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Ahonen, L.

Publications and source records attributed to Ahonen, L..

8 recordsLinked to original sources

Species-specific metabolic networks shape evolutionary routes to functional rescue

Metabolic networks are highly interconnected. Still, it remains unclear whether organism- and environment-specific factors shape their capacity to evolve in response to metabolic stress or whether it follows general principles. Here, we studied metabolic evolvability in Bacillus subtilis using auxotrophic mutants lacking central biosynthetic enzymes. Across two genetic backgrounds with contrasting biofilm-forming capacities and under direct or gradual selection through nutrient gradients, B. subtilis bypassed 9 of 17 essential functions. Rescue was more frequent in the biofilm-proficient background and under gradual selection, which was also associated with more mutations in coding regions, particularly nonsynonymous. Adaptation proceeded through loss-of-function mutations that relieved regulatory or enzymatic constraints and redirected metabolic flux. Comparison with Escherichia coli revealed substantial differences in bypassability and genetic routes that persisted under matched conditions, although two cross-species solutions converged at the pathway level. Our data show species-specific metabolic networks shape available rescue routes, while ecological context influences their evolutionary accessibility during adaptation.

evolutionary biology↗

CIFR (Clone-Integrate-Flip-out-Repeat): a toolset for iterative genome and pathway engineering of Gram-negative bacteria

Advances in genome engineering enable precise and customizable modifications of bacterial species. Toolsets for metabolic engineering that exhibit broad-host compatibility are particularly valued owing to their portability. Tn5 transposon vectors have been widely used to establish random integrations of desired DNA sequences into bacterial genomes. However, the iteration of the procedure remains challenging because of the limited availability of selection markers. Here, we present CIFR, a mini-Tn5 integration system for iterative genome engineering. The pCIFR vectors incorporate attP and attB sites flanking an antibiotic resistance marker used to select for the insertion. Subsequent removal of these antibiotic determinants is facilitated by the Bxb1 integrase, and a user-friendly counter-selection marker, both encoded in auxiliary plasmids. Hence, CIFR delivers engineered strains harboring stable DNA insertions and free of any antibiotic resistance cassette, allowing for the reusability of the tool. The system was validated in Pseudomonas putida, Escherichia coli, and Cupriavidus necator, underscoring its portability across diverse industrially-relevant hosts. The CIFR toolbox was calibrated through combinatorial integrations of chromoprotein genes in P. putida, generating strains displaying a diverse color palette. Next, we introduced a carotenoid biosynthesis pathway in P. putida in a two-step engineering process, showcasing the potential of the tool for pathway balancing. The broad utility of the toolbox expands the synthetic biology toolkit for metabolic engineering, allowing for the construction of complex phenotypes, while opening new possibilities in bacterial genetic manipulations.

synthetic biology↗

Metabolic engineering of yeast for de novo production of kratom monoterpene indole alkaloids

Monoterpene indole alkaloids (MIAs) from Mitragyna speciosa ("kratom"), such as mitragynine and speciogynine, are promising novel scaffolds for opioid receptor ligands for treatment of pain, addiction, and depression. While kratom leaves have been used for centuries in South-East Asia as stimulant and pain management substance, the biosynthetic pathway of these psychoactives have only recently been partially elucidated. Here, we demonstrate the de novo production of mitragynine and speciogynine in Saccharomyces cerevisiae through the reconstruction of a five-step synthetic pathway from common MIA precursor strictosidine comprising fungal tryptamine 4-monooxygenase to bypass an unknown kratom hydroxylase. Upon optimizing cultivation conditions, a titer of [~]290 {micro}g/L kratom MIAs from glucose was achieved. Untargeted metabolomics analysis of lead production strains led to the identification of numerous shunt products derived from the activity of strictosidine synthase (STR) and dihydrocorynantheine synthase (DCS), highlighting them as candidates for enzyme engineering to further improve kratom MIAs production in yeast. Finally, by feeding fluorinated tryptamine and expressing a human tailoring enzyme, we further demonstrate production of fluorinated and hydroxylated mitragynine derivatives with potential applications in drug discovery campaigns. Altogether, this study introduces a yeast cell factory platform for the biomanufacturing of complex natural and new-to-nature kratom MIAs derivatives with therapeutic potential.

synthetic biology↗

CARDIOVASCULAR AUTONOMIC NEUROPATHY IN TYPE 1 DIABETES IS ASSOCIATED WITH SEVERAL METABOLIC PATHWAYS: New Risk Markers on the horizon

ObjectiveCardiovascular autonomic neuropathy (CAN) in diabetes is associated with increased mortality and morbidity and is a non-treatable complication. We investigated associations between circulating metabolites and presence of CAN in persons with type 1 diabetes (T1D). MethodsCAN was assessed by cardiovascular reflex tests (CARTs) in 302 persons with T1D as heart rate response to: deep breathing; lying-to-standing test; and the Valsalva manoeuvre. More than 1 pathological CART defined the CAN diagnosis. Serum metabolomics and lipidomics profiles were analysed with two complementary non-targeted massspectrometry methods. Cross-sectional associations between single metabolites and CAN were assessed by linear regression. Models were fitted with and without adjustments for relevant confounders and multiple testing. ResultsParticipants were mean (IQR) aged 55(49, 63) years, 50% males, with diabetes duration 39(32, 47) years, HbA1c 63(55,69) mmol/mol and 34% had the CAN diagnosis. A total of 75 metabolites and 106 lipids were examined. In crude models, CAN diagnosis was associated with higher levels of hydroxy fatty acids (2,4- and 3,4-dihydroxybutanoic acids, 4-deoxytetronic acid), creatinine, sugar derivates (ribitol, ribonic acid, myo-inositol), citric acid, glycerol, phenols, phosphatidylcholines and lower levels of free fatty acids and amino acid methionine (p<0.05). Upon adjustment, positive associations with CAN were retained with hydroxy fatty acids, tricarboxylic acid (TCA) cycle-based sugar derivates, and citric acid and phenols (Padjusted<0.05). ConclusionsMetabolic pathways, including the TCA cycle, hydroxy fatty acids, phosphatidylcholines and sugar derivatives, were associated with CAN in T1D. These novel metabolic pathways associated with CAN could prove to be future modifiable risk factors.

neuroscience↗

Lipidomics of human adipose tissue reveals diversity between body areas

Background and aimsAdipose tissue plays a pivotal role in storing excess fat and its composition reflects the history of persons lifestyle and metabolic health. Broad profiling of lipids with mass spectrometry has potential for uncovering new knowledge on the pathology of obesity, metabolic syndrome, diabetes and other related conditions. Here, we developed a lipidomic method for analyzing human subcutaneous adipose biopsies. We applied the method to four body areas to understand the differences in lipid composition between these areas. Materials and methodsAdipose tissue biopsies from 10 participants were analyzed using ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry. The method development included the optimization of the lipid extraction, the sample amount and the sample dilution factor to detect lipids in an appropriate concentration range. Lipidomic analyses were performed for adipose tissue collected from the abdomen, breast, thigh and lower back. Differences in lipid levels between tissues were visualized with heatmaps. ResultsLipidomic analysis on human adipose biopsies lead to the identification of 187 lipids in 2 mg of sample. Technical variation of the lipid-class specific internal standards were below 5 %, thus indicating acceptable repeatability. Triacylglycerols were highly represented in the adipose tissue samples, and lipids from 13 lipid classes were identified. Long polyunsaturated triacylglycerols in higher levels in thigh (q<0.05), when compared with the abdomen, breast and lower back, indicating that the lipidome was area-specific. ConclusionThe method presented here is suitable for the analysis of lipid profiles in 2 mg of adipose tissue. The amount of fat across the body is important for health but we argue that also the distribution and the particular profile of the lipidome may be relevant for metabolic outcomes. We suggest that the method presented in this paper could be useful for detecting such aberrations.

biophysics↗

Describing the fecal metabolome in cryogenically collected samples from healthy participants.

IntroductionThe chemical composition of feces plays an important role in human metabolism. Metabolomics and lipidomics are valuable tools for screening the metabolite composition in feces. Here we set out to describe fecal metabolite composition in healthy participants in frozen stools.\n\nMethodsFrozen stool samples were collected from 10 healthy volunteers and cryogenically drilled in four areas along the specimen. Polar metabolites were analyzed using derivatization followed by two-dimensional gas chromatography and time of flight mass spectrometry. Lipids were detected using ultra high-performance liquid chromatography coupled with quadruple time-of-flight mass spectrometry. The technical variation threshold was set to 30% in pooled quality control samples and metabolite variation was then assessed in four areas per specimen. A data-generated network using metabolites found in all areas was computed for healthy participants.\n\nResults2326 metabolic features were detected. Out of a total of 298 metabolites that were annotated we report here 185 that showed a technical variation of x< 30%. These metabolites included amino acids, fatty acid derivatives, carboxylic acids and phenolic compounds. Lipids predominantly belonged to the groups of diacylglycerols, triacylglycerols and ceramides. Metabolites varied between sampling areas (14%-80%). A network using metabolites present in all areas showed two main clusters, DAG lipids and phenyllactic acid.\n\nConclusionsIn feces from healthy participants, the main groups detected were phenolic compounds, ceramides, diacylglycerols and triacylglycerols. Metabolite levels differed considerably depending on the sampling area.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=52 SRC=\"FIGDIR/small/708685v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (16K):\norg.highwire.dtl.DTLVardef@17db665org.highwire.dtl.DTLVardef@51e140org.highwire.dtl.DTLVardef@19b55d7org.highwire.dtl.DTLVardef@120d399_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

Targeted Clinical Metabolomics Platform for the Stratification of Diabetic Patients

BackgroundSeveral small molecule biomarkers have been reported in the literature for prediction and diagnosis of (pre)diabetes, its co-morbidities and complications. Here, we report the development and validation of a novel, quantitative, analytical method for use in the diabetes clinic. This method enables the determination of a selected panel of 36 metabolite biomarkers from human plasma.\n\nMethodsBased on a review of the literature and our own data, we selected a panel of metabolites indicative of various clinically-relevant pathogenic stages of diabetes. We combined these candidate biomarkers into a single ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method and optimized it, prioritizing simplicity of sample preparation and time needed for analysis, enabling high-throughput analysis in clinical laboratory settings.\n\nResultsWe validated the method in terms of limit of (a) detection (LOD), (b) limit of quantitation (LOQ), (c) linearity (R2), (d) linear range, and (e) intra- and inter-day repeatability of each metabolite. The methods performance was demonstrated in the analysis of selected samples from a diabetes cohort study. Metabolite levels were associated with clinical measurements and kidney complications in type 1 diabetes (T1D) patients. Specifically, both amino acids and amino acid-related analytes were associated with macro-albuminuria. Additionally, specific bile acids were associated with kidney function, anti-hypertensive medication, statin medication and clinical lipid measurements.\n\nConclusionsThe developed analytical method is suitable for robust determination of selected plasma metabolites in the diabetes clinic.

biochemistry↗

Dynamics of Plasma Lipidome in Progression to Islet Autoimmunity and Type 1 Diabetes: Type 1 Diabetes Prediction and Prevention Study (DIPP)

Type 1 diabetes (T1D) is one of the most prevalent autoimmune diseases among children in Western countries. Earlier metabolomics studies suggest that T1D is preceded by dysregulation of lipid metabolism. Here we used a lipidomics approach to analyze molecular lipids in a prospective series of 428 plasma samples from 40 children who progressed to T1D (PT1D), 40 children who developed at least a single islet autoantibody but did not progress to T1D during the follow-up (P1Ab) and 40 matched controls (CTR). Sphingomyelins were found to be persistently downregulated in PT1D when compared to the P1Ab and CTR groups. Triacylglycerols and phosphatidylcholines were mainly downregulated in PT1D as compared to P1Ab at the age of 3 months. Our study suggests that children who progressed to islet autoimmunity or overt T1D are characterized by distinct lipidomic signatures, which may be helpful in the identification of at-risk children before the initiation of autoimmunity.

biochemistry↗