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Sökning: WFRF:(Ji Boyang 1983)

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1.
  • Chen, Xin, 1980, et al. (författare)
  • Dataset for suppressors of amyloid-beta toxicity and their functions in recombinant protein production in yeast
  • 2022
  • Ingår i: Data in Brief. - : Elsevier BV. - 2352-3409. ; 42
  • Tidskriftsartikel (refereegranskat)abstract
    • The production of recombinant proteins at high levels often induces stress-related phenotypes by protein misfolding or aggregation. These are similar to those of the yeast Alzheimer's disease (AD) model in which amyloid-beta peptides (A beta 42) were accumulated [1,2] . We have previously identified suppressors of A beta 42 cytotoxicity via the genome-wide synthetic genetic array (SGA) [3] and here we use them as metabolic engineering targets to evaluate their potentiality on recombinant protein production in yeast Saccharomyces cerevisiae. In order to investigate the mechanisms linking the genetic modifications to the improved recombinant protein production, we perform systems biology approaches (transcriptomics and proteomics) on the resulting strain and intermediate strains. The RNAseq data are preprocessed by the nf-core/RNAseq pipeline and analyzed using the Platform for Integrative Analysis of Omics (PIANO) package [4] . The quantitative proteome is analyzed on an Orbitrap Fusion Lumos mass spectrometer interfaced with an Easy-nLC1200 liquid chromatography (LC) system. LC-MS data files are processed by Proteome Discoverer version 2.4 with Mascot 2.5.1 as a database search engine. The original data presented in this work can be found in the research paper titled "Suppressors of Amyloid-beta Toxicity Improve Recombinant Protein Produc-tion in yeast by Reducing Oxidative Stress and Tuning Cellu-lar Metabolism", by Chen et al. [5] . (C) 2022 The Author(s). Published by Elsevier Inc.
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2.
  • Chen, Xin, 1980, et al. (författare)
  • Suppressors of amyloid-β toxicity improve recombinant protein production in yeast by reducing oxidative stress and tuning cellular metabolism
  • 2022
  • Ingår i: Metabolic Engineering. - : Elsevier BV. - 1096-7176 .- 1096-7184. ; 72, s. 311-324
  • Tidskriftsartikel (refereegranskat)abstract
    • High-level production of recombinant proteins in industrial microorganisms is often limited by the formation of misfolded proteins or protein aggregates, which consequently induce cellular stress responses. We hypothesized that in a yeast Alzheimer's disease (AD) model overexpression of amyloid-β peptides (Aβ42), one of the main peptides relevant for AD pathologies, induces similar phenotypes of cellular stress. Using this humanized AD model, we previously identified suppressors of Aβ42 cytotoxicity. Here we hypothesize that these suppressors could be used as metabolic engineering targets to alleviate cellular stress and improve recombinant protein production in the yeast Saccharomyces cerevisiae. Forty-six candidate genes were individually deleted and twenty were individually overexpressed. The positive targets that increased recombinant α-amylase production were further combined leading to an 18.7-fold increased recombinant protein production. These target genes are involved in multiple cellular networks including RNA processing, transcription, ER-mitochondrial complex, and protein unfolding. By using transcriptomics and proteomics analyses, combined with reverse metabolic engineering, we showed that reduced oxidative stress, increased membrane lipid biosynthesis and repressed arginine and sulfur amino acid biosynthesis are significant pathways for increased recombinant protein production. Our findings provide new insights towards developing synthetic yeast cell factories for biosynthesis of valuable proteins.
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3.
  • Li, Gang, 1991, et al. (författare)
  • Performance of Regression Models as a Function of Experiment Noise
  • 2021
  • Ingår i: Bioinformatics and Biology Insights. - : SAGE Publications. - 1177-9322. ; 15
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: A challenge in developing machine learning regression models is that it is difficult to know whether maximal performance has been reached on the test dataset, or whether further model improvement is possible. In biology, this problem is particularly pronounced as sample labels (response variables) are typically obtained through experiments and therefore have experiment noise associated with them. Such label noise puts a fundamental limit to the metrics of performance attainable by regression models on the test dataset. Results: We address this challenge by deriving an expected upper bound for the coefficient of determination (R2) for regression models when tested on the holdout dataset. This upper bound depends only on the noise associated with the response variable in a dataset as well as its variance. The upper bound estimate was validated via Monte Carlo simulations and then used as a tool to bootstrap performance of regression models trained on biological datasets, including protein sequence data, transcriptomic data, and genomic data. Conclusions: The new method for estimating upper bounds for model performance on test data should aid researchers in developing ML regression models that reach their maximum potential. Although we study biological datasets in this work, the new upper bound estimates will hold true for regression models from any research field or application area where response variables have associated noise.
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4.
  • Wang, Jinpeng, et al. (författare)
  • Metabolic engineering for increased lipid accumulation in Yarrowia lipolytica – A Review
  • 2020
  • Ingår i: Bioresource Technology. - : Elsevier BV. - 0960-8524 .- 1873-2976. ; 313
  • Forskningsöversikt (refereegranskat)abstract
    • Current energy security and climate change policies encourage the development and utilization of bioenergy. Oleaginous yeasts provide a particularly attractive platform for the sustainable production of biofuels and industrial chemicals due to their ability to accumulate high amounts of lipids. In particular, microbial lipids in the form of triacylglycerides (TAGs) produced from renewable feedstocks have attracted considerable attention because they can be directly used in the production of biodiesel and oleochemicals analogous to petrochemicals. As an oleaginous yeast that is generally regarded as safe, Yarrowia lipolytica has been extensively studied, with large amounts of data on its lipid metabolism, genetic tools, and genome sequencing and annotation. In this review, we highlight the newest strategies for increasing lipid accumulation using metabolic engineering and summarize the research advances on the overaccumulation of lipids in Y. lipolytica. Finally, perspectives for future engineering approaches are proposed.
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5.
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6.
  • Abdel-Haleem, Alyaa M., et al. (författare)
  • Integrated Metabolic Modeling, Culturing, and Transcriptomics Explain Enhanced Virulence of Vibrio cholerae during Coinfection with Enterotoxigenic Escherichia coli
  • 2020
  • Ingår i: mSystems. - 2379-5077. ; 5:5
  • Tidskriftsartikel (refereegranskat)abstract
    • Gene essentiality is altered during polymicrobial infections. Nevertheless, most studies rely on single-species infections to assess pathogen gene essentiality. Here, we use genome-scale metabolic models (GEMs) to explore the effect of coinfection of the diarrheagenic pathogen Vibrio cholerae with another enteric pathogen, enterotoxigenic Escherichia coli (ETEC). Model predictions showed that V. cholerae metabolic capabilities were increased due to ample cross-feeding opportunities enabled by ETEC. This is in line with increased severity of cholera symptoms known to occur in patients with dual infections by the two pathogens. In vitro co-culture systems confirmed that V. cholerae growth is enhanced in cocultures relative to single cultures. Further, expression levels of several V. cholerae metabolic genes were significantly perturbed as shown by dual RNA sequencing (RNAseq) analysis of its cocultures with different ETEC strains. A decrease in ETEC growth was also observed, probably mediated by nonmetabolic factors. Single gene essentiality analysis predicted conditionally independent genes that are essential for the pathogen's growth in both single-infection and coinfection scenarios. Our results reveal growth differences that are of relevance to drug targeting and efficiency in polymicrobial infections. IMPORTANCE Most studies proposing new strategies to manage and treat infections have been largely focused on identifying druggable targets that can inhibit a pathogen's growth when it is the single cause of infection. In vivo, however, infections can be caused by multiple species. This is important to take into account when attempting to develop or use current antibacterials since their efficacy can change significantly between single infections and coinfections. In this study, we used genome-scale metabolic models (GEMs) to interrogate the growth capabilities of Vibrio cholerae in single infections and coinfections with enterotoxigenic E. coli (ETEC), which cooccur in a large fraction of diarrheagenic patients. Coinfection model predictions showed that V. cholerae growth capabilities are enhanced in the presence of ETEC relative to V. cholerae single infection, through cross-fed metabolites made available to V. cholerae by ETEC. In vitro, cocultures of the two enteric pathogens further confirmed model predictions showing an increased growth of V. cholerae in coculture relative to V. cholerae single cultures while ETEC growth was suppressed. Dual RNAseq analysis of the cocultures also confirmed that the transcriptome of V. cholerae was distinct during coinfection compared to single-infection scenarios where processes related to metabolism were significantly perturbed. Further, in silico gene-knockout simulations uncovered discrepancies in gene essentiality for V. cholerae growth between single infections and coinfections. Integrative model-guided analysis thus identified druggable targets that would be critical for V. cholerae growth in both single infections and coinfections; thus, designing inhibitors against those targets would provide a broader spectrum of coverage against cholera infections.
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7.
  • Babaei, Parizad, 1990, et al. (författare)
  • Challenges in modeling the human gut microbiome
  • 2018
  • Ingår i: Nature Biotechnology. - : Springer Science and Business Media LLC. - 1087-0156 .- 1546-1696. ; 36:8, s. 682-686
  • Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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8.
  • Belda, E., et al. (författare)
  • Impairment of gut microbial biotin metabolism and host biotin status in severe obesity: effect of biotin and prebiotic supplementation on improved metabolism
  • 2022
  • Ingår i: Gut. - : BMJ. - 0017-5749 .- 1468-3288. ; 71:12
  • Tidskriftsartikel (refereegranskat)abstract
    • Objectives Gut microbiota is a key component in obesity and type 2 diabetes, yet mechanisms and metabolites central to this interaction remain unclear. We examined the human gut microbiome's functional composition in healthy metabolic state and the most severe states of obesity and type 2 diabetes within the MetaCardis cohort. We focused on the role of B vitamins and B7/B8 biotin for regulation of host metabolic state, as these vitamins influence both microbial function and host metabolism and inflammation. Design We performed metagenomic analyses in 1545 subjects from the MetaCardis cohorts and different murine experiments, including germ-free and antibiotic treated animals, faecal microbiota transfer, bariatric surgery and supplementation with biotin and prebiotics in mice. Results Severe obesity is associated with an absolute deficiency in bacterial biotin producers and transporters, whose abundances correlate with host metabolic and inflammatory phenotypes. We found suboptimal circulating biotin levels in severe obesity and altered expression of biotin-associated genes in human adipose tissue. In mice, the absence or depletion of gut microbiota by antibiotics confirmed the microbial contribution to host biotin levels. Bariatric surgery, which improves metabolism and inflammation, associates with increased bacterial biotin producers and improved host systemic biotin in humans and mice. Finally, supplementing high-fat diet-fed mice with fructo-oligosaccharides and biotin improves not only the microbiome diversity, but also the potential of bacterial production of biotin and B vitamins, while limiting weight gain and glycaemic deterioration. Conclusion Strategies combining biotin and prebiotic supplementation could help prevent the deterioration of metabolic states in severe obesity.
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9.
  • Chen, Xin, 1980, et al. (författare)
  • FMN reduces Amyloid-beta toxicity in yeast by regulating redox status and cellular metabolism
  • 2020
  • Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Alzheimer's disease (AD) is defined by progressive neurodegeneration, with oligomerization and aggregation of amyloid-beta peptides (A beta) playing a pivotal role in its pathogenesis. In recent years, the yeast Saccharomyces cerevisiae has been successfully used to clarify the roles of different human proteins involved in neurodegeneration. Here, we report a genome-wide synthetic genetic interaction array to identify toxicity modifiers of A beta 42, using yeast as the model organism. We find that FMN1, the gene encoding riboflavin kinase, and its metabolic product flavin mononucleotide (FMN) reduce A beta 42 toxicity. Classic experimental analyses combined with RNAseq show the effects of FMN supplementation to include reducing misfolded protein load, altering cellular metabolism, increasing NADH/(NADH+NAD(+)) and NADPH/(NADPH+NADP(+)) ratios and increasing resistance to oxidative stress. Additionally, FMN supplementation modifies Htt103QP toxicity and alpha-synuclein toxicity in the humanized yeast. Our findings offer insights for reducing cytotoxicity of A beta 42, and potentially other misfolded proteins, via FMN-dependent cellular pathways.Saccharomyces cerevisiae is a model organism to study proteins involved in neurodegeneration. Here, the authors performed a yeast genome-wide synthetic genetic interaction array (SGA) to screen for toxicity modifiers of A beta 42 and identify riboflavin kinase and its metabolic product flavin mononucleotide as modulators that alleviate cellular A beta 42 toxicity, which is supported by further experimental analyses.
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10.
  • Chen, Xin, 1980, et al. (författare)
  • Interplay of Energetics and ER Stress Exacerbates Alzheimer's Amyloid-beta (A beta) Toxicity in Yeast
  • 2017
  • Ingår i: Frontiers in Molecular Neuroscience. - : Frontiers Media SA. - 1662-5099. ; 10
  • Tidskriftsartikel (refereegranskat)abstract
    • Alzheimer's disease (AD) is a progressive neurodegeneration. Oligomers of amyloid-beta peptides (A beta) are thought to play a pivotal role in AD pathogenesis, yet the mechanisms involved remain unclear. Two major isoforms of A beta associated with AD are A beta 40 and A beta 42, the latter being more toxic and prone to form oligomers. Here, we took a systems biology approach to study two humanized yeast AD models which expressed either A beta 40 or A beta 42 in bioreactor cultures. Strict control of oxygen availability and culture pH, strongly affected chronological lifespan and reduced variations during cell growth. Reduced growth rates and biomass yields were observed upon A beta 42 expression, indicating a redirection of energy from growth to maintenance. Quantitative physiology analyses furthermore revealed reduced mitochondria' functionality and ATP generation in A beta 42 expressing cells, which matched with observed aberrant mitochondria' structures. Genome-wide expression level analysis showed that A beta 42 expression triggered strong ER stress and unfolded protein responses. Equivalent expression of A beta 40, however, induced only mild ER stress, which resulted in hardly affected physiology. Using AD yeast models in well controlled cultures strengthened our understanding on how cells translate different A beta toxicity signals into particular cell fate programs, and further enhance their potential as a discovery platform to identify possible therapies.
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11.
  • Das, Promi, 1990, et al. (författare)
  • In vitro co-cultures of human gut bacterial species as predicted from co-occurrence network analysis
  • 2018
  • Ingår i: Plos One. - : Public Library of Science (PLoS). - 1932-6203. ; 13:3
  • Tidskriftsartikel (refereegranskat)abstract
    • Network analysis of large metagenomic datasets generated by current sequencing technologies can reveal significant co-occurrence patterns between microbial species of a biological community. These patterns can be analyzed in terms of pairwise combinations between all species comprising a community. Here, we construct a co-occurrence network for abundant microbial species encompassing the three dominant phyla found in human gut. This was followed by an in vitro evaluation of the predicted microbe-microbe co-occurrences, where we chose species pairs Bifidobacterium adolescentis and Bacteroides thetaiotaomicron, as well as Faecalibacterium prausnitzii and Roseburia inulinivorans as model organisms for our study. We then delineate the outcome of the co-cultures when equal distributions of resources were provided. The growth behavior of the co-culture was found to be dependent on the types of microbial species present, their specific metabolic activities, and resulting changes in the culture environment. Through this reductionist approach and using novel in vitro combinations of microbial species under anaerobic conditions, the results of this work will aid in the understanding and design of synthetic community formulations.
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12.
  • Das, Promi, 1990, et al. (författare)
  • Metagenomic analysis of bile salt biotransformation in the human gut microbiome
  • 2019
  • Ingår i: BMC Genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 20:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: In the biochemical milieu of human colon, bile acids act as signaling mediators between the host and its gut microbiota. Biotransformation of primary to secondary bile acids have been known to be involved in the immune regulation of human physiology. Several 16S amplicon-based studies with inflammatory bowel disease (IBD) subjects were found to have an association with the level of fecal bile acids. However, a detailed investigation of all the bile salt biotransformation genes in the gut microbiome of healthy and IBD subjects has not been performed. Results: Here, we report a comprehensive analysis of the bile salt biotransformation genes and their distribution at the phyla level. Based on the analysis of shotgun metagenomes, we found that the IBD subjects harbored a significantly lower abundance of these genes compared to the healthy controls. Majority of these genes originated from Firmicutes in comparison to other phyla. From metabolomics data, we found that the IBD subjects were measured with a significantly low level of secondary bile acids and high levels of primary bile acids compared to that of the healthy controls. Conclusions: Our bioinformatics-driven approach of identifying bile salt biotransformation genes predicts the bile salt biotransformation potential in the gut microbiota of IBD subjects. The functional level of dysbiosis likely contributes to the variation in the bile acid pool. This study sets the stage to envisage potential solutions to modulate the gut microbiome with the objective to restore the bile acid pool in the gut.
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13.
  • Forslund, Sofia K., et al. (författare)
  • Combinatorial, additive and dose-dependent drug–microbiome associations
  • 2021
  • Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 600:7889, s. 500-505
  • Tidskriftsartikel (refereegranskat)abstract
    • During the transition from a healthy state to cardiometabolic disease, patients become heavily medicated, which leads to an increasingly aberrant gut microbiome and serum metabolome, and complicates biomarker discovery1–5. Here, through integrated multi-omics analyses of 2,173 European residents from the MetaCardis cohort, we show that the explanatory power of drugs for the variability in both host and gut microbiome features exceeds that of disease. We quantify inferred effects of single medications, their combinations as well as additive effects, and show that the latter shift the metabolome and microbiome towards a healthier state, exemplified in synergistic reduction in serum atherogenic lipoproteins by statins combined with aspirin, or enrichment of intestinal Roseburia by diuretic agents combined with beta-blockers. Several antibiotics exhibit a quantitative relationship between the number of courses prescribed and progression towards a microbiome state that is associated with the severity of cardiometabolic disease. We also report a relationship between cardiometabolic drug dosage, improvement in clinical markers and microbiome composition, supporting direct drug effects. Taken together, our computational framework and resulting resources enable the disentanglement of the effects of drugs and disease on host and microbiome features in multimedicated individuals. Furthermore, the robust signatures identified using our framework provide new hypotheses for drug–host–microbiome interactions in cardiometabolic disease.
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14.
  • Fromentin, S., et al. (författare)
  • Microbiome and metabolome features of the cardiometabolic disease spectrum
  • 2022
  • Ingår i: Nature Medicine. - : Springer Science and Business Media LLC. - 1078-8956 .- 1546-170X. ; 28:2, s. 303-314
  • Tidskriftsartikel (refereegranskat)abstract
    • By studying individuals along a spectrum of cardiometabolic disease and adjusting for effects of lifestyle and medication, this investigation identifies alterations of the metabolome and microbiome from dysmetabolic conditions, such as obesity and type 2 diabetes, to ischemic heart disease. Previous microbiome and metabolome analyses exploring non-communicable diseases have paid scant attention to major confounders of study outcomes, such as common, pre-morbid and co-morbid conditions, or polypharmacy. Here, in the context of ischemic heart disease (IHD), we used a study design that recapitulates disease initiation, escalation and response to treatment over time, mirroring a longitudinal study that would otherwise be difficult to perform given the protracted nature of IHD pathogenesis. We recruited 1,241 middle-aged Europeans, including healthy individuals, individuals with dysmetabolic morbidities (obesity and type 2 diabetes) but lacking overt IHD diagnosis and individuals with IHD at three distinct clinical stages-acute coronary syndrome, chronic IHD and IHD with heart failure-and characterized their phenome, gut metagenome and serum and urine metabolome. We found that about 75% of microbiome and metabolome features that distinguish individuals with IHD from healthy individuals after adjustment for effects of medication and lifestyle are present in individuals exhibiting dysmetabolism, suggesting that major alterations of the gut microbiome and metabolome might begin long before clinical onset of IHD. We further categorized microbiome and metabolome signatures related to prodromal dysmetabolism, specific to IHD in general or to each of its three subtypes or related to escalation or de-escalation of IHD. Discriminant analysis based on specific IHD microbiome and metabolome features could better differentiate individuals with IHD from healthy individuals or metabolically matched individuals as compared to the conventional risk markers, pointing to a pathophysiological relevance of these features.
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15.
  • Froslev Nielsen, Jens Christian, 1987, et al. (författare)
  • Comparative Transcriptome Analysis Shows Conserved Metabolic Regulation during Production of Secondary Metabolites in Filamentous Fungi
  • 2019
  • Ingår i: mSystems. - 2379-5077. ; 4:2
  • Tidskriftsartikel (refereegranskat)abstract
    • Filamentous fungi possess great potential as sources of medicinal bioactive compounds, such as antibiotics, but efficient production is hampered by a limited understanding of how their metabolism is regulated. We investigated the metabolism of six secondary metabolite-producing fungi of the Penicillium genus during nutrient depletion in the stationary phase of batch fermentations and assessed conserved metabolic responses across species using genome-wide transcriptional profiling. A coexpression analysis revealed that expression of biosynthetic genes correlates with expression of genes associated with pathways responsible for the generation of precursor metabolites for secondary metabolism. Our results highlight the main metabolic routes for the supply of precursors for secondary metabolism and suggest that the regulation of fungal metabolism is tailored to meet the demands for secondary metabolite production. These findings can aid in identifying fungal species that are optimized for the production of specific secondary metabolites and in designing metabolic engineering strategies to develop high-yielding fungal cell factories for production of secondary metabolites. IMPORTANCE Secondary metabolites are a major source of pharmaceuticals, especially antibiotics. However, the development of efficient processes of production of secondary metabolites has proved troublesome due to a limited understanding of the metabolic regulations governing secondary metabolism. By analyzing the conservation in gene expression across secondary metabolite-producing fungal species, we identified a metabolic signature that links primary and secondary metabolism and that demonstrates that fungal metabolism is tailored for the efficient production of secondary metabolites. The insight that we provide can be used to develop high-yielding fungal cell factories that are optimized for the production of specific secondary metabolites of pharmaceutical interest.
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16.
  • Froslev Nielsen, Jens Christian, 1987, et al. (författare)
  • Global analysis of biosynthetic gene clusters reveals vast potential of secondary metabolite production in Penicillium species
  • 2017
  • Ingår i: Nature Microbiology. - : Springer Science and Business Media LLC. - 2058-5276. ; 2:6
  • Tidskriftsartikel (refereegranskat)abstract
    • Filamentous fungi produce a wide range of bioactive compounds with important pharmaceutical applications, such as antibiotic penicillins and cholesterol-lowering statins. However, less attention has been paid to fungal secondary metabolites compared to those from bacteria. In this study, we sequenced the genomes of 9 Penicillium species and, together with 15 published genomes, we investigated the secondary metabolism of Penicillium and identified an immense, unexploited potential for producing secondary metabolites by this genus. A total of 1,317 putative biosynthetic gene clusters (BGCs) were identified, and polyketide synthase and non-ribosomal peptide synthetase based BGCs were grouped into gene cluster families and mapped to known pathways. The grouping of BGCs allowed us to study the evolutionary trajectory of pathways based on 6-methylsalicylic acid (6-MSA) synthases. Finally, we cross-referenced the predicted pathways with published data on the production of secondary metabolites and experimentally validated the production of antibiotic yanuthones in Penicillia and identified a previously undescribed compound from the yanuthone pathway. This study is the first genus-wide analysis of the genomic diversity of Penicillia and highlights the potential of these species as a source of new antibiotics and other pharmaceuticals.
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17.
  • Gao, Xiang, et al. (författare)
  • Characterization of two β-galactosidases LacZ and WspA1 from Nostoc flagelliforme with focus on the latter’s central active region
  • 2021
  • Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322 .- 2045-2322. ; 11:1
  • Tidskriftsartikel (refereegranskat)abstract
    • The identification and characterization of new β-galactosidases will provide diverse candidate enzymes for use in food processing industry. In this study, two β-galactosidases, Nf-LacZ and WspA1, from the terrestrial cyanobacterium Nostoc flagelliforme were heterologously expressed in Escherichia coli, followed by purification and biochemical characterization. Nf-LacZ was characterized to have an optimum activity at 40 °C and pH 6.5, different from that (45 °C and pH 8.0) of WspA1. Two enzymes had a similar Michaelis constant (Km = 0.5 mmol/liter) against the substrate o-nitrophenyl-β-D-galactopyranoside. Their activities could be inhibited by galactostatin bisulfite, with IC50 values of 0.59 µM for Nf-LacZ and 1.18 µM for WspA1, respectively. Gel filtration analysis suggested that the active form of WspA1 was a dimer, while Nf-LacZ was functional as a larger multimer. WspA1 was further characterized by the truncation test, and its minimum central region was found to be from residues 188 to 301, having both the glycosyl hydrolytic and transgalactosylation activities. Finally, transgenic analysis with the GFP reporter protein found that the N-terminus of WspA1 (35 aa) might play a special role in the export of WspA1 from cells. In summary, this study characterized two cyanobacterial β-galactosidases for potential applications in food industry.
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18.
  • Gao, Xiang, et al. (författare)
  • Cold adaptation in drylands: transcriptomic insights into cold-stressed Nostoc flagelliforme and characterization of a hypothetical gene with cold and nitrogen stress tolerance
  • 2021
  • Ingår i: Environmental Microbiology. - : Wiley. - 1462-2920 .- 1462-2912. ; 23:2, s. 713-727
  • Tidskriftsartikel (refereegranskat)abstract
    • Environmental stressors, especially low temperature, are very common on the earth's dryland systems. Terrestrial cyanobacteria have evolved with cold adaptability in addition to extreme dryness and high irradiation resistance. The dryland soil surface-dwelling species, Nostoc flagelliforme, serves as a potential model organism to gain insights into cyanobacterial cold adaptation. In this study, we performed transcriptomic analysis of N. flagelliforme samples in response to low temperature. The results revealed that the biological processes, such as terpenoid biosynthetic process, oxidoreductase activity, carbohydrate metabolism, biosynthesis of secondary metabolites, lipid and nitrogen metabolism, were significantly and dynamically changed during the cold stress. It was noteworthy that the transcription of the denitrification pathway for ammonia accumulation was enhanced, implying an importance for nitrogen utilization in stress resistance. In addition, characterization of a cold-responsive hypothetical gene csrnf1 found that it could greatly improve the cold-resistant performance of cells when it was heterologously expressed in transgenic Nostoc sp. PCC 7120. It was also found that csrnf1 transgenic strain exhibited resistance to nitrogen-deficient environmental stress. Considering that dryland cyanobacteria have to cope with low temperature on infertile soils, this study would enrich our understanding on the importance of multifunction of the genes for environmental cold adaptation in drylands.
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19.
  • Gao, Xiang, et al. (författare)
  • Profiling of Small Molecular Metabolites in Nostoc flagelliforme during Periodic Desiccation
  • 2019
  • Ingår i: Marine Drugs. - : MDPI AG. - 1660-3397. ; 17:5
  • Tidskriftsartikel (refereegranskat)abstract
    • The mass spectrometry-based metabolomics approach has become a powerful tool for the quantitative analysis of small-molecule metabolites in biological samples. Nostoc flagelliforme, an edible cyanobacterium with herbal value, serves as an unexploited bioresource for small molecules. In natural environments, N. flagelliforme undergoes repeated cycles of rehydration and dehydration, which are interrupted by either long- or short-term dormancy. In this study, we performed an untargeted metabolite profiling of N. flagelliforme samples at three physiological states: Dormant (S1), physiologically fully recovered after rehydration (S2), and physiologically partially inhibited following dehydration (S3). Significant metabolome differences were identified based on the OPLS-DA (orthogonal projections to latent structures discriminant analysis) model. In total, 183 differential metabolites (95 up-regulated; 88 down-regulated) were found during the rehydration process (S2 vs. S1), and 130 (seven up-regulated; 123 down-regulated) during the dehydration process (S3 vs. S2). Thus, it seemed that the metabolites' biosynthesis mainly took place in the rehydration process while the degradation or possible conversion occurred in the dehydration process. In addition, lipid profile differences were particularly prominent, implying profound membrane phase changes during the rehydration-dehydration cycle. In general, this study expands our understanding of the metabolite dynamics in N. flagelliforme and provides biotechnological clues for achieving the efficient production of those metabolites with medical potential.
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20.
  • Gao, Xiang, et al. (författare)
  • Promoting efficient production of scytonemin in cell culture of Nostoc flagelliforme by periodic short-term solar irradiation
  • 2023
  • Ingår i: Bioresource Technology Reports. - : Elsevier BV. - 2589-014X. ; 21
  • Tidskriftsartikel (refereegranskat)abstract
    • The ultraviolet-screening pigment scytonemin is bio-synthesized in some sheathed cyanobacteria, exhibiting important ecological and medicinal values. Scytonemin is recognized to be predominantly induced by ultraviolet (UV)-A/B, but UV radiation is often inhibitory for cyanobacterial biomass increase. Here, we found that short-term shock (within 1 h) of natural sunlight could trigger a persistent production of scytonemin in cell suspension culture of Nostoc flagelliforme for several days. We thus exposed the cultures to solar radiation with different time intervals and durations, and found that everyday 30-min solar irradiation was the most effective for achieving the scytonemin production with less growth inhibition. Besides, the technological potential could be advanced by supplementing NaHCO3 or tryptophan in the cultural medium. This work presents a good example of rationally utilizing environmental solar radiation for effectively producing UV-inducible biochemicals in cyanobacteria.
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21.
  • Geng, Jun, 1985, et al. (författare)
  • CODY enables quantitatively spatiotemporal predictions on in vivo gut microbial variability induced by diet intervention
  • 2021
  • Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 118:13
  • Tidskriftsartikel (refereegranskat)abstract
    • Microbial variations in the human gut are harbored in temporal and spatial heterogeneity, and quantitative prediction of spatiotemporal dynamic changes in the gut microbiota is imperative for development of tailored microbiome-directed therapeutics treatments, e.g. precision nutrition. Given the high-degree complexity of microbial variations, subject to the dynamic interactions among host, microbial, and environmental factors, identifying how microbiota colonize in the gut represents an important challenge. Here we present COmputing the DYnamics of microbiota (CODY), a multiscale framework that integrates species-level modeling of microbial dynamics and ecosystem-level interactions into a mathematical model that characterizes spatial-specific in vivo microbial residence in the colon as impacted by host physiology. The framework quantifies spatiotemporal resolution of microbial variations on species-level abundance profiles across site-specific colon regions and in feces, independent of a priori knowledge. We demonstrated the effectiveness of CODY using cross-sectional data from two longitudinal metagenomics studies—the microbiota development during early infancy and during short-term diet intervention of obese adults. For each cohort, CODY correctly predicts the microbial variations in response to diet intervention, as validated by available metagenomics and metabolomics data. Model simulations provide insight into the biogeographical heterogeneity among lumen, mucus, and feces, which provides insight into how host physical forces and spatial structure are shaping microbial structure and functionality.
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22.
  • Ji, Boyang, 1983, et al. (författare)
  • From next-generation sequencing to systematic modeling of the gut microbiome
  • 2015
  • Ingår i: Frontiers in Genetics. - : Frontiers Media SA. - 1664-8021. ; 6:JUN
  • Forskningsöversikt (refereegranskat)abstract
    • Changes in the human gut microbiome are associated with altered human metabolism and health, yet the mechanisms of interactions between microbial species and human metabolism have not been clearly elucidated. Next-generation sequencing has revolutionized the human gut microbiome research, but most current applications concentrate on studying the microbial diversity of communities and have at best provided associations between specific gut bacteria and human health. However, little is known about the inner metabolic mechanisms in the gut ecosystem. Here we review recent progress in modeling the metabolic interactions of gut microbiome, with special focus on the utilization of metabolic modeling to infer host-microbe interactions and microbial species interactions. The systematic modeling of metabolic interactions could provide a predictive understanding of gut microbiome, and pave the way to synthetic microbiota design and personalized-microbiome medicine and healthcare. Finally, we discuss the integration of metabolic modeling and gut microbiome engineering, which offer a new way to explore metabolic interactions across members of the gut microbiota.
  •  
23.
  • Ji, Boyang, 1983, et al. (författare)
  • New insight into the gut microbiome through metagenomics
  • 2015
  • Ingår i: Advances in Genomics and Genetics. - 1179-9870. ; 5, s. 77-91
  • Tidskriftsartikel (refereegranskat)abstract
    • The human gut is colonized by different types of microorganisms, which are known to play important roles in the human host by maintaining physiological homeostasis. The human host provides a nutrient-rich environment, and the microbiota provides some necessary functions that humans cannot perform. A comprehensive analysis of the human gut microbiome is thus important for revealing the mechanisms of these host–microbe interactions. The development of high-throughput sequencing technology and related computational frameworks enables exploration of the metabolic interactions and their roles in human health and diseases. Herein, we describe the metagenomic methods used in human gut microbiome studies and review the roles of gut microbiota as well as the integrative analyses of metagenomic data with other omics data. Finally, we discuss the application of constraint-based modeling to elucidate the microbe–microbe interaction and host–microbe interaction in the human gut microbiota.
  •  
24.
  • Ji, Boyang, 1983, et al. (författare)
  • The chimeric nature of the genomes of marine magnetotactic coccoid-ovoid bacteria defines a novel group of Proteobacteria
  • 2017
  • Ingår i: Environmental Microbiology. - : Wiley. - 1462-2920 .- 1462-2912. ; 19:3, s. 1103-1119
  • Tidskriftsartikel (refereegranskat)abstract
    • Magnetotactic bacteria (MTB) are a group of phylogenetically and physiologically diverse Gram-negative bacteria that synthesize intracellular magnetic crystals named magnetosomes. MTB are affiliated with three classes of Proteobacteria phylum, Nitrospirae phylum, Omnitrophica phylum and probably with the candidate phylum Latescibacteria. The evolutionary origin and physiological diversity of MTB compared with other bacterial taxonomic groups remain to be illustrated. Here, we analysed the genome of the marine magneto-ovoid strain MO-1 and found that it is closely related to Magnetococcus marinus MC-1. Detailed analyses of the ribosomal proteins and whole proteomes of 390 genomes reveal that, among the Proteobacteria analysed, only MO-1 and MC-1 have coding sequences (CDSs) with a similarly high proportion of origins from Alphaproteobacteria, Betaproteobacteria, Deltaproteobacteria and Gammaproteobacteria. Interestingly, a comparative metabolic network analysis with anoxic network enzymes from sequenced MTB and non-MTB successfully allows the eventual prediction of an organism with a metabolic profile compatible for magnetosome production. Altogether, our genomic analysis reveals multiple origins of MO-1 and M. marinus MC-1 genomes and suggests a metabolism-restriction model for explaining whether a bacterium could become an MTB upon acquisition of magnetosome encoding genes.
  •  
25.
  • Kalantari, Aida, 1986, et al. (författare)
  • Conversion of Glycerol to 3-Hydroxypropanoic Acid by Genetically Engineered Bacillus subtilis
  • 2017
  • Ingår i: Frontiers in Microbiology. - : Frontiers Media SA. - 1664-302X. ; 8:APR
  • Tidskriftsartikel (refereegranskat)abstract
    • 3-Hydroxypropanoic acid (3-HP) is an important biomass-derivable platform chemical that can be converted into a number of industrially relevant compounds. There have been several attempts to produce 3-HP from renewable sources in cell factories, focusing mainly on Escherichia coli, Klebsiella pneumoniae, and Saccharomyces cerevisiae. Despite the significant progress made in this field, commercially exploitable large-scale production of 3-HP in microbial strains has still not been achieved. In this study, we investigated the potential of Bacillus subtilis as a microbial platform for bioconversion of glycerol into 3-HP. Our recombinant B. subtilis strains overexpress the two-step heterologous pathway containing glycerol dehydratase and aldehyde dehydrogenase from K. pneumoniae. Genetic engineering, driven by in silico optimization, and optimization of cultivation conditions resulted in a 3-HP titer of 10 g/L, in a standard batch cultivation. Our findings provide the first report of successful introduction of the biosynthetic pathway for conversion of glycerol into 3-HP in B. subtilis. With this relatively high titer in batch, and the robustness of B. subtilis in high density fermentation conditions, we expect that our production strains may constitute a solid basis for commercial production of 3-HP.
  •  
26.
  • Kumar, Manish, 1982, et al. (författare)
  • Gut microbiota dysbiosis is associated with malnutrition and reduced plasma amino acid levels: Lessons from genome-scale metabolic modeling
  • 2018
  • Ingår i: Metabolic Engineering. - : Elsevier BV. - 1096-7176 .- 1096-7184. ; 49, s. 128-142
  • Tidskriftsartikel (refereegranskat)abstract
    • Malnutrition is a severe non-communicable disease, which is prevalent in children from low-income countries. Recently, a number of metagenomics studies have illustrated associations between the altered gut microbiota and child malnutrition. However, these studies did not examine metabolic functions and interactions between individual species in the gut microbiota during health and malnutrition. Here, we applied genome-scale metabolic modeling to model the gut microbial species, which were selected from healthy and malnourished children from three countries. Our analysis showed reduced metabolite production capabilities in children from two lowincome countries compared with a high-income country. Additionally, the models were also used to predict the community-level metabolic potentials of gut microbes and the patterns of pairwise interactions among species. Hereby we found that due to bacterial interactions there may be reduced production of certain amino acids in malnourished children compared with healthy children from the same communities. To gain insight into alterations in the metabolism of malnourished (stunted) children, we also performed targeted plasma metabolic profiling in the first 2 years of life of 25 healthy and 25 stunted children. Plasma metabolic profiling further revealed that stunted children had reduced plasma levels of essential amino acids compared to healthy controls. Our analyses provide a framework for future efforts towards further characterization of gut microbial metabolic capabilities and their contribution to malnutrition.
  •  
27.
  • Kumar, Manish, 1982, et al. (författare)
  • Human gut microbiota and healthy aging: Recent developments and future prospective
  • 2016
  • Ingår i: Nutrition and healthy aging. - 2451-9480. ; 4:1, s. 3-16
  • Tidskriftsartikel (refereegranskat)abstract
    • The human gut microbiota alters with the aging process. In the first 2-3 years of life, the gut microbiota varies extensively in composition and metabolic functions. After this period, the gut microbiota demonstrates adult-like more stable and diverse microbial species. However, at old age, deterioration of physiological functions of the human body enforces the decrement in count of beneficial species (e.g. Bifidobacteria) in the gut microbiota, which promotes various gut-related diseases (e.g. inflammatory bowel disease). Use of plant-based diets and probiotics/prebiotics may elevate the abundance of beneficial species and prevent gut-related diseases. Still, the connections between diet, microbes, and host are only partially known. To this end, genome-scale metabolic modeling can help to explore these connections as well as to expand the understanding of the metabolic capability of each species in the gut microbiota. This systems biology approach can also predict metabolic variations in the gut microbiota during ageing, and hereby help to design more effective probiotics/prebiotics.
  •  
28.
  • Kumar, Manish, 1982, et al. (författare)
  • Modelling approaches for studying the microbiome
  • 2019
  • Ingår i: Nature Microbiology. - : Springer Science and Business Media LLC. - 2058-5276. ; 4:8, s. 1253-1267
  • Forskningsöversikt (refereegranskat)abstract
    • Advances in metagenome sequencing of the human microbiome have provided a plethora of new insights and revealed a close association of this complex ecosystem with a range of human diseases. However, there is little knowledge about how the different members of the microbial community interact with each other and with the host, and we lack basic mechanistic understanding of these interactions related to health and disease. Mathematical modelling has been demonstrated to be highly advantageous for gaining insights into the dynamics and interactions of complex systems and in recent years, several modelling approaches have been proposed to enhance our understanding of the microbiome. Here, we review the latest developments and current approaches, and highlight how different modelling strategies have been applied to unravel the highly dynamic nature of the human microbiome. Furthermore, we discuss present limitations of different modelling strategies and provide a perspective of how modelling can advance understanding and offer new treatment routes to impact human health.
  •  
29.
  • Lappa, Dimitra, 1988, et al. (författare)
  • Self-organized metabotyping of obese individuals identifies clusters responding differently to bariatric surgery
  • 2023
  • Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203 .- 1932-6203. ; 18:3, s. e0279335-
  • Tidskriftsartikel (refereegranskat)abstract
    • Weight loss through bariatric surgery is efficient for treatment or prevention of obesity related diseases such as type 2 diabetes and cardiovascular disease. Long term weight loss response does, however, vary among patients undergoing surgery. Thus, it is difficult to identify predictive markers while most obese individuals have one or more comorbidities. To overcome such challenges, an in-depth multiple omics analyses including fasting peripheral plasma metabolome, fecal metagenome as well as liver, jejunum, and adipose tissue transcriptome were performed for 106 individuals undergoing bariatric surgery. Machine leaning was applied to explore the metabolic differences in individuals and evaluate if metabolism-based patients' stratification is related to their weight loss responses to bariatric surgery. Using Self-Organizing Maps (SOMs) to analyze the plasma metabolome, we identified five distinct metabotypes, which were differentially enriched for KEGG pathways related to immune functions, fatty acid metabolism, protein-signaling, and obesity pathogenesis. The gut metagenome of the most heavily medicated metabotypes, treated simultaneously for multiple cardiometabolic comorbidities, was significantly enriched in Prevotella and Lactobacillus species. This unbiased stratification into SOM-defined metabotypes identified signatures for each metabolic phenotype and we found that the different metabotypes respond differently to bariatric surgery in terms of weight loss after 12 months. An integrative framework that utilizes SOMs and omics integration was developed for stratifying a heterogeneous bariatric surgery cohort. The multiple omics datasets described in this study reveal that the metabotypes are characterized by a concrete metabolic status and different responses in weight loss and adipose tissue reduction over time. Our study thus opens a path to enable patient stratification and hereby allow for improved clinical treatments.
  •  
30.
  • Li, Gang, 1991, et al. (författare)
  • Bayesian genome scale modelling identifies thermal determinants of yeast metabolism
  • 2021
  • Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 12:1
  • Tidskriftsartikel (refereegranskat)abstract
    • The molecular basis of how temperature affects cell metabolism has been a long-standing question in biology, where the main obstacles are the lack of high-quality data and methods to associate temperature effects on the function of individual proteins as well as to combine them at a systems level. Here we develop and apply a Bayesian modeling approach to resolve the temperature effects in genome scale metabolic models (GEM). The approach minimizes uncertainties in enzymatic thermal parameters and greatly improves the predictive strength of the GEMs. The resulting temperature constrained yeast GEM uncovers enzymes that limit growth at superoptimal temperatures, and squalene epoxidase (ERG1) is predicted to be the most rate limiting. By replacing this single key enzyme with an ortholog from a thermotolerant yeast strain, we obtain a thermotolerant strain that outgrows the wild type, demonstrating the critical role of sterol metabolism in yeast thermosensitivity. Therefore, apart from identifying thermal determinants of cell metabolism and enabling the design of thermotolerant strains, our Bayesian GEM approach facilitates modelling of complex biological systems in the absence of high-quality data and therefore shows promise for becoming a standard tool for genome scale modeling.
  •  
31.
  • Li, Gang, 1991, et al. (författare)
  • The pan-genome of Saccharomyces cerevisiae
  • 2019
  • Ingår i: FEMS Yeast Research. - : Oxford University Press (OUP). - 1567-1356 .- 1567-1364. ; 19:7
  • Tidskriftsartikel (refereegranskat)abstract
    • Understanding genotype-phenotype relationship is fundamental in biology. With the benefit from next-generation sequencing and high-throughput phenotyping methodologies, there have been generated much genome and phenome data for Saccharomyces cerevisiae. This makes it an excellent model system to understand the genotype-phenotype relationship. In this paper, we presented the reconstruction and application of the yeast pan-genome in resolving genotype-phenotype relationship by a machine learning-assisted approach.
  •  
32.
  • Li, Peishun, 1988, et al. (författare)
  • Machine learning for data integration in human gut microbiome
  • 2022
  • Ingår i: Microbial Cell Factories. - : Springer Science and Business Media LLC. - 1475-2859. ; 21:1
  • Forskningsöversikt (refereegranskat)abstract
    • Recent studies have demonstrated that gut microbiota plays critical roles in various human diseases. High-throughput technology has been widely applied to characterize the microbial ecosystems, which led to an explosion of different types of molecular profiling data, such as metagenomics, metatranscriptomics and metabolomics. For analysis of such data, machine learning algorithms have shown to be useful for identifying key molecular signatures, discovering potential patient stratifications, and particularly for generating models that can accurately predict phenotypes. In this review, we first discuss how dysbiosis of the intestinal microbiota is linked to human disease development and how potential modulation strategies of the gut microbial ecosystem can be used for disease treatment. In addition, we introduce categories and workflows of different machine learning approaches, and how they can be used to perform integrative analysis of multi-omics data. Finally, we review advances of machine learning in gut microbiome applications and discuss related challenges. Based on this we conclude that machine learning is very well suited for analysis of gut microbiome and that these approaches can be useful for development of gut microbe-targeted therapies, which ultimately can help in achieving personalized and precision medicine.
  •  
33.
  • Li, Peishun, 1988, et al. (författare)
  • Metabolic Alterations in Older Women With Low Bone Mineral Density Supplemented With Lactobacillus reuteri
  • 2021
  • Ingår i: JBMR Plus. - : Wiley. - 2473-4039. ; 5:4
  • Tidskriftsartikel (refereegranskat)abstract
    • JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research. Osteoporosis and its associated fractures are highly prevalent in older women. Recent studies have shown that gut microbiota play important roles in regulating bone metabolism. A previous randomized controlled trial (RCT) found that supplementation with Lactobacillus reuteri ATCC PTA 6475 (L.reuteri) led to substantially reduced bone loss in older women with low BMD. However, the total metabolic effects of L. reuteri supplementation on older women are still not clear. In this study, a post hoc analysis (not predefined) of serum metabolomic profiles of older women from the previous RCT was performed to investigate the metabolic dynamics over 1 year and to evaluate the effects of L. reuteri supplementation on human metabolism. Distinct segregation of the L. reuteri and placebo groups in response to the treatment was revealed by partial least squares-discriminant analysis. Although no individual metabolite was differentially and significantly associated with treatment after correction for multiple testing, 97 metabolites responded differentially at any one time point between L. reuteri and placebo groups (variable importance in projection score >1 and p value <0.05). These metabolites were involved in multiple processes, including amino acid, peptide, and lipid metabolism. Butyrylcarnitine was particularly increased at all investigated time points in the L. reuteri group compared with placebo, indicating that the effects of L. reuteri on bone loss are mediated through butyrate signaling. Furthermore, the metabolomic profiles in a case (low BMD) and control population (high BMD) of elderly women were analyzed to confirm the associations between BMD and the identified metabolites regulated by L. reuteri supplementation. The amino acids, especially branched-chain amino acids, showed association with L. reuteri treatment and with low BMD in older women, and may serve as potential therapeutic targets. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
  •  
34.
  • Li, Peishun, 1988, et al. (författare)
  • Metabolic engineering of human gut microbiome: Recent developments and future perspectives
  • 2023
  • Ingår i: Metabolic Engineering. - 1096-7176 .- 1096-7184. ; 79, s. 1-13
  • Forskningsöversikt (refereegranskat)abstract
    • Many studies have demonstrated that the gut microbiota is associated with human health and disease. Manipulation of the gut microbiota, e.g. supplementation of probiotics, has been suggested to be feasible, but subject to limited therapeutic efficacy. To develop efficient microbiota-targeted diagnostic and therapeutic strategies, metabolic engineering has been applied to construct genetically modified probiotics and synthetic microbial consortia. This review mainly discusses commonly adopted strategies for metabolic engineering in the human gut microbiome, including the use of in silico, in vitro, or in vivo approaches for iterative design and construction of engineered probiotics or microbial consortia. Especially, we highlight how genome-scale metabolic models can be applied to advance our understanding of the gut microbiota. Also, we review the recent applications of metabolic engineering in gut microbiome studies as well as discuss important challenges and opportunities.
  •  
35.
  • Li, Peishun, 1988, et al. (författare)
  • One-year supplementation with Lactobacillus reuteri ATCC PTA 6475 counteracts a degradation of gut microbiota in older women with low bone mineral density
  • 2022
  • Ingår i: npj Biofilms and Microbiomes. - : Springer Science and Business Media LLC. - 2055-5008. ; 8:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Recent studies have shown that probiotic supplementation has beneficial effects on bone metabolism. In a randomized controlled trial (RCT) we demonstrated that supplementation of Lactobacillus reuteri ATCC PTA 6475 reduced bone loss in older women with low bone mineral density. To investigate the mechanisms underlying the effect of L. reuteri ATCC PTA 6475 on bone metabolism, 20 women with the highest changes (good responders) and the lowest changes (poor responders) in tibia total volumetric BMD after one-year supplementation were selected from our previous RCT. In the current study we characterized the gut microbiome composition and function as well as serum metabolome in good responders and poor responders to the probiotic treatment as a secondary analysis. Although there were no significant differences in the microbial composition at high taxonomic levels, gene richness of the gut microbiota was significantly higher (P < 0.01 by the Wilcoxon rank-sum test) and inflammatory state was improved (P < 0.05 by the Wilcoxon signed-rank test) in the good responders at the end of the 12-month daily supplementation. Moreover, detrimental changes including the enrichment of E. coli (adjusted P < 0.05 by DESeq2) and its biofilm formation (P < 0.05 by GSA) observed in the poor responders were alleviated in the good responders by the treatment. Our results indicate that L. reuteri ATCC PTA 6475 supplementation has the potential to prevent a deterioration of the gut microbiota and inflammatory status in elderly women with low bone mineral density, which might have beneficial effects on bone metabolism.
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36.
  • Li, Yonghong, et al. (författare)
  • Microbial profiling identifies potential key drivers in gastric cancer patients
  • 2021
  • Ingår i: Biotechnology and Biotechnological Equipment. - : Informa UK Limited. - 1310-2818 .- 1314-3530. ; 35:1, s. 496-503
  • Tidskriftsartikel (refereegranskat)abstract
    • Gastric cancer (GC) is the fifth most commonly diagnosed cancer and the third leading cause of cancer-related death in the world. Microbiota is believed to be associated with GC. Growing evidences showed Helicobacter pylori played a key role in GC development. However, little was known about the microbiota in gastric juices and tissues in GC patients, and thus it was difficult to understand other potential microbial causation for GC. Here, we collected the gastric juice and surgically removed gastric tissues from GC patients to give insight into GC microbiota. Most microbes identified in the gastric samples were opportunistic pathogens or resident flora of the human microbiota. Further network analyses identified five opportunistic pathogens as keystone species. H. pylori is the direct cause of GC, but other opportunistic microbes might also function in GC development. The microbiota in the gastric juice and gastric tissue of the GC patients were complex, and some dominant opportunistic pathogens contributed to the GC development. This study introduces microbiota in gastric juice, gastric normal tissue and gastric cancer tissue of GC patients, and highlights the potential keystone microbes functioned during GC development.
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37.
  • Limeta, Angelo, 1996, et al. (författare)
  • Leveraging high-resolution omics data for predicting responses and adverse events to immune checkpoint inhibitors
  • 2023
  • Ingår i: Computational and Structural Biotechnology Journal. - 2001-0370. ; 21, s. 3912-3919
  • Forskningsöversikt (refereegranskat)abstract
    • A long-standing goal of personalized and precision medicine is to enable accurate prediction of the outcomes of a given treatment regimen for patients harboring a disease. Currently, many clinical trials fail to meet their endpoints due to underlying factors in the patient population that contribute to either poor responses to the drug of interest or to treatment-related adverse events. Identifying these factors beforehand and correcting for them can lead to an increased success of clinical trials. Comprehensive and large-scale data gathering efforts in biomedicine by omics profiling of the healthy and diseased individuals has led to a treasure-trove of host, disease and environmental factors that contribute to the effectiveness of drugs aiming to treat disease. With increasing omics data, artificial intelligence allows an in-depth analysis of big data and offers a wide range of applications for real-world clinical use, including improved patient selection and identification of actionable targets for companion therapeutics for improved translatability across more patients. As a blueprint for complex drug-disease-host interactions, we here discuss the challenges of utilizing omics data for predicting responses and adverse events in cancer immunotherapy with immune checkpoint inhibitors (ICIs). The omics-based methodologies for improving patient outcomes as in the ICI case have also been applied across a wide-range of complex disease settings, exemplifying the use of omics for in-depth disease profiling and clinical use.
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38.
  • Limeta, Angelo, 1996, et al. (författare)
  • Meta-analysis of the gut microbiota in predicting response to cancer immunotherapy in metastatic melanoma.
  • 2020
  • Ingår i: JCI insight. - : American Society for Clinical Investigation. - 2379-3708. ; 5:23
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUNDIdentifying factors conferring responses to therapy in cancer is critical to select the best treatment for patients. For immune checkpoint inhibition (ICI) therapy, mounting evidence suggests that the gut microbiome can determine patient treatment outcomes. However, the extent to which gut microbial features are applicable across different patient cohorts has not been extensively explored.METHODSWe performed a meta-analysis of 4 published shotgun metagenomic studies (Ntot = 130 patients) investigating differential microbiome composition and imputed metabolic function between responders and nonresponders to ICI.RESULTSOur analysis identified both known microbial features enriched in responders, such as Faecalibacterium as the prevailing taxa, as well as additional features, including overrepresentation of Barnesiella intestinihominis and the components of vitamin B metabolism. A classifier designed to predict responders based on these features identified responders in an independent cohort of 27 patients with the area under the receiver operating characteristic curve of 0.625 (95% CI: 0.348-0.899) and was predictive of prognosis (HR = 0.35, P = 0.081).CONCLUSIONThese results suggest the existence of a fecal microbiome signature inherent across responders that may be exploited for diagnostic or therapeutic purposes.FUNDINGThis work was funded by the Knut and Alice Wallenberg Foundation, BioGaia AB, and Cancerfonden.
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39.
  • Liu, Xiaoqin, et al. (författare)
  • Mapping of Nonhomologous End Joining-Mediated Integration Facilitates Genome-Scale Trackable Mutagenesis in Yarrowia lipolytica
  • 2022
  • Ingår i: ACS Synthetic Biology. - : American Chemical Society (ACS). - 2161-5063. ; 11:1, s. 216-227
  • Tidskriftsartikel (refereegranskat)abstract
    • Genome-scale mutagenesis, phenotypic screening, and tracking the causal mutations is a powerful approach for genetic analysis. However, classic mutagenesis approaches require extensive effort to identify causal mutations. It is desirable to demonstrate a powerful approach for rapid trackable mutagenesis. Here, we mapped the distribution of nonhomologous end joining (NHEJ)-mediated integration for the first time and demonstrated that it can be used for constructing the genome-scale trackable mutagenesis library in Yarrowia lipolytica. The sequencing of 9.15 x 10(5) insertions showed that NHEJ-mediated integration inserted DNA randomly across the chromosomes, and the transcriptional regulatory regions exhibited integration preference. The insertions were located in both nucleosome-occupancy regions and nucleosome-free regions. Using NHEJ-mediated integration to construct the genome-scale mutagenesis library, the new targets that improved beta-carotene biosynthesis and acetic acid tolerance were identified rapidly. This mutagenesis approach is readily applicable to other organisms with strong NHEJ preference and will contribute to cell factory construction.
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40.
  • Liu, Yuanfeng, et al. (författare)
  • Exploring Gut Microbiota in Patients with Colorectal Disease Based on 16S rRNA Gene Amplicon and Shallow Metagenomic Sequencing
  • 2021
  • Ingår i: Frontiers in Molecular Biosciences. - : Frontiers Media SA. - 2296-889X. ; 8
  • Tidskriftsartikel (refereegranskat)abstract
    • The gastrointestinal tract, the largest human microbial reservoir, is highly dynamic. The gut microbes play essential roles in causing colorectal diseases. In the present study, we explored potential keystone taxa during the development of colorectal diseases in central China. Fecal samples of some patients were collected and were allocated to the adenoma (Group A), colorectal cancer (Group C), and hemorrhoid (Group H) groups. The 16S rRNA amplicon and shallow metagenomic sequencing (SMS) strategies were used to recover the gut microbiota. Microbial diversities obtained from 16S rRNA amplicon and SMS data were similar. Group C had the highest diversity, although no significant difference in diversity was observed among the groups. The most dominant phyla in the gut microbiota of patients with colorectal diseases were Bacteroidetes, Firmicutes, and Proteobacteria, accounting for >95% of microbes in the samples. The most abundant genera in the samples were Bacteroides, Prevotella, and Escherichia/Shigella, and further species-level and network analyses identified certain potential keystone taxa in each group. Some of the dominant species, such as Prevotella copri, Bacteroides dorei, and Bacteroides vulgatus, could be responsible for causing colorectal diseases. The SMS data recovered diverse antibiotic resistance genes of tetracycline, macrolide, and beta-lactam, which could be a result of antibiotic overuse. This study explored the gut microbiota of patients with three different types of colorectal diseases, and the microbial diversity results obtained from 16S rRNA amplicon sequencing and SMS data were found to be similar. However, the findings of this study are based on a limited sample size, which warrants further large-scale studies. The recovery of gut microbiota profiles in patients with colorectal diseases could be beneficial for future diagnosis and treatment with modulation of the gut microbiota. Moreover, SMS data can provide accurate species- and gene-level information, and it is economical. It can therefore be widely applied in future clinical metagenomic studies.
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41.
  • Lu, Hongzhong, 1987, et al. (författare)
  • Yeast metabolic innovations emerged via expanded metabolic network and gene positive selection
  • 2021
  • Ingår i: Molecular Systems Biology. - : EMBO. - 1744-4292. ; 17:10
  • Tidskriftsartikel (refereegranskat)abstract
    • 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.
  •  
42.
  • Luo, Hao, 1992, et al. (författare)
  • Genome-scale insights into the metabolic versatility of Limosilactobacillus reuteri
  • 2021
  • Ingår i: BMC Biotechnology. - : Springer Science and Business Media LLC. - 1472-6750. ; 21:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Background Limosilactobacillus reuteri (earlier known as Lactobacillus reuteri) is a well-studied lactic acid bacterium, with some specific strains used as probiotics, that exists in different hosts such as human, pig, goat, mouse and rat, with multiple body sites such as the gastrointestinal tract, breast milk and mouth. Numerous studies have confirmed the beneficial effects of orally administered specific L. reuteri strains, such as preventing bone loss and promoting regulatory immune system development. L. reuteri ATCC PTA 6475 is a widely used strain that has been applied in the market as a probiotic due to its positive effects on the human host. Its health benefits may be due, in part, to the production of beneficial metabolites. Considering the strain-specific effects and genetic diversity of L. reuteri strains, we were interested to study the metabolic versatility of these strains. Results In this study, we aimed to systematically investigate the metabolic features and diversities of L. reuteri strains by using genome-scale metabolic models (GEMs). The GEM of L. reuteri ATCC PTA 6475 was reconstructed with a template-based method and curated manually. The final GEM iHL622 of L. reuteri ATCC PTA 6475 contains 894 reactions and 726 metabolites linked to 622 metabolic genes, which can be used to simulate growth and amino acids utilization. Furthermore, we built GEMs for the other 35 L. reuteri strains from three types of hosts. The comparison of the L. reuteri GEMs identified potential metabolic products linked to the adaptation to the host. Conclusions The GEM of L. reuteri ATCC PTA 6475 can be used to simulate metabolic capabilities and growth. The core and pan model of 35 L. reuteri strains shows metabolic capacity differences both between and within the host groups. The GEMs provide a reliable basis to investigate the metabolism of L. reuteri in detail and their potential benefits on the host.
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43.
  • Luo, Hao, 1992, et al. (författare)
  • Modeling the metabolic dynamics at the genome-scale by optimized yield analysis
  • 2023
  • Ingår i: Metabolic Engineering. - : Elsevier BV. - 1096-7176 .- 1096-7184. ; 75, s. 119-130
  • Tidskriftsartikel (refereegranskat)abstract
    • The hybrid cybernetic model (HCM) approach is a dynamic modeling framework that integrates enzyme synthesis and activity regulation. It has been widely applied in bioreaction engineering, particularly in the simulation of microbial growth in different mixtures of carbon sources. In a HCM, the metabolic network is decomposed into elementary flux modes (EFMs), whereby the network can be reduced into a few pathways by yield analysis. However, applying the HCM approach on conventional genome-scale metabolic models (GEMs) is still a challenge due to the high computational demands. Here, we present a HCM strategy that introduced an optimized yield analysis algorithm (opt-yield-FBA) to simulate metabolic dynamics at the genome-scale without the need for EFMs calculation. The opt-yield-FBA is a flux-balance analysis (FBA) based method that can calculate optimal yield solutions and yield space for GEM. With the opt-yield-FBA algorithm, the HCM strategy can be applied to get the yield spaces and avoid the computational burden of EFMs, and it can therefore be applied for developing dynamic models for genome-scale metabolic networks. Here, we illustrate the strategy by applying the concept to simulate the dynamics of microbial communities.
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44.
  • Marcisauskas, Simonas, 1988, et al. (författare)
  • Draft genome sequences of five fungal strains isolated from Kefir
  • 2021
  • Ingår i: Microbiology Resource Announcements. - 2576-098X. ; 10:21
  • Tidskriftsartikel (refereegranskat)abstract
    • We present the annotated draft genome sequences of five fungal strains isolated from kefir grains. These isolates included three ascomycetous (Candida californica, Kazachstania exigua, and Kazachstania unispora) and one basidiomycetous (Rhodotorula mucilaginosa) species. The results revealed a detailed overview of the metabolic features of kefir fungi that will be potentially useful in biotechnological applications.
  •  
45.
  • Marcisauskas, Simonas, 1988, et al. (författare)
  • Reconstruction and analysis of a Kluyveromyces marxianus genome-scale metabolic model
  • 2019
  • Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 20:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Kluyveromyces marxianus is a thermotolerant yeast with multiple biotechnological potentials for industrial applications, which can metabolize a broad range of carbon sources, including less conventional sugars like lactose, xylose, arabinose and inulin. These phenotypic traits are sustained even up to 45 °C, what makes it a relevant candidate for industrial biotechnology applications, such as ethanol production. It is therefore of much interest to get more insight into the metabolism of this yeast. Recent studies suggested, that thermotolerance is achieved by reducing the number of growth-determining proteins or suppressing oxidative phosphorylation. Here we aimed to find related factors contributing to the thermotolerance of K. marxianus. Results: Here, we reported the first genome-scale metabolic model of Kluyveromyces marxianus, iSM996, using a publicly available Kluyveromyces lactis model as template. The model was manually curated and refined to include the missing species-specific metabolic capabilities. The iSM996 model includes 1913 reactions, associated with 996 genes and 1531 metabolites. It performed well to predict the carbon source utilization and growth rates under different growth conditions. Moreover, the model was coupled with transcriptomics data and used to perform simulations at various growth temperatures. Conclusions: K. marxianus iSM996 represents a well-annotated metabolic model of thermotolerant yeast, which provides a new insight into theoretical metabolic profiles at different temperatures of K. marxianus. This could accelerate the integrative analysis of multi-omics data, leading to model-driven strain design and improvement.
  •  
46.
  • Motwalli, Olaa, et al. (författare)
  • In silico screening for candidate chassis strains of free fatty acid-producing cyanobacteria
  • 2017
  • Ingår i: BMC Genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 18:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Finding a source from which high-energy-density biofuels can be derived at an industrial scale has become an urgent challenge for renewable energy production. Some microorganisms can produce free fatty acids (FFA) as precursors towards such high-energy-density biofuels. In particular, photosynthetic cyanobacteria are capable of directly converting carbon dioxide into FFA. However, current engineered strains need several rounds of engineering to reach the level of production of FFA to be commercially viable thus new chassis strains that require less engineering are needed. Although more than 120 cyanobacterial genomes are sequenced, the natural potential of these strains for FFA production and excretion has not been systematically estimated. Results: Here we present the FFA SC (FFASC), an in silico screening method that evaluates the potential for FFA production and excretion of cyanobacterial strains based on their proteomes. A literature search allowed for the compilation of 64 proteins, most of which influence FFA production and a few of which affect FFA excretion. The proteins are classified into 49 orthologous groups (OGs) that helped create rules used in the scoring/ranking of algorithms developed to estimate the potential for FFA production and excretion of an organism. Among 125 cyanobacterial strains, FFASC identified 20 candidate chassis strains that rank in their FFA producing and excreting potential above the specifically engineered reference strain, Synechococcus sp. PCC 7002. We further show that the top ranked cyanobacterial strains are unicellular and primarily include Prochlorococcus (order Prochlorales) and marine Synechococcus (order Chroococcales) that cluster phylogenetically. Moreover, two principal categories of enzymes were shown to influence FFA production the most: those ensuring precursor availability for the biosynthesis of lipids, and those involved in handling the oxidative stress associated to FFA synthesis. Conclusion: To our knowledge FFASC is the first in silico method to screen cyanobacteria proteomes for their potential to produce and excrete FFA, as well as the first attempt to parameterize the criteria derived from genetic characteristics that are favorable/non-favorable for this purpose. Thus, FFASC helps focus experimental evaluation only on the most promising cyanobacteria.
  •  
47.
  • Qin, Jiufu, 1985, et al. (författare)
  • Engineering yeast metabolism for the discovery and production of polyamines and polyamine analogues
  • 2021
  • Ingår i: Nature Catalysis. - : Springer Science and Business Media LLC. - 2520-1158. ; 4:6, s. 498-509
  • Tidskriftsartikel (refereegranskat)abstract
    • Structurally complex and diverse polyamines and polyamine analogues are potential therapeutics and agrochemicals that can address grand societal challenges, for example, healthy ageing and sustainable food production. However, their structural complexity and low abundance in nature hampers either bulk chemical synthesis or extraction from natural resources. Here we reprogrammed the metabolism of baker’s yeast Saccharomyces cerevisiae and recruited nature’s diverse reservoir of biochemical tools to enable a complete biosynthesis of multiple polyamines and polyamine analogues. Specifically, we adopted a systematic engineering strategy to enable gram-per-litre-scale titres of spermidine, a central metabolite in polyamine metabolism. To demonstrate the potential of our polyamine platform, various polyamine synthases and ATP-dependent amide-bond-forming systems were introduced for the biosynthesis of natural and unnatural polyamine analogues. The yeast platform serves as a resource to accelerate the discovery and production of polyamines and polyamine analogues, and thereby unlocks this chemical space for further pharmacological and insecticidal studies. [Figure not available: see fulltext.]
  •  
48.
  • Shi, Lei, 1981, et al. (författare)
  • Evolution of Bacterial Protein-Tyrosine Kinases and Their Relaxed Specificity Toward Substrates
  • 2014
  • Ingår i: Genome Biology and Evolution. - : Oxford University Press (OUP). - 1759-6653. ; 6:4, s. 800-817
  • Tidskriftsartikel (refereegranskat)abstract
    • It has often been speculated that bacterial protein-tyrosine kinases (BY-kinases) evolve rapidly and maintain relaxed substrate specificity to quickly adopt new substrates when evolutionary pressure in that direction arises. Here, we report a phylogenomic and biochemical analysis of BY-kinases, and their relationship to substrates aimed to validate this hypothesis. Our results suggest that BY-kinases are ubiquitously distributed in bacterial phyla and underwent a complex evolutionary history, affected considerably by gene duplications and horizontal gene transfer events. This is consistent with the fact that the BY-kinase sequences represent a high level of substitution saturation and have a higher evolutionary rate compared with other bacterial genes. On the basis of similarity networks, we could classify BY kinases into three main groups with 14 subgroups. Extensive sequence conservation was observed only around the three canonical Walker motifs, whereas unique signatures proposed the functional speciation and diversification within some subgroups. The relationship between BY-kinases and their substrates was analyzed using a ubiquitous substrate (Ugd) and some Firmicute-specific substrates (YvyG and YjoA) from Bacillus subtilis. No evidence of coevolution between kinases and substrates at the sequence level was found. Seven BY-kinases, including well-characterized and previously uncharacterized ones, were used for experimental studies. Most of the tested kinases were able to phosphorylate substrates from B. subtilis (Ugd, YvyG, and YjoA), despite originating from very distant bacteria. Our results are consistent with the hypothesis that BY-kinases have evolved relaxed substrate specificity and are probably maintained as rapidly evolving platforms for adopting new substrates.
  •  
49.
  • Shi, Xiao Jing, et al. (författare)
  • Systems Biology of Gastric Cancer: Perspectives on the Omics-Based Diagnosis and Treatment
  • 2020
  • Ingår i: Frontiers in Molecular Biosciences. - : Frontiers Media SA. - 2296-889X. ; 7
  • Forskningsöversikt (refereegranskat)abstract
    • Gastric cancer is the fifth most diagnosed cancer in the world, affecting more than a million people and causing nearly 783,000 deaths each year. The prognosis of advanced gastric cancer remains extremely poor despite the use of surgery and adjuvant therapy. Therefore, understanding the mechanism of gastric cancer development, and the discovery of novel diagnostic biomarkers and therapeutics are major goals in gastric cancer research. Here, we review recent progress in application of omics technologies in gastric cancer research, with special focus on the utilization of systems biology approaches to integrate multi-omics data. In addition, the association between gastrointestinal microbiota and gastric cancer are discussed, which may offer insights in exploring the novel microbiota-targeted therapeutics. Finally, the application of data-driven systems biology and machine learning approaches could provide a predictive understanding of gastric cancer, and pave the way to the development of novel biomarkers and rational design of cancer therapeutics.
  •  
50.
  • Stancik, Ivan Andreas, et al. (författare)
  • Serine/Threonine Protein Kinases from Bacteria, Archaea and Eukarya Share a Common Evolutionary Origin Deeply Rooted in the Tree of Life
  • 2018
  • Ingår i: Journal of Molecular Biology. - : Elsevier BV. - 0022-2836 .- 1089-8638. ; 430:1, s. 27-32
  • Tidskriftsartikel (refereegranskat)abstract
    • The main family of serine/threonine/tyrosine protein kinases present in eukarya was defined and described by Hanks et al. in 1988 (Science, 241, 42–52). It was initially believed that these kinases do not exist in bacteria, but extensive genome sequencing revealed their existence in many bacteria. For historical reasons, the term “eukaryotic-type kinases” propagated in the literature to describe bacterial members of this protein family. Here, we argue that this term should be abandoned as a misnomer, and we provide several lines of evidence to support this claim. Our comprehensive phylostratigraphic analysis suggests that Hanks-type kinases present in eukarya, bacteria and archaea all share a common evolutionary origin in the lineage leading to the last universal common ancestor (LUCA). We found no evidence to suggest substantial horizontal transfer of genes encoding Hanks-type kinases from eukarya to bacteria. Moreover, our systematic structural comparison suggests that bacterial Hanks-type kinases resemble their eukaryal counterparts very closely, while their structures appear to be dissimilar from other kinase families of bacterial origin. This indicates that a convergent evolution scenario, by which bacterial kinases could have evolved a kinase domain similar to that of eukaryal Hanks-type kinases, is not very likely. Overall, our results strongly support a monophyletic origin of all Hanks-type kinases, and we therefore propose that this term should be adopted as a universal name for this protein family.
  •  
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