Miracle-dz/UniFAR-FTUs huggingface dataset:
The Late Miocene‐Early Pliocene Biogenic Bloom in the Eastern Equatorial Pacific: New Insights From Integrated Ocean Drilling Program Site U1335

The late Miocene‐early Pliocene “biogenic bloom” (BB) manifests as greatly enhanced biogenic sedimentation in sites along the Equator that has been linked to cooler sea surface temperature (SST) in the eastern equatorial Pacific (EEP). However, the full extent and geometry of the BB in the EEP is less known. To improve on this, we have generated new carbonate content (CaCO3%) and bulk carbonate stable isotope (δ13C and δ18O) records spanning the last 7 Ma at IODP Site U1335, located ca. 5° north of the Equator and to the west of the EEP. Site U1335 δ13C and δ18O records display high‐frequency variations coupled to changes in sediment composition and physical properties comparable to patterns seen at on‐Equator sites further east. During the late Miocene and the early Pliocene bulk δ18O is higher at Site U1335 compared to two off‐Equator sites further east, suggesting cooler SSTs generated by stronger equatorial upwelling reaching northwest of the modern core‐equatorial upwelling belt. Enhanced upwelling at Site U1335 is supported by relatively higher sedimentation rates prior to 4.6 Ma, symptomatic of higher biological production during the BB. These observations suggest that during the BB the equatorial upwelling circulation was more focused and less parallel to the Equator compared to present day.
The Venturia inaequalis effector repertoire is expressed in waves and is dominated by expanded families with predicted structural similarity to avirulence proteins from other plant-pathogenic fungi

Background Scab, caused by the biotrophic fungus Venturia inaequalis, is the most economically important disease of apples worldwide. During infection, V. inaequalis occupies the subcuticular environment, where it secretes virulence factors, termed effectors, to promote host colonization. Consistent with other plant-pathogenic fungi, many of these effectors are expected to be non-enzymatic proteins, some of which can be recognized by corresponding host resistance proteins to activate plant defences, thus acting as avirulence determinants. To develop durable control strategies against scab, a better understanding of the roles that these effector proteins play in promoting subcuticular growth by V. inaequalis, as well as in activating, suppressing or circumventing resistance protein-mediated defences in apple, is required. Results We generated the first comprehensive RNA-seq transcriptome of V. inaequalis during colonization of apple. Analysis of this transcriptome revealed five temporal waves of gene expression that peaked during early, mid or mid-late infection. While the number of genes encoding secreted, non-enzymatic proteinaceous effector candidates (ECs) varied in each wave, most belonged to waves that peaked in expression during mid-late infection. Spectral clustering based on sequence similarity determined that the majority of ECs belonged to expanded protein families. To gain insights into function, the tertiary structures of ECs were predicted using AlphaFold2. Strikingly, despite an absence of sequence similarity, many ECs were predicted to have structural similarity to avirulence proteins from other plant-pathogenic fungi, including members of the MAX, LARS, ToxA and FOLD effector families. In addition, several other ECs, including an EC family with sequence similarity to the AvrLm6 avirulence effector from Leptosphaeria maculans, were predicted to adopt a KP6-like fold. Thus, proteins with a KP6-like fold represent another structural family of effectors shared among plant-pathogenic fungi. Conclusions Our study reveals the transcriptomic profile underpinning subcuticular growth by V. inaequalis and provides an enriched list of ECs that can be investigated for roles in virulence and avirulence. Furthermore, our study supports the idea that numerous sequence-unrelated effectors across plant-pathogenic fungi share common structural folds. In doing so, our study gives weight to the hypothesis that many fungal effectors evolved from ancestral genes through duplication, followed by sequence diversification, to produce sequence-unrelated but structurally similar proteins.
Strain design optimization using reinforcement learning

Engineered microbial cells present a sustainable alternative to fossil-based synthesis of chemicals and fuels. Cellular synthesis routes are readily assembled and introduced into microbial strains using state-of-the-art synthetic biology tools. However, the optimization of the strains required to reach industrially feasible production levels is far less efficient. It typically relies on trial-and-error leading into high uncertainty in total duration and cost. New techniques that can cope with the complexity and limited mechanistic knowledge of the cellular regulation are called for guiding the strain optimization. In this paper, we put forward a multi-agent reinforcement learning (MARL) approach that learns from experiments to tune the metabolic enzyme levels so that the production is improved. Our method is model-free and does not assume prior knowledge of the microbe’s metabolic network or its regulation. The multi-agent approach is well-suited to make use of parallel experiments such as multi-well plates commonly used for screening microbial strains. We demonstrate the method’s capabilities using the genome-scale kinetic model of Escherichia coli, k-ecoli457, as a surrogate for an in vivo cell behaviour in cultivation experiments. We investigate the method’s performance relevant for practical applicability in strain engineering i.e. the speed of convergence towards the optimum response, noise tolerance, and the statistical stability of the solutions found. We further evaluate the proposed MARL approach in improving L-tryptophan production by yeast Saccharomyces cerevisiae, using publicly available experimental data on the performance of a combinatorial strain library. Overall, our results show that multi-agent reinforcement learning is a promising approach for guiding the strain optimization beyond mechanistic knowledge, with the goal of faster and more reliably obtaining industrially attractive production levels. Author summary Engineered microbial cells offer a sustainable alternative solution to chemical production from fossil resources. However, to make the chemical production using microbial cells economically feasible, they need to be substantially optimized. Due to the biological complexity, this optimization to reach sufficiently high production is typically a costly trial and error process. This paper presents an Artificial Intelligence (AI) approach to guide this task. Our tool learns a model from previous experiments and uses the model to suggest improvements to the engineering design, until a satisfactory production performance is reached. This paper evaluates the behaviour of the proposed AI method from several angles, including the amount of experiments needed, the tolerance to noise as well as the stability of the proposed designs.
Comparative analysis of right ventricular metabolic reprogramming in pre-clinical rat models of severe pulmonary hypertension-induced right ventricular failure

Background Pulmonary hypertension (PH) leads to right ventricular (RV) hypertrophy and failure (RVF). The precise mechanisms of the metabolic basis of maladaptive PH-induced RVF (PH-RVF) are yet to be fully elucidated. Here we performed a comparative analysis of RV-metabolic reprogramming in MCT and Su/Hx rat models of severe PH-RVF using targeted metabolomics and multi-omics. Methods Male Sprague Dawley rats (250-300gm; n=15) were used. Rats received subcutaneous monocrotaline (60mg/kg; MCT; n=5) and followed for ∼30-days or Sugen (20mg/kg; Su/Hx; n=5) followed by hypoxia (10%O2; 3-weeks) and normoxia (2-weeks). Controls received saline (Control; n=5). Serial echocardiography was performed to assess cardiopulmonary hemodynamics. Terminal RV-catheterization was performed to assess PH. Targeted metabolomics was performed on RV tissue using UPLC-MS. RV multi-omics analysis was performed integrating metabolomic and transcriptomic datasets using Joint Pathway Analysis (JPA). Results MCT and Su/Hx rats developed severe PH, RV-hypertrophy and decompensated RVF. Targeted metabolomics of RV of MCT and Su/Hx rats detected 126 and 125 metabolites respectively. There were 28 and 24 metabolites significantly altered in RV of MCT and Su/Hx rats, respectively, including 11 common metabolites. Common significantly upregulated metabolites included aspartate and GSH, whereas downregulated metabolites included phosphate, α-ketoglutarate, inositol, glutamine, 5-Oxoproline, hexose phosphate, creatine, pantothenic acid and acetylcarnitine. JPA highlighted common genes and metabolites from key pathways such as glycolysis, fatty acid metabolism, oxidative phosphorylation, TCA cycle etc. Conclusions Comparative analysis of metabolic reprogramming of RV from MCT and Su/Hx rats reveals common and distinct metabolic signatures which may serve as RV-specific novel therapeutic targets for PH-RVF.
Screening of Relevant Metabolism-Disrupting Chemicals on Pancreatic β-Cells: Evaluation of Murine and Human In Vitro Models

Endocrine-disrupting chemicals (EDCs) are chemical substances that can interfere with the normal function of the endocrine system. EDCs are ubiquitous and can be found in a variety of consumer products such as food packaging materials, personal care and household products, plastic additives, and flame retardants. Over the last decade, the impact of EDCs on human health has been widely acknowledged as they have been associated with different endocrine diseases. Among them, a subset called metabolism-disrupting chemicals (MDCs) are able to promote metabolic changes that can lead to the development of metabolic disorders such as diabetes, obesity, hepatic steatosis, and metabolic syndrome, among others. Despite this, today, there are still no definitive and standardized in vitro tools to support the metabolic risk assessment of existing and emerging MDCs for regulatory purposes. Here, we evaluated two different pancreatic cell-based in vitro systems, the murine pancreatic β-cell line MIN6 as well as the human pancreatic β-cell line EndoC- βH1. Both were challenged with a range of relevant concentrations of seven well-known EDCs (bisphenol-A (BPA), bisphenol-S (BPS), bisphenol-F (BPF), perfluorooctanesulfonic acid (PFOS), di(2-ethylhexyl) phthalate (DEHP), cadmium chloride (CdCl2) and dichlorodiphenyldichloroethylene (DDE)). The screening revealed that most of the tested chemicals have detectable deleterious effects on glucose-stimulated insulin release, insulin content, electrical activity, gene expression, and/or viability. Our data provide new molecular information on the direct effects of the selected chemicals on key aspects of pancreatic β-cell function such as the stimulus-secretion coupling and ion channel activity. In addition, we found that, in general, the sensitivity and responses were comparable to those from other in vivo studies reported in the literature. Overall, our results suggest that both systems can serve as effective tools for rapid screening of potential MDC effects on pancreatic β-cell physiology as well for deciphering and better understanding the molecular mechanisms that underlie their action.
The GR2D2 Estimator for the Precision Matrices

Biological networks are important for the analysis of human diseases, which summarize the regulatory interactions and other relationships between different molecules. Understanding and constructing networks for molecules, such as DNA, RNA and proteins, can help elucidate the mechanisms of complex biological systems. The Gaussian Graphical Models (GGMs) are popular tools for the estimation of biological networks. Nonetheless, reconstructing GGMs from high-dimensional datasets is still challenging. Current methods cannot handle the sparsity and high-dimensionality issues arising from datasets very well. Here we developed a new GGM, called the GR2D2 (Graphical R2-induced Dirichlet Decomposition) model, based on the R2D2 priors for linear models. Besides, we provided a data-augmented block Gibbs sampler algorithm. The R code is available at https://github.com/RavenGan/GR2D2. The GR2D2 estimator shows superior performance in estimating the precision matrices compared to existing techniques in various simulation settings. When the true precision matrix is sparse and of high dimension, the GR2D2 provides the estimates with smallest information divergence from the underlying truth. We also compare the GR2D2 estimator to the graphical horseshoe estimator in five cancer RNA-seq gene expression datasets grouped by three cancer types. Our results show that GR2D2 successfully identifies common cancer pathways and cancer-specific pathways for each dataset.
Full-Length Transcriptome Maps of Reef-Building Coral Illuminate the Molecular Basis of Calcification, Symbiosis, and Circadian Genes

Background Reef-building corals are critical species for sustaining coral reefs and are highly threatened by global climate change. However, relevant transcriptomic data largely rely on short-read sequencing, which severely limits the understanding of coral molecular mechanisms and leaves many important biological questions unresolved. Results We sequenced the full-length transcriptomes of four common and frequently dominant reef-building corals, including two Robusta clade species, Pocillopora damicornis and Pocillopora verrucosa, and two Complexa clade species, Acropora muricata and Montipora foliosa, using the PacBio Sequel II platform. We obtained information on gene functions, structures and expression profiles. Among them, a comparative analysis of biomineralization-related genes provided insights into the molecular basis of coral skeletal density. The gene expression profiles of the symbiote Symbiodiniaceae were also isolated and annotated from the holobiont sequence data; these profiles showed more highly convergent traits related to gene structure and expression level than those of coral hosts. Interestingly, we observed that intracellular algal cells share some evolutionary convergence between intracellular symbiosis in corals and intracellular digestion in amphioxus. Finally, a phylogenetic analysis of key circadian clock genes among 27 evolutionarily representative species indicated that there are four key members in early metazoans, including cry genes; Clock or Npas2; cyc or Arntl; and tim, while per, as the fifth member, occurs in Bilateria. Conclusions Our work overcomes the incompleteness of short-read sequencing and illuminates the molecular basis of calcification, symbiosis, and circadian genes, thus providing a foundation for further work on the manipulation of skeleton production or symbiosis to promote the survival of these important organisms.
Comparative analysis of genome-wide protein-DNA interactions across domains of life reveals unique binding patterns for hypersaline archaeal histones

DNA-binding proteins with roles in chromatin architecture and transcriptional regulation are present in all three domains of life. Histones package DNA and regulate gene expression in eukaryotes, and find their evolutionary origin in the domain of life Archaea. Previously characterised archaeal histones have a somewhat conserved functional role in nucleosome formation and DNA packaging. However, previous research has indicated that the histone-like proteins of high salt-adapted archaea, or halophiles, appear to function differently. The sole histone protein encoded by the model halophilic species Halobacterium salinarum is non-essential, is involved in direct and indirect transcriptional regulation, and does not appear to package DNA. Here we use protein-DNA binding assays, computational analysis, and quantitative phenotyping to compare DNA binding patterns across halophilic histone proteins, bacterial and archaeal TFs, NAPs, and eukaryotic histones. Like TFs, halophilic histones bind the genome too sparsely to compact the genome. However, unlike TFs, binding occurs in both coding and intergenic regions. Unlike histones, halophilic histone occupancy is not depleted at the start sites of genes, and halophilic genomes lack the dinucleotide periodicity known to facilitate histone binding. We detect unique sequence preferences for histone binding in halophiles. Together these data suggest that the non-essentiality and genome-wide binding features of halophilic histone-like proteins are conserved across halophiles; they bind DNA in ways resembling both TFs and chromatin proteins, but do not appear to play a role in forming chromatin. IMPORTANCE Most cells in eukaryotic species – from yeast to humans– possess histone proteins that pack and unpack DNA in response to environmental cues. These essential proteins regulate the genes necessary for important cellular processes, including development and stress protection. The domain of life Archaea represent the evolutionary progenitors of eukaryotes. The universal conservation of the primary sequences of histone proteins across archaeal lineages suggests that eukaryotic histones originated in the Archaea. However, archaeal histones lack N-terminal tails and, in some species, package DNA in a continuous helix with no linker DNA between nucleosomes. We recently discovered that histones in hypersaline adapted archaeal species do not package DNA, and can act like transcription factors (TFs) to regulate stress response gene expression. Here we compare hypersaline histone function to a variety of DNA binding proteins across the tree of life, revealing a mosaic of functions for hypersaline-adapted histones.
Examination of Genome-Wide Ortholog Variation in Clinical and Environmental Isolates of the Fungal Pathogen Aspergillus fumigatus

Aspergillus fumigatus is a cosmopolitan species of fungus responsible for thousands of cases of invasive disease annually. Clinical and environmental isolates of A. fumigatus exhibit extensive phenotypic differences, including differences related to virulence and antifungal drug resistance. ABSTRACT Aspergillus fumigatus is both an environmental saprobe and an opportunistic human fungal pathogen. Knowledge of genomic variation across A. fumigatus isolates is essential for understanding the evolution of pathogenicity, virulence, and resistance to antifungal drugs. Here, we investigated 206 A. fumigatus isolates (133 clinical and 73 environmental isolates), aiming to identify genes with variable presence across isolates and test whether this variation was related to the clinical or environmental origin of isolates. The PanOrtho genome of A. fumigatus consists of 13,085 ortholog groups, of which 7,773 (59.4%) are shared by all isolates (core groups) and 5,312 (40.6%) vary in their gene presence across isolates (accessory groups plus singletons). Despite differences in the distribution of orthologs across all isolates, no significant differences were observed among clinical versus environmental isolates when phylogeny was accounted for. Orthologs that differ in their distribution across isolates tend to occur at low frequency and/or be restricted to specific isolates; thus, the degree of genomic conservation between orthologs of A. fumigatus is high. These results suggest that differences in the distribution of orthologs within A. fumigatus cannot be associated with the clinical or environmental origin of isolates. IMPORTANCE Aspergillus fumigatus is a cosmopolitan species of fungus responsible for thousands of cases of invasive disease annually. Clinical and environmental isolates of A. fumigatus exhibit extensive phenotypic differences, including differences related to virulence and antifungal drug resistance. A comprehensive survey of the genomic diversity present in A. fumigatus and its relationship to the clinical or environmental origin of isolates can contribute to the prediction of the mechanisms of evolution and infection of the species. Our results suggest that there is no significant variation in ortholog distribution between clinical and environmental isolates when accounting for evolutionary history. The work supports the hypothesis that environmental and clinical isolates of A. fumigatus do not differ in their gene contents.
Mendelian randomization for causal inference accounting for pleiotropy and sample structure using genome-wide summary statistics

Mendelian Randomization (MR) is a valuable tool for inferring causal relationships among a wide range of traits using summary statistics from genome-wide association studies (GWASs). Existing summary-level MR methods often rely on strong assumptions, resulting in many false positive findings. To relax MR assumptions, ongoing research has been primarily focused on accounting for confounding due to pleiotropy. Here we show that sample structure is another major confounding factor, including population stratification, cryptic relatedness, and sample overlap. We propose a unified MR approach, MR-APSS, which (i) accounts for pleiotropy and sample structure simultaneously by leveraging genome-wide information; and (ii) allows to include more genetic variants with moderate effects as instrument variables (IVs) to improve statistical power without inflating type I errors. We first evaluated MR-APSS using comprehensive simulations and negative controls, and then applied MR-APSS to study the causal relationships among a collection of diverse complex traits. The results suggest that MR-APSS can better identify plausible causal relationships with high reliability. In particular, MR-APSS can perform well for highly polygenic traits, where the IV strengths tend to be relatively weak and existing summary-level MR methods for causal inference are vulnerable to confounding effects.
Introduction of the Rapid Deployment Aortic Valve System Use in Elderly Patients With Endocarditis

Introduction The rapid-deployment valve system (RDVS) was introduced to facility minimally invasive aortic valve replacement. In this study we evaluate the potential benefits of RDVS in elderly high-risk patients with endocarditis of the aortic valve. Materials and Methods Since the introduction of RDVS in our institution in December 2017 through October 2021, EDWARDS INTUITY rapid-deployment prosthesis (Model 8300A, Edwards Lifesciences, Irvine, CA, USA) has been implanted in a total of 115 patients for different indications by a single surgeon. Out of one-hundred and fifteen cases of RDVS implantation, seven patients with a median age of 77 yrs. (range 62–84yrs.), suffered from active infective endocarditis of the aortic valve. The median EuroSCORE II of these highly selected patient cohort was 77% (range 19–80%). Patient data were evaluated perioperatively including intra-operative data as well as in-hospital morbidity/mortality and follow-up after discharge from hospital. Results Three patients underwent previous cardiac surgery. Concomitant procedures were performed in six patients including, ascending aorta replacement (n = 3), mitral valve repair (n = 1), pulmonary valve replacement (n = 1), bypass surgery (n = 1), left atrial appendix resection (n = 1) and anterior mitral valve repair (n = 1). Median aortic cross-clamp and cardiopulmonary bypass time was 56 min (range 29–122 min) and 81 min (range 45–162 min.), respectively. Post-operative complications in these elderly high-risk patients were atrial fibrillation (n = 3) and re-exploration for pericardial effusion (n = 1). One pacemaker implantation was required on postoperative day 6 due to sick sinus syndrome. There was one in-hospital death (14%) and one during follow-up (14%). Conclusion Rapid-deployment aortic valve system seems to be a viable option with acceptable morbidity and mortality in elderly high-risk patients with active infective endocarditis of the aortic valve.