HGTphyloDetect: facilitating the identification and phylogenetic analysis of horizontal gene transfer.

BACKGROUND: Horizontal gene transfer (HGT) is an important driver in genome evolution, gain-of-function, and metabolic adaptation to environmental niches. Genome-wide identification of putative HGT events has become increasingly practical, given the rapid growth of genomic data. However, existing HGT analysis toolboxes are not widely used, limited by their inability to perform phylogenetic reconstruction to explore potential donors, and the detection of HGT from both evolutionarily distant and closely related species. RESULTS: In this study, we have developed HGTphyloDetect, which is a versatile computational toolbox that combines high-throughput analysis with phylogenetic inference, to facilitate comprehensive investigation of HGT events. Two case studies with Saccharomyces cerevisiae and Candida versatilis demonstrate the ability of HGTphyloDetect to identify horizontally acquired genes with high accuracy. In addition, HGTphyloDetect enables phylogenetic analysis to illustrate a likely path of gene transmission among the evolutionarily distant or closely related species. CONCLUSIONS: The HGTphyloDetect computational toolbox is designed for ease of use and can accurately find HGT events with a very low false discovery rate in a high-throughput manner. The HGTphyloDetect toolbox and its related user tutorial are freely available at https://github.com/SysBioChalmers/HGTphyloDetect.

Yeast9: a consensus genome-scale metabolic model for S. cerevisiae curated by the community.

Genome-scale metabolic models (GEMs) can facilitate metabolism-focused multi-omics integrative analysis. Since Yeast8, the yeast-GEM of Saccharomyces cerevisiae, published in 2019, has been continuously updated by the community. This has increased the quality and scope of the model, culminating now in Yeast9. To evaluate its predictive performance, we generated 163 condition-specific GEMs constrained by single-cell transcriptomics from osmotic pressure or reference conditions. Comparative flux analysis showed that yeast adapting to high osmotic pressure benefits from upregulating fluxes through central carbon metabolism. Furthermore, combining Yeast9 with proteomics revealed metabolic rewiring underlying its preference for nitrogen sources. Lastly, we created strain-specific GEMs (ssGEMs) constrained by transcriptomics for 1229 mutant strains. Well able to predict the strains' growth rates, fluxomics from those large-scale ssGEMs outperformed transcriptomics in predicting functional categories for all studied genes in machine learning models. Based on those findings we anticipate that Yeast9 will continue to empower systems biology studies of yeast metabolism.

GotEnzymes: an extensive database of enzyme parameter predictions.

Enzyme parameters are essential for quantitatively understanding, modelling, and engineering cells. However, experimental measurements cover only a small fraction of known enzyme-compound pairs in model organisms, much less in other organisms. Artificial intelligence (AI) techniques have accelerated the pace of exploring enzyme properties by predicting these in a high-throughput manner. Here, we present GotEnzymes, an extensive database with enzyme parameter predictions by AI approaches, which is publicly available at https://metabolicatlas.org/gotenzymes for interactive web exploration and programmatic access. The first release of this data resource contains predicted turnover numbers of over 25.7 million enzyme-compound pairs across 8099 organisms. We believe that GotEnzymes, with the readily-predicted enzyme parameters, would bring a speed boost to biological research covering both experimental and computational fields that involve working with candidate enzymes.

Sustainable Oily Liquid-Proof Passive Cooling (SOC) Textile for Personal Thermal Management.

Sweat passive-cooling textiles with asymmetric wettabilities on different sides offer an effective and low-energy consumption solution to personal thermal management in extreme thermal environments. However, the sweat-wicking and the cooling abilities decrease when the textile is contaminated by low-surface tension oily liquid fouling. The integration of anti-oily liquid fouling and sweat-wicking abilities on textile involves resolving the contradiction between hydrophilic and oleophobic properties and seeking eco-friendly short-chain fluorides to reduce the surface energy. Herein, a sustainable oily liquid-proof passive cooling (SOC) textile for personal thermal management is proposed. The SOC textile is obtained by applying a fluoride-free hydrophobic coating layer to one side of the high thermal conductive superoleophobic/superhydrophilic basal textile, which is fabricated using eco-friendly short-chain fluoride. The SOC textile preserves the anti-oily liquid fouling property even after 2000 abrasion cycles. Experimental test revealed that the SOC textile exhibits a cooling effect of ≈5 °C compared with the cotton textile, and the up to 70% reduction in sweating rate under the constant metabolic heat production rates. The configuration of the SOC textile would inspire the future design of intelligent textiles for personal thermal management, and the proposed strategy have implications for fabrication of eco-friendly oil-water separation materials.

Yeast optimizes metal utilization based on metabolic network and enzyme kinetics.

Metal ions are vital to metabolism, as they can act as cofactors on enzymes and thus modulate individual enzymatic reactions. Although many enzymes have been reported to interact with metal ions, the quantitative relationships between metal ions and metabolism are lacking. Here, we reconstructed a genome-scale metabolic model of the yeast Saccharomyces cerevisiae to account for proteome constraints and enzyme cofactors such as metal ions, named CofactorYeast. The model is able to estimate abundances of metal ions binding on enzymes in cells under various conditions, which are comparable to measured metal ion contents in biomass. In addition, the model predicts distinct metabolic flux distributions in response to reduced levels of various metal ions in the medium. Specifically, the model reproduces changes upon iron deficiency in metabolic and gene expression levels, which could be interpreted by optimization principles (i.e., yeast optimizes iron utilization based on metabolic network and enzyme kinetics rather than preferentially targeting iron to specific enzymes or pathways). At last, we show the potential of using the model for understanding cell factories that harbor heterologous iron-containing enzymes to synthesize high-value compounds such as p-coumaric acid. Overall, the model demonstrates the dependence of enzymes on metal ions and links metal ions to metabolism on a genome scale.

Evaluating the prognostic significance of p53 and TP53 mutations in HPV-negative hypopharyngeal carcinoma patients: a 5-year follow-up retrospective study.

PURPOSE: To evaluate prognostic significance of human papillomavirus (HPV) in hypopharyngeal squamous cell carcinoma patients, and to investigate the effect of p53 and TP53 mutations on the prognosis of patients. METHODS: A total of 111 patients were enrolled in our retrospective study. HPV infection status was detected in formalin-fixed paraffin-embedded tissue by real-time multiplex PCR test. p53 expression was evaluate by immunohistochemical staining. TP53 exon mutations were analyzed by PCR amplification and Sanger sequencing. HPV infection status, p53 expression and TP53 mutation were compared with clinical outcome including overall survival and recurrence-free survival by Kaplan-Meier method and Log-rank test. RESULTS: Of the 111 investigated patients, 18 (16.22%) were positive for HPV infection. HPV(-) patients have a worse clinical outcome than HPV(+) patients. TP53 mutations have similar mutation rates in patients with and without HPV (55.56% vs. 41.94%). p53 and TP53 mutation were not associated with prognosis of patients in HPV(-) patients. TP53 disruptive mutations were found both in patients with or without HPV infection. Furthermore, TP53 non-disruptive mutation had a significantly better clinical outcome than those with disruptive mutation in HPV(-) patients. CONCLUSION: Our results showed that HPV infection status is a strong prognostic indicator of survival. p53 and TP53 mutations do not appear to significantly impact survival in HPV(-) patients. TP53 disruptive mutation is associated with reduced survival in HPV(-)/TP53 mutation patients.

Membrane-coated nanoparticles for direct recognition by T cells.

The direct modulation of T cell responses is an emerging therapeutic strategy with the potential to modulate undesired immune responses including, autoimmune disease, and allogeneic cells transplantation. We have previously demonstrated that poly(lactide-co-glycolide) particles were able to modulate T cell responses indirectly through antigen-presenting cells (APCs). In this report, we investigated the design of nanoparticles that can directly interact and modulate T cells by coating the membranes from APCs onto nanoparticles to form membrane-coated nanoparticles (MCNPs). Proteins within the membranes of the APCs, such as Major Histocompatibility Complex class II and co-stimulatory factors, were effectively transferred to the MCNP. Using alloreactive T cell models, MCNP derived from allogeneic dendritic cells were able to stimulate proliferation, which was not observed with membranes from syngeneic dendritic cells and influenced cytokine secretion. Furthermore, we investigated the engineering of the membranes either on the dendritic cells or postfabrication of MCNP. Engineered membranes could be to promote antigen-specific responses, to differentially activate T cells, or to directly induce apoptosis. Collectively, MCNPs represent a tunable platform that can directly interact with and modulate T cell responses.

Diagnostic and prognostic value of plasma cell-free DNA combined with VEGF-C in laryngeal squamous cell carcinoma.

BACKGROUND: Circulating cell-free DNA (cfDNA) and vascular endothelial growth factor-C (VEGF-C) can be utilized to detect cancer and predict its prognosis. However, their potential application in laryngeal squamous cell carcinoma (LSCC) is unclear. PURPOSE: This study aimed to identify the diagnostic and prognostic value of cfDNA and VEGF-C in LSCC patients. METHODS: The plasma cfDNA of 148 LSCC patients and 43 non-tumor patients were isolated. Quantitative real-time PCR (qRT-PCR) was performed to assess long and short DNA fragments in plasma by amplifying the ALU repeats. ALU-qPCR results (ALU247/ALU115) were used to calculate cfDNA integrity index. Vascular endothelial growth factor-C (VEGF-C) level was detected by ELISA assay. Correlation between cfDNA and clinical features was analyzed. For detecting the sensitivity and specificity of cfDNA and VEGF-C alone or in combination for diagnosing LSCC, receiver operator characteristic (ROC) was established. For evaluating the overall survival (OS) of LSCC, Kaplan-Meier curves were established. RESULTS: LSCC patients had significantly higher levels of plasma cfDNA (ALU115, ALU247, and cfDNA integrity index) and VEGF-C than those without cancer (p < 0.05), showing area under the curve (AUC) values of 0.79, 0.74, 0.62 and 0.80, when cutoff value was correspondingly defined at 2.14 ng/mL, 1.39 ng/mL, 0.73 and 412.90 pg/mL, respectively. The AUC for distinguishing LSCC patients from non-tumor patients by plasma cfDNA combined with VEGF-C was 0.89 (95% CI: 0.83-0.94). A significant correlation was found between plasma cfDNA levels and Ki-67, tumor size, pT stage, and smoking history (p < 0.05). Based on survival analysis, low VEGF-C concentration groups had longer OS than those with high VEGF-C concentration (p = 0.02). CONCLUSION: Indicators such as plasma cfDNA and VEGF-C may be used to diagnose and monitor LSCC for its noninvasiveness and rapid accessibility.

Transcriptome profiling of lung immune responses potentially related to acute respiratory distress syndrome in forest musk deer.

BACKGROUND: Forest musk deer is an endangered species globally. The death of captive forest musk deer can be caused by certain respiratory system diseases. Acute respiratory distress syndrome (ARDS) is a huge threat to the life of forest muck deer that breed in our department. METHODS: Lung histopathologic analysis was conducted by hematoxylin and eosin (HE) staining. The lung gene changes triggered by ARDS were examined by RNA sequencing and related bioinformatics analysis in forest musk deer. The potential functions of unigenes were investigated by NR, SwissProt KOG, GO, and KEGG annotation analyses. Vital biological processes or pathways in ARDS were examined by GO and KEGG enrichment analyses. RESULTS: A total of 3265 unigenes were differentially expressed (|log2fold-change|> 2 and adjusted P value < 0.01) in lung tissues of 3 forest musk deer with ARDS compared with normal lung tissues of the non-ARDS group. These differentially expressed unigenes (DEGs) played crucial roles in immunity and defense responses to pathogens. Moreover, we identified the DEGs related to one or more of the following biological processes: lung development, immunity, and bacterial/viral/fungal infection. And six DEGs that might be involved in lung injury caused by immune dysregulation or viral/fungal infection were identified. CONCLUSION: ARDS-mediated lung gene alterations were identified in forest musk deer. Moreover, multiple genes involved in lung development and lung defense responses to bacteria/viruses/fungi in ARDS were filtered out in forest musk deer.

Yeast metabolic innovations emerged via expanded metabolic network and gene positive selection.

Yeasts are known to have versatile metabolic traits, while how these metabolic traits have evolved has not been elucidated systematically. We performed integrative evolution analysis to investigate how genomic evolution determines trait generation by reconstructing genome-scale metabolic models (GEMs) for 332 yeasts. These GEMs could comprehensively characterize trait diversity and predict enzyme functionality, thereby signifying that sequence-level evolution has shaped reaction networks towards new metabolic functions. Strikingly, using GEMs, we can mechanistically map different evolutionary events, e.g. horizontal gene transfer and gene duplication, onto relevant subpathways to explain metabolic plasticity. This demonstrates that gene family expansion and enzyme promiscuity are prominent mechanisms for metabolic trait gains, while GEM simulations reveal that additional factors, such as gene loss from distant pathways, contribute to trait losses. Furthermore, our analysis could pinpoint to specific genes and pathways that have been under positive selection and relevant for the formulation of complex metabolic traits, i.e. thermotolerance and the Crabtree effect. Our findings illustrate how multidimensional evolution in both metabolic network structure and individual enzymes drives phenotypic variations.

Prognostic and clinicopathological significance of transcription factor c-Jun in hypopharyngeal squamous cell carcinoma: a 3-year follow-up retrospective study.

PURPOSE: To investigate the expression and prognostic value of c-Jun in hypopharyngeal squamous cell carcinoma (HPSCC). METHODS: A retrospective study was performed on a cohort of 99 HPSCC patients. The expression of c-Jun and phosphorylated-c-Jun (p-c-Jun) was evaluated via immunohistochemistry (IHC) staining. Overall survival (OS) and progression-free survival (PFS) were assessed using Kaplan-Meier method and multivariate Cox regression analysis. RESULTS: The high expression of c-Jun and p-c-Jun in HPSCC accounted for 60.61% and 16.16%, respectively. High expression of c-Jun was closely associated with cT stage (p = 0.0401), tumor size (p = 0.0276), number of lymph node metastases (p = 0.0205) and pathological differentiation (p = 0.0108). The expression of c-Junhigh (p = 0.0043), p-c-Junhigh (p = 0.0376) and c-Junhigh/p-c-Junhigh were closely associated with poor OS. The Cox proportional multivariate hazard model revealed that lymphovascular invasion and c-Jun expression were independent influencing factors of OS in HPSCC patients. CONCLUSION: Our findings suggest that c-Jun is a reliable prognostic factors in HPSCC patients.

Genome-scale modeling of yeast metabolism: retrospectives and perspectives.

Yeasts have been widely used for production of bread, beer and wine, as well as for production of bioethanol, but they have also been designed as cell factories to produce various chemicals, advanced biofuels and recombinant proteins. To systematically understand and rationally engineer yeast metabolism, genome-scale metabolic models (GEMs) have been reconstructed for the model yeast Saccharomyces cerevisiae and nonconventional yeasts. Here, we review the historical development of yeast GEMs together with their recent applications, including metabolic flux prediction, cell factory design, culture condition optimization and multi-yeast comparative analysis. Furthermore, we present an emerging effort, namely the integration of proteome constraints into yeast GEMs, resulting in models with improved performance. At last, we discuss challenges and perspectives on the development of yeast GEMs and the integration of proteome constraints.

Sodium butyrate ameliorates thiram-induced tibial dyschondroplasia and gut microbial dysbiosis in broiler chickens.

Thiram is a dithiocarbamate pesticide widely used in agriculture as a fungicide for storing grains to prevent fungal diseases. However, its residues have threatened the safety of human beings and the stability of the ecosystem by causing different disease conditions, e.g., tibial dyschondroplasia (TD), which results in a substantial economic loss for the poultry industry. So, the research on TD has a great concern for the industry and the overall GDP of a country. In current study, we investigated whether different concentrations (300, 500, and 700 mg/kg) of sodium butyrate alleviated TD induced under acute thiram exposure by regulating osteogenic gene expression, promoting chondrocyte differentiation, and altering the gut microbial community. According to the findings, sodium butyrate restored clinical symptoms in broilers, improved growth performance, bone density, angiogenesis, and chondrocyte morphology and arrangement. It could activate the signal transduction of the Wnt/ß-catenin pathway, regulate the expression of GSK-3ß and ß-catenin, and further promote the production of osteogenic transcription factors Runx2 and OPN for restoration of lameness. In addition, the 16S rRNA sequencing revealed a significantly different community composition among the groups. The TD group increased the abundance of the harmful bacteria Proteobacteria, Subdoligranulum, and Erysipelatoclostridium. The sodium butyrate enriched many beneficial bacteria, such as Bacteroidetes, Verrucomicrobia, Faecalibacterium, Barnesiella, Rikenella, and Butyricicoccus, etc., especially at the concentration of 500 mg/kg. The mentioned concentration significantly limited the intestinal disorders under thiram exposure, and restored bone metabolism.

[Pharmacokinetic interaction of Jiaotai Pills and Fluoxetine in rats with CUMS-induced depression].

A high-performance liquid chromatography-tandem mass spectrometry(LC-MS/MS) was developed for simultaneously determining the components(magnoflorine, jatrorrhizine, berberrubine, coptisine, berberine) of Jiaotai Pills and Fluoxetine in plasma of rats with chronic unpredictable mild stress(CUMS)-induced depression to investigate the pharmacokinetic herb-drug interaction of Jiaotai Pills and Fluoxetine in the rats. The six components showed good linear relationship within the corresponding concentration ranges, and the method showed high specificity, accuracy, precision, and stability. Their pharmacokinetic parameters were calculated by DAS 3.2.2, and the results showed that the in vivo metabolic processes of the six components accorded with the characteristics of non-compartmental model. When Jiaotai Pills and Fluoxetine were used together, the AUC_(0-t), AUC_(0-∞), C_(max), and C_(av) of magnoflorine all significantly increased(P<0.05), while the pharmacokinetic trend of berberrubine was opposite to that of magnoflorine, as manifested by the decrease in AUC_(0-t), AUC_(0-∞), T_(max), C_(max), and C_(av)(P<0.01, P<0.05). The pharmacokinetic characteristics of jatrorrhizine, coptisine, and berberine followed the trend of berberrubine. There was no significant difference in the pharmacokinetic characteristics of Fluoxetine in the single or combination groups. This study suggests that the enhanced antidepressant efficacy of Jiaotai Pills and Fluo-xetine may be attributed to the pharmacokinetic interaction.

Evaluating accessibility, usability and interoperability of genome-scale metabolic models for diverse yeasts species.

Metabolic network reconstructions have become an important tool for probing cellular metabolism in the field of systems biology. They are used as tools for quantitative prediction but also as scaffolds for further knowledge contextualization. The yeast Saccharomyces cerevisiae was one of the first organisms for which a genome-scale metabolic model (GEM) was reconstructed, in 2003, and since then 45 metabolic models have been developed for a wide variety of relevant yeasts species. A systematic evaluation of these models revealed that-despite this long modeling history-the sequential process of tracing model files, setting them up for basic simulation purposes and comparing them across species and even different versions, is still not a generalizable task. These findings call the yeast modeling community to comply to standard practices on model development and sharing in order to make GEMs accessible and useful for a wider public.

[Effects of Jiaotai Pills on CUMS-induced depression model in mice based on changes of SIRT1 expression in hippocampus].

The present study investigated the effects and mechanisms of Jiaotai Pills on depressed mice induced by chronic unpredictable mild stress(CUMS). The CUMS-induced depression model mice were established and the depression behaviors of mice were evaluated by sucrose preference test, open field test, tail suspension test, and forced swimming test. Molecular docking was employed to simulate the interaction of six main active ingredients in Jiaotai Pills with SIRT1. Immunohistochemical staining was used to detect the level of SIRT1 in the hippocampus of mice. Western blot was used to detect the protein expression levels of SIRT1, p-NF-κB p65, NF-κB p65, and FoxO1 in the hippocampus of mice. Enzyme-linked immunosorbent assay(ELISA) kits were used to detect the levels of interleukin(IL)-1ß, IL-6, tumor necrosis factor-α(TNF-α), and brain-derived neurotrophic factor(BDNF) in the hippocampus and serum of mice. Biochemical kits were used to detect superoxide dismutase(SOD) activity and malondialdehyde(MDA) and glutathione(GSH) levels in the hippocampus and serum of mice. Liquid chromatography-tandem mass spectrometry(LC-MS/MS) was used to detect the levels of dopamine(DA), 5-hydroxytryptamine(5-HT), and norepinephrine(NE) in the hippocampus and serum of mice. The results showed that the sucrose preference rate, movement distance, and the number of crossing centers were reduced in the model group(P<0.01), and the tail suspension time and swimming immobility time were increased(P<0.01). Molecular docking results indicated good binding of six main active ingredients in Jiaotai Pills to SIRT1. In the hippocampus, the expression level of SIRT1 was reduced(P<0.01), and the levels of p-NF-κB p65/NF-κB p65 and FoxO1 were increased(P<0.01). In the hippocampus and serum, the levels of IL-1ß, IL-6, TNF-α, and MDA were increased(P<0.01), and the activity of SOD and the levels of GSH, DA, 5-HT, NE, and BDNF were reduced(P<0.01). The treatment with high-dose Jiaotai Pills increased the sucrose preference rate, movement distance, and the number of crossing centers(P<0.05), reduced tail suspension time and swimming immobility time(P<0.01), elevated hippocampal SIRT1 expression level(P<0.01), decreased hippocampal and serum IL-1ß, IL-6, TNF-α, and MDA levels(P<0.01), potentiated SOD activity, and up-regulated GSH, DA, 5-HT, NE, and BDNF levels in the hippocampus and serum(P<0.05, P<0.01) in model mice. In conclusion, the results showed that Jiaotai Pills could improve the depression behaviors of model mice with CUMS-induced depression, and the underlying mechanism was related to the up-regulation of SIRT1 in the hippocampus of mice to exert anti-inflammatory and anti-oxidative stress effects.

Mimicking Chemotactic Cell Migration with DNA Programmable Synthetic Vesicles.

Chemotactic cell motility plays a critical role in many biological functions, such as immune response and embryogenesis. Constructing synthetic cell-mimicking systems, such as a dynamic protocell, likewise requires molecular mechanisms that respond to environmental stimuli and execute programmed motility behaviors. Although various molecular components were proposed to achieve diverse functions in synthetic protocells, chemotactic motility on surfaces has not been reported thus far. Here we show directional motility in synthetic lipid vesicles capable of chasing each other by programming DNA components. We demonstrate that the "follow" vesicle recognizes and migrates along the moving trajectory of the "lead" vesicle with an enhanced speed, thus mimicking natural chemotaxis in cell migration. This work provides new possibilities for building synthetic protocells with complex functions such as programmed morphogenesis and cooperative motion. With the vast library of dynamic DNA components, we envision that this platform will enable new discoveries in fundamental sciences and novel applications in biotechnology.

Systematic design and in vitro validation of novel one-carbon assimilation pathways.

The utilization of one-carbon (C1) assimilation pathways to produce chemicals and fuels from low-cost C1 compounds could greatly reduce the substrate-related production costs, and would also alleviate the pressure of the resource supply for bio-manufacturing. However, the natural C1 assimilation pathways normally involve ATP consumption or the loss of carbon resources as CO2, resulting in low product yields, making the design of novel pathways highly pertinent. Here we present several new ATP-independent and carbon-conserving C1 assimilation cycles with 100% theoretical carbon yield, which were discovered by computational analysis of metabolic reaction set with 6578 natural reactions from MetaCyc database and 73 computationally predicted aldolase reactions from ATLAS database. Then, kinetic evaluation of these cycles was conducted and the cycles without kinetic traps were chosen for further experimental verification. Finally, we used the two engineered enzymes Gals and TalBF178Y for the artificial reactions to construct a novel C1 assimilation pathway in vitro and optimized the pathway to achieve 88% carbon yield. These results demonstrate the usefulness of computational design in finding novel metabolic pathways for the efficient utilization of C1 compounds and shedding light on other promising pathways.