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Graph4Med: a web application and a graph database for visualizing and analyzing medical databases
(2022)
Background
Medical databases normally contain large amounts of data in a variety of forms. Although they grant significant insights into diagnosis and treatment, implementing data exploration into current medical databases is challenging since these are often based on a relational schema and cannot be used to easily extract information for cohort analysis and visualization. As a consequence, valuable information regarding cohort distribution or patient similarity may be missed. With the rapid advancement of biomedical technologies, new forms of data from methods such as Next Generation Sequencing (NGS) or chromosome microarray (array CGH) are constantly being generated; hence it can be expected that the amount and complexity of medical data will rise and bring relational database systems to a limit.
Description
We present Graph4Med, a web application that relies on a graph database obtained by transforming a relational database. Graph4Med provides a straightforward visualization and analysis of a selected patient cohort. Our use case is a database of pediatric Acute Lymphoblastic Leukemia (ALL). Along routine patients’ health records it also contains results of latest technologies such as NGS data. We developed a suitable graph data schema to convert the relational data into a graph data structure and store it in Neo4j. We used NeoDash to build a dashboard for querying and displaying patients’ cohort analysis. This way our tool (1) quickly displays the overview of patients’ cohort information such as distributions of gender, age, mutations (fusions), diagnosis; (2) provides mutation (fusion) based similarity search and display in a maneuverable graph; (3) generates an interactive graph of any selected patient and facilitates the identification of interesting patterns among patients.
Conclusion
We demonstrate the feasibility and advantages of a graph database for storing and querying medical databases. Our dashboard allows a fast and interactive analysis and visualization of complex medical data. It is especially useful for patients similarity search based on mutations (fusions), of which vast amounts of data have been generated by NGS in recent years. It can discover relationships and patterns in patients cohorts that are normally hard to grasp. Expanding Graph4Med to more medical databases will bring novel insights into diagnostic and research.
Climate forecasts show that in many regions the temporal distribution of precipitation events will become less predictable. Root traits may play key roles in dealing with changes in precipitation predictability, but their functional plastic responses, including transgenerational processes, are scarcely known. We investigated root trait plasticity of Papaver rhoeas with respect to higher versus lower intra-seasonal and inter-seasonal precipitation predictability (i.e., the degree of temporal autocorrelation among precipitation events) during a four-year outdoor multi-generation experiment. We first tested how the simulated predictability regimes affected intra-generational plasticity of root traits and allocation strategies of the ancestors, and investigated the selective forces acting on them. Second, we exposed three descendant generations to the same predictability regime experienced by their mothers or to a different one. We then investigated whether high inter-generational predictability causes root trait differentiation, whether transgenerational root plasticity existed and whether it was affected by the different predictability treatments. We found that the number of secondary roots, root biomass and root allocation strategies of ancestors were affected by changes in precipitation predictability, in line with intra-generational plasticity. Lower predictability induced a root response, possibly reflecting a fast-acquisitive strategy that increases water absorbance from shallow soil layers. Ancestors’ root traits were generally under selection, and the predictability treatments did neither affect the strength nor the direction of selection. Transgenerational effects were detected in root biomass and root weight ratio (RWR). In presence of lower predictability, descendants significantly reduced RWR compared to ancestors, leading to an increase in performance. This points to a change in root allocation in order to maintain or increase the descendants’ fitness. Moreover, transgenerational plasticity existed in maximum rooting depth and root biomass, and the less predictable treatment promoted the lowest coefficient of variation among descendants’ treatments in five out of six root traits. This shows that the level of maternal predictability determines the variation in the descendants’ responses, and suggests that lower phenotypic plasticity evolves in less predictable environments. Overall, our findings show that roots are functional plastic traits that rapidly respond to differences in precipitation predictability, and that the plasticity and adaptation of root traits may crucially determine how climate change will affect plants.
In response to pathogen infection, gasdermin (GSDM) proteins form membrane pores that induce a host cell death process called pyroptosis1–3. Studies of human and mouse GSDM pores reveal the functions and architectures of 24–33 protomers assemblies4–9, but the mechanism and evolutionary origin of membrane targeting and GSDM pore formation remain unknown. Here we determine a structure of a bacterial GSDM (bGSDM) pore and define a conserved mechanism of pore assembly. Engineering a panel of bGSDMs for site-specific proteolytic activation, we demonstrate that diverse bGSDMs form distinct pore sizes that range from smaller mammalian-like assemblies to exceptionally large pores containing >50 protomers. We determine a 3.3 Å cryo-EM structure of a Vitiosangium bGSDM in an active slinky-like oligomeric conformation and analyze bGSDM pores in a native lipid environment to create an atomic-level model of a full 52-mer bGSDM pore. Combining our structural analysis with molecular dynamics simulations and cellular assays, we define a stepwise model of GSDM pore assembly and demonstrate that pore formation is driven by local unfolding of membrane-spanning β-strand regions and pre-insertion of a covalently bound palmitoyl into the target membrane. These results yield insights into the diversity of GSDM pores found in nature and the function of an ancient post-translational modification in enabling a programmed host cell death process.
In response to pathogen infection, gasdermin (GSDM) proteins form membrane pores that induce a host cell death process called pyroptosis1–3. Studies of human and mouse GSDM pores reveal the functions and architectures of 24–33 protomers assemblies4–9, but the mechanism and evolutionary origin of membrane targeting and GSDM pore formation remain unknown. Here we determine a structure of a bacterial GSDM (bGSDM) pore and define a conserved mechanism of pore assembly. Engineering a panel of bGSDMs for site-specific proteolytic activation, we demonstrate that diverse bGSDMs form distinct pore sizes that range from smaller mammalian-like assemblies to exceptionally large pores containing >50 protomers. We determine a 3.3 Å cryo-EM structure of a Vitiosangium bGSDM in an active slinky-like oligomeric conformation and analyze bGSDM pores in a native lipid environment to create an atomic-level model of a full 52-mer bGSDM pore. Combining our structural analysis with molecular dynamics simulations and cellular assays, our results support a stepwise model of GSDM pore assembly and suggest that a covalently bound palmitoyl can leave a hydrophobic sheath and insert into the membrane before formation of the membrane-spanning β-strand regions. These results reveal the diversity of GSDM pores found in nature and explain the function of an ancient post-translational modification in enabling programmed host cell death.
Background: Alternative splicing is a key mechanism in eukaryotic cells to increase the effective number of functionally distinct gene products. Using bulk RNA sequencing, splicing variation has been studied both across human tissues and in genetically diverse individuals. This has identified disease-relevant splicing events, as well as associations between splicing and genomic variations, including sequence composition and conservation. However, variability in splicing between single cells from the same tissue and its determinants remain poorly understood.
Results: We applied parallel DNA methylation and transcriptome sequencing to differentiating human induced pluripotent stem cells to characterize splicing variation (exon skipping) and its determinants. Our results shows that splicing rates in single cells can be accurately predicted based on sequence composition and other genomic features. We also identified a moderate but significant contribution from DNA methylation to splicing variation across cells. By combining sequence information and DNA methylation, we derived an accurate model (AUC=0.85) for predicting different splicing modes of individual cassette exons. These explain conventional inclusion and exclusion patterns, but also more subtle modes of cell-to-cell variation in splicing. Finally, we identified and characterized associations between DNA methylation and splicing changes during cell differentiation.
Conclusions: Our study yields new insights into alternative splicing at the single-cell level and reveals a previously underappreciated component of DNA methylation variation on splicing.
Background: Alternative splicing is a key regulatory mechanism in eukaryotic cells and increases the effective number of functionally distinct gene products. Using bulk RNA sequencing, splicing variation has been studied across human tissues and in genetically diverse populations. This has identified disease-relevant splicing events, as well as associations between splicing and genomic variations, including sequence composition and conservation. However, variability in splicing between single cells from the same tissue or cell type and its determinants remain poorly understood.
Results: We applied parallel DNA methylation and transcriptome sequencing to differentiating human induced pluripotent stem cells to characterize splicing variation (exon skipping) and its determinants. Our results shows that variation in single-cell splicing can be accurately predicted based on local sequence composition and genomic features. We observe moderate but consistent contributions from local DNA methylation profiles to splicing variation across cells. A combined model that is built based on sequence as well as DNA methylation information accurately predicts different splicing modes of individual cassette exons (AUC=0.85). These categories include the conventional inclusion and exclusion patterns, but also more subtle modes of cell-to-cell variation in splicing. Finally, we identified and characterized associations between DNA methylation and splicing changes during cell differentiation.
Conclusions: Our study yields new insights into alternative splicing at the single-cell level and reveals a previously underappreciated link between DNA methylation variation and splicing.
Background: Alternative splicing is a key regulatory mechanism in eukaryotic cells and increases the effective number of functionally distinct gene products. Using bulk RNA sequencing, splicing variation has been studied across human tissues and in genetically diverse populations. This has identified disease-relevant splicing events, as well as associations between splicing and genomic features, including sequence composition and conservation. However, variability in splicing between single cells from the same tissue or cell type and its determinants remains poorly understood.
Results: We applied parallel DNA methylation and transcriptome sequencing to differentiating human induced pluripotent stem cells to characterize splicing variation (exon skipping) and its determinants. Our results show that variation in single-cell splicing can be accurately predicted based on local sequence composition and genomic features. We observe moderate but consistent contributions from local DNA methylation profiles to splicing variation across cells. A combined model that is built based on genomic features as well as DNA methylation information accurately predicts different splicing modes of individual cassette exons. These categories include the conventional inclusion and exclusion patterns, but also more subtle modes of cell-to-cell variation in splicing. Finally, we identified and characterized associations between DNA methylation and splicing changes during cell differentiation.
Conclusions: Our study yields new insights into alternative splicing at the single-cell level and reveals a previously underappreciated link between DNA methylation variation and splicing.
ABC transporters are found in all organisms and almost every cellular compartment. They mediate the transport of various solutes across membranes, energized by ATP binding and hydrolysis. Dysfunctions can result in severe diseases, such as cystic fibrosis or antibiotic resistance. In type IV ABC transporters, each of the two nucleotide-binding domains is connected to a transmembrane domain by two coupling helices, which are part of cytosolic loops. Although there are many structural snapshots of different conformations, the interdomain communication is still enigmatic. Therefore, we analyzed the function of three conserved, charged residues in the intra-cytosolic loop 1 of the human homodimeric, lysosomal peptide transporter TAPL. Substitution of D278 in coupling helix 1 by alanine interrupted peptide transport by impeding ATP hydrolysis. Alanine substitution of R288 and D292, both localized next to the coupling helix 1 extending to transmembrane helix 3, reduced peptide transport but increased basal ATPase activity. Surprisingly, the ATPase activity of the R288A variant dropped in a peptide-dependent manner while ATPase activity of wildtype and D292A was unaffected. Interestingly, R288A and D292A mutants did not differentiate between ATP and GTP in respect of hydrolysis. However, in contrast to wildtype TAPL, only ATP energized peptide transport. In sum, D278 seems to be involved in bidirectional interdomain communication mediated by network of polar interactions while the two residues in the cytosolic extension of TMH3 are involved in regulation of ATP hydrolysis, most likely by stabilization of the outward facing conformation.
Exploring strategies to improve the reverse beta-oxidation pathway in Saccharomyces cerevisiae
(2024)
Microbes are the most diverse living organisms on Earth, with various metabolic adaptations that allow them to live in different conditions and produce compounds with different chemical complexity. Microbial biotechnology exploits the metabolic diversity of microorganisms to manufacture products for different industries. Today, the chemical industry is a significant energy consumer and carbon dioxide emitter, with processes that harm natural ecosystems, like the extraction of medium-chain fatty acids (MCFAs). MCFAs are used as precursors for biofuels, volatile esters, surfactants, or polymers in materials with enhanced properties.
However, their current extraction process uses large, non-sustainable monocultures of coconut and palm trees. Therefore, the microbial production of MCFAs can help reduce the current environmental impact of obtaining these products and their derivatives.
In nature, fatty acids are mostly produced via fatty acid biosynthesis (FAB). However, the reverse β-oxidation (rBOX) is a more energy-efficient pathway compared to FAB. The rBOX pathway consists of four reactions, which result in the elongation of an acyl-CoA molecule by two carbon units from acetyl-CoA in each cycle. In this work we used Saccharomyces cerevisiae, an organism with a high tolerance towards toxic compounds, as the expression host of the rBOX pathway to produce MCFAs and medium-chain fatty alcohols (MCFOHs).
In the first part of this work, we expanded the length of the products from expressing the rBOX in the cytosol and increased the MCFAs titres. First, we deleted the major glycerol-3-phosphate dehydrogenase (GPD2). This resulted in a platform strain with significantly reduced glycerol fermentation and increased rBOX pathway activity, probably due to an increased availability of NADH. Then, we tested different combinations of rBOX enzymes to increase the length and titres of MCFA. Expressing the thiolase CnbktB and β-hydroxyacyl-CoA dehydrogenase CnpaaH1 from Cupriavidus necator, Cacrt from Clostridium acetobutylicum and the trans-enoyl-CoA reductase Tdter (Treponema denticola) resulted in hexanoic acid as the main product.
Expressing Cncrt2 (C. necator) or YlECH (Y. lipolytica) as enoyl-CoA hydratases resulted in octanoic acid as the main product. Then, we integrated the octanoic (Cncrt2 or YlECH) and the hexanoic acid (Cacrt)-producing variants in the genome of the platform strain and we achieved titers of ≈75 mg/L (hexanoic acid) and ≈ 60 mg/L (octanoic acid) when growing these strains in a complex, highly buffered medium. These are the highest titers of octanoic and hexanoic acid obtained in S. cerevisiae with the rBOX. Additionally, we deleted TES1 and FAA2 to prevent competition for butyryl-CoA and degradation of the produced fatty acids, respectively.
However, these deletions did not improve MCFA titers. In addition, we tested two dual acyl-CoA reductase/alcohol dehydrogenases (ACR/ADH), CaadhE2 from C. acetobutylicum and the putative ACR/ADH EceutE from Escherichia coli, in an octanoyl-CoA-producing strain to produce MCFOH. As a result, we produced 1-hexanol and 1-octanol for the first time in S. cerevisiae with these two enzymes. Nonetheless, the titres were low (<10 mg/L and <2 mg/L, respectively), and four-carbon 1-butanol was the main product in both cases (>80 mg/L). This showed the preference of these two enzymes for butyryl-CoA.
In the second part of this work, we expressed the rBOX in the mitochondria of S. cerevisiae to benefit from the high levels of acetyl-CoA and the reducing environment in that organelle. First, in an adh-deficient strain, we mutated MTH1, a transcription factor regulating the expression of hexose transporters, and deleted GPD2. This resulted in a strain with a reduced Crabtree effect and, therefore, an increased carbon flux to the mitochondria. We partially validated the increased flux to the mitochondria by expressing the ethanol-acetyltransferase EAT1 from Kluyveromyces marxianus in this organelle. This resulted in a higher isoamyl acetate production in the MTH1-mutant strain. Isoamyl acetate is synthesised by Eat1 from acetyl-CoA and isoamyl alcohol, a product of the metabolism of amino acids in the mitochondria. Then, we targeted different butyryl-CoA-producing rBOX variants to the mitochondria, and we used the production of 1-butanol and butyric acid as a proof-of-concept. The strong expression of all the enzymes was toxic for the cell, and the highest butyric acid titres (≈ 50 mg/L) in the mitochondria from the rBOX were obtained from the weak expression of the pathway. The highest 1-butanol titers (≈ 5 mg/L) were obtained with the downregulation of the mitochondrial NADH-oxidase NDI1. However, this downregulation led to a non-desirable petite phenotype.
In summary, we produced hexanoic and octanoic acid for the first time in S. cerevisiae using the rBOX and achieved the highest reported titers of hexanoic and octanoic acid so far using this pathway in S. cerevisiae. In addition, we successfully compartmentalised the rBOX in the mitochondria. However, competing reactions, some of them essential for the viability of the cell, limit the use of this organelle for the rBOX.
Climate change affects ecosystems worldwide and is threatening biodiversity. Insects, as ectotherm organisms, are strongly dependent on the thermal environment. Yet, little is known about the effects of summer heat and drought on insect diversity. In the Mediterranean climate zone, a region strongly affected by climate change, hot summers might have severe effects on insect communities. Especially the larval stage might be sensitive to thermal variation, as larvae—compared to other life stages—cannot avoid hot temperatures and drought by dormancy. Here we ask, whether inter-annual fluctuations in Mediterranean moth diversity can be explained by temperature (TLarv) and precipitation during larval development (HLarv). To address our question, we analyzed moth communities of a Mediterranean coastal forest during the last 20 years. For species with summer-developing larvae, species richness was significantly negatively correlated with TLarv, while the community composition was affected by both, TLarv and HLarv. Therefore, summer-developing larvae seem particularly sensitive to climate change, as hot summers might exceed the larval temperature optima and drought reduces food plant quality. Increasing frequency and severity of temperature and drought extremes due to climate change, therefore, might amplify insect decline in the future.