVPE243; high ZIKV) virus titers were injected into immunocompetent (ICompetent C57BL/6) and immunocompromised (ICompromised A129) mice at gestational day (GD) 12.5 for tissue collection at GD18.5 (term). High ZIKV elicited fetal death rates of 66% and 100%, whereas low ZIKV induced fetal death rates of 0% and 60% in C57BL/6 and A129 dams, respectively. All surviving fetuses exhibited intrauterine growth restriction (IUGR) and decreased placental efficiency. High-ZIKV infection in C57BL/6 and A129 mice resulted in virus detection in maternal spleens and placenta, but only A129 fetuses presented virus RNA in the brain. Nevertheless, pregnancies in both strains produced fetuses with decreased head sizes (p<0.05). Low-ZIKV-A129 dams had higher IL-6 and CXCL1 levels (p<0.05), and their placentas showed increased CCL-2 and CXCL-1 contents (p<0.05). In contrast, low-ZIKV-C57BL/6 dams had an elevated CCL2 serum level and increased type I and II IFN expression in the placenta. Notably, less abundant microvilli and mitochondrial degeneration were evidenced in the placental labyrinth zone (Lz) of ICompromised and high-ZIKV-ICompetent mice but not in low-ZIKV-C57BL/6 mice. In addition, decreased placental expression of the drug transporters P-glycoprotein (P-gp) and breast cancer resistance protein (Bcrp) and the lipid transporter Abca1 was detected in all ZIKV-infected groups, but Bcrp and Abca1 were only reduced in ICompromised and high-ZIKV ICompetent mice. Our data indicate that gestational ZIKV infection triggers specific proinflammatory responses and affects placental turnover and transporter expression in a manner dependent on virus concentration and maternal immune status. Placental damage may impair proper fetal-maternal exchange function and fetal growth/survival, likely contributing to congenital Zika syndrome. An alternative UPF1 isoform drives conditional remodeling of nonsense-mediated mRNA decay The nonsense-mediated mRNA decay (NMD) pathway monitors translation termination to degrade transcripts with premature stop codons and regulate thousands of human genes. Here we show that an alternative mammalian-specific isoform of the core NMD factor UPF1, termed UPF1LL, enables condition-dependent remodeling of NMD specificity. Previous studies indicate that the extension of a conserved regulatory loop in the UPF1LL helicase core confers a decreased propensity to dissociate from RNA upon ATP hydrolysis relative to the major UPF1 isoform, designated UPF1 SL. Using biochemical and transcriptome-wide approaches, we find that UPF1LL overcomes the protective RNA binding proteins PTBP1 and hnRNP L to preferentially bind and down-regulate long 3UTRs normally shielded from NMD. Unexpectedly, UPF1LL supports induction of NMD on new populations of substrate mRNAs in response to activation of the integrated stress response and impaired translation efficiency. Thus, while canonical NMD is abolished by moderate translational repression, UPF1LL activity is enhanced, providing a mechanism to rapidly rewire NMD specificity in response to cellular stress. 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 Hierarchy of Biomolecular Proportional-Integral-Derivative Feedback Controllers for Robust Perfect Adaptation and Dynamic Performance Proportional-Integral-Derivative (PID) feedback controllers have been the most widely used controllers in industry for almost a century due to their good performance, simplicity, and ease of tuning. Motivated by their success in various engineering disciplines, PID controllers recently found their way into synthetic biology, where the design of feedback molecular control systems has been identified as an important goal. In this paper, we consider the mathematical realization of PID controllers via biomolecular interactions. We propose an array of topologies that offer a compromise between simplicity and high performance. We first demonstrate that different Proportional-Integral (PI) controllers exhibit different capabilities for enhancing the dynamics and reducing variance (cell-to-cell variability). Next, we introduce several derivative controllers that are realized based on incoherent feedforward loops acting in a feedback configuration. Alternatively, we show that differentiators can be realized by placing molecular integrators in a negative feedback loop--an arrangement that can then be augmented by PI components to yield PID feedback controllers. We demonstrate that the derivative component can be exploited for enhancing system stability, dramatically increasing the molecular control systems dynamic performance, and for reducing the noise effect on the output of interest. The PID controller features are established through various deterministic and stochastic analyses as well as numerical simulations. Finally, we provide an experimental demonstration using a recently developed hybrid setup, the cyberloop, where the controller is implemented in silico to control a biological genetic circuit in vivo. The large array of novel biomolecular PID controllers introduced here forms a basis for the design and construction of advanced high-performance biomolecular control systems that robustly regulate the dynamics of living systems. 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. Tackling polypharmacology of kinase inhibitors and selecting chemical kinase probes by transcription factor activity profiling. Protein kinase inhibitors (PKI) evolved as promising drugs for multiple diseases. However, PKIs promiscuity causes polypharmacological effects challenging therapeutic development. We show that the polypharmacology of PKIs can be inferred from their impact on transcription factors (TF) lying at the apexes of signaling pathways. Using a high-content reporter assay, we evaluated TF activity profiles (TFAP) in cells treated with Akt, CDK, Aurora, Raf, MEK, and ERK inhibitors. For each kinase family, we found kinase-specific consensus TFAP signatures signifying the on-target PKI activity. Remarkably, proximal kinases had the highest similarity of their PKIs consensus signatures. Furthermore, we show that individual PKIs exhibited the consensus, "on-target signatures" within certain "specificity windows" and distinct "off-target signatures" at other concentrations. We also show that the TFAP signatures permit pinpointing the off-target PKI activity at irrelevant kinases and non-kinase effectors. Therefore, the TFAP approach provides clear-cut quantitative metrics for assessing PKI activity and concentration ranges where the on-target activity dominates cell response. By illuminating PKI biology invisible to target-based techniques, this effect-based approach streamlines the selection of kinase chemical probes and PKI drug prioritization. Correlation between speed and turning naturally arises for sparsely sampled cell movements Mechanisms regulating cell movement are not fully understood. One feature of cell movement that determines how far cells displace from an initial position is persistence, the ability to perform movements in a direction similar to the previous movement direction. Persistence is thus determined by turning angles between two sequential displacements and be characterized by an average turning angle or persistence time. Recent studies found that a cells average speed and turning are negatively correlated, suggesting a fundamental cell-intrinsic program whereby cells with a lower turning ability (i.e., larger persistence time) are intrinsically faster (or faster cells turn less). By simulating correlated or persistent random walks (PRWs) using two different frameworks (one based on von Mises-Fisher (vMF) distribution and another based on Ornstein-Uhlenbeck (OU) process) we show that the negative correlation between speed and turning naturally arises when cell trajectories are sub-sampled, i.e., when the frequency of sampling is lower than frequency at which cells make movements. This effect is strongest when the sampling frequency is on the order of magnitude with the typical cell persistence time and when cells vary in persistence time. Both conditions are observed for datasets of T cell movements in vivo that we have analyzed. In simulations the correlation arises due to randomness of cell movements resulting in highly variable persistence times for individual cells that with sub-sampling leads to large variability of average cell speeds. Interestingly, previously suggested methodology of calculating displacement of cell cohorts with different speeds resulted in similar results whether or not there is a cell-intrinsic correlation between cell speed and persistence. For both vMF- and OU-based simulations of PRWs we could find parameter values (distribution of persistence times, speeds, and sampling frequency) that matched experimentally measured correlations between speed and turning for two datasets of T cell movement in vivo suggesting that such simple correlations are not fully informative on the intrinsic link between speed and persistence. Our results thus suggest that sub-sampling may contribute to (and perhaps fully explains) the observed correlation between speed and turning at least for some cell trajectory data and emphasize the role of sampling frequency in inference of critical cellular parameters of cell motility such as speeds.

Secondary AbstractMeasurement of cell movements often results in a negative correlation between average speed and average turning angle suggesting an existence of a universal, cell-intrinsic movement program. We show that such a negative correlation may arise if cells in the population differ in their ability for persistent movement when the movement data are sub-sampled. We show that sub-sampling of cell trajectories generated using two different frameworks of persistent random walk can match the experimentally observed correlation between speed and turning for T cell movements in vivo. SERCA function is impaired in skeletal and cardiac muscles from young DBA/2J mdx mice The DBA/2J (D2) mdx mouse has emerged as a more severe model of Duchenne muscular dystrophy when compared to the traditional C57BL/10 (C57) mdx mouse. Here, we questioned whether sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA) function would differ in muscles from young D2 and C57 mdx mice. In gastrocnemius muscles, both D2- and C57 mdx mice exhibited signs of impaired Ca2+ uptake, however, this was more severe in D2 mdx mice. Maximal SERCA activity was lowered only in D2 mdx gastrocnemius muscles and not C57 mdx muscles. Furthermore, in the left ventricle and diaphragm, Ca2+ uptake was impaired in C57 mdx muscles with lowered rates of Ca2+ uptake compared with C57 WT mice, whereas in muscles from D2 mdx mice, rates of Ca2+ uptake were unattainable due to the severe impairments in their ability to transport Ca2+. Overall, our study demonstrates that SERCA function is drastically impaired in young D2 mdx mice. Modeling miRNA-driven post-transcriptional regulation by using exon-intron split analysis (EISA) in pigs The contribution of microRNAs (miRNAs) to mRNA regulation has often been explored by post hoc selection of downregulated genes and determining whether they harbor binding sites for miRNAs of interest. This approach, however, does not discriminate whether these mRNAs are also downregulated at the transcriptional level. Here, we have characterized the transcriptional and post-transcriptional changes of mRNA expression in two porcine tissues: gluteus medius muscle of fasted and fed Duroc gilts and adipose tissue of lean and obese Duroc-Gottingen minipigs. Exon-intron split analysis (EISA) of RNA-seq data allowed us to identify downregulated mRNAs with high post-transcriptional signals in fed or obese states, and we assessed whether they harbor binding sites for upregulated miRNAs in any of these two physiological states. We found 26 downregulated mRNAs with high post-transcriptional signals in the muscle of fed gilts and 21 of these were predicted targets of upregulated miRNAs also in the fed state. For adipose tissue, 44 downregulated mRNAs in obese minipigs displayed high post-transcriptional signals, and 25 of these were predicted targets of miRNAs upregulated in the obese state. These results suggest that the contribution of miRNAs to mRNA repression is more prominent in the skeletal muscle system. Finally, we identified several genes that may play relevant roles in the energy homeostasis of the pig skeletal muscle (DKK2 and PDK4) and adipose (SESN3 and ESRRG) tissues. By differentiating transcriptional from post-transcriptional changes in mRNA expression, EISA provides a valuable view about the regulation of gene expression, complementary to canonical differential expression analyses. Optimization of avian perching manoeuvres Perching at speed is amongst the most challenging flight behaviours that birds perform1,2, and beyond the capability of current autonomous vehicles. Smaller birds may touchdown by hovering3-8, but larger birds typically swoop upward to perch1,2 - presumably because the adverse scaling of their power margin prohibits slow flapping flight9, and because swooping transfers excess kinetic to potential energy1,2,10. Perching is risky in larger birds6,11, demanding precise control of velocity and pose12-15, but it is unknown how they optimize this challenging manoeuvre. More generally, whereas cruising flight behaviours such as migration and commuting are adapted to minimize cost-of-transport or time-of-flight16, the optimization of unsteady flight manoeuvres remains largely unexplored7,17. Here we show that swooping minimizes neither the time nor energy required to perch safely in Harris hawks Parabuteo unicinctus, but instead minimizes the distance flown under hazardous post-stall conditions. By combining motion capture data from 1,563 flights with flight dynamics modelling, we found that the birds choice of where to transition from powered dive to unpowered climb minimizes the distance from the landing perch over which very high lift coefficients are required. Time and energy are therefore invested to maintain the control authority needed to execute a safe landing, rather than being minimized continuously as in technical applications of autonomous perching under nonlinear feedback control13 and deep reinforcement learning18,19. Naive birds learn this behaviour on-the-fly, so our findings suggest an alternative reward function for reinforcement learning of autonomous perching in air vehicles. Naming of human diseases on the wrong side of history BackgroundIn the medical sphere, understanding naming conventions strengthen the integrity of naming human diseases remains nominal rather than substantial yet. Since the current nosology-based standard for human diseases could not offer a one-size-fits-all corrective mechanism, many idiomatic but flawed names frequently appear in scientific literature and news outlets at the cost of sociocultural impacts.

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

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

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

ConclusionsOur findings indicate that the nosological evolution of anachronistic names could result in sociocultural impacts without a corrective mechanism. To mitigate such impacts, we introduce some ethical principles for formulating an improved naming scheme. Based on deep learning models and post-hoc explanations, our illustrated experiments could provide hallmark references to the remedial mechanism of naming practices and pertinent credit allocations. SynergyFinder Plus: Toward Better Interpretation and Annotation of Drug Combination Screening Datasets Combinatorial therapies have been recently proposed to improve the efficacy of anticancer treatment. The SynergyFinder R package is a software used to analyze pre-clinical drug combination datasets. Here, we report the major updates to the SynergyFinder R package for improved interpretation and annotation of drug combination screening results. Unlike the existing implementations, the updated SynergyFinder R package includes five main innovations. (1) We extend the mathematical models to higher-order drug combination data analysis and implement dimension reduction techniques for visualizing the synergy landscape. (2) We provide a statistical analysis of drug combination synergy and sensitivity with confidence intervals and P values. (3) We incorporate a synergy barometer to harmonize multiple synergy scoring methods to provide a consensus metric for synergy. (4) We evaluate drug combination synergy and sensitivity to provide an unbiased interpretation of the clinical potential. (5) We enable fast annotation of drugs and cell lines, including their chemical and target information. These annotations will improve the interpretation of the mechanisms of action of drug combinations. To facilitate the use of the R package within the drug discovery community, we also provide a web server at www.synergyfinderplus.org as a user-friendly interface to enable a more flexible and versatile analysis of drug combination data. In vivo profiling of site-specific human cancer cell states in zebrafish Tissue microenvironments affect the functional states of cancer cells, but determining these influences in vivo has remained a significant challenge. We present a quantitative high-resolution imaging assay of cancer cell morphology in zebrafish xenografts to probe functional adaptation to variable cell extrinsic cues and molecular interventions. We focus on Ewing Sarcoma, a pediatric cancer driven by a single oncogenic fusion protein EWSR1-FLI1, and with little to no additional somatic mutations, making it a prototypical form of cancer whose adaptation to microenvironments is likely driven by acute, non-genomic mechanisms. Using computer vision analysis of 3D cell shapes, we find systematic shifts in the distribution of cell morphotypes between distinct sites in the fish embryo. We also find site-specific morphological responses to differential expression of EWSR1-FLI1. Combining these data we propose a model where Ewing Sarcoma cancer cell plasticity is sensitive both to expression fluctuation of EWSR1-FLI1 and signals from the surrounding tissue microenvironment, with either or both factors possibly contributing to the oncogenic potential of these cells. Gradient-mixing LEGO robots for purifying DNA origami nanostructures of multiple components by rate-zonal centrifugation DNA origami purification is critical in emerging applications of functionalized DNA nanostructures from basic fundamental biophysics, nanorobots to therapeutics. Advances in DNA origami purification have led to the establishment of rate-zonal centrifugation (RZC) as a scalable, high-yield, and contamination-free approach to purifying DNA origami nanostructures. In RZC purification, a linear density gradient is created using viscous agents, such as glycerol and sucrose, to separate molecules based on their mass and shape during high-rpm centrifugation. However, current methods for creating density gradients are typically time-consuming because of their reliance on slow passive diffusion. Here, we built a LEGO gradient mixer to rapidly create a quasi-continuous density gradient with minimal layering of concentrations using simple rotational motion. We found that rotating two layers of different concentrations at an angle can reduce the diffusion time from a few hours to mere minutes. The instrument needed to perform the movement can be constructed from low-cost components, such as Arduino and LEGO Mindstorms pieces, and has comparable efficacy to commercial gradient mixers currently available. Our results demonstrate that the creation of a linear density gradient can be achieved with minimal labor, time, and cost with this machine. With the recent advances in DNA origami production, we anticipate our findings to further improve the viability of scaling up DNA origami purification in grams quantities. Our simple process enables automated large-scale purification of functionalized DNA origami more feasible in resource-constrained settings. Mapping the genetic and environmental aetiology of autistic traits in Sweden and the United Kingdom BackgroundAutistic traits are influenced by both genetic and environmental factors, and are known to vary geographically in prevalence. But to what extent does their aetiology also vary from place to place?

MethodsWe applied a novel spatial approach to data on autistic traits from two large twin studies, the Child and Adolescent Twin Study in Sweden (CATSS; N=16,677, including 8,307 twin pairs) and the Twins Early Development Study in the UK (TEDS; N=11,594, including 5,796 twin pairs), to explore how the influence of nature and nurture on autistic traits varies from place to place.

ResultsWe present maps of gene- and environment-by geography interactions in Sweden and the United Kingdom (UK), showing geographical variation in both genetic and environmental influences across the two countries. In Sweden genetic influences appear higher in the far south and in a band running across the centre of the country. Environmental influences appear greatest in the south and north, with reduced environmental influence across the central band. In the UK genetic influences appear greater in the south, particularly in more central southern areas and the southeast, the Midlands and the north of England. Environmental influences appear greatest in the south and east of the UK, with less influence in the north and the west.

ConclusionsWe hope this systematic approach to identifying aetiological interactions will inspire research to examine a wider range of previously unknown environmental influences on the aetiology of autistic traits. By doing so, we will gain greater understanding of how these environments draw out or mask genetic predisposition and interact with other environmental influences in the development of autistic traits. The Digital 3D-Atlas MAKER (DAMAKER): a dynamic and expandable digital 3D-tool for monitoring the temporal changes in tissue growth during hindbrain morphogenesis Reconstruction of prototypic three-dimensional (3D) atlases at the scale of whole tissues or organs requires specific methods to be developed. We have established a digital 3D-atlas maker (DAMAKER) and built a digital 3D-temporal atlas to monitor the changes in the growth of the tissue and neuronal differentiation domain in the zebrafish hindbrain. DAMAKER integrates spatial and temporal data from cell populations, neuronal differentiation and brain morphogenesis, through in vivo imaging techniques paired with image analyses and segmentation tools. First, we generated a 3D-reference from several imaged hindbrains and segmented them using a trainable tool; these were aligned using rigid registration, revealing distribution of neuronal differentiation growth patterns along the axes. Second, we quantified the dynamic growth of the neuronal differentiation domain vs. the progenitor domain, and by in vivo neuronal birthdating experiments we generated a digital 3D-temporal map of the neuronal growth in the whole hindbrain, revealing the spatiotemporal dynamics of neuronal differentiation upon morphogenesis. Last, we applied it to glutamatergic and GABAergic neurons, as proof-of-concept that the digital 3D-temporal map could be used as a proxy to infer neuronal birthdate. As this protocol uses open-access tools and algorithms, it can be shared for standardized, accessible, tissue-wide cell population atlas construction. Morphology of immatures of the thelytokous ant, Monomorium triviale Wheeler (Formicidae: Myrmicinae: Solenopsidini) with descriptions of the extraordinary last-instar queen larvae The ant genus Monomorium is one of the most species-rich but taxonomically problematic groups in the hyperdiverse subfamily Myrmicinae. An East Asian species, M. triviale Wheeler, produces both reproductive queens and sterile workers via obligate thelytokous parthenogenesis. Here, we describe the immature forms of M. triviale based on light and scanning electron microscopy observations, with a note on the striking caste dimorphism in the last larval instar. The last-instar queen larvae were easily recognized by their large size, "aphaenogastroid" body shape, and rows of doorknob-like tubercles on the lateral and dorsal body surface. This type of queen-specific structure has not been found in ants in general, let alone congeneric species found in Japan. In stark contrast to the queen larvae, worker larvae showed a "pheidoloid" body shape and a body surface similar to other ants. The worker larvae were estimated to have three instars, consistent with previously described congeners. The pupae of both castes had no cocoon, a characteristic commonly described in other Myrmicinae species. In total, the developmental period from egg to adult worker averaged 59 days under 25{degrees}C. We discuss possible functions of the tubercles of queen larvae based on previous studies. Distinct Synaptic Transfer Functions in Same-Type Photoreceptors Many sensory systems use ribbon-type synapses to transmit their signals to downstream circuits. The properties of this synaptic transfer fundamentally dictate which aspects in the original stimulus will be accentuated or suppressed, thereby partially defining the detection limits of the circuit. Accordingly, sensory neurons have evolved a wide variety of ribbon geometries and vesicle pool properties to best support their diverse functional requirements. However, the need for diverse synaptic functions does not only arise across neuron types, but also within. Here we show that UV-cones, a single type of photoreceptor of the larval zebrafish eye, exhibit striking differences in their synaptic ultrastructure and consequent calcium to glutamate transfer function depending on their location in the eye. We arrive at this conclusion by combining serial section electron microscopy and simultaneous "dual-colour" 2-photon imaging of calcium and glutamate signals from the same synapse in vivo. We further use the functional dataset to fit a cascade-like model of the ribbon synapse with different vesicle pool sizes, transfer rates and other synaptic properties. Exploiting recent developments in simulation-based inference, we obtain full posterior estimates for the parameters and compare these across different retinal regions. The model enables us to extrapolate to new stimuli and to systematically investigate different response behaviours of various ribbon configurations. We also provide an interactive, easy-to-use version of this model as an online tool. Overall, we show that already on the synaptic level of single neuron types there exist highly specialized mechanisms which are advantageous for the encoding of different visual features.