Constraints on the evolution of toxin-resistant Na,K-ATPases have limited dependence on sequence divergence A growing body of theoretical and experimental evidence suggests that intramolecular epistasis is a major determinant of rates and patterns of protein evolution and imposes a substantial constraint on the evolution of novel protein functions. Here, we examine the role of intramolecular epistasis in the recurrent evolution of resistance to cardiotonic steroids (CTS) across tetrapods, which occurs via specific amino acid substitutions to the -subunit family of Na,K-ATPases (ATP1A). After identifying a series of recurrent substitutions at two key sites of ATP1A that are predicted to confer CTS resistance in diverse tetrapods, we then performed protein engineering experiments to test the functional consequences of introducing these substitutions onto divergent species backgrounds. In line with previous results, we find that substitutions at these sites can have substantial background-dependent effects on CTS resistance. Globally, however, these substitutions also have pleiotropic effects that are consistent with additive rather than background-dependent effects. Moreover, the magnitude of a substitutions effect on activity does not depend on the overall extent of ATP1A sequence divergence between species. Our results suggest that epistatic constraints on the evolution of CTS-resistant forms of Na,K-ATPase likely depend on a small number of sites, with little dependence on overall levels of protein divergence. We propose that dependence on a limited number sites may account for the observation of convergent CTS resistance substitutions observed among taxa with highly divergent Na,K-ATPases.

Significance StatementIndividual amino acid residues within a protein work in concert to produce a functionally coherent structure that must be maintained even as orthologous proteins in different species diverge over time. Given this dependence, we expect identical mutations to have more similar effects on protein function in more closely related species. We tested this hypothesis by performing protein-engineering experiments on ATP1A, an enzyme mediating target-site insensitivity to cardiotonic steroids (CTS) in diverse animals. These experiments reveal that the phenotypic effects of substitutions can sometimes be background-dependent, but also that the magnitude of these phenotypic effects does not correlate with overall levels of ATP1A sequence divergence. Our results suggest that epistatic constraints are determined by states at a small number of sites, potentially explaining the frequent convergent CTS resistance substitutions among Na,K-ATPases of highly divergent taxa.
Holobiont Evolution: Population Theory for the Hologenome This article develops mathematical theory for the population dynamics of microbiomes with their hosts and theory for microbiome evolution caused by holobiont selection.

A holobiont is the union of a host with its microbiome. Holobiont selection is natural selection on the combined host and microbiome as a unit. The hologenome is the union of genes in the microbiome with genes in the host nucleus. The deep integration within many holobionts of microbiomes with their hosts extends to development, metabolism, physiology and behavior. The kind of eco-evolutionary processes producing this integration is unclear.

For a microbe to join a hosts microbiome, its population-dynamic parameters must sufficiently align with the hosts population-dynamic parameters. Accordingly, a microbe might be excluded from the microbiome, might enter the microbiome in a way leading to its subsequent gradual shedding from the holobiont, might join the microbiome and coexist with the host, or might, for a deleterious microbe, enter the microbiome culminating in the extinction of both it and the host.

A horizontally transmitted microbiome constitutes a genetic system that features "collective inheritance" capable of underwriting Darwinian descent with modification. The microbial source pool in the environment is the counterpart for the microbiome of the gamete pool for the nuclear genome. Poisson sampling of the microbial source pool is the counterpart of binomial sampling of the gamete pool. However, holobiont selection on the microbiome does not lead to a counterpart of the Hardy-Weinberg Law, a concept of selective neutrality, or directional selection that produces fixation of the microbial gene with the highest fitness. The effectiveness of holobiont selection on microbial genes is limited compared to the effectiveness of natural selection on nuclear genes. Nonetheless, holobiont selection can affect the composition of the microbiome by permitting the coexistence of a competitively inferior microbial strain with a superior strain in a colonization-extinction equilibrium and by permitting a polymorphism between altruistic and selfish microbial strains.

An altruistic microbe might strike an optimal balance between lowering within-host fitness to increase holobiont fitness. However, altruistic microbes are replaced by otherwise identical microbes that contribute nothing to holobiont fitness. This replacement can be reversed by hosts that discriminate against colonization by selfish microbes--likely brought about by hosts making antibodies against selfish microbes. This discrimination leads to a process of microbial species sorting orchestrated by the host immune system. Holobiont assembly with host-orchestrated species sorting (HOSS) followed by microbial competition, rather than coevolution or multi-level selection, is the likely cause of host-microbiome integration.
Metabarcoding faecal samples to investigate spatiotemporal variation in the diet of the endangered Westland petrel (Procellaria westlandica) As top predators, seabirds can be indirectly impacted by climate variability and commercial fishing activities through changes in marine communities. However, high mobility and foraging behaviour enables seabirds to exploit prey distributed patchily in time and space. This capacity to adapt to environmental change can be described through the study of their diet. Traditionally, the diet of seabirds is assessed through the morphological identification of prey remains in regurgitates. This sampling method is invasive for the bird and limited in terms of taxonomic resolution. However, the recent progress in DNA-based approaches is now providing a non-invasive means to more comprehensively and accurately characterize animal diets. Here, we used a non-invasive metabarcoding approach to characterize the diet of the Westland petrel (Procellaria westlandica), which is an endangered burrowing species, endemic to the South Island of New Zealand. We collected 99 fresh faecal samples at two different seasons and in two different sub-colonies. Our aims were to describe the diet of the Westland petrel, investigate seasonal and spatial variation in the petrels diet, and assess potential impacts of the New Zealand fishery industry. We found that amphipods were the most common prey, followed by cephalopods and fish. Our results could be the result of natural foraging behaviour, but also suggest a close link between the composition of prey items and New Zealands commercial fishing activities. In particular, the high abundance of amphipods could be the result of Westland petrels feeding on discarded fisheries waste (fish guts). Our results also showed significant differences in diet between seasons (before hatching vs chick-rearing season) and between sampling sites (two sub-colonies 1.5 km apart), indicating plasticity in the foraging strategy of the Westland petrel. Due to its non-invasive nature, metabarcoding of faecal samples can be applied to large numbers of samples to help describe dietary variation in seabirds and indicate their ecological requirements. In our example, dietary DNA (dDNA) provided valuable information regarding the dietary preferences of an iconic species in New Zealands unique biodiversity. dDNA can thus inform the conservation of endangered or at-risk species that have elusive foraging behaviours. Improved radiation expression profiling in blood by sequential application of sensitive and specific gene signatures PurposeCombinations of expressed genes can discriminate radiation-exposed from normal control blood samples by machine learning based signatures (with 8 to 20% misclassification rates). These signatures can quantify therapeutically-relevant as well as accidental radiation exposures. The prodromal symptoms of Acute Radiation Syndrome (ARS) overlap those present in Influenza and Dengue Fever infections. Surprisingly, these human radiation signatures misclassified gene expression profiles of virally infected samples as false positive exposures. The present study investigates these and other confounders, and then mitigates their impact on signature accuracy.

MethodsThis study investigated recall by previous and novel radiation signatures independently derived from multiple Gene Expression Omnibus datasets on common and rare non-malignant blood disorders and blood-borne infections (thromboembolism, S. aureus bacteremia, malaria, sickle cell disease, polycythemia vera, and aplastic anemia). Normalized expression levels of signature genes are used as input to machine learning-based classifiers to predict radiation exposure in other hematological conditions.

ResultsExcept for aplastic anemia, these blood-borne disorders modify the normal baseline expression values of genes present in radiation signatures, leading to false-positive misclassification of radiation exposures in 8 to 54% of individuals. Shared changes, predominantly in DNA damage response and apoptosis-related gene transcripts in radiation and confounding hematological conditions, compromise the utility of these signatures for radiation assessment. These confounding conditions (sickle cell disease, thromboembolism, S. aureus bacteremia, malaria) induce neutrophil extracellular traps, initiated by chromatin decondensation, DNA damage response and fragmentation followed by programmed cell death. Riboviral infections (for example, Influenza or Dengue fever) have been proposed to bind and deplete host RNA binding proteins, inducing R-loops in chromatin. R-loops that collide with incoming replication forks can result in incompletely repaired DNA damage, inducing apoptosis and releasing mature virus. To mitigate the effects of confounders, we evaluated predicted radiation-positive samples with novel gene expression signatures derived from radiation-responsive transcripts encoding secreted blood plasma proteins whose expression levels are unperturbed by these conditions.

ConclusionsThis approach identifies and eliminates misclassified samples with underlying hematological or infectious conditions, leaving only samples with true radiation exposures. Diagnostic accuracy is significantly improved by selecting genes that maximize both sensitivity and specificity in the appropriate tissue using combinations of the best signatures for each of these classes of signatures. Classification of daily crop phenology in PhenoCams using deep learning and hidden markov models Near surface cameras, such as those in the PhenoCam network, are a common source of ground truth data in modelling and remote sensing studies. Despite having locations across numerous agricultural sites, few studies have used near surface cameras to track the unique phenology of croplands. Due to management activities, crops do not have a natural vegetation cycle which many phenological extraction methods are based on. For example, a field may experience abrupt changes due to harvesting and tillage throughout the year. A single camera can also record several different plants due to crop rotations, fallow fields, and cover crops. Current methods to estimate phenology metrics from image time series compress all image information into a relative greenness metric, which discards a large amount of contextual information. This can include the type of crop present, whether snow or water is present on the field, the crop phenology, or whether a field lacking green plants consists of bare soil, fully senesced plants, or plant residue. Here we developed a modelling workflow to create a daily time series of crop type and phenology, while also accounting for other factors such as obstructed images and snow covered fields. We used a mainstream deep learning image classification model, VGG16. Deep learning classification models do not have a temporal component, so to account for temporal correlation among images our workflow incorporates a hidden markov model in the post-processing. The initial image classification model had out of sample F1 scores of 0.83-0.85, which improved to 0.86-0.91 after all post-processing steps. The resulting time series show the progression of crops from emergence to harvest, and can serve as a daily, local scale dataset of field states and phenological stages for agricultural research. Citation needed?Wikipedia bibliometrics during the first waveof the COVID-19 pandemic. BackgroundWith the COVID-19 pandemics outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an "infodemic", ensuring the quality of information is a crucial vector of public health. Investigating if and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked: which sources informed Wikipedias COVID-19-related articles before and during the pandemics first wave (January-May 2020).

ResultsWe found that coronavirus-related articles referenced trusted media sources and high-quality academic research. Moreover, despite a surge in COVID-19 preprints, Wikipedia had a clear preference for open-access studies published in respected journals and made little use of preprints. Building a timeline of English COVID-19 articles from 2001-2020 revealed a nuanced trade-off between quality and timeliness. It further showed how preexisting articles on key topics related to the virus created a framework for integrating new knowledge. Supported by a rigid sourcing policy, this "scientific infrastructure" facilitated contextualization and regulated the influx of new information. Lastly, we constructed a network of DOI-Wikipedia articles, which showed the shifting landscape of pandemic-related knowledge on Wikipedia and how academic citations create a web of shared knowledge supporting topics like COVID-19 vaccine development.

ConclusionsUnderstanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its "citizen encyclopedists", it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts. 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. First detection of herpesvirus and frequency of mycoplasma infection in free-ranging Hermann s tortoises (Testudo hermanni), and in potential pet vectors AO_SCPLOWBSTRACTC_SCPLOWTwo types of pathogens cause highly contagious upper respiratory tract diseases (URTD) in Chelonians: testudinid herpesviruses (TeHV) and a mycoplasma (Mycoplasma agassizii). In captivity, these infections are frequent and can provoke outbreaks. Pet trade generates international flow of tortoises, often without sanitary checking; individuals intentionally or accidentally released in the wild may spread pathogens. A better understanding of the transmission of infectious agents from captivity to wild tortoises is needed. Many exotic individuals have been introduced in populations of the endangered western Hermanns tortoise (Testudo hermanni hermanni), notably spur-thighed tortoises (Testudo graeca). We assessed the presence of TeHV and mycoplasma in native western Hermanns tortoises and in potential pet vectors in south-eastern France. Using a large sample (N=572 tortoises), this study revealed, by PCR, the worrying presence of herpesvirus in 7 free-ranging individuals (3 sub-populations). Additionally, Mycoplasma agassizii was detected, by PCR, in 15 of the 18 populations sampled with a frequency ranging from 3.4% (1 of 29 tortoises) to 25% (3 of 12 tortoises). Exotic spur-thighed tortoises showed high frequency of mycoplasma infection in captivity (18.2%) and in individuals (50%) found in native Hermanns tortoise sub-populations, suggesting that this species could be a significant vector. The paucity of information of TeHV on European tortoise URTD in natural settings, especially in combination with mycoplasma, prompts for further studies. Indeed, sick tortoises remain concealed and may not be easily detected in the field. Our results indicate a good health for most infected tortoise but it should be screened in the field as well as in captivity. Metacells untangle large and complex single-cell transcriptome networks The exponential scaling of scRNA-seq data represents an important hurdle for downstream analyses. Here we develop a coarse-graining framework where highly similar cells are merged into metacells. We demonstrate that metacells not only preserve but often improve the results of downstream analyses including visualization, clustering, differential expression, cell type annotation, gene correlation, imputation, RNA velocity and data integration. By capitalizing on the redundancy inherent to scRNA-seq data, metacells significantly facilitate and accelerate the construction and interpretation of single-cell atlases, as demonstrated by the integration of 1.46 million cells from COVID-19 patients in less than two hours on a standard desktop. Variation in female songbird state determines signal strength needed to evoke copulation It is the female response to male signals that determines courtship success. In most songbirds, females control reproduction via the copulation solicitation display (CSD), an innate, stereotyped posture produced in direct response to male displays. Because CSD can be elicited in the absence of males by the presentation of recorded song, CSD production enables investigations into the effects of underlying signal features and behavioral state on female mating preferences. Using computer vision to quantify CSD trajectory in female brown-headed cowbirds (Molothrus ater), we show that both song quality and a females internal state predict CSD production, as well as the onset latency and duration of the display. We also show that CSD can be produced in a graded fashion based on both signal strength and internal state. These results emphasize the importance of underlying receiver state in determining behavioral responses and suggest that female responsiveness acts in conjunction with male signal strength to determine the efficacy of male courtship. Prediction of survival after partial hepatectomy using a physiologically based pharmacokinetic model of indocyanine green liver function tests The evaluation of hepatic function and functional capacity of the liver are essential tasks in hepatology as well as in hepatobiliary surgery. Indocyanine green (ICG) is a widely applied test compound that is used in clinical routine to evaluate hepatic function. Important questions for the functional evaluation with ICG in the context of hepatectomy are how liver disease such as cirrhosis alters ICG elimination, and if postoperative survival can be predicted from preoperative ICG measurements. Within this work a physiologically based pharmacokinetic (PBPK) model of ICG was developed and applied to the prediction of the effects of a liver resection under various degrees of cirrhosis. For the parametrization of the computational model and validation of model predictions a database of ICG pharmacokinetic data was established. The model was applied (i) to study the effect of liver cirrhosis and liver resection on ICG pharmacokinetics; and (ii) to evaluate the model-based prediction of postoperative ICG-R15 as a measure for postoperative outcome. Key results are the accurate prediction of changes in ICG pharmacokinetics caused by liver cirrhosis and postoperative changes of ICG-elimination after liver resection, as validated with a wide range of data sets. Based on the PBPK model, individual survival after liver resection could be classified, demonstrating its potential value as a clinical tool. The ChAdOx1 vectored vaccine, AZD2816, induces strong immunogenicity against SARS-CoV-2 Beta (B.1.351) and other variants of concern in preclinical studies. There is an ongoing global effort to design, manufacture, and clinically assess vaccines against SARS-CoV-2. Over the course of the ongoing pandemic a number of new SARS-CoV-2 virus isolates or variants of concern (VoC) have been identified containing mutations in key proteins. In this study we describe the generation and preclinical assessment of a ChAdOx1-vectored vaccine (AZD2816) which expresses the spike protein of the Beta VoC (B.1.351). We demonstrate that AZD2816 is immunogenic after a single dose. When AZD2816 is used as a booster dose in animals primed with a vaccine encoding the original spike protein (ChAdOx1 nCoV-19/ [AZD1222]), high titre binding and neutralising antibodies against Beta (B.1.351), Gamma (P.1) and Delta (B.1.617.2) are induced. In addition, a strong and polyfunctional T cell response was measured in these booster regimens. These data support the ongoing clinical development and testing of this new variant vaccine. Tunable Cellular Localization and Extensive Cytoskeleton-Interplay of Reflectins Reflectin proteins are nature copolymers consist of repeated canonical domains, locating in a biophotonic system called Bragg lamellae and manipulating the dynamic structural coloration of iridocytes. Their biological functions are intriguing, but the underlying mechanism is not fully understood. In this study, reflectin A1, A2, B1 and C were found to present distinguished cyto-/nucleoplasmic localization preferences. Comparable intracellular localization can be reproduced by truncated reflectin variants, suggesting a conceivable evolutionary order among reflectin proteins. Secondly, the size-dependent access of reflectin variants into nucleus demonstrate a potential model of how reflectins get into Bragg lamellae. Thirdly, RfA1 was found to extensively interact with cytoskeleton, including its binding to actin and microtubule minus-end-directed movement. This implies cytoskeleton system plays fundamental role during the organization and transportation of reflectin proteins. Findings presented here recommend reflectins as programmable biomaterials which can be used to decipher their evolution processes, to delineate their biological mechanism, and to achieve tunable intracellular targeting as editable tags. 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. Characterization of divalent cation interactions with AASTY native nanodiscs Amphiphilic copolymers show promise in extracting membrane proteins directly from lipid bilayers into  native nanodiscs. However, many such copolymers are polyanionic and sensitive to divalent cations, limiting their applicability. We characterize the Ca2+ and Mg2+ sensitivity of poly(acrylic acid-co-styrene) (AASTY) copolymers with analytical UV and fluorescent size exclusion chromatography, enabling us to separate signals from nanodiscs, copolymers, and soluble aggregates. We find that divalent cations promote aggregation and precipitation of both free and lipid bound copolymers. We see that excess, free copolymer acts as a  cation sink that protects nanodiscs from Ca2+ induced aggregation. Removal of the free copolymer through dialysis induces aggregation that can be mitigated by KCl. Finally, we find that the nanodisc size is dynamic and dependent on lipid concentration. Our results offer insight to nanodisc behaviour, and can help guide experimental design, aimed at mitigating the shortcomings inherent in negatively charged nanodisc forming copolymers. Optogenetic dissection of actomyosin-dependent mechanics underlying tissue fluidity Rapid epithelial tissue flows are essential to building and shaping developing embryos. However, it is not well understood how the mechanical properties of tissues and the forces driving them to flow are jointly regulated to accommodate rapid tissue remodeling. To dissect the roles of actomyosin in the mechanics of epithelial tissue flows, here we use two optogenetic tools, optoGEF and optoGAP, to manipulate Rho/Rho-kinase signaling and actomyosin contractility in the germband epithelium, which flows via convergent extension movements during Drosophila body axis elongation. The ability to perturb actomyosin in the tissue allows us to analyze the effects of actomyosin on cell rearrangements, tissue tensions, and tissue mechanical properties. We find that either optogenetic activation or deactivation of Rho1 signaling and actomyosin contractility at the apical surface of the germband disrupts cell rearrangements and tissue-level flows. Rho1 activation leads to poorly oriented rearrangements that are associated with a redistribution of myosin II from the junctional to the medial-apical domain, whereas Rho1 deactivation leads to fewer, slower cell rearrangements that are associated with decreased junctional and medial myosin. By probing mechanical tensions in the tissue using laser ablation and inferring tissue mechanical properties from cell packings, we find that actomyosin influences both the anisotropic forces that drive tissue flow and the mechanical properties of the tissue that resist flow, leading to complex relationships between actomyosin activity and tissue fluidity. Moreover, our results link the subcellular distribution of myosin II to tissue tension and cell packings, revealing how junctional and medial myosin have differential roles in promoting and orienting cell rearrangements during tissue flow. Fungicide resistance characterised across seven modes of action in a Botrytis cinerea isolated from Australian vineyards BACKGROUNDBotrytis bunch rot, caused by Botrytis cinerea, is an economically important disease of grapes in Australia and across grape growing regions worldwide. Control of this disease relies on canopy management and the application of fungicides. Fungicide application can lead to the selection of resistant B. cinerea populations, which has an adverse effect on management of the disease. Characterising the distribution and severity of resistant B. cinerea populations is needed to inform resistance management strategies.

RESULTSIn this study, 725 isolates were sampled from 75 Australian vineyards during 2013 - 2016 and were screened against seven fungicides with different modes of action (MOAs). The resistance frequencies for azoxystrobin, boscalid, fenhexamid, fludioxonil, iprodione, pyrimethanil and tebuconazole were 5, 2.8, 2.1, 6.2, 11.6, 7.7 and 2.9% respectively. Nearly half of the resistant isolates (43.8%) were resistant to more than one of the fungicides tested. The frequency of vineyards with at least one isolate simultaneously resistant to 1, 2, 3, 4 or 5 fungicides was 19.5, 7.8, 6.5, 10.4 and 2.6%. Resistance was associated with previously published genotypes in CytB (G143A), SdhB (H272R/Y), Erg27 (F412S), Mrr1 (D354Y), Bos1 (I365S, N373S + Q369P, I365S + D757N) and Pos5 (V273I, P319A, L412F/V). Novel genotypes were also described in Mrr1 (S611N, D616G) Pos5 (V273L) and Cyp51 (P347S). Expression analysis was used to characterise fludioxonil resistant isolates exhibiting overexpression (6.3-9.6-fold) of the ABC transporter gene AtrB (MDR1 phenotype).

CONCLUSIONResistance frequencies were lower when compared to most previously published surveys of B. cinerea resistance in grape and other crops. Nevertheless, continued monitoring of critical MOAs used in Australian vineyards is recommended. Patterns of piRNA regulation in Drosophila revealed through transposable element clade inference Transposable elements (TEs) are self-replicating "genetic parasites" ubiquitous to eukaryotic genomes. In addition to conflict between TEs and their host genomes, TEs of the same family are in competition with each other. They compete for the same genomic niches while experiencing the same regime of copy-number selection. This suggests that competition among TEs may favor the emergence of new variants that can outcompete their ancestral forms. To investigate the sequence evolution of TEs, we developed a method to infer clades: collections of TEs that share SNP variants and represent distinct TE family lineages. We applied this method to a panel of 85 Drosophila melanogaster genomes and found that the genetic variation of several TE families shows significant population structure that arises from the population- specific expansions of single clades. We used population genetic theory to classify these clades into younger versus older clades and found that younger clades are associated with a greater abundance of sense and antisense piRNAs per copy than older ones. Further, we find that the abundance of younger, but not older clades, is positively correlated with antisense piRNA production, suggesting a general pattern where hosts preferentially produce antisense piRNAs from recently active TE variants. Together these findings suggest a pattern whereby new TE variants arise by mutation and then increase in copy number, followed by the host producing antisense piRNAs that may be used to silence these emerging variants. An IPI based immune prognostic model for diffuse large B-cell lymphoma BackgroundInternational Prognostic Index (IPI) was widely used to better discriminate prognosis of patients with diffuse large B-cell lymphoma (DLBCL). However, there is a significant need to identify novel valuable biomarkers in the context of targeted therapies, such as immune checkpoint blockade (ICB) therapy.

MethodsGene expression data and clinical information of DLBCL were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. 371 immune-related hub genes in DLBCL patients with different IPI levels were identified by weighted gene co-expression network analysis (WGCNA), and 8 genes were selected to construct an IPI-based immune prognostic model (IPI-IPM). Afterward, the genetic, somatic mutational and molecular profiles of IPI-IPM subgroups were analyzed, as well as the potential clinical response of ICB in different IPI-IPM subgroups.

ResultsThe IPI-IPM was constructed based on the expression of CMBL, TLCD3B, SYNDIG1, ESM1, EPHA3, HUNK, PTX3 and IL12A, where high-risk patients had shorter overall survival (OS) than low-risk patients, consistent with the results in the GEO cohorts. The comprehensive results showed that high IPI-IPM risk scores were correlated with immune-related signaling pathways, high KMT2D and CD79B mutation rates, as well as up-regulation of inhibitory immune checkpoints including PD-L1, BTLA and SIGLEC7, indicating more potential response to ICB therapy.

ConclusionThe IPI-IPM has independent prognostic significance for DLBCL patients, which provides an immunological perspective to elucidate the mechanisms on tumor progression, also sheds a light on developing immunotherapy for DLBCL. Interfacial tension driven open droplet microfluidics We developed an open channel droplet microfluidic system that autonomously generates droplets at low Ca (~10-4-10-3) by leveraging competing hydrostatic and capillary pressure. With only our open channel polytetrafluoroethylene (PTFE) device, pipettes, and commercially available carrier fluid, we produce hundreds of microliter droplets; tubing, electronics, or pumps are not required, making droplet technology feasible for research labs without external flow generators. Furthermore, we demonstrated conceptual applications that showcase the process of droplet generation, splitting, transport, incubation, mixing, and sorting in our system. Unlike conventional droplet microfluidics, the open nature of the device enables the use of physical tools such as tweezers and styli to directly access the system; with this, we developed a new method of droplet sorting and transfer that capitalizes on the Cheerios effect, the aggregation of buoyant objects along a liquid interface. Our platform offers enhanced usability, direct access to the droplet contents, easy manufacturability, compact footprint, and high customizability. This design is a first step in exploring the space of power-free open droplet microfluidic systems and provide design rules for similar channel designs. Ecologically pre-trained RNNs explain suboptimal animal decisions The strategies found by animals facing a new task are determined both by individual experience and by structural priors evolved to leverage the statistics of natural environments. Rats can quickly learn to capitalize on the trial sequence correlations of two-alternative forced choice (2AFC) tasks after correct trials, but consistently deviate from optimal behavior after error trials, when they waive the accumulated evidence. To understand this outcome-dependent gating, we first show that Recurrent Neural Networks (RNNs) trained in the same 2AFC task outperform rats as they can readily learn to use across-trial information both after correct and error trials. We hypothesize that, while RNNs can optimize their behavior in the 2AFC task without any a priori restrictions, rats strategy is constrained by a structural prior adapted to a natural environment in which rewarded and non-rewarded actions provide largely asymmetric information. When pre-training RNNs in a more ecological task with more than two possible choices, networks develop a strategy by which they gate off the across-trial evidence after errors, mimicking rats behavior. Population analyses show that the pre-trained networks form an accurate representation of the sequence statistics independently of the outcome in the previous trial. After error trials, gating is implemented by a change in the network dynamics which temporarily decouples the categorization of the stimulus from the across-trial accumulated evidence. Our results suggest that the suboptimal behavior observed in rats reflects the influence of a structural prior that reacts to errors by isolating the network decision dynamics from the context, ultimately constraining the performance in a 2AFC laboratory task. Unevolved proteins from modern and prebiotic amino acids manifest distinct structural profiles Natural proteins represent numerous but tiny structure/function islands in a vast ocean of possible protein sequences, most of which has not been explored by either biological evolution or research. Recent studies have suggested this uncharted sequence space possesses surprisingly high structural propensity, but development of an understanding of this phenomenon has been awaiting a systematic high-throughput approach.

Here, we designed, prepared, and characterized two combinatorial protein libraries consisting of randomized proteins, each 105 residues in length. The first library constructed proteins from the entire canonical alphabet of 20 amino acids. The second library used a subset of only 10 residues (A,S,D,G,L,I,P,T,E,V) that represent a consensus view of plausibly available amino acids through prebiotic chemistry. Our study shows that compact conformations resistant to proteolysis are (i) abundant (up to 40%) in random sequence space, (ii) independent of general Hsp70 chaperone system activity, and (iii) not granted solely by "late" and complex amino acid additions. The Hsp70 chaperone system effectively increases solubility and refoldability of the canonical alphabet but has only a minor impact on the "early" library. The early alphabet proteins are inherently more soluble and refoldable, possibly assisted by the cell-like environment in which these assays were performed.

Our work indicates that both early and modern amino acids are predisposed to supporting protein structure (either in forms of oligomers or globular/molten globule structures) and that protein structure may not be a unique outcome of evolution. Rho Kinase regulates neutrophil NET formation that is involved in UVB-induced skin inflammation ObjectiveUltraviolet B (UVB) is an important trigger of skin inflammation and lupus with leukocyte recruitment to inflamed skin. We recently reported the involvement of neutrophil NETosis in UVB-induced skin inflammation, and that NETotic nuclear envelope rupture is driven by PKC-mediated nuclear lamin B disassembly. To address the role of Actin cytoskeleton in NETosis, we investigated the effects of Rho kinase (ROCK) and its downstream actomyosin cytoskeletal networks on PKC nuclear translocation and NET formation, as well as their involvement in UVB-induced skin inflammation.

MethodsWe studied the dynamic changes of ROCK and actomyosin cytoskeletal networks during NETosis induction and their involvement in PKC nuclear translocation. Using mice with hematopoietic-specific ROCK1 deficiency, we investigated the effects of ROCK1 deficiency on NETosis, and its involvement in UVB-induced skin inflammation.

ResultsOur time course studies demonstrated the dynamic changes of actin polymerization and ROCK activation, support the role of actin cytoskeleton in nuclear translocation of cytosolic PKC in early stage of NETosis induction. Inhibition of actin polymerization or key molecules of the ROCK/MLCK/myosin pathway decreased PKC nuclear translocation and NET formation. Genetic deficiency of ROCK1, inhibited NETosis ex vivo and in vivo, decreased extracellular display of NET-associated IL-17A, TNF, IFN{gamma}, and IFN in inflamed skin, which were correlated with the ameliorated skin inflammation in UVB-irradiated mice with hematopoietic-specific ROCK1 deficiency.

ConclusionsROCK regulated NETosis through modulation of PKC nuclear translocation via actomyosin cytoskeletal networks in neutrophils. ROCK1 deficiency ameliorated UVB- induced skin inflammation by attenuation of NETosis and NET-associated cytokines. Phenotypic heterogeneity driven by plasticity of the intermediate EMT state governs disease progression and metastasis in breast cancer The Epithelial-to-Mesenchymal Transition (EMT) is a developmental cellular program frequently coopted by cancer cells1 and is a key contributor to both heterogeneity in solid tumors2-4 and later stage chemo-resistance and metastasis5,6. Rather than being a switch from an epithelial to a mesenchymal state, increasing evidence points to the existence of intermediate EMT states, wherein cells co-express both epithelial and mesenchymal traits7-13. Multiple stable intermediate EMT states possessing unique characteristics exist across the EMT spectrum7,8,14,15, contributing to the complex heterogeneity of tumors to promote metastasis16. While much work has been carried out identifying and characterizing EMT-inducing transcription factors17-20, the transcriptional and epigenetic networks responsible for the stability and maintenance of the midpoints along the EMT spectrum are poorly defined. In addition, there are currently no approaches to identifying and quantifying intermediate EMT subpopulations within patient tumors to evaluate their prognostic significance. Using clonally isolated derivatives of the SUM149PT breast cancer cell line, we systematically interrogate how each EMT state independently contributes to heterogeneity and influences metastatic progression, uncovering the role of RUNX2 in stabilizing certain intermediate states. Using SUM149PT-derived tumors as a training set, we develop an entropy-based model to quantify phenotypic heterogeneity and EMT status. Remarkably, the majority of cell states captured in the SUM149PT model are represented in a selection of patient tumors, laying the foundation for quantification of epithelial-mesenchymal heterogeneity and understanding the role of the intermediate EMT state in tumor progression. O-specific antigen-dependent surface hydrophobicity mediates aggregate assembly type in Pseudomonas aeruginosa Bacteria live in spatially organized aggregates during chronic infections, where they adapt to the host environment, evade immune responses and resist therapeutic interventions. Although it is known that environmental factors such as polymers influence bacterial aggregation, it is not clear how bacterial adaptation during chronic infection impacts the formation and spatial organization of aggregates in the presence of polymers. Here we show that in an in vitro model of cystic fibrosis (CF) containing the polymers eDNA and mucin, O-specific antigen is a major factor in determining the formation of two distinct aggregate assembly types of Pseudomonas aeruginosa due to alterations in cell surface hydrophobicity. Our findings suggest that during chronic infection, interplay between cell surface properties and polymers in the environment may influence the formation and structure of bacterial aggregates, which would shed new light on the fitness costs and benefits of O-antigen production in environments such as CF lungs.

ImportanceDuring chronic infection, several factors contribute to the biogeography of microbial communities. Heterogeneous populations of Pseudomonas aeruginosa form aggregates in cystic fibrosis airways, however, the impact of this population heterogeneity on spatial organization and aggregate assembly is not well understood. In this study we found that changes in O-specific antigen determine the spatial organization of P. aeruginosa cells by altering the relative cell surface hydrophobicity. This finding suggests a role for O-antigen in regulating P. aeruginosa aggregate size and shape in cystic fibrosis airways. Elucidation of SARS-CoV-2 budding mechanisms through molecular dynamics simulations of M and E protein complexes SARS-CoV-2 and other coronaviruses pose major threats to global health, yet computational efforts to understand them have largely overlooked the process of budding, a key part of the coronavirus life cycle. When expressed together, coronavirus M and E proteins are sufficient to facilitate budding into the ER-Golgi intermediate compartment (ERGIC). To help elucidate budding, we ran atomistic molecular dynamics (MD) simulations using the Feig laboratorys refined structural models of the SARS-CoV-2 M protein dimer and E protein pentamer. Our MD simulations consisted of M protein dimers and E protein pentamers in patches of membrane. By examining where these proteins induced membrane curvature in silico, we obtained insights around how the budding process may occur. Multiple M protein dimers acted together to induce global membrane curvature through protein-lipid interactions while E protein pentamers kept the membrane planar. These results could eventually help guide development of antiviral therapeutics which inhibit coronavirus budding.