Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermal stress induces positive phenotypic and molecular feedback loops in zebrafish embryos

Aquatic organisms must cope with both rising and rapidly changing temperatures. These environmental changes can affect numerous traits, from molecular to ecological scales. Biotic stressors can induce the release of chemical cues which trigger behavioural responses in other individuals. In this study, we infer whether abiotic stressors, such as fluctuating temperature, may similarly propagate stress responses between individuals in fish not directly exposed to the stressor. To test this hypothesis, zebrafish (Danio rerio) embryos were exposed for 24 hours to fluctuating thermal stress, to medium in which another embryo was thermally stressed before (“stress medium”), and to a combination of these. Growth, behaviour, and expression of a panel of genes were used to characterise the thermal stress response and its propagation between embryos. Both high temperatures and stress medium significantly accelerated development and altered embryonic behaviour. Thermal stress significantly decreased the expression of the antioxidant gene SOD1, eight hours after the end of exposure. Of note, we found that the expression of sulfide:quinone oxidoreductase (SQOR), likewise a part of the antioxidant metabolism relevant in vertebrate stress response, and of interleukin-1β (IL-1β), involved in the immune response, were significantly altered by stress medium. This study illustrates the existence of positive thermal stress feedback loops in zebrafish embryos that induce stress in conspecifics. This evidence that thermal stress due to fluctuating, high temperatures can be propagated may be relevant for species found in high densities, either in aquaculture or in the natural environment, in a context of global change.
The TIR-NBS-LRR protein CSA1 is required for autoimmune cell death in Arabidopsis pattern recognition co-receptor bak1 and bir3 mutants

The BRI1-associated kinase BAK1/SERK3 is a positive regulator of multiple leucine rich receptor kinase-mediated signaling pathways including pattern triggered immunity (PTI). Absence or overexpression of BAK1 leads to spontaneous cell death formation. BAK1-interacting receptors (BIR) constitutively interact with BAK1, and plants lacking or overexpressing BIR proteins phenocopy the cell death symptoms observed in bak1 knock outs or overexpressors. In the interactome of BIR3, the TIR-NBS-LRR protein CONSTITUTIVE SHADE-AVOIDANCE 1 (CSA1) was identified by mass spectrometry. CSA1 physically interacts with BIR proteins and can be detected in complexes with BAK1. Direct interaction was shown only for CSA1 with BIR proteins but not BAK1. Double mutant bak1 bir3 genotypes develop strong dwarfism and cell death symptoms that are dependent on EDS1 and salicylic acid. Loss of CSA1 blocks bak1 and bak1 bir3-mediated cell death formation thus demonstrating that CSA1 is causal for this type of cell death. We propose that CSA1 guards BIR proteins and initiates autoimmune cell death that is observed when BAK1 BIR complexes are impaired. Our findings reveal how cell death in the absence of BAK1 and BIR3 is executed and links BAK1, a common co-receptor of many pattern recognition receptors, to NLR proteins typically implicated in effector-triggered immunity.
Reinforcement Learning Based Approach for Ligand Pose Prediction

Identification of the potential binding site and the correct ligand pose are two crucial steps among the various steps in protein ligand interaction for a novel or known target. Currently most of the deep learning methods work on protein ligand pocket datasets for various predictions. In this study, we propose a reinforcement learning (RL) based method for predicting the optimized ligand pose where the RL agent also identifies the binding site based on its training. In order to apply various reinforcement learning techniques, we suggest a novel approach to represent the protein ligand complex using graph CNN which would help utilize both atomic and spatial features. To the best of our knowledge, this is the first time an RL based approach has been put forward for predicting optimized ligand pose.
Fungal communities from geothermal soils in Yellowstone National Park

5 Department of Zoology, University of British Columbia, Vancouver, BC 6 2 Department of Microbiology and Immunology, Montana State University, Bozeman, MT 7 3 Department of Microbiology, Cornell University, Ithaca, NY 8 4 Department of Tropical Plant and Soil Sciences, University of Hawaii, Honolulu, HI 9 5 Department of Integrative Biology, University of Colorado Denver, Denver, CO 10 *Corresponding author: bazzicalupo@zoology.ubc. ca 11
Macrophage and dendritic cell subset composition can distinguish endotypes in adjuvant-induced asthma mouse models

Asthma is a heterogeneous disease with neutrophilic and eosinophilic asthma as the main endotypes that are distinguished according to the cells recruited to the airways and the related pathology. Eosinophilic asthma is the treatment-responsive endotype, which is mainly associated with allergic asthma. Neutrophilic asthma is a treatment-resistant endotype, affecting 5-10% of asthmatics. Although eosinophilic asthma is well-studied, a clear understanding of the endotypes is essential to devise effective diagnosis and treatment approaches for neutrophilic asthma. To this end, we directly compared adjuvant-induced mouse models of neutrophilic (CFA/OVA) and eosinophilic (Alum/OVA) asthma side-by-side. The immune response in the inflamed lung was analyzed by multi-parametric flow cytometry and immunofluorescence. We found that eosinophilic asthma was characterized by a preferential recruitment of interstitial macrophages and myeloid dendritic cells, whereas in neutrophilic asthma plasmacytoid dendritic cells, exudate macrophages, and GL7+ activated B cells predominated. This differential distribution of macrophage and dendritic cell subsets reveals important aspects of the pathophysiology of asthma and holds the promise to be used as biomarkers to diagnose asthma endotypes.
Pre-Diabetes Increases Tuberculosis Disease Severity, While High Body Fat Without Impaired Glucose Tolerance Is Protective

Type 2 diabetes (T2D) is a well-known risk factor for tuberculosis (TB), but little is known about pre-diabetes and the relative contribution of impaired glucose tolerance vs. obesity towards susceptibility to TB. Here, we developed a preclinical model of pre-diabetes and TB. Mice fed a high fat diet (HFD) for 12 weeks presented with impaired glucose tolerance and hyperinsulinemia compared to mice fed normal chow diet (NCD). Infection with M. tuberculosis (Mtb) H37Rv after the onset of dysglycemia was associated with significantly increased lung pathology, lower concentrations of TNF-a, IFN-g, IFN-β and IL-10 and a trend towards higher bacterial burden at 3 weeks post infection. To determine whether the increased susceptibility of pre-diabetic mice to TB is reversible and is associated with dysglycemia or increased body fat mass, we performed a diet reversal experiment. Pre-diabetic mice were fed a NCD for 10 additional weeks (HFD/NCD) at which point glucose tolerance was restored, but body fat mass remained higher compared to control mice that consumed NCD throughout the entire experiment (NCD/NCD). Upon Mtb infection HFD/NCD mice had significantly lower bacterial burden compared to NCD/NCD mice and this was accompanied by restored IFN-γ responses. Our findings demonstrate that pre-diabetes increases susceptibility to TB, but a high body mass index without dysglycemia is protective. This murine model offers the opportunity to further study the underlying immunological, metabolic and endocrine mechanisms of this association.
Head model personalization: A framework for morphing lifespan brain images and brains with substantial anatomical changes

Finite element (FE) head models have emerged as a powerful tool in many fields within neuroscience, especially for studying the biomechanics of traumatic brain injury (TBI). Personalized head models are needed to account for geometric variations among subjects for more reliable predictions. However, the generation of subject-specific head models with conforming hexahedral elements suitable for studying the biomechanics of TBIs remains a significant challenge, which has been a bottleneck hindering personalized simulations. This study presents a framework capable of generating lifespan brain models and pathological brains with substantial anatomical changes, morphed from a previously developed baseline model. The framework combines hierarchical multiple feature and multimodality imaging registrations with mesh grouping, which is shown to be efficient with a heterogeneous dataset of seven brains, including a newborn, 1-year-old (1Y), 2Y, 6Y, adult, 92Y, and a hydrocephalus brain. The personalized models of the seven subjects show competitive registration accuracy, demonstrating the potential of the framework for generating personalized models for almost any brains with substantial anatomical changes. The family of head injury models generated in this study opens vast opportunities for studying age-dependent and groupwise brain injury mechanisms. The framework is equally applicable for personalizing head models in other fields, e.g., in tDCS, TMS, TUS, as an efficient approach for generating subject-specific head models than from scratch.
Chemical–genetic interaction mapping links carbon metabolism and cell wall structure to tuberculosis drug efficacy

Current chemotherapy against Mycobacterium tuberculosis (Mtb), an important human pathogen, requires a multidrug regimen lasting several months. While efforts have been made to optimize therapy by exploiting drug-drug synergies, testing new drug combinations in relevant host environments remains arduous. In particular, host environments profoundly affect the bacterial metabolic state and drug efficacy, limiting the accuracy of predictions based on in vitro assays alone. In this study, we utilize conditional Mtb knockdown mutants of essential genes as an experimentally-tractable surrogate for drug treatment, and probe the relationship between Mtb carbon metabolism and chemical-genetic interactions (CGI). We examined the anti-tubercular drugs isoniazid, rifampicin and moxifloxacin, and found that CGI are differentially responsive to the metabolic state, defining both environment-independent and –dependent interactions. Specifically, growth on the in vivo-relevant carbon source, cholesterol, reduced rifampicin efficacy by altering mycobacterial cell surface lipid composition. We report that a variety of perturbations in cell wall synthesis pathways restore rifampicin efficacy during growth on cholesterol, and that both environment-independent and cholesterol-dependent in vitro CGI could be leveraged to enhance bacterial clearance in the mouse infection model. Our findings present an atlas of novel chemical-genetic-environmental interactions that can be used to optimize drug-drug interactions as well as provide a framework for understanding in vitro correlates of in vivo efficacy. Significance Efforts to improve tuberculosis therapy include optimizing multi-drug regimens to take advantage of drug-drug synergies. However, the complex host environment has a profound effect on bacterial metabolic state and drug activity, making predictions of optimal drug combinations difficult. In this study, we leverage a newly developed library of conditional knockdown Mycobacterium tuberculosis mutants in which genetic depletion of essential genes mimics the effect of drug therapy. This tractable system allowed us to assess the effect of growth condition on predicted drug-drug interactions. We found that these interactions can be differentially sensitive to the metabolic state and select in vitro-defined interactions can be leveraged to accelerate bacterial killing during infection. These findings suggest new strategies for optimizing tuberculosis therapy.
Comprehensive proteomic quantification of bladder stone progression in a cystinuric mouse model using data-independent acquisitions

Cystinuria is one of various disorders that cause biomineralization in the urinary system, including bladder stone formation in humans. It is most prevalent in children and adolescents and more aggressive in males. There is no cure, and only limited disease management techniques help to solubilize the stones. Recurrence, even after treatment, occurs frequently. Other than a buildup of cystine, little is known about factors involved in the formation, expansion, and recurrence of these stones. This study sought to define the growth of bladder stones, guided by micro-computed tomography imaging, and to profile dynamic stone proteome changes in a cystinuria mouse model. After bladder stones developed in vivo, they were harvested and separated into four developmental stages (sand, small, medium and large stone), based on their size. Data-dependent and data-independent acquisitions allowed deep profiling of stone proteomics. The proteomic signatures and pathways illustrated major changes as the stones grew. Stones initiate from a small nidus, grow outward, and show major enrichment in ribosomal proteins and factors related to coagulation and platelet degranulation, suggesting a major dysregulation in specific pathways that can be targeted for new therapeutic options.
The Shu complex prevents mutagenesis and cytotoxicity of single-strand specific alkylation lesions

Three-methyl cytosine (3meC) are toxic DNA lesions, blocking base pairing. Bacteria and humans, express members of the AlkB enzymes family, which directly remove 3meC. However, other organisms, including budding yeast, lack this class of enzymes. It remains an unanswered evolutionary question as to how yeast repairs 3meC, particularly in single-stranded DNA. The yeast Shu complex, a conserved homologous recombination factor, aids in preventing replication-associated mutagenesis from DNA base damaging agents such as methyl methanesulfonate (MMS). We found that MMS-treated Shu complex-deficient cells, exhibit a genome-wide increase in A:T and G:C substitutions mutations. The G:C substitutions displayed transcriptional and replicational asymmetries consistent with mutations resulting from 3meC. Ectopic expression of a human AlkB homolog in Shu-deficient yeast rescues MMS-induced growth defects and increased mutagenesis. Finally, the Shu complex exhibits increased affinity for 3meC-containing DNA. Thus, our work identifies a novel mechanism for coping with alkylation adducts.
Legacy effect of constant and diurnally oscillating temperatures on soil respiration and microbial community structure

Laboratory incubation studies evaluating the temperature sensitivity of soil respiration often use measurements of respiration taken at a constant incubation temperature from soil that has been pre-incubated at the same constant temperature. However, such constant temperature incubations do not represent the field situation where soils undergo diurnal temperature oscillations. We investigated the effects of constant and diurnally oscillating temperatures on soil respiration and soil microbial community composition. A grassland soil from the UK was either incubated at a constant temperature of 5 °C, 10 °C, or 15 °C, or diurnally oscillated between 5 °C and 15 °C. Soil CO2 flux was measured by temporarily moving incubated soils from each of the abovementioned treatments to 5 °C, 10 °C or 15 °C, such that soils incubated at each temperature had CO2 flux measured at every temperature. We hypothesised that, irrespective of measurement temperature, CO2 emitted from the 5 °C to 15 °C oscillating incubation would be most similar to the soil incubated at 10 °C. The results showed that both incubation and measurement temperatures influence soil respiration. Incubating soil at a temperature oscillating between 5 °C and 15 °C resulted in significantly greater CO2 flux than constant incubations at 10 °C or 5 °C, but was not significantly different to the 15 °C incubation. The greater CO2 flux from soils incubated at 15 °C, or oscillating between 5 °C and 15 °C, coincided with a depletion of dissolved organic carbon and a shift in the phospholipid fatty acid profile of the soil microbial community, consistent with the thermal adaptation of microbial communities to higher temperatures. However, diurnal temperature oscillation did not significantly alter Q10. Our results suggest that daily maximum temperatures are more important than daily minimum or daily average temperatures when considering the response of soil respiration to warming.
HNF4A is required to specify glucocorticoid action in the liver

The glucocorticoid receptor (GR) is a nuclear hormone receptor critical to the regulation of energy metabolism and the inflammatory response. The actions of GR are highly dependent on cell type and environmental context. Here, we demonstrate the necessity for liver lineage-determining factor hepatocyte nuclear factor 4A (HNF4A) in defining liver-specificity of GR action. In normal mouse liver, the HNF4 motif lies adjacent to the glucocorticoid response element (GRE) at GR binding sites found within regions of open chromatin. In the absence of HNF4A, the liver GR cistrome is remodelled, with both loss and gain of GR recruitment evident. Lost sites are characterised by HNF4 motifs and weak GRE motifs. Gained sites are characterised by strong GRE motifs, and typically show GR recruitment in non-liver tissues. The functional importance of these HNF4A-regulated GR sites is further demonstrated by evidence of an altered transcriptional response to glucocorticoid treatment in the Hnf4a-null liver.
CRISPR Knock-in Designer: automatic oligonucleotide design software to introduce point mutations using CRISPR/Cas9

Knock-in of precise point mutations into protein-coding genes has been one of the earliest and most important applications of Clustered Regularly Interspaced Palindromic Repeats (CRISPR)/Cas9. The ability to perform such precise gene editing is crucial to interrogate the function of specific protein residues and to create models of human diseases caused by protein amino acid changes. The homologous protein residues can be mutated in model animal species, and the consequences of these mutations can be studied, leading to a better understanding of the disease in question. Design of point mutation knock-in strategies has been a combination of manual steps assisted by several computational tools resulting in a time-consuming process and preventing a single rapid and integrated solution. We have therefore designed CRISPR Knock-in Designer, which can perform rapid and automatic design of point mutation knock-in DNA oligonucleotides upon provision of the mutation, a guide RNA, and essential identifier or sequence information. The tool supports most experimentally established CRISPR types and has multiple options for the resulting oligonucleotides to satisfy the needs of most users. We also provide allele-specific PCR-based and restriction enzyme-based genotyping strategies as part of the program output. CRISPR Knock-in Designer adjusts to the genomic context of any target codon and tries to design knock-in strategies when a codon straddles two exons, a situation we explored in whole genomes of several model species. CRISPR Knock-in Designer output can also be adapted for use with some of the newer Prime Editing design tools to facilitate the introduction of a specific mutation sequence using this advanced technology.
Effect of diet modification in intestinal Escherichia coli population and antimicrobial resistance

The fluctuations in the number of some intestinal bacterial lineages may be associated with increased antimicrobial resistance and disease. Adaptation to a given environment may select bacterial mutants that have reduced ability to adapt to new environments and changes in diet have been associated with alterations in microbiome taxon composition. We wanted to see the effect of diet change in linage composition and antimicrobial resistance profiles of numerically dominant E. coli. We subjected 50 chickens from an industrial operation (under corn-based diet supplemented with antimicrobials) to 2 antimicrobial-free diets; one based on corn and the other based on alfalfa. Fecal samples were obtained from all animals at arrival and after five weeks under different diets. Five E. coli colonies (from each sample) were subjected to genetic typing and antimicrobial susceptibility testing. We observed high diversity and high turnover rate of numerically dominant E. coli strains from animals from both diet groups. We did not find differences in antimicrobial resistance profiles in isolates from different diet groups. Our results suggest that there is high diversity and high turnover rate of E. coli strains in the intestines regardless of the diet. Chicken intestines seemed to contain many E. coli lineages able to thrive in different substrates. The absence of differences in antimicrobial resistance among bacteria, from animals in different diets, may indicate that the carriage of antimicrobial resistance genes does not affect the bacterial ability to adapt to different substrates.
Uncovering the modified immunopeptidome reveals insights into principles of PTM-driven antigenicity

Antigen processing and presentation are critical for modulating tumor-host interactions. While post-translational modifications (PTMs) can alter the binding and recognition of antigens, their identification remains challenging. Here we uncover the role PTMs may play in antigen presentation and recognition in human cancers by profiling 29 different PTM combinations in immunopeptidomics data from multiple clinical samples and cell lines. We established and validated an antigen discovery pipeline and showed that newly identified modified antigens from a murine cancer model are cancer-specific and can elicit T cell killing. Systematic analysis of PTMs across multiple cohorts defined new haplotype preferences and binding motifs in association with specific PTM types. By expanding the antigenic landscape with modifications, we uncover disease-specific targets, including thousands of novel cancer-specific antigens and reveal insight into PTM-driven antigenicity. Collectively, our findings highlight an immunomodulatory role for modified peptides presented on HLA I, which may have broad implications for T-cell mediated therapies in cancer and beyond. Significance Major efforts are underway to identify cancer-specific antigens for personalized immunotherapy. Here, we enrich the immunopeptidome landscape by uncovering thousands of novel putative antigens that are post-translationally modified. We define unique preferences for PTM-driven alterations affecting HLA binding and TCR recognition, which in turn alter tumor-immune interactions. Conflict of interest statement Authors declare no conflicts of interest.