Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of a human gut microbe on Vibrio cholerae host colonization through biofilm enhancement

Recent studies indicate that the human intestinal microbiota could impact the outcome of infection by Vibrio cholerae, the etiological agent of the diarrheal disease cholera. A commensal bacterium, Paracoccus aminovorans, was previously identified in high abundance in stool collected from individuals infected with V. cholerae when compared to stool from uninfected persons. However, if and how P. aminovorans interacts with V. cholerae has not been experimentally determined; moreover, whether any association between this bacterium alters the behaviors of V. cholerae to affect the disease outcome is unclear. Here we show that P. aminovorans and V. cholerae together form dual-species biofilm structures at the air-liquid interface, with previously uncharacterized novel features. Importantly, the presence of P. aminovorans within the murine small intestine enhances V. cholerae colonization in the same niche that is dependent on the Vibrio exopolysaccharide (VPS) and other major components of mature V. cholerae biofilm. These studies illustrate that dual-species biofilm formation is a plausible mechanism used by a gut microbe to increase the virulence of the pathogen, and this interaction may alter outcomes in enteric infections. Significance Statement While ample evidence suggests that the outcome of some enteric infections can be affected by the intestinal microbiota, how specific gut microbes change the behaviors of a pathogen is unclear. Here we characterize the interaction between Vibrio cholerae and Paracoccus aminovorans, a gut microbe known to increase in abundance in the intestines during active V. cholerae infection in humans. These two bacteria form a dual-species biofilm structure at the air-liquid interface, and the gut microbe increases the host colonization efficiency of V. cholerae. Importantly, our study identifies a previously unknown mechanism of gut microbe-pathogen interaction that has the potential to alter the disease outcome.
An artificial self-assembling nanocompartment for organising metabolic pathways in yeast

Metabolic pathways are commonly organised by sequestration into discrete cellular compartments. Compartments prevent unfavourable interactions with other pathways and provide local environments conducive to the activity of encapsulated enzymes. Such compartments are also useful synthetic biology tools for examining enzyme/pathway behaviour and for metabolic engineering. Here, we expand the intracellular compartmentalisation toolbox for budding yeast (Saccharomyces cerevisiae) with engineered Murine polyomavirus virus-like particles (MPyV VLPs). The MPyV system has two components: VP1 which self-assembles into the compartment shell; and a short anchor, VP2C, which mediates cargo protein encapsulation via binding to the inner surface of the VP1 shell. Destabilised GFP fused to VP2C was specifically sorted into VLPs and thereby protected from host-mediated degradation. In order to access metabolites of native and engineered yeast metabolism, VLP-based nanocompartments were directed to assemble in the cytosol by removal of the VP1 nuclear localisation signal. To demonstrate their ability to function as a metabolic compartment, MPyV VLPs were used to encapsulate myo-inositol oxygenase (MIOX), an unstable and rate-limiting enzyme in D-glucaric acid biosynthesis. Strains with encapsulated MIOX produced ~20% more D-glucaric acid compared to controls expressing ‘free’ MIOX - despite accumulating dramatically less expressed protein - and also grew to higher cell densities. These effects were linked to enzyme stabilisation and mitigation of cellular toxicity by the engineered compartment. This is the first demonstration in yeast of an artificial biocatalytic compartment that can participate in a metabolic pathway and establishes the MPyV platform as a promising synthetic biology tool for yeast engineering.
Properties of Indium Oxide Semiconducting Sensors Deposited by Different Techniques

Semiconducting In2O3 gas sensors have been fabricated by two different deposition techniques, i.e., spin-coating and screen-printing. In both cases the same starting material – sol-gel-prepared cubic In2O3 – was used for the deposition in order to ensure a better comparability of the different sensing layers. The morphology of the layers has been characterized using scanning electron microscopy (SEM) technique. The layers deposited by different methods show similar grain size and porosity. Furthermore, Dc electrical tests have been performed to analyze the sensing properties of the different gas sensors. Reducing gases (CO and propanal) as well as oxidizing gases (NO2 and ozone) were used as test gases in the background of dry and humidified synthetic air. All measurements were performed at several temperatures. It was found that the spin-coated and screen-printed layers show different sensing properties, i.e., screen-printed sensors showed higher sensor signals than spin-coated sensors for CO, propanal, and NO2. The most striking differences appeared in the detection of ozone. In this case, spin-coated sensors showed a higher performance than screen-printed sensors. Higher ozone concentrations led to saturation effects for the latter.
Experimental sexual selection reveals rapid evolutionary divergence in sex‐specific transcriptomes and their interactions following mating

Postcopulatory interactions between the sexes in internally fertilizing species elicits both sexual conflict and sexual selection. Macroevolutionary and comparative studies have linked these processes to rapid transcriptomic evolution in sex-specific tissues and substantial transcriptomic postmating responses in females, patterns of which are altered when mating between reproductively isolated species. Here we test multiple predictions arising from sexual selection and conflict theory about the evolution of sex-specific and tissue-specific gene expression and the postmating response at the microevolutionary level. Following over 150 generations of experimental evolution under either reduced (enforced monogamy) or elevated (polyandry) sexual selection in Drosophila pseudoobscura, we found a substantial effect of sexual selection treatment on transcriptomic divergence in virgin male and female reproductive tissues (testes, male accessory glands, the female reproductive tract and ovaries). Sexual selection treatment also had a dominant effect on the postmating response, particularly in the female reproductive tract – the main arena for sexual conflict - compared to ovaries. This affect was asymmetric with monandry females typically showing more postmating responses than polyandry females, with enriched gene functions varying across treatments. The evolutionary history of the male partner had a larger effect on the postmating response of monandry females, but females from both sexual selection treatments showed unique patterns of gene expression and gene function when mating with males from the alternate treatment. Our microevolutionary results mostly confirm comparative macroevolutionary predictions on the role of sexual selection on transcriptomic divergence and altered gene regulation arising from divergent coevolutionary trajectories between sexual selection treatments.
Refining the Identity and Role of Kv4 Channels in Mouse Substantia Nigra Dopaminergic Neurons

Abstract Substantia nigra pars compacta (SNc) dopaminergic (DA) neurons display a peculiar electrical phenotype characterized in vitro by a spontaneous tonic regular activity (pacemaking activity), a broad action potential (AP) and a biphasic postinhibitory response. The transient A-type current (IA) is known to play a crucial role in this electrical phenotype, and so far, this current was considered to be carried exclusively by Kv4.3 potassium channels. Using Kv4.3−/− transgenic mice, we demonstrate that the constitutive loss of this channel is associated with increased exploratory behavior and impaired motor learning at the behavioral level. Consistently, it is also associated with a lack of compensatory changes in other ion currents at the cellular level. Using antigen retrieval (AR) immunohistochemistry, we then demonstrate that Kv4.2 potassium channels are also expressed in SNc DA neurons, although their contribution to IA appears significant only in a minority of neurons (∼5–10%). Using correlative analysis on recorded electrophysiological parameters and multicompartment modeling, we then demonstrate that, rather than its conductance level, IA gating kinetics (inactivation time constant) appear as the main biophysical property defining postinhibitory rebound delay and pacemaking frequency. Moreover, we show that the hyperpolarization-activated current (IH) has an opposing and complementary influence on the same firing features.
DRDOCK: A Drug Repurposing platform integrating automated docking, simulations and a log-odds-based drug ranking scheme

Motivation Drug repurposing, where drugs originally approved to treat a disease are reused to treat other diseases, has received escalating attention especially in pandemic years. Structure-based drug design, integrating small molecular docking, molecular dynamic (MD) simulations and AI, has demonstrated its evidenced importance in streamlining new drug development as well as drug repurposing. To perform a sophisticated and fully automated drug screening using all the FDA drugs, intricate programming, accurate drug ranking methods and friendly user interface are very much needed. Results Here we introduce a new web server, DRDOCK, Drug Repurposing DOcking with Conformation-sampling and pose re-ranKing - refined by MD and statistical models, which integrates small molecular docking and molecular dynamic (MD) simulations for automatic drug screening of 2016 FDA-approved drugs over a user-submitted single-chained target protein. The drugs are ranked by a novel drug-ranking scheme using log-odds (LOD) scores, derived from feature distributions of true binders and decoys. Users can submit a selection of LOD-ranked poses for further MD-based binding affinity evaluation. We demonstrated that our platform can indeed recover one of the substrates for nsp16, a cap ribose 2′-O methyltransferase, and recommends that fluralaner, tegaserod and fenoterol could be repurposed for the COVID19 treatment with the latter two being confirmed in SARS-CoV2 suppression experiments. All the sampled docking poses and trajectories can be 3D-viewed and played via our web interface. This platform shall be easy-to-use for general scientists and medicinal researchers to carry out drug repurposing within a couple of days which should add value to our timely responses to, particularly, emergent disease outbreaks. Availability and implementation DRDOCK can be freely accessed from https://dyn.life. nthu.edu. tw/drdock/. (Due to the hardware upgrade, the service is NOT available before 7/18, 2021)
Thermodynamic modeling reveals widespread multivalent binding by RNA-binding proteins

Motivation Understanding how proteins recognize their RNA targets is essential to elucidate regulatory processes in the cell. Many RNA-binding proteins (RBPs) form complexes or have multiple domains that allow them to bind to RNA in a multivalent, cooperative manner. They can thereby achieve higher specificity and affinity than proteins with a single RNA-binding domain. However, current approaches to de-novo discovery of RNA binding motifs do not take multivalent binding into account. Results We present Bipartite Motif Finder (BMF), which is based on a thermodynamic model of RBPs with two cooperatively binding RNA-binding domains. We show that bivalent binding is a common strategy among RBPs, yielding higher affinity and sequence specificity. We furthermore illustrate that the spatial geometry between the binding sites can be learned from bound RNA sequences. These discovered bipartite motifs are consistent with previously known motifs and binding behaviors. Our results demonstrate the importance of multivalent binding for RNA-binding proteins and highlight the value of bipartite motif models in representing the multivalency of protein-RNA interactions. Availability BMF source code is available at https://github.com/soedinglab/bipartite_motif_finder under a GPL license. The BMF web server is accessible at https://bmf.soedinglab. org.
A catalogue of omics biological ageing clocks reveals substantial commonality and associations with disease risk

Biological age (BA), a measure of functional capacity and prognostic of health outcomes that discriminates between individuals of the same chronological age (chronAge), has been estimated using a variety of biomarkers. Previous comparative studies have mainly used epigenetic models (clocks), we use ~1000 participants to create eleven omics ageing clocks, with correlations of 0.45-0.97 with chronAge, even with substantial sub-setting of biomarkers. These clocks track common aspects of ageing with 94% of the variance in chronAge being shared among clocks. The difference between BA and chronAge - omics clock age acceleration (OCAA) - often associates with health measures. One year’s OCAA typically has the same effect on risk factors/10-year disease incidence as 0.46/0.45 years of chronAge. Epigenetic and IgG glycomics clocks appeared to track generalised ageing while others capture specific risks. We conclude BA is measurable and prognostic and that future work should prioritise health outcomes over chronAge.
Accurate and robust inference of microbial growth dynamics from metagenomic sequencing

Patterns of sequencing coverage along a bacterial genome—summarized by a peak-to-trough ratio (PTR)—have been shown to accurately reflect microbial growth rates, revealing a new facet of microbial dynamics and host-microbe interactions. Here, we introduce CoPTR (Compute PTR): a tool for computing PTRs from complete reference genomes and assemblies. We show that CoPTR is more accurate than the current state-of-the-art, while also providing more PTR estimates overall. We further develop theory formalizing a biological interpretation for PTRs. Using a reference database of 2935 species, we applied CoPTR to a case-control study of 1304 metagenomic samples from 106 individuals with irritable bowel disease. We show that PTRs have high inter-individual variation, are only loosely correlated with relative abundances, and are associated with disease status. We conclude by demonstrating how PTRs can be combined with relative abundances and metabolomics to investigate their effect on the microbiome. Availability CoPTR is available from https://github.com/tyjo/coptr, with documentation on https://coptr.readthedocs. io.
OmicsTIDE: interactive exploration of trends in multi-omics data

Motivation The increasing amount of data produced by omics technologies has significantly improved the understanding of how biological information is transferred across different omics layers and to which extent it is involved in the manifestation of a given phenotype. Besides data-driven analysis strategies, interactive visualization tools have been developed to make the analysis in the multi-omics field more transparent. However, most state-of-the-art tools do not reconstruct the impact of a given omics layer on the final integration result. In general, the amount of omics data analyses strategies and the fields of applications lack a clearer classification of the different approaches. Results We developed a classification for omics data focusing on different aspects of multi-omics data sets, such as data type and experimental design. Based on this classification we developed the Omics Trend-comparing Interactive Data Explorer (OmicsTIDE), an interactive visualization tool developed to address the limitations of current visualization approaches in the multi-omics field. The tool consists of an automated part that clusters omics data to determine trends and an interactive visualization. The trends are visualized as profile plots and are connected by a Sankey diagram that allows an interactive pairwise trend comparison to discover concordant and discordant trends. Moreover, large-scale omics data sets are broken down into small subsets of concordant and discordant regulatory trends within few analysis steps. We demonstrate the interactive analysis using OmicsTIDE with two case studies focusing on different types of experimental designs. Availability OmicsTIDE is a web tool and available via http://tuevis.informatik. uni-tuebingen.de/ Contact kay.nieselt@uni-tuebingen.de
Contextualization of causal regulatory networks from toxicogenomics data applied to drug-induced liver injury

Toxicogenomics studies typically reveal a group of genes relevant to the pathophysiology of drug-induced organ injury. In recent years, network-based methods have become an attractive analytical approach as they can capture not only the global changes of regulatory gene networks but also the relationships between their components. Among them, a causal reasoning approach additionally depicts the mechanisms of regulation that connect upstream regulators in signaling networks towards their downstream gene targets. In this work, we applied CARNIVAL, a causal network contextualisation tool, to infer upstream regulatory signaling networks based on gene expression microarray data from the TG-GATEs database. We focussed on six compounds that induce observable histopathologies linked to drug-induced liver injury (DILI) from repeated dosing experiments in rats. We compared responses in vitro and in vivo to identify potential cross-platform concordances in rats as well as network preservations between rat and human. Our results showed similarities of enriched pathways and network motifs between compounds. These pathways and motifs induce the same pathology in rats but not in humans. In particular, the causal interactions “LCK activates SOCS3, which in turn inhibits TFDP1” was commonly identified as a regulatory path among the fibrosis-inducing compounds. This potential pathology-inducing regulation illustrates the value of our approach to generate hypotheses that can be further validated experimentally.
Functional dynamic genetic effects on gene regulation are specific to particular cell types and environmental conditions

Genetic effects on gene expression and splicing can be modulated by cellular and environmental factors; yet interactions between genotypes, cell type and treatment have not been comprehensively studied together. We used an induced pluripotent stem cell system to study multiple cell types derived from the same individuals and exposed them to a large panel of treatments. Cellular responses involved different genes and pathways for gene expression and splicing processes, and were also highly variable across cell types and treatments. For thousands of genes, we identified variable allelic expression across contexts, and characterized different types of gene-environment interactions. Many of these G×E genes are associated with complex traits. We characterized promoter functional and evolutionary features that distinguish genes with elevated allelic imbalance mean and variance. More than 47% of the genes with dynamic regulatory interactions were missed by GTEx, but we identified them using a suitable allelic imbalance study design. This indicates the importance of exploring multiple treatments to reveal previously unrecognized regulatory loci that may be important for disease.
Recurrent TB: a systematic review and meta-analysis of the incidence rates and the proportions of relapses and reinfections

Background A recurrent tuberculosis (TB) episode results from exogenous reinfection or relapse after cure. The use of genotyping allows the distinction between both. Methods We did a systematic review and meta-analysis, using four databases to search for studies in English, French and Spanish published between 1 January 1980 and 30 September 2020 that assessed recurrences after TB treatment success and/or differentiated relapses from reinfections using genotyping. We calculated person years of follow-up and performed random-effects model meta-analysis for estimating pooled recurrent TB incidence rates and proportions of relapses and reinfections. We performed subgroup analyses by clinical–epidemiological factors and by methodological study characteristics. Findings The pooled recurrent TB incidence rate was 2.26 per 100 person years at risk (95% CI 1.87 to 2.73; 145 studies). Heterogeneity was high (I2=98%). Stratified pooled recurrence rates increased from 1.47 (95% CI 0.87 to 2.46) to 4.10 (95% CI 2.67 to 6.28) per 100 person years for studies conducted in low versus high TB incidence settings. Background HIV prevalence, treatment drug regimen, sample size and duration of follow-up contributed too. The pooled proportion of relapses was 70% (95% CI 63% to 77%; I²=85%; 48 studies). Heterogeneity was determined by background TB incidence, as demonstrated by pooled proportions of 83% (95% CI 75% to 89%) versus 59% (95% CI 42% to 74%) relapse for studies from settings with low versus high TB incidence, respectively. Interpretation The risk of recurrent TB is substantial and relapse is consistently the most frequent form of recurrence. Notwithstanding, with increasing background TB incidence the proportion of reinfections increases and the predominance of relapses among recurrences decreases. PROSPERO registration number CRD42018077867
A Novel Rat Model of Persistent Gouty Arthritis by Minimally Invasive Saturated Msu Embedding 

Background: Animal models are valid for in vivo research on the pathophysiological process and drug screening of gout arthritis. Intra-articular injection of monosodium urate (MSU) is commonly used to establish animal model at present, while stable MSU deposition and tophi formation were rarely reported. Method: A total of twenty-four rats were randomly allocated into six groups. Three intervention groups of rats received MSU embedment for 3-5 times, respectively. Sham groups received pseudo surgeries with normal saline (NS). Gross parameters and pathological features of synovium harvested from anterior capsule. Mechanical pain threshold tests of rats were conducted over a 96-hour period postoperatively. Result: Significant synovial swelling was detected in the MSU group compared to the sham group(P<0.05). Behavioral tests showed that the embedding of MSU resulted in prolonged mechanical hyperalgesia (P<0.05 during 2 hours to 96 hours postoperatively). MSU depositions enveloped by neutrophil extracellular traps (NETs) were detected where the IL-1β and TNF-α were co-expressed in embedding groups. Quantitative immunofluorescence suggested that the frequencies of MSU interventions promoted expression of proinflammatory factors (P<0.05). Conclusion: A minimally invasive surgical method was developed to establish the novel rat model of intra-articular MSU deposition. This model was proved to be a simple reproducible method to mimic the pathological characteristics of intra-articular crystal arthritis.