How to Approach Machine Learning-based Prediction of Drug/Compound-Target Interactions The identification of drug/compound-target interactions (DTIs) constitutes the basis of drug discovery, for which computational predictive approaches have been applied. As a relatively new data-driven paradigm, proteochemometric (PCM) modeling utilizes both protein and compound properties as a pair at the input level and processes them via statistical/machine learning. The representation of input samples (i.e., proteins and their ligands) in the form of quantitative feature vectors is crucial for the extraction of interaction-related properties during the artificial learning and subsequent prediction of DTIs. Lately, the representation learning approach, in which input samples are automatically featurized via training and applying a machine/deep learning model, has been utilized in biomedical sciences. In this study, we performed a comprehensive investigation of different computational approaches/techniques for protein featurization (including both conventional approaches and the novel learned embeddings), data preparation and exploration, machine learning-based modeling, and performance evaluation with the aim of achieving better data representations and more successful learning in DTI prediction. For this, we first constructed realistic and challenging benchmark datasets on small, medium, and large scales to be used as reliable gold standards for specific DTI modeling tasks. We developed and applied a network analysis-based splitting strategy to divide datasets into structurally different training and test folds. Using these datasets together with various featurization methods, we trained and tested DTI prediction models and evaluated their performance from different angles. Our main findings can be summarized under 3 items: (i) random splitting of datasets into train and test folds lead to near-complete data memorization and produce highly over-optimistic results, as a result, it should be avoided, (ii) learned protein sequence embeddings work well in DTI prediction and offer high potential, even though no information related to protein structures, interactions or biochemical properties is utilized during their generation, and (iii) PCM models tend to learn from compound features and leave out protein features, mostly due to the natural bias in DTI data, indicating the requirement for new and unbiased datasets. We hope this study will aid researchers in designing robust and high-performing data-driven DTI prediction systems that have real-world translational value in drug discovery.
Protein Complex Structure Prediction Powered by Multiple Sequence Alignments of Interologs from Multiple Taxonomic Ranks and AlphaFold2 AlphaFold2 is expected to be able to predict protein complex structures as long as a multiple sequence alignment (MSA) of the interologs of the target protein-protein interaction (PPI) can be provided. However, preparing the MSA of protein-protein interologs is a non-trivial task due to the existence of paralogs. In this study, a simplified phylogeny-based approach was applied to generate the MSA of interologs, which was then used as the input to AlphaFold2 for protein complex structure prediction. Extensively benchmarked this protocol on non-redundant PPI dataset including 107 bacterial PPIs and 442 eukaryotic PPIs, we show complex structures of 79.5% of the bacterial PPIs and 49.8% of the eukaryotic PPIs can be successfully predicted. Considering PPIs may not be conserved in species with long evolutionary distances, we further restricted interologs in the MSA to different taxonomic ranks of the species of the target PPI in protein complex structure prediction. We found the success rates can be increased to 87.9% for the bacterial PPIs and 56.3% for the eukaryotic PPIs if interologs in the MSA are restricted to a specific taxonomic rank of the species of each target PPI. Finally, we show the optimal taxonomic ranks for protein complex structure prediction can be selected with the application of the recalculated predicted TM-scores of the output models.
Native proline-rich motifs exploit sequence context to target actin-remodeling Ena/VASP proteins The human proteome is replete with short linear motifs (SLiMs) of 4-6 residues that are critical for protein-protein interactions, yet the importance of the sequence surrounding such motifs is underexplored. We devised a proteomic screen to systematically examine the influence of SLiM sequence context on protein-protein interactions. Focusing on the EVH1 domain of ENAH, an actin regulator that is upregulated in invasive cancers, we screened 36-residue proteome-derived peptides for binding. We discovered a pocket on the ENAH EVH1 domain that diverged from its orthologs to recognize extended SLiMs, and we found that proteins with two EVH1-binding SLiMs can wrap around a single domain. We also found that the ciliary protein PCARE uses an extended 23-residue region to obtain higher affinity than any known ENAH EVH1-binding motif. Our screen provides a way to uncover the effects of broader proteomic context on motif-mediated interactions, revealing diverse mechanisms of contextual control over EVH1 interactions and establishing that SLiMs cant be fully understood outside of their native context. The combined treatment of Molnupiravir and Favipiravir results in a marked potentiation of antiviral efficacy in a SARS-CoV-2 hamster infection model Favipiravir and Molnupiravir, orally available antivirals, have been reported to exert antiviral activity against SARS-CoV2. In recent days preliminary efficacy data have been reported in COVID-19 patients. We here studied the combined antiviral effect of the drugs in the SARS-CoV2 hamster infection model. We first demonstrate that Molnupiravir can reduce infectious virus titers in lungs of infected animals in a dose-dependent manner by up to 3.5 log10 which is associated with a marked improvement of virus-induced lung pathology. When animals are treated with a combination of suboptimal doses of Molnupiravir and Favipiravir (that each alone result in respectively a 1.3 log10 and 1.1 log10 reduction of infectious virus titers in the lungs), a marked combined potency is observed. Infectious virus titers in the lungs of animals treated with the combo are on average reduced by 4.5 log10 and infectious virus are no longer detected in the lungs of 60% of treated infected animals. Both drugs result in an increased mutation frequency of the remaining viral RNA recovered from the lungs. In the combo-treated hamsters an increased frequency of C-to-T and G-to-A mutations in the viral RNA is observed as compared to the single treatment groups which may explain the pronounced antiviral potency of the combination. Our findings may lay the basis for the design of clinical studies to test the efficacy of the combination of Molnupiravir and Favipiravir in the treatment of COVID-19. 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. Effect of a low concentration in chloride, sodium and potassium on oocyte maturation, oocyte hydration, ovulation and egg quality in rainbow trout. Water salinity is an important environmental factor known to have detrimental effects on salmonid reproduction, mostly when migrating female broodfish are held in sea water. In contrast, data obtained in freshwater are scarce and the impact of low water salinity, and more specifically of low water concentrations in sodium, chloride and potassium, during reproduction in freshwater is currently unknown. For this reason, and because ion and water fluxes are critical for the final steps of the female gamete formation, including oocyte hydration and ovulation, the aim of the present study was to investigate the impact of low salinity water on final oocyte maturation, ovulation and, ultimately, on egg quality, using rainbow trout as a physiological model and relevant aquaculture species.

Fish from the same commercial strain were raised either in a site characterized by low concentrations of Na+, K+, and Cl- ions in the water or in a closely located control site exhibiting higher concentration in these elements. Egg quality and duration of final oocyte maturation were investigated using innovative phenotyping tools such as automatic assessment of egg viability using the VisEgg system and non-invasive echograph-based monitoring of final oocyte maturation duration, respectively. Oocyte hydration during final oocyte maturation and after ovulation was also investigated. Finally, molecular phenotyping was performed using real-time PCR-based monitoring of several key players of final oocyte maturation and ovulation associated with ion and water transport, inflammation, proteolytic activity, and coagulation. Oocyte hydration and gene expression data were analyzed in the light of the duration of final oocyte maturation.

Here we show that low water salinity (i.e., low water concentration in chloride, sodium and potassium) negatively influences final oocyte maturation, ovulation and, ultimately, egg quality. Low water salinity triggered delayed ovulation and lower oocyte viability. When investigating the impact of low water salinity on final oocyte maturation duration, individuals presenting the most severe phenotypes exhibited impaired oocyte hydration and abnormally reduced gene expression levels of several key players of the ovulatory process. While the under expression of water (i.e., aquaporins) and ion (i.e., solute carriers) transporters is consistent with impaired oocyte hydration, our observations also indicate that the overall ovulatory gene expression program is disrupted. Our results raise the question of the mechanisms underlying the negative influence of low salinity water on the dynamics of the preovulatory phase, on the control of the oocyte homeostasis, including hydration, and on the overall success of the maturation-ovulation process.

HighlightsO_LILow water salinity impairs final oocyte maturation and egg quality in rainbow trout
C_LIO_LILow water salinity induces delayed ovulation and impaired oocyte hydration
C_LIO_LILow water salinity induces a dysregulation of several key ovulatory genes
C_LIO_LIMonitoring of final oocyte maturation can be performed using ultrasound staging
C_LI 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. Exploitation of the genetic variability in the genotype of Egyptian Wheat by studding Molecular Markers, Molecular Docking and Nano Composites. Regulation of leaf and stem rust This manuscript has been withdrawn by the authors as it was submitted and made public without the full consent of all the authors. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author. Relationship between shear wave velocity and muscle activation is inconsistent across different muscle types There is an increasing use of shear wave ultrasound elastography to quantify mechanical properties of muscles under various conditions such as changes muscle length and levels of activation in healthy and pathological muscle. However, little is known about the variability in shear wave velocity among muscles as most studies investigate one specific muscle. The purpose of this study was to determine if the relationship between SWV and muscle activation is consistent across muscles with different architectures: biceps brachii, tibialis anterior, and medial gastrocnemius, All measures were made at matching levels of activation and approximately at the optimal length for each muscle to control for length-dependent changes in the relationship between activation and force or stiffness. We also conducted a control experiment to determine how the passive force within a muscle alters the relationship between muscle activation and shear wave velocity. The relationship between shear wave velocity-squared and activation above 10% MVC differed across muscles, with biceps brachii and medial gastrocnemius showing a lower slope than tibialis anterior. Shear wave velocity-squared also differed between muscles at the shortest length (p<0.001) and the increase in shear wave velocity-squared with muscle lengthening also differed between muscle types (p = 0.005) Muscle-specific differences could not be explained by the architectural features such as pennation angle, fiber length, and physiological cross-sectional area. Our results demonstrate that there is not a unique relationship between muscle activation and shear wave velocity, highlighting the importance of understanding the many factors contributing to shear wave propagation in muscle before elastography can be used to make quantitative comparisons across muscle types. Identification of two cancer stem cell-like populations in triple-negative breast cancer xenografts Gene expression analysis at the single-cell level by next generation sequencing has revealed the existence of clonal dissemination and microheterogeneity in cancer metastasis. The current spatial analysis technologies can elucidate the heterogeneity of cell-cell interactions in situ. To reveal the regional and expressional heterogeneity in primary tumors and metastases, we performed transcriptomic analysis of microtissues dissected from a triple-negative breast cancer (TNBC) cell line MDA-MB-231 xenograft model with our automated tissue microdissection punching technology. This multiple-microtissue transcriptome analysis revealed three cancer cell-type clusters in the primary tumor and axillary lymph node metastasis, two of which were cancer stem cell (CSC)-like clusters (CD44/MYC-high, HMGA1-high). Reanalysis of public single-cell RNA-seq (scRNA-seq) datasets confirmed that the two CSC-like populations existed both in TNBC xenograft models and TNBC patients. In addition, the gene signature of the HMGA1-high CSC-like cluster has the potential to serve as a novel biomarker for diagnosis. The diversity of these multiple CSC-like populations may cause differential anticancer drug resistance, increasing the difficulty of curing this cancer. Genetic basis of a spontaneous mutation's expressivity Genetic background often influences the phenotypic consequences of mutations, resulting in variable expressivity. How standing genetic variants collectively cause this phenomenon is not fully understood. Here, we comprehensively identify loci in a budding yeast cross that impact the growth of individuals carrying a spontaneous missense mutation in the nuclear-encoded mitochondrial ribosomal gene MRP20. Initial results suggested that a single large effect locus influences the mutations expressivity, with one allele causing inviability in mutants. However, further experiments revealed this simplicity was an illusion. In fact, many additional loci shape the mutations expressivity, collectively leading to a wide spectrum of mutational responses. These results exemplify how complex combinations of alleles can produce a diversity of qualitative and quantitative responses to the same mutation. Changes in Behavior and Salivary Serum Amyloid A in cows with Subclinical Mastitis The aim of this study was to identify detailed changes in behavior, and in salivary serum amyloid A (SAA), associated with subclinical mastitis. This included standard sickness behaviors (which form part of an adaptive response to conserve energy, minimize heat loss and facilitate recovery following infection and inflammation) and lesser-studied behaviors, that are biologically predicted to change at low-level infection, and therefore particularly relevant for detecting subclinical mastitis (here labelled  luxury behaviors). SAA is a physiological marker of systemic inflammation, with levels in milk and serum already known to increase during subclinical mastitis. We investigated whether the same was true for SAA in cow saliva. Data were collected for n = 34 commercial barn-housed dairy cows, tested in 17 matched-pairs. Each pair comprised a cow with subclinical mastitis (SCM) and a healthy control (CTRL), identified using somatic cell count (SCC) (SCM: SCC >200 x1000 cells/ml; CTRL: SCC <100 x1000 cells/ml). SCM cows were selected for study ad-hoc, at which point they were paired with a CTRL cow, based upon parity and calving date; consequently, the full data set was accrued over several months. Data were collected for each pair over 3 days: SCC (l4:00-l5:00h) Day 1; behavior (24h from 00:00h) Day 2; salivary serum amyloid-A (SAA) Day 3. We report, for the first time, that an increase in salivary SAA occurs during subclinical mastitis; SAA was higher in SCM cows and demonstrated a positive (weak) correlation with SCC. The behavioral comparisons revealed that SCM cows had reductions in activity (behavioral transitions and distance moved), social exploration, social reactivity (here: likelihood to move away/be displaced following receipt of agonism), performance of social grooming and head butts, and the receipt of agonistic non-contact challenges. In addition, SCM cows received more head swipes, and spent a greater proportion of time lying with their head on their flank than CTRL cows. SCM cows also displayed an altered feeding pattern; they spent a greater proportion of feeding time in direct contact with two conspecifics, and a lower proportion of feeding time at self-locking feed barriers, than CTRL cows. Behavioral measures were found to correlate, albeit loosely, with serum SAA in a direction consistent with predictions for sickness behavior. These included positive correlations with both lying duration and the receipt of all agonistic behavior, and negative correlations with feeding, drinking, the performance of all social and all agonistic behavior, and social reactivity. We conclude that changes in salivary SAA, social behavior, and activity offer potential in the detection of subclinical mastitis and recommend further investigation to substantiate and refine our findings. Identification of Antimalarial Compounds that Inhibit Apicomplexan AP2 Proteins in the Human Malaria Parasite Plasmodium falciparum Plasmodium parasites are reliant on the Apicomplexan AP2 (ApiAP2) transcription factor family to regulate gene expression programs. AP2 DNA binding domains have no homologs in the human or mosquito host genomes, making them potential antimalarial drug targets. Using an in-silico screen to dock thousands of small molecules into the crystal structure of the AP2-EXP (Pf3D7_1466400) AP2 domain (PDB:3IGM), we identified compounds that interact with this domain. Four compounds were found to compete for DNA binding with AP2-EXP and at least one additional ApiAP2 protein. Our top ApiAP2 competitor compound perturbs the transcriptome of P. falciparum trophozoites and results in a decrease in abundance of log2 fold change > 2 for 50% (46/93) of AP2-EXP target genes. Additionally, two ApiAP2 competitor compounds have multi-stage anti-Plasmodium activity against blood and mosquito stage parasites. In summary, we describe a novel set of antimalarial compounds that are targeted against the ApiAP2 family of proteins. These compounds may be used for future chemical genetic interrogation of ApiAP2 proteins or serve as starting points for a new class of antimalarial therapeutics.

Author SummaryPlasmodium parasites are the causative agent of malaria, which resulted in over 600,000 deaths in 2021. Due to resistance arising for every antimalarial therapeutic deployed to date, new drug targets and druggable pathways must be explored. To address this concern, we used a molecular docking screen to predict competitors of DNA binding by the parasite specific family of Apicomplexan AP2 (ApiAP2) transcription factor proteins for testing in vitro and in vivo. We find that ApiAP2 competing compounds have antimalarial activity consistent with the disruption of gene regulation. This work will further our understanding of both the biological role and targetability of parasite transcriptional regulation. Juvenile Gouldian Finches (Erythrura gouldiae) form sibling sub-groups during social integration The formation of social relationships in complex groups is critical in shaping patterns of social organization and behavioral development. In many birds, young individuals remain dependent on their parents for extended periods but must abruptly transition to navigating interactions in the wider group after independence. While lack of social relationships during this period is detrimental in the development of later social skills, little is known about the social relationships juveniles form after independence in many bird species. In this study we describe patterns of social interactions in juvenile Gouldian Finches (Erythrura gouldiae) during transitions from family groups into flocks of unfamiliar individuals. A group of 20 juveniles from 4 families were introduced into two flocks. After introductions juveniles showed a gradient of approach rates with most approaches directed towards siblings, followed by juvenile peers, adult females, and lastly adult males. Significant preferences for siblings resulted in the emergence of sibling subgroups within the larger social network. This active self-assortment of siblings suggests that sibling sub-groups are an important bridge linking social connections within the family and the wider group. Such findings suggests that sibling relationships have a critical role in the socialization after independence, as well as structuring the social organization of Gouldian finch flocks. SARS-CoV-2 Can Infect Human Embryos The spread of SARS-CoV-2 has led to a devastating pandemic, with infections resulting in a range of symptoms collectively known as COVID-19. The full repertoire of human tissues and organs susceptible to infection is an area of active investigation, and some studies have implicated the reproductive system. The effects of COVID-19 on human reproduction remain poorly understood, and particularly the impact on early embryogenesis and establishment of a pregnancy are not known. In this work, we explore the susceptibility of early human embryos to SARS-CoV-2 infection. We note that ACE2 and TMPRSS2, two canonical cell entry factors for SARS-CoV-2, are co-expressed in cells of the trophectoderm in blastocyst-stage preimplantation embryos. Using fluorescent reporter virions pseudotyped with Spike (S) glycoprotein from SARS-CoV-2, we observe robust infection of trophectoderm cells, and this permissiveness could be attenuated with blocking antibodies targeting S or ACE2. When exposing human blastocysts to the live, fully infectious SARS-CoV-2, we detected cases of infection that compromised embryo health. Therefore, we identify a new human target tissue for SARS-CoV-2 with potential medical implications for reproductive health during the COVID-19 pandemic and its aftermath. Patterns of and processes shaping population structure and introgression among recently differentiated Drosophila melanogaster populations Despite a century of genetic analysis, the evolutionary history underlying patterns of exceptional genetic and phenotypic variation in the model organism Drosophila melanogaster remains poorly understood. How genetic and phenotypic variation is partitioned across the range of D. melanogaster, particularly in its putative ancestral range in Subtropical Africa, remains unresolved. Here, we assess patterns of population genetic structure, admixture, mate preference, and genetic incompatibility across a global sample, including 174 new accessions from remote regions within Subtropical Africa. While almost all Out of Africa genomes correspond to a single genetic ancestry, different geographic regions within Africa contain multiple ancestries, with substantial cryptic diversity in Subtropical Africa. Admixture between distinct lineages is prevalent across the range, but admixture rates vary between lineages. Female mate choice within Subtropical Africa is highly polymorphic and behavioral types are not monophyletic. The genetic architecture of mate choice is highly polygenic, including loci associated with neurological development, behavior, olfactory perception, and learning. Finally, we discovered that many segregating putative incompatibilities likely evolved during or after expansion out of Africa. This work contributes to our understanding of the evolutionary history of a key model system, and provides insight into the distribution of polymorphic reproductive barriers. Structural basis of anti-SARS-CoV-2 activity of HCQ: specific binding to N protein to disrupt its interaction with nucleic acids and LLPS Great efforts have led to successfully developing the spike-based vaccines but challenges still exist to completely terminate the SARS-CoV-2 pandemic. SARS-CoV-2 nucleocapsid (N) protein plays the essential roles in almost all key steps of the viral life cycle, thus representing a top drug target. Almost all key functions of N protein including liquid-liquid phase separation (LLPS) depend on its capacity in interacting with nucleic acids. Therefore, only the variants with their N proteins functional in binding nucleic acids might survive and spread in evolution and indeed, the residues critical for binding nucleic acids are highly conserved. Very recently, hydroxychloroquine (HCQ) was shown to prevent the transmission in a large-scale clinical study in Singapore but so far, no specific SARS-CoV-2 protein was experimentally identified to be targeted by HCQ. Here by NMR, we unambiguously decode that HCQ specifically binds NTD and CTD of SARS-CoV-2 N protein with Kd of 112.1 and 57.1 M respectively to inhibit their interaction with nucleic acid, as well as to disrupt LLPS essential for the viral life cycle. Most importantly, HCQ-binding residues are identical in SARS-CoV-2 variants and therefore HCQ is likely effective to them all. The results not only provide a structural basis for the anti-SARS-CoV-2 activity of HCQ, but also renders HCQ to be the first known drug capable of targeting LLPS. Furthermore, the unique structure of the HCQ-CTD complex decodes a promising strategy for further design of better anti-SARS-CoV-2 drugs from HCQ. Therefore, HCQ is a promising candidate to help terminate the pandemic. Citation needed? Wikipedia and 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. A critical period of translational control during brain development at codon resolution Translation modulates the timing and amplification of gene expression after transcription. Brain development requires uniquely complex gene expression patterns, but large-scale measurements of translation directly in the prenatal brain are lacking. We measure the reactants, synthesis, and products of translation spanning mouse neocortex neurogenesis, and discover a transient window of dynamic regulation at mid-gestation. Timed translation upregulation of chromatin binding proteins like Satb2, which is essential for neuronal subtype differentiation, restricts protein expression in neuronal lineages despite broad transcriptional priming in progenitors. In contrast, translation downregulation of ribosomal proteins sharply decreases ribosome number, coinciding with a major shift in protein synthesis dynamics at mid-gestation. Changing levels of eIF4EBP1, a direct inhibitor of ribosomal protein translation, are concurrent with ribosome downregulation and controls Satb2 fate acquisition during neuronal differentiation. Thus, the refinement of transcriptional programs by translation is central to the molecular logic of brain development. Modeling of the developmental neocortex translatome is provided as an open-source searchable resource: https://shiny.mdc-berlin.de/cortexomics/. The cyclic dinucleotide 2'3'-cGAMP induces a broad anti-bacterial and anti-viral response in the sea anemone Nematostella vectensis In mammals, cyclic dinucleotides (CDNs) bind and activate STING to initiate an anti-viral type I interferon response. CDNs and STING originated in bacteria and are present in most animals. By contrast, interferons are believed to have emerged in vertebrates; thus, the function of CDN signaling in invertebrates is unclear. Here, we use a CDN, 23-cGAMP, to activate immune responses in a model cnidarian invertebrate, the starlet sea anemone Nematostella vectensis. Using RNA-Seq, we found that 23-cGAMP induces robust transcription of both anti-viral and anti-bacterial genes in N. vectensis. Many of the anti-viral genes induced by 23-cGAMP are homologs of vertebrate interferon stimulated genes, implying that the interferon response predates the evolution of interferons. Knockdown experiments identified a role for NF-{kappa}B in specifically inducing anti-bacterial genes downstream of 23-cGAMP. Some of these putative anti-bacterial genes were also found to be induced during Pseudomonas aeruginosa infection. We characterized the protein product of one of the putative anti-bacterial genes, the N. vectensis homolog of Dae4, and found that it has conserved anti-bacterial activity. This work suggests that a broad anti-bacterial and anti-viral transcriptional response is an evolutionarily ancestral output of 23-cGAMP signaling in animals.

Significance statementCyclic dinucleotides are signaling molecules that originated in bacteria and were subsequently acquired and co-opted by animals for immune signaling. The major cyclic dinucleotide signaling pathway in mammals results in the production of anti-viral molecules called interferons. Invertebrates such as sea anemones lack interferons, and thus it was unclear whether cyclic dinucleotide signaling would play a role in immunity in these animals. Here we report that in the anemone Nematostella vectensis, cyclic dinucleotides activate both anti-viral and anti-bacterial immune responses, and do so through a conserved pathway. These results provide insights into the evolutionary origins of innate immunity, and suggest a broader ancestral role for cyclic dinucleotide signaling that evolved toward more specialized anti-viral functions in mammals. Integrative Modelling of Signalling Network Dynamics Identifies Cell Type-selective Therapeutic Strategies for FGFR4-driven Cancers Oncogenic FGFR4 signalling represents a potential therapeutic target in many cancer types, including triple negative breast cancer (TNBC) and hepatocellular carcinoma (HCC). However, resistance to single-agent therapy directed at FGFR4 remains a major challenge, prompting the need to identify more effective combinatorial therapeutic strategies. Here, we integrated computational network modelling and experimental validation to characterise dynamic reprogramming of the FGFR4 signalling network in TNBC following FGFR4 kinase inhibition. We found that AKT, which signals downstream of FGFR4, displayed a rapid and potent reactivation following FGFR4 targeting. Through model-based simulation and systematic prediction of the effect of co-targeting specific network nodes, we predicted, and validated experimentally, strong synergism of co-targeting FGFR4 and particular ErbB kinases or AKT, but not the upstream kinase PI3K. Further, incorporation of protein expression data from hundreds of cancer cell types enabled us to adapt our model to other diverse cellular contexts, leading to the prediction that while AKT rebound occurs frequently, it is not a general phenomenon. Instead, ERK is reactivated in a subset of cell types, including the FGFR4-driven HCC cell line Hep3B. This was subsequently corroborated, and moreover, co-targeting FGFR4 and MEK in Hep3B cells markedly enhanced inhibition of cell proliferation. Overall, these findings provide novel insights into the dynamics of drug-induced network remodelling in cancer cells, highlight the impact of protein expression heterogeneity on network response to targeted therapy and identify candidate cell type-selective combination treatments for FGFR4-driven cancer. A phenomics approach for in vitro antiviral drug discovery BackgroundThe current COVID-19 pandemic has highlighted the need for new and fast methods to identify novel or repurposed therapeutic drugs. Here we present a method for untargeted phenotypic drug screening of virus-infected cells, combining Cell Painting with antibody-based detection of viral infection in a single assay. We designed an image analysis pipeline for segmentation and classification of virus-infected and non-infected cells, followed by extraction of morphological properties.

ResultsWe show that the methodology can successfully capture virus-induced phenotypic signatures of MRC-5 human lung fibroblasts infected with Human coronavirus 229E (CoV-229E). Moreover, we demonstrate that our method can be used in phenotypic drug screening using a panel of nine host- and virus-targeting antivirals. Treatment with effective antiviral compounds reversed the morphological profile of the host cells towards a non-infected state.

ConclusionsThe method can be used in drug discovery for morphological profiling of novel antiviral compounds on both infected and non-infected cells. Trade-offs in biosensor optimization for dynamic pathway engineering Recent progress in synthetic biology allows the construction of dynamic control circuits for metabolic engineering. This technology promises to overcome many challenges encountered in traditional pathway engineering, thanks to their ability to self-regulate gene expression in response to bioreactor perturbations. The central components in these control circuits are metabolite biosensors that read out pathway signals and actuate enzyme expression. However, the construction of metabolite biosensors is a major bottleneck for strain design, and a key challenge is to understand the relation between biosensor dose-response curves and pathway performance. Here we employ multiobjective optimization to quantify performance trade-offs that arise in the design and calibration of metabolite biosensors. Our approach reveals strategies for tuning dose-response curves along an optimal trade-off between production flux and the cost of an increased expression burden on the host. We explore properties of control architectures built in the literature, and identify their advantages and caveats in terms of performance and robustness to growth conditions and leaky promoters. We demonstrate the optimality of a control circuit for glucaric acid production in Escherichia coli, which has been shown to increase titer by 2.5-fold as compared to static designs. Our results lay the groundwork for the automated design of control circuits for pathway engineering, with applications in the food, energy and pharmaceutical sectors. What is valued in conservation? A framework to compare ethical perspectives Perspectives in conservation are based on a variety of value systems. Such differences in how people value nature and its components lead to different evaluations of the morality of conservation goals and approaches, and often underlie disagreements in the formulation and implementation of environmental management policies. Specifically, whether a conservation action (e.g. killing feral cats to reduce predation on bird species threatened with extinction) is viewed as appropriate or not can vary among people with different value systems. Here, we present a conceptual, mathematical framework intended as a tool to systematically explore and clarify core value statements in conservation approaches. Its purpose is to highlight how fundamental differences between these value systems can lead to different prioritizations of available management options and offer a common ground for discourse. The proposed equations decompose the question underlying many controversies around management decisions in conservation: what or who is valued, how, and to what extent? We compare how management decisions would likely be viewed under three different idealised value systems: ecocentric conservation, which aims to preserve biodiversity; new conservation, which considers that biodiversity can only be preserved if it benefits humans; and sentientist conservation, which aims at minimising suffering for sentient beings. We illustrate the utility of the framework by applying it to case studies involving invasive alien species, rewilding, and trophy hunting. By making value systems and their consequences in practice explicit, the framework facilitates debates on contested conservation issues, and complements philosophical discursive approaches about moral reasoning. We believe dissecting the core value statements on which conservation decisions are based will provide an additional tool to understand and address conservation conflicts. High-throughput analysis of DNA replication in single human cells reveals the complex nature of replication timing control DNA replication initiates from replication origins firing throughout S phase. Debate remains about whether origins are a fixed set of loci, or a loose agglomeration of potential sites used stochastically in individual cells, and about how consistent their firing time is. We developed an approach to profile DNA replication from whole-genome sequencing of thousands of single cells, which includes "in silico flow cytometry", a method for discriminating replicating and non-replicating cells. Using two microfluidic platforms, we analyzed up to 2,437 replicating cells from a single sample. The resolution and scale of the data allow focused analysis of replication initiation sites, demonstrating that most occur in confined genomic regions. While initiation order is remarkably similar across cells, we unexpectedly identify several subtypes of initiation regions in late-replicating regions. Taken together, high throughput, high resolution sequencing of individual cells reveals previously underappreciated variability in replication initiation and progression. Increasing triacylglycerol formation and lipid storage by unsaturated lipids protects renal proximal tubules in diabetes In diabetic patients, dyslipidemia frequently contributes to organ damage such as diabetic kidney disease (DKD). DKD is associated with excessive renal deposition of triacylglycerol (TAG) in lipid droplets (LD). Yet, it is unclear whether LDs play a protective or damaging role and how this might be influenced by dietary patterns. By using a diabetes mouse model, we find here that high fat diet enriched in the unsaturated oleic acid (OA) caused more lipid storage in LDs in renal proximal tubular cells (PTC) but less tubular damage than a corresponding butter diet with the saturated palmitic acid (PA). Mechanistically, we identify endoplasmic reticulum (ER) stress as the main cause of PA-induced PTC injury. ER stress is caused by elevated cellular levels of saturated TAG precursors and to higher membrane order in the ER. The resulting cell death is preceded by a transcriptional rewiring of phospholipid metabolism. Simultaneous addition of OA rescues the cytotoxic effects by normalizing membrane order and by increasing the total TAG amount. The latter also stimulates the formation of LDs that in turn can release unsaturated lipids upon demand by lipolysis. Our study thus clarifies mechanisms underlying PA-induced cell stress in PTCs and emphasizes the importance of olive oil for the prevention of DKD.