The snoGloBe interaction predictor reveals a broad spectrum of C/D snoRNA RNA targets Box C/D small nucleolar RNAs (snoRNAs) are a conserved class of RNA known for their role in guiding ribosomal RNA 2-O-ribose methylation. Recently, C/D snoRNAs were also implicated in regulating the expression of non-ribosomal genes through different modes of binding. Large scale RNA-RNA interaction datasets detect many snoRNAs binding messenger RNA, but are limited by specific experimental conditions. To enable a more comprehensive study of C/D snoRNA interactions, we created snoGloBe, a human C/D snoRNA interaction predictor based on a gradient boosting classifier. SnoGloBe considers the target type, position and sequence of the interactions, enabling it to outperform existing predictors. Interestingly, for specific snoRNAs, snoGloBe identifies strong enrichment of interactions near gene expression regulatory elements including splice sites. Abundance and splicing of predicted targets were altered upon the knockdown of their associated snoRNA. Strikingly, the predicted snoRNA interactions often overlap with the binding sites of functionally related RNA binding proteins, reinforcing their role in gene expression regulation. SnoGloBe is also an excellent tool for discovering viral RNA targets, as shown by its capacity to identify snoRNAs targeting the heavily methylated SARS-CoV-2 RNA. Overall, snoGloBe is capable of identifying experimentally validated binding sites and predicting novel sites with shared regulatory function.
Improving epigenetic clock performance and interpretation with deep learning Several age predictors based on DNA methylation, dubbed epigenetic clocks, have been created in recent years, with the vast majority based on regularized linear regression. This study explores the improvement in the performance and interpretation of epigenetic clocks using deep learning. First, we gathered 143 publicly available data sets from several human tissues to develop AltumAge, a neural network framework that is a highly accurate and precise age predictor. Compared to ElasticNet, AltumAge performs better for within-data set and cross-data set age prediction, being particularly more generalizable in older ages and new tissue types. We then used deep learning interpretation methods to learn which methylation sites contributed to the final model predictions. We observe that while most important CpG sites are linearly related to age, some highly-interacting CpG sites can influence the relevance of such relationships. Using chromatin annotations, we show that the CpG sites with the highest contribution to the model predictions were related to gene regulatory regions in the genome, including proximity to CTCF binding sites. We also found age-related KEGG pathways for genes containing these CpG sites. Lastly, we perform downstream analyses of AltumAge to explore its applicability and compare its age acceleration with Horvaths model. We show that our neural network approach predicts higher age acceleration for tumors and for cells that exhibit age-related changes in vitro, such as replicative senescence and mitochondrial dysfunction. Altogether, our neural network approach provides significant improvement and flexibility to current epigenetic clocks for both performance and model interpretability.
Feed efficiency of lactating Holstein cows was not as repeatable across diets as within diet over subsequent lactation stages BackgroundImproving feed efficiency has become a common target for dairy farmers to meet the requirement of producing more milk with fewer resources. To improve feed efficiency, a prerequisite is to ensure that the cows identified as most or least efficient will remain as such, independently of diet composition. Therefore, the current research analysed the ability of lactating dairy cows to maintain their feed efficiency while changing the energy density of the diet by changing its concentration in starch and fibre. A total of 60 lactating Holstein cows, including 33 primiparous cows, were first fed a high starch diet-low fibre (diet S+F-), then switched over to a low starch diet-high fibre (diet S-F+). To know if diet affect feed efficiency, we compared the ability of feed efficiency to be maintained within a diet over subsequent lactation stages, known as repeatability of feed efficiency, with its ability to be maintained across diets, known as reproducibility of feed efficiency. To do so we used two indicators: the estimation of the error of repeatability/reproducibility, which is commonly used in metrology, and the coefficient of correlation of concordance (CCC), which is used in biology. The effect of diet change could also lead to a change in cows sorting behaviour which could potentially affect feed efficiency if for example the most efficient cows select more concentrate than the least efficient. We therefore analysed the relationship between the differences in individual feed refusals composition and the differences in feed efficiency. To do so, the composition of each feed refusal was described with its near infra-red (NIR) spectroscopy and was performed on each individual feed ingredient, diet and refusals and used as composition variable. The variability of the NIR spectra of the refusals was described with its principal components thanks to a principal component analysis (PCA). The Pearson correlation was estimated to check the relationship between feed efficiency and refusals composition, i.e. sorting behaviour.

ResultsThe error of reproducibility of feed efficiency across diets was 2.95 MJ/d. This error was significantly larger than the errors of repeatability estimated within diet, which were 2.01 MJ/d within diet S-F+ and 2.40 MJ/d within diet S+F-. The CCC was 0.64 between feed efficiency estimated within diet S+F- and feed efficiency estimated within diet S-F+. This CCC was smaller than the one observed for feed efficiency estimated within diet between two subsequent lactation stages (CCC = 0.72 within diet S+F- and 0.85 within diet S-F+). Feed efficiency was poorly correlated to the first two principal components, which explained 90% of the total variability of the NIR spectra of the individual refusals. This suggests that feed sorting behaviour did not explain differences in feed efficiency.

ConclusionsFeed efficiency was significantly less reproducible across diets than repeatable within the same diet over subsequent lactation stages, but cows ranking for feed efficiency was not significantly affected by diet change. This loss in repeatability across diets could be due to a more pronounced feed sorting subsequent to the change in diet composition. However, the differences in sorting behaviour between cows were not associated to feed efficiency differences in this trial neither with the S+F- diet nor with the S-F+ diet. Those results have to be confirmed on diets having different forage to concentrate ratios to ensure that the least and most efficient cows will not change. Living with high potassium: how plants balance nutrient acquisition 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 Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: the Multi-Targeting Drug DREAM Challenge A continuing challenge in modern medicine is the identification of safer and more efficacious drugs. Precision therapeutics, which have one molecular target, have been long promised to be safer and more effective than traditional therapies. This approach has proven to be challenging for multiple reasons including lack of efficacy, rapidly acquired drug resistance, and narrow patient eligibility criteria. An alternative approach is the development of drugs that address the overall disease network by targeting multiple biological targets ( polypharmacology). Rational development of these molecules will require improved methods for predicting single chemical structures that target multiple drug targets. To address this need, we developed the Multi-Targeting Drug DREAM Challenge, in which we challenged participants to predict single chemical entities that target pro-targets but avoid anti-targets for two unrelated diseases: RET-based tumors and a common form of inherited Tauopathy. Here, we report the results of this DREAM Challenge and the development of two neural network-based machine learning approaches that were applied to the challenge of rational polypharmacology. Together, these platforms provide a potentially useful first step towards developing lead therapeutic compounds that address disease complexity through rational polypharmacology.

Author SummaryMany modern drugs are developed with the goal of modulating a single cellular pathway or target. However, many drugs are, in fact,  dirty; they target multiple cellular pathways or targets. This phenomenon is known as multi-targeting or polypharmacology. While some strive to develop  cleaner therapeutics that eliminate secondary targets, recent work has shown that multi-targeting therapeutics have key advantages for a variety of diseases. However, while multi-targeting drugs that affect a precisely-defined profile of targets may be more effective, it is difficult to computationally predict which molecules have desirable target profiles. Here, we report the results of a competitive crowdsourcing project (the Multi-Targeting Drug DREAM Challenge), where we challenged participants to predict chemicals that have desired target profiles for cancer and neurodegenerative disease. Tracing back variations in archaeal cell division to protein domain architectures The Endosomal Sorting Complex Required for Transport (ESCRT) system is a multi-protein machinery that is involved in cell division of both Eukaryotes and Archaea. This spread across super-phyla suggests that a precursor ESCRT machinery existed already at an evolutionary early stage of life, making it a promising candidate for the (re)construction of a minimal cell division machinery. There are, however, only few experimental data about ESCRT machineries in Archaea, due to high technical challenges in cultivation and microscopy. Here, we analyse the proteins of archaeal ESCRT machineries bioinformatically on a domain level, to enable mechanistical comparison without such challenging experiments. First, we infer that there are at least three different cell division mechanisms utilizing ESCRT proteins in archaea, probably similar in their constriction mechanisms but different in membrane tethering. Second, we show that ESCRT proteins in Asgard archaea are highly similar to eukaryotic ESCRT proteins, strengthening the recently developed idea that all Eukaryotes descended from archaea. Third, we reconstruct a plausible evolutionary development of ESCRT machineries and suggest that a simple ESCRT-based constriction machinery existed in the last archaeal common ancestor. These findings not only give very interesting insights into the evolution of cell division in Archaea and Eukaryotes, but also reveal new research avenues by suggesting hypothesis-driven experiments for both, cell biology and bottom-up synthetic biology. GCN5L1 promotes diastolic dysfunction by inhibiting cardiac pyruvate oxidation Left ventricular diastolic dysfunction is a structural and functional condition that precedes the development of heart failure with preserved ejection fraction (HFpEF). The etiology of diastolic dysfunction includes alterations in fuel substrate metabolism that negatively impact cardiac bioenergetics, and may precipitate the eventual transition to heart failure. To date, the molecular mechanisms that regulate early changes in fuel metabolism leading to diastolic dysfunction remain unclear. In this report, we use a diet-induced obesity model and quantitative acetylproteomics in aged mice to show that inhibitory lysine acetylation of the pyruvate dehydrogenase (PDH) complex promotes energetic deficits and diastolic dysfunction in mouse hearts. Cardiomyocyte-specific deletion of the mitochondrial lysine acetylation regulatory protein GCN5L1 prevented hyperacetylation of the PDH complex subunit PDHA1, allowing aged obese mice to continue using pyruvate as a bioenergetic substrate in the heart. Our findings suggest that changes in mitochondrial protein lysine acetylation represent a key metabolic component of diastolic dysfunction that precedes the development of heart failure. A chromosome-level genome assembly of a maize elite breeding line Dan340 The maize cultivar Dan340 is an excellent backbone inbred line of Luda Red Cob Group with several desirable characters, such as disease resistance, lodging resistance, high combining ability, wide adaptability and so on. In this study, we constructed a high-quality chromosome-level reference genome for Dan340 by combining PacBio long HiFi sequencing, Illumina short reads and chromosomal conformational capture (Hi-C) sequencing reads. The final assembly of Dan340 genome was 2,348.72 Mb, including 2,738 contigs and 2,315 scaffolds with a N50 of 41.49 Mb and 215.35 Mb, respectively. The percent of high quality Illumina reads mapped to the reference genome was up to 97.48%. The assembly of this genome will not only facilitate our understanding about intraspecific genome diversity in maize, but also provides a novel resource for maize breeding.

Key findingsO_LIThe final assembly of Dan340 genome was 2,348.72 Mb, including 2,738 contigs and 2,315 scaffolds with a N50 of 41.49 Mb and 215.35 Mb, respectively.
C_LIO_LIThe percent of reads mapped to the reference genome was up to 97.48%.
C_LIO_LIThe results showed that 96.84% of the plant single-copy orthologues were complete. Complete single-copy and multi copy genes accounted for 87.36% and 9.48% of the genes, respectively. Taken together, these results indicated that our Dan340 genome assembly presented high quality and coverage.
C_LI 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. Immediate and sustained effects of cobalt and zinc-containing pigments on macrophages Pigments are among the oldest nanoparticulate products known to mankind, and their use in tattoos is also very old. Nowadays, 25% American people aged 18 to 50 are tattooed, which poses the question of the delayed effects of tattoos. In this article, we investigated three cobalt (Pigment Violet 14 (purple color)) or cobalt alloy pigments (Pigment Blue 28 (blue color), Pigment Green 14 (green color)), and one zinc pigment (Pigment White 4 (white color)) which constitute a wide range of colors found in tattoos. These pigments contain microparticles and a significant proportion of nanoparticles (in either aggregate or free form). Because of the key role of macrophages in the scavenging of particulate materials, we tested the effects of cobalt- and zinc-based pigments on the J774A.1 macrophage cell line. In order to detect delayed effects, we compared two exposure schemes: acute exposure for 24 hours and an exposure for 24 hours followed by a 3-day post-exposure recovery period. The conjunction of these two schemes allowed for the investigation of the delayed or sustained effects of pigments. All pigments induced functional effects on macrophages, most of which were pigment-dependent. For example, Pigment Green 19, Pigment Blue 28, and Pigment White 4 showed a delayed alteration of the phagocytic capacity of cells. Moreover, all the pigments tested induced a slight but significant increase in TNF secretion. This effect, however, was transitory. Conversely, only Pigment Blue 28 induced a short and sustained increase in interleukin 6. Results showed that in response to bacterial stimuli (LPS), the secretion of tumor necrosis factor and interleukin 6 declined after recovery exposure with pigments. The pigments also induced persisting changes in some important macrophage membrane markers such as CD11b, an integrin contributing to cell adhesion and immunological tolerance. In conclusion, the pigments induced functional dis-orders in macrophages, which, in some cases, persist long after exposure, even at non-toxic doses. Affordable Caenorhabditis elegans tracking system for classroom use For decades the nematode C. elegans has served as an outstanding research organism owing to its unsurpassed experimental amenability. This advantage has also made this tiny worm an attractive vehicle for science instruction across higher learning institutions. However, the prohibitive cost associated with the automated behavioral assessment of these animals remains an obstacle preventing their full adoption in undergraduate and high school settings. To improve this situation, we developed an inexpensive worm tracking system for use by high school interns and undergraduate students. Over the past two years this tracker has been successfully used by undergraduate students in our introductory Cell and Molecular lab (BSC220) at Illinois State University. Here we describe and demonstrate the use of our inexpensive worm tracking system. Flexible reprogramming of Pristionchus pacificus motivation for attacking Caenorhabditis elegans in predator-prey competition Animals with diverse diets must adapt their food priorities to a wide variety of environmental conditions. This diet optimization problem is especially complex for predators that compete with prey for food. Although predator-prey competition is widespread and ecologically critical, it remains difficult to disentangle predatory and competitive motivations for attacking competing prey. Here, we dissect the foraging decisions of the omnivorous nematode Pristionchus pacificus to reveal that its seemingly failed predatory attempts against Caenorhabditis elegans are actually motivated acts of efficacious territorial aggression. While P. pacificus easily kills and eats larval C. elegans with a single bite, adult C. elegans typically survives and escapes from bites. However, nonfatal biting can provide competitive benefits by reducing access of adult C. elegans and its progeny to bacterial food that P. pacificus also eats. We show that P. pacificus considers costs and benefits of both predatory and territorial outcomes to decide which food goal, prey or bacteria, should guide its motivation for biting. These predatory and territorial motivations impose different sets of rules for adjusting willingness to bite in response to changes in bacterial abundance. In addition to biting, predatory and territorial motivations also influence which search tactic P. pacificus uses to increase encounters with C. elegans. When treated with an octopamine receptor antagonist, P. pacificus switches from territorial to predatory motivation for both biting and search. Overall, we demonstrate that P. pacificus assesses alternate outcomes of attacking C. elegans and flexibly reprograms its foraging strategy to prioritize either prey or bacterial food. 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. Links between memory, synapses, amyloid-beta, tau and microglial changes after tau pathology induction by Alzheimer's brain inoculation in amyloid-beta-plaque bearing mice BackgroundAlzheimers disease (AD) is characterized by the presence of both extracellular amyloid-{beta} (A{beta}) plaques and intracellular tau accumulations. The causative interactions between these lesions, and the subsequent neuroinflammation, synaptic alterations and memory impairment are still debated. Intracerebral infusion of human AD brain extracts in A{beta} bearing mice that do not overexpress pathological tau proteins induces widespread A{beta} and tau pathologies following heterotopic seeding of mouse tau. These models provide a unique opportunity to assess relationships between AD lesions and downstream events.

MethodsHuman AD and control-brain extracts (ADbe and Ctrlbe) were infused in the hippocampus of A{beta} plaque-bearing APPswe/PS1dE9 mice. We evaluated the links between A{beta} plaques, tau aggregates, microgliosis, astrogliosis at the inoculation site and in connected regions (perirhinal/entorhinal cortex), and memory impairment and synaptic density 4 and 8 months post-inoculation.

ResultsADbe-inoculated animals displayed memory deficit and synaptic loss in addition to A{beta} and tau pathological aggregates. A{beta} plaques were detected in both ADbe- and Ctrlbe-inoculated APPswe/PS1dE9 mice, but their load was increased close to the inoculation site in ADbe- inoculated animals. Tau-positive neuropil threads and neurofibrillary tangles occurred next to the inoculation site only in ADbe-inoculated animals and were not detected in Ctrlbe mice. These lesions spread to connected regions notably the perirhinal/entorhinal cortex. Tau-positive neuritic plaques were detected in both ADbe- and Ctrlbe-inoculated animals. Unexpectedly, ADbe inoculation did not increase the number of neuritic plaques close to the inoculation site as compared to Ctrlbe inoculation. ADbe inoculation however increased the area of tau-positive elements within these neuritic plaques. Increased tau pathology as well as lower Iba1-positive microglial load in the hippocampus and perirhinal/entorhinal cortex were correlated with memory impairment and with synaptic loss.

ConclusionsThe integrative analysis of pathological events associated with ADbe inoculation in A{beta}-bearing mice highlighted memory and synaptic loss as well as the induction of tau lesions that spread in the brain. Increased tau lesions and lower microglial load are the two main events correlated with memory impairment and synaptic loss. The study suggests that microglial activity may be protective.

Graphical abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=174 SRC="FIGDIR/small/438654v3_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@10e62dorg.highwire.dtl.DTLVardef@177b11corg.highwire.dtl.DTLVardef@10cd534org.highwire.dtl.DTLVardef@18178a5_HPS_FORMAT_FIGEXP  M_FIG C_FIG EGFR-driven profibrotic signals in AKI-to-CKD transition are blocked by TNF inhibition: Opportunities for etanercept treatment Proximal-tubule-cell EGFR activation mediates tubule cell proliferation and repair early after kidney injury, while sustained EGFR activation causes kidney fibrosis. Inflammation is a key driver of AKI-to-CKD transition and fibrosis, but mechanisms of EGFR-driven profibrotic responses are not well understood. In a mouse model of AKI-to-CKD transition and CKD progression, we show that EGFR-inhibition significantly reduced kidney expression of many immunoregulatory molecules already by day two after injury, including the potent inflammatory cytokine tumor-necrosis-factor (TNF). Single nuclei RNA-sequencing analysis showed that macrophages were among the main early cellular sources of TNF in the injured kidney. In vitro, EGFR activation in macrophages increased macrophage TNF expression, while EGFR inhibition in vivo reduced kidney macrophage accumulation, as early as two days after injury. Thus, profibrotic EGFR signaling increases kidney TNF levels both directly and indirectly. TNF inhibition did not alter tubule EGFR activation and in contrast to EGFR inhibition did not reduce early macrophage accumulation in the kidney, suggesting that TNF does not promote early infiltration of immune cells in the kidney, but rather regulates profibrotic functions of kidney and/or immune cells. TNF inhibition with etanercept in vivo in AKI-injured mice downregulated a number of cytokines, including TNF itself. This cytokine downregulation overlapped with EGFR inhibition, and additional non-overlapping downregulated cytokines shared the same functions, predicting that TNF inhibition would prevent AKI-to-CKD transition like EGFR inhibition. Indeed, TNF-inhibition with etanercept reduced AKI-induced fibrosis to the same degree as the EGFR-inhibition, while the combination of both treatments showed no additive effect. In conclusion, our results identify TNF as a downstream effector of profibrotic EGFR activation and motivate the examination of TNF pathway inhibition in human AKI or CKD.

Translational statementProximal tubule epidermal-growth-factor (EGFR) activation in mice and likely also in humans drives inflammation in the kidney after acute-kidney-injury (AKI) and causes chronic-kidney-disease (CKD) with fibrosis in a process termed AKI-to-CKD transition. Recent retrospective data shows that patients treated with TNF inhibitors show decreased incidence and progression of CKD. Our current work shows that TNF inhibition in mice is equally as effective as EGFR inhibition in preventing AKI-to-CKD transition and fibrosis. Thus, our results have translational potential and may stimulate examination of short-term TNF inhibition in AKI to prevent AKI-to-CKD transition or possibly of longer-term TNF inhibition in CKD to prevent CKD progression. Co-option of immune effectors by the hormonal signalling system triggering metamorphosis in Drosophila melanogaster Insect metamorphosis is regulated by the production, secretion and degradation of two peripheral hormones: 20-hydroxyecdysone (ecdysone) and juvenile hormone (JH). In addition to their roles in developmental regulation, increasing evidence suggests that these hormones are involved in innate immunity processes, such as phagocytosis and the induction of antimicrobial peptide (AMP) production. AMP regulation includes systemic responses as well as local responses at surface epithelia that contact with the external environment. At pupariation, Drosophila melanogaster increases dramatically the expression of three AMP genes, drosomycin (drs), drosomycin-like 2 (drsl2) and drosomycin-like 5 (drsl5). We show that the systemic action of drs at pupariation is dependent on ecdysone signalling in the fat body and operates via the ecdysone downstream target, Broad-Z4. In parallel, ecdysone also regulates local responses, specifically through the activation of drsl2 expression in the gut. Finally, we confirm the relevance of this ecdysone dependent AMP expression for the control of bacterial persistence by showing that flies lacking drs expression in the fat body have higher bacterial persistence over metamorphosis. Together, our data emphasize the importance of the association between ecdysone signalling and immunity using in vivo studies and establish a new role for ecdysone at pupariation, which impacts developmental success by regulating the immune system in a stage-dependent manner. We speculate that this co-option of immune effectors by the hormonal system may constitute a pre-emptive mechanism to control bacterial numbers in the pupa at the core of metamorphosis evolution. Nonideal polar residues in the core of the coiled coil of FtsLB are critical for modulating its stability and activation in cell division The FtsLB complex is a key regulator of bacterial cell division, existing in either an off or on state which supports the activation of septal peptidoglycan synthesis. In Escherichia coli, residues known to be critical for this activation are located in a region near the C-terminal end of the periplasmic coiled-coil domain of FtsLB, raising questions about the precise role of this conserved domain in the activation mechanism. Here, we investigate an unusual cluster of polar amino acids found within the core of the FtsLB coiled coil. We hypothesized that these amino acids likely reduce the structural stability of the domain and thus may be important for governing conformational changes. We found that mutating these positions to hydrophobic residues increased the thermal stability of FtsLB but caused cell division defects, suggesting that the coiled-coil domain is a "detuned" structural element. In addition, we identified suppressor mutations within the polar cluster, indicating that the precise identity of the polar amino acids is important for fine-tuning the structural balance between the off and on states. We propose a revised structural model of the tetrameric FtsLB (named the "Y-model") in which the periplasmic domain splits into a pair of coiled-coil branches. In this configuration, the hydrophilic terminal moieties of the polar amino acids remain more favorably exposed to water than in the original four-helix bundle model ("I-model"). We propose that a shift in this architecture, dependent on its marginal stability, is involved in activating the FtsLB complex and triggering septal cell wall reconstruction. Cryptic pathogen-sugar interactions revealed by universal saturation transfer analysis Many host pathogen interactions such as human viruses (including non-SARS-coronaviruses) rely on attachment to host cell-surface glycans. There are conflicting reports about whether the Spike protein of SARS-CoV-2 binds to sialic acid commonly found on host cell-surface N-linked glycans. In the absence of a biochemical assay, the ability to analyze the binding of glycans to heavily- modified proteins and resolve this issue is limited. Classical Saturation Transfer Difference (STD) NMR can be confounded by overlapping sugar resonances that compound with known experimental constraints. Here we present  universal saturation transfer analysis (uSTA), an NMR method that builds on existing approaches to provide a general and automated workflow for studying protein-ligand interactions. uSTA reveals that B-origin-lineage-SARS-CoV-2 spike trimer binds sialoside sugars in an  end on manner and modelling guided by uSTA localises binding to the spike N-terminal domain (NTD). The sialylated-polylactosamine motif is found on tetraantennary human N-linked-glycoproteins in deeper lung and may have played a role in zoonosis. Provocatively, sialic acid binding is abolished by mutations in some subsequent SARS- CoV-2 variants-of-concern. A very high resolution cryo-EM structure confirms the NTD location and  end on mode; it rationalises the effect of NTD mutations and the structure-activity relationship of sialic acid analogues. uSTA is demonstrated to be a robust, rapid and quantitative tool for analysis of binding, even in the most demanding systems.

Extended AbstractThe surface proteins found on both pathogens and host cells mediate entry (and exit) and influence disease progression and transmission. Both types can bear host-generated post- translational modifications such as glycosylation that are essential for function but can confound biophysical methods used for dissecting key interactions. Several human viruses (including non- SARS-coronaviruses) attach to host cell-surface N-linked glycans that include forms of sialic acid (sialosides). There remains, however, conflicting evidence as to if or how SARS-associated coronaviruses might use such a mechanism. Here, we demonstrate quantitative extension of  saturation transfer protein NMR methods to a complete mathematical model of the magnetization transfer caused by interactions between protein and ligand. The method couples objective resonance-identification via a deconvolution algorithm with Bloch-McConnell analysis to enable a structural, kinetic and thermodynamic analysis of ligand binding beyond previously-perceived limits of exchange rates, concentration or system. Using an automated and openly available workflow this  universal saturation transfer analysis (uSTA) can be readily-applied in a range of even heavily-modified systems in a general manner to now obtain quantitative binding interaction parameters (KD, kEx). uSTA proved critical in mapping direct interactions between natural sialoside sugar ligands and relevant virus-surface attachment glycoproteins - SARS-CoV-2-spike and influenza-H1N1-haemagglutinin variants - by quantitating ligand signal in spectral regions otherwise occluded by resonances from mobile protein glycans (that also include sialosides). In B- origin-lineage-SARS-CoV-2 spike trimer  end on-binding to sialoside sugars was revealed contrasting with  extended surface-binding for heparin sugar ligands; uSTA-derived constraints used in structural modelling suggested sialoside-glycan binding sites in a beta-sheet-rich region of spike N-terminal domain (NTD). Consistent with this, uSTA-glycan binding was minimally- perturbed by antibodies that neutralize the ACE2-binding domain (RBD) but strongly disrupted in spike from the B1.1.7/alpha and B1.351/beta variants-of-concern, which possess hotspot mutations in the NTD. Sialoside binding in B-origin-lineage-NTD was unequivocally pinpointed by cryo-EM to a site that is created from residues that are notably deleted in variants (e.g. H69,V70,Y145 in alpha). An analysis of beneficial genetic variances in cohorts of patients from early 2020 suggests a model in which this site in the NTD of B-origin-lineage-SARS-CoV-2 (but not in alpha/beta-variants) may have exploited a specific sialylated-polylactosamine motif found on tetraantennary human N-linked-glycoproteins in deeper lung. Together these confirm a novel binding mode mediated by the unusual NTD of SARS-CoV-2 and suggest how it may drive virulence and/or zoonosis via modulation of glycan attachment. Since cell-surface glycans are widely relevant to biology and pathology, uSTA can now provide ready, quantitative, widespread analysis of complex, host-derived and post-translationally modified proteins with putative ligands relevant to disease even in previously confounding complex systems. The elevational ascent and spread of exotic annual grass dominance in the Great Basin, USA AimIn the western US, sagebrush (Artemisia spp.) and salt desert shrublands are rapidly transitioning to communities dominated by exotic annual grasses, a novel and often self-reinforcing state that threatens the economic sustainability and conservation value of rangelands. Climate change is predicted to directly and indirectly favor annual grasses, potentially pushing transitions to annual grass dominance into higher elevations and north-facing aspects. We sought to quantify the expansion of annual grass-dominated vegetation communities along topographic gradients over the past several decades.

LocationOur analysis focused on rangelands among three ecoregions in the Great Basin of the western US, where several species of exotic annual grasses are widespread among shrub and perennial grass-dominated vegetation communities.

MethodsWe used recently developed remote sensing-based rangeland vegetation data to produce yearly maps of annual grass-dominated vegetation communities spanning the period 1990-2020. With these maps, we quantified the rate of spread and characterized changes in the topographic distribution (i.e., elevation and aspect) of areas transitioning to annual grass dominance.

ResultsWe documented more than an eight-fold increase in annual grass-dominated area (to >77,000 km2) occurring at an average rate of >2,300 km2 yr-1. In 2020, annual grasses dominated one fifth (19.8%) of Great Basin rangelands. This rapid expansion is associated with a broadening of the topographic niche, with widespread movement into higher elevations and north-facing aspects.

Main conclusionsAccelerated, strategic intervention is critically needed to conserve the fragile band of rangelands being compressed between annual grassland transitions at lower elevations and woodland expansion at higher elevations. Predictability of drug sensitivity in multi-species environments Microbes associate in nature forming complex communities, but they are often studied in purified form. Here I show that differences in antibiotic sensitivity between co-existing bacterial species can modify the diffusion of antibiotic molecules, and alter the drug efficacy measured in conventional in vitro assays. I developed a model, validated experimentally using an artificial two-species community, showing antibiotic molecules re-distribute evenly across all species if they have similar drug sensitivity. The result is lower drug efficacy with respect to conventional in vitro assays. However, when species have different sensitivities, the re-distribution of antibiotic is uneven and most sensitive species accumulate more drug. The result is increased drug efficacy against these species. Despite this discrepancy with conventional laboratory assays, my data suggests the changes in drug efficacy are predictable and provides insight into how communities can affect the diffusion of other molecules in the environment. Diverse classes of constraints enable broader applicability of a linear programming-based dynamic metabolic modeling framework Current metabolic modeling tools suffer from a variety of limitations, from scalability to simplifying assumptions, that preclude their use in many applications. We recently created a modeling framework, LK-DFBA, that addresses a key gap: capturing metabolite dynamics and regulation while retaining a potentially scalable linear programming structure. Key to this frameworks success are the linear kinetics and regulatory constraints imposed on the system. However, while the linearity of these constraints reduces computational complexity, it may not accurately capture the behavior of many biochemical systems. Here, we developed three new classes of LK-DFBA constraints to better model interactions between metabolites and the reactions they regulate. We tested these new approaches on several synthetic and biological systems, and also performed the first-ever comparison of LK-DFBA predictions to experimental data. We found that no single constraint approach was optimal across all systems examined, and systems with the same topological structure but different parameters were often best modeled by different types of constraints. However, we did find that the optimal constraint approach was generally robust to local perturbations of the system, indicating that just a single wild-type dataset could allow identification of the ideal constraint for a given system. These results suggest that the availability of multiple constraint approaches will allow LK-DFBA to model a wider range of metabolic systems. Re-convolving the compositional landscape of primary and recurrent glioblastoma reveals prognostic andtargetable tissue states Glioblastoma is an aggressive diffusely infiltrating neoplasm that spreads beyond surgical resection margins, where it intermingles with non-neoplastic brain cells. This complex microenvironment harbouring infiltrating glioma and non-neoplastic brain cells is the origin of tumor recurrence. Thus, understanding the cellular and molecular features of the glioma microenvironment is therapeutically and prognostically important. Here, we used single-nucleus RNA sequencing (snRNAseq) of primary and recurrent glioma to define three compositional  tissue-states rooted in cohabitation of cell-types and transcriptional states. These comprise a state featuring A) abundant normal brain microenvironment cells, B) reactive/inflamed brain microenvironment, and C) cellular/proliferative tumor. All these states exhibited variable degrees of infiltration by glioma cells. Spatial transcriptomics confirmed that the cell-types and transcriptomics states which compositionally cohabitate tissue states also colocalize in space. Tissue states are clinically significant because they correlate with radiographic, histopathologic, and prognostic features. We found that enrichment of tissue state B signature correlated with shorter survival. Importantly, we found that our compositionally defined tissue states are enriched in distinct metabolic pathways. One such pathway is fatty acid biosynthesis, which was enriched in tissue state B - a state enriched in recurrent glioblastoma and composed of astrocyte-like/mesenchymal glioma cells, reactive astrocytes resembling those seen in neurodegeneration, and monocyte-like myeloid cells. We showed that treating acute slices of GBM with a fatty acid synthesis inhibitor is sufficient to deplete the transcriptional signature of tissue state B. Our findings define a novel compositional approach to the glioma-infiltrated tissue which allows us to discover prognostic and targetable features, paving the way to new mechanistic and therapeutic discoveries. Warmer temperatures result in maladaptive learning of sexual preferences O_LIEmpirical studies predicting the effects of the climate crisis on biodiversity loss that take into account learning ability and sexual selection are currently lacking.
C_LIO_LIUsing the African butterfly Bicyclus anynana, which shows strong phenotypic plasticity (i.e., polyphenism) in response to temperature, we find that learning produces a maladaptive mate preference under climate warming.
C_LIO_LIWe first modelled climate warming scenarios and then showed experimentally that as temperature becomes an unreliable cue to the onset of the dry season, adult butterflies displayed the wet season rather than the dry season form.
C_LIO_LIFemale learning further suppressed their innate, adaptive sexual preference for dry season males. Instead, females learned to prefer a phenotype transiently present during the seasonal transition.
C_LIO_LIFemale fertility and longevity were also indirectly affected by learning, likely reducing female fitness following climate warming.
C_LIO_LIOur results emphasize the importance of sexual selection, learning, and their fitness consequences for understanding (mal)adaptation of natural populations to climate warming.
C_LI CHRM1 is a Druggable Melanoma Target Whose Endogenous Activity is Determined by Inherited Genetic Variation in DOPA Production Melanoma risk is 30 times higher in people with lightly pigmented skin compared to those with darkly pigmented skin. Here we show that this difference results from more than melanin pigment and its ultraviolet radiation (UVR) shielding effect. Using primary human melanocytes representing the full human skin pigment continuum and several preclinical melanoma models, we show that cell-intrinsic differences between dark and light melanocytes regulate melanocyte proliferative capacity, overall cellular differentiation state, and susceptibility to malignant transformation, independently of melanin and UV exposure. We determined that these differences result from dihydroxyphenylalanine (DOPA), a melanin precursor synthesized at higher levels in melanocytes from dark skin. Although DOPA was not previously known to have specific signaling activity, we used both high throughput pharmacologic and genetic in vivo CRISPR screens to determine that DOPA limits melanocyte and melanoma cell proliferation by directly inhibiting the muscarinic acetylcholine receptor M1 (CHRM1), a G Protein-Coupled Receptor (GPCR) not previously known to bind DOPA, nor to affect melanoma pathobiology. Pharmacologic CHRM1 antagonism in melanoma leads to depletion of c-Myc and FOXM1, both of which are proliferation drivers associated with aggressive melanoma. In preclinical mouse melanoma models using both immune deficient and syngeneic immune competent mice, pharmacologic inhibition of CHRM1 or FOXM1 inhibited tumor growth. CHRM1 and FOXM1 may be new therapeutic targets for melanoma. 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. Dosage sensitivity in Pumilio1-associated diseases involves two distinct mechanisms Mutations in the RNA-binding protein (RBP) Pumilio1 (PUM1) can cause dramatically different phenotypes. Mild mutations that reduce PUM1 levels by 25% lead to a mild, adult-onset ataxia, whereas more severe mutations that reduce PUM1 levels 40-60% produce an infantile syndrome involving multiple developmental delays and seizures. Why this difference in expression should cause such different phenotypes has been unclear; known PUM1 targets are de-repressed to equal degrees in both diseases. We therefore sought to identify PUM1s protein partners in the murine brain. We identified a number of putative interactors involved in different aspects of RNA metabolism such as silencing, alternative splicing, and polyadenylation. We find that PUM1 haploinsufficiency alters the stability of several interactors and disrupts the regulation of targets of those interactors, whereas mild PUM1 loss only de-represses PUM1-specific targets. We validated these phenomena in patient-derived cell lines and show that normalizing PUM1 levels rescues the levels of interactors and their targets. We therefore propose that dosage sensitivity does not necessarily reflect a linear change in levels but can involve distinct mechanisms. Studying the interactors of RBPs in vivo will be necessary to understand their functions in neurological diseases.