Shifts in metabolic scaling, production, and efficiency across major evolutionary transitions of life

The diversification of life involved enormous increases in size and complexity. The evolutionary transitions from prokaryotes to unicellular eukaryotes to metazoans were accompanied by major innovations inmetabolicdesign.Hereweshowthat thescalingsofmetabolic rate, population growth rate, and production efficiency with body size have changed across the evolutionary transitions.Metabolic rate scales with body mass superlinearly in prokaryotes, linearly in protists, and sublinearly inmetazoans, so Kleiber’s 3/4 power scaling law does not apply universally across organisms. The scaling ofmaximum population growth rate shifts from positive in prokaryotes to negative in protists and metazoans, and the efficiency of production declines across these groups.Major changes inmetabolic processes duringtheearlyevolutionof life overcameexistingconstraints, exploited new opportunities, and imposed new constraints. The 3.5 billion year history of life on earth was characterized by

Assessing hepatic metabolic changes during progressive colonization of germ-free mouse by 1H NMR spectroscopy

It is well known that gut bacteria contribute significantly to the host homeostasis, providing a range of benefits such as immune protection and vitamin synthesis. They also supply the host with a considerable amount of nutrients, making this ecosystem an essential metabolic organ. In the context of increasing evidence of the link between the gut flora and the metabolic syndrome, understanding the metabolic interaction between the host and its gut microbiota is becoming an important challenge of modern biology.1-4 Colonization (also referred to as normalization process) designates the establishment of micro-organisms in a former germ-free animal. While it is a natural process occurring at birth, it is also used in adult germ-free animals to control the gut floral ecosystem and further determine its impact on the host metabolism. A common procedure to control the colonization process is to use the gavage method with a single or a mixture of micro-organisms. This method results in a very quick colonization and presents the disadvantage of being extremely stressful5. It is therefore useful to minimize the stress and to obtain a slower colonization process to observe gradually the impact of bacterial establishment on the host metabolism. In this manuscript, we describe a procedure to assess the modification of hepatic metabolism during a gradual colonization process using a non-destructive metabolic profiling technique. We propose to monitor gut microbial colonization by assessing the gut microbial metabolic activity reflected by the urinary excretion of microbial co-metabolites by 1H NMR-based metabolic profiling. This allows an appreciation of the stability of gut microbial activity beyond the stable establishment of the gut microbial ecosystem usually assessed by monitoring fecal bacteria by DGGE (denaturing gradient gel electrophoresis).6 The colonization takes place in a conventional open environment and is initiated by a dirty litter soiled by conventional animals, which will serve as controls. Rodents being coprophagous animals, this ensures a homogenous colonization as previously described.7 Hepatic metabolic profiling is measured directly from an intact liver biopsy using 1H High Resolution Magic Angle Spinning NMR spectroscopy. This semi-quantitative technique offers a quick way to assess, without damaging the cell structure, the major metabolites such as triglycerides, glucose and glycogen in order to further estimate the complex interaction between the colonization process and the hepatic metabolism7-10. This method can also be applied to any tissue biopsy11,12.

Integrated cytokine and metabolic analysis of pathological responses to parasite exposure in rodents

Parasitic infections cause a myriad of responses in their mammalian hosts, on immune as well as on metabolic level. A multiplex panel of cytokines and metabolites derived from four parasite-rodent models, namely, Plasmodium berghei-mouse, Trypanosoma brucei brucei-mouse, Schistosoma mansoni-mouse, and Fasciola hepatica-rat were statistically coanalyzed. 1H NMR spectroscopy and multivariate statistical analysis were used to characterize the urine and plasma metabolite profiles in infected and noninfected animals. Each parasite generated a unique metabolic signature in the host. Plasma cytokine concentrations were obtained using the ‘Meso Scale Discovery’ multi cytokine assay platform. Multivariate data integration methods were subsequently used to elucidate the component of the metabolic signature which is associated with inflammation and to determine specific metabolic correlates with parasite-induced changes in plasma cytokine levels. For example, the relative levels of acetyl glycoproteins extracted from the plasma metabolite profile in the P. berghei-infected mice were statistically correlated with IFN-γ, whereas the same cytokine was anticorrelated with glucose levels. Both the metabolic and the cytokine data showed a similar spatial distribution in principal component analysis scores plots constructed for the combined murine data, with samples from all infected animals clustering according to the parasite species and whereby the protozoan infections (P. berghei and T. b. brucei) grouped separately from the helminth infection (S. mansoni). For S. mansoni, the main infection-responsive cytokines were IL-4 and IL-5, which covaried with lactate, choline, and D-3-hydroxybutyrate. This study demonstrates that the inherently differential immune response to single and multicellular parasites not only manifests in the cytokine expression, but also consequently imprints on the metabolic signature, and calls for in-depth analysis to further explore direct links between immune features and biochemical pathways.

Insulin receptor substrate-2 gene variants in subjects with metabolic syndrome: association with plasma fatty acid levels and insulin resistance

Several insulin receptor substrate-2 (IRS-2) polymorphisms have been studied in relation to insulin resistance and type 2 diabetes. To examine whether the genetic variability at the IRS-2 gene locus was associated with the degree of insulin resistance and plasma fatty acid levels in metabolic syndrome (MetS) subjects. Methods and results: Insulin sensitivity, insulin secretion, glucose effectiveness, plasma fatty acid composition and three IRS-2 tag-single nucleotide polymorphisms (SNPs) were determined in 452 MetS subjects. Among subjects with the lowest level of monounsaturated (MUFA) (below the median), the rs2289046 A/A genotype was associated with lower glucose effectiveness (p<0.038), higher fasting insulin concentrations (p<0.028) and higher HOMA IR (p<0.038) as compared to subjects carrying the minor G-allele (A/G and G/G). In contrast, among subjects with the highest level of MUFA (above the median), the A/A genotype was associated with lower fasting insulin concentrations and HOMA-IR, whereas individuals carrying the G allele and with the highest level of ω-3 polyunsaturated fatty acids (above the median) showed lower fasting insulin (p<0.01) and HOMA-IR (p<0.02) as compared with A/A subjects. Conclusion: The rs2289046 polymorphism at the IRS2 gene locus may influence insulin sensitivity by interacting with certain plasma fatty acids in MetS subjects.

A gene variation (rs12691) in the CCAT/enhancer building α modulates glucose metabolism in metabolic syndrome

Background and aims CCAAT/enhancer-binding protein alpha (CEBPA) is a transcription factor involved in adipogenesis and energy homeostasis. Caloric restriction reduces CEBPA protein expression in patients with metabolic syndrome (MetS). A previous report linked rs12691 SNP in CEBPA to altered concentration of fasting triglycerides. Our objective was to assess the effects of rs12691 in glucose metabolism in Metabolic Syndrome (MetS) patients. Methods and results Glucose metabolism was assessed by static (glucose, insulin, adiponectin, leptin and resistin plasma concentrations) and dynamic (disposition index, insulin sensitivity index, HOMA-IR and acute insulin response to glucose) indices, performed at baseline and after 12 weeks of 4 dietary interventions (high saturated fatty acid (SFA), high monounsaturated fatty acid (MUFA), low-fat and low-fat-high-n3 polyunsaturated fatty acid (PUFA)) in 486 subjects with MetS. Carriers of the minor A allele of rs12691 had altered disposition index (p = 0.0003), lower acute insulin response (p = 0.005) and a lower insulin sensitivity index (p = 0.025) indicating a lower insulin sensitivity and a lower insulin secretion, at baseline and at the end of the diets. Furthermore, A allele carriers displayed lower HDL concentration. Conclusion The presence of the A allele of rs12691 influences glucose metabolism of MetS patients. Clinical Trials Registry number NCT00429195.

The type and quantity of dietary fat and carbohydrate alter faecal microbiome and short-chain fatty acid excretion in a metabolic syndrome ‘at-risk’ population syndrome.

An obese-type human microbiota with an increased Firmicutes:Bacteroidetes ratio has been described that may link the gut microbiome with obesity and metabolic syndrome (MetS) development. Dietary fat and carbohydrate are modifiable risk factors that may impact on MetS by altering the human microbiome composition. We determined the effect of the amount and type of dietary fat and carbohydrate on faecal bacteria and short chain fatty acid (SCFA) concentrations in people ‘at risk’ of MetS.

Host-gut microbiota metabolic interactions

The composition and activity of the gut microbiota codevelop with the host from birth and is subject to a complex interplay that depends on the host genome, nutrition, and life-style. The gut microbiota is involved in the regulation of multiple host metabolic pathways, giving rise to interactive host-microbiota metabolic, signaling, and immune-inflammatory axes that physiologically connect the gut, liver, muscle, and brain. A deeper understanding of these axes is a prerequisite for optimizing therapeutic strategies to manipulate the gut microbiota to combat disease and improve health.

Therapeutic modulation of microbiota-host metabolic interactions

The complex metabolic relationships between the host and its microbiota change throughout life and vary extensively between individuals, affecting disease risk factors and therapeutic responses through drug metabolism. Elucidating the biochemical mechanisms underlying this human supraorganism symbiosis is yielding new therapeutic insights to improve human health, treat disease, and potentially modify human disease risk factors. Therapeutic options include targeting drugs to microbial genes or co-regulated host pathways and modifying the gut microbiota through diet, probiotic and prebiotic interventions, bariatric surgery, fecal transplants, or ecological engineering. The age-associated co-development of the host and its microbiota provides a series of windows for therapeutic intervention from early life through old age

The metabolic impact of zinc oxide on porcine intestinal cells and enterotoxigenic Escherichia coli K88

Pharmacological levels of zinc oxide (ZnO) incorporated into the post-weaning piglet diet reduce the incidence of diarrhoea caused by enterotoxigenic Escherichia coli (ETEC) K88. The mechanism for this is not understood. Here, Intestinal Porcine Epithelial Cells (IPEC) J2 were used as an in vitro model of the porcine intestine. ZnO reduced IPEC J2 viability at concentrations >= 200 mu M, and ETEC adhesion to the host cell was unaffected by ZnO. Characterisation of the metabolism of IPEC J2 cells and ETEC established the effects of ZnO treatment on the metabolic profile of both. Although 100 mu M ZnO did not inhibit growth of either host or pathogen in fully supplemented media, metabolic profiles were significantly altered. Glucose and mannose were essential energy sources for IPEC J2 cells in the presence of ZnO, as the ability to utilise other sources was compromised. The increase in specificity of requirements to support respiration in ETEC was more pronounced, in particular the need for cysteine as a nitrogen source. These findings indicate that ZnO impacts on both host cell and pathogen metabolism and may provide insight into the mechanism for diarrhoea reduction. (C) 2010 Elsevier B.V. All rights reserved.

Phenotype MicroArray (TM) in the metabolic characterisation of Salmonella serotypes Agona, Enteritidis, Give, Hvittingfoss, Infantis, Newport and Typhimurium

The Phenotype MicroArray (TM) (PM) technology was used to study the metabolic characteristics of 29 Salmonella strains belonging to seven serotypes of S. enterica spp. enterica. Strains of serotypes Typhimurium (six strains among definite phage types DTs 1, 40 and 104) and Agona (two strains) were tested for 949 substrates, Enteritidis (six strains of phage type PT1), Give, Hvittingfoss, Infantis and Newport strains (two of each) were tested for 190 substrates and seven other Agona strains for 95 substrates. The strains represented 18 genotypes in pulsed-field gel electrophoresis (PFGE). Among 949 substrates, 18 were identified that could be used to differentiate between the strains of those seven serotypes or within a single serotype. Unique metabolic differences between the Finnish endemic Typhimurium DT1 and Agona strains were detected, for example, in the metabolism of d-tagatose, d-galactonic acid gamma-lactone and l-proline as a carbon source. Thus, the PM technique is a useful tool for identifying potential differential markers on a metabolic basis that could be used for epidemiological surveillance.

Genome scale reconstruction of a Salmonella metabolic model comparison of similarity and differences with a commensal Escherichia coli strain

Salmonella are closely related to commensal Escherichia coli but have gained virulence factors enabling them to behave as enteric pathogens. Less well studied are the similarities and differences that exist between the metabolic properties of these organisms that may contribute toward niche adaptation of Salmonella pathogens. To address this, we have constructed a genome scale Salmonella metabolic model (iMA945). The model comprises 945 open reading frames or genes, 1964 reactions, and 1036 metabolites. There was significant overlap with genes present in E. coli MG1655 model iAF1260. In silico growth predictions were simulated using the model on different carbon, nitrogen, phosphorous, and sulfur sources. These were compared with substrate utilization data gathered from high throughput phenotyping microarrays revealing good agreement. Of the compounds tested, the majority were utilizable by both Salmonella and E. coli. Nevertheless a number of differences were identified both between Salmonella and E. coli and also within the Salmonella strains included. These differences provide valuable insight into differences between a commensal and a closely related pathogen and within different pathogenic strains opening new avenues for future explorations.

Rensch's rule in large herbivorous mammals derived from metabolic scaling

Rensch’s rule, which states that the magnitude of sexual size dimorphism tends to increase with increasing body size, has evolved independently in three lineages of large herbivorous mammals: bovids (antelopes), cervids (deer), and macropodids (kangaroos). This pattern can be explained by a model that combines allometry,life-history theory, and energetics. The key features are thatfemale group size increases with increasing body size and that males have evolved under sexual selection to grow large enough to control these groups of females. The model predicts relationships among body size and female group size, male and female age at first breeding,death and growth rates, and energy allocation of males to produce body mass and weapons. Model predictions are well supported by data for these megaherbivores. The model suggests hypotheses for why some other sexually dimorphic taxa, such as primates and pinnipeds(seals and sea lions), do or do not conform to Rensh’s rule.

A period 2 genetic variant interacts with plasma SFA to modify plasma lipid concentrations in adults with metabolic syndrome

Genetic variants of Period 2 (PER2), a circadian clock gene, have been linked to metabolic syndrome (MetS). However, it is still unknown whether these genetic variants interact with the various types of plasma fatty acids. This study investigated whether common single nucleotide polymorphisms (SNPs) in the PER2 locus (rs934945 and rs2304672) interact with various classes of plasma fatty acids to modulate plasma lipid metabolism in 381 participants with MetS in the European LIPGENE study. Interestingly, the rs2304672 SNP interacted with plasma total SFA concentrations to affect fasting plasma TG, TG-rich lipoprotein (TRL-TG), total cholesterol, apoC-II, apoB, and apoB-48 concentrations (P-interaction < 0.001–0.046). Carriers of the minor allele (GC+GG) with the highest SFA concentration (>median) had a higher plasma TG concentration (P = 0.001) and higher TRL-TG (P < 0.001) than the CC genotype. In addition, participants carrying the minor G allele for rs2304672 SNP and with a higher SFA concentration (>median) had higher plasma concentrations of apo C-II (P < 0.001), apo C-III (P = 0.009), and apoB-48 (P = 0.028) compared with the homozygotes for the major allele (CC). In summary, the rs2304672 polymorphism in the PER2 gene locus may influence lipid metabolism by interacting with the plasma total SFA concentration in participants with MetS. The understanding of these gene-nutrient interactions could help to provide a better knowledge of the pathogenesis in MetS.

Weaning diet induces sustained metabolic phenotype shift in the pig and influences host response to Bifidobacterium lactis NCC2818

Background The process of weaning causes a major shift in intestinal microbiota and is a critical period for developing appropriate immune responses in young mammals.Objective To use a new systems approach to provide an overview of host metabolism and the developing immune system in response to nutritional intervention around the weaning period.Design Piglets (n=14) were weaned onto either an egg-based or soya-based diet at 3 weeks until 7 weeks, when all piglets were switched onto a fish-based diet. Half the animals on each weaning diet received Bifidobacterium lactis NCC2818 supplementation from weaning onwards. Immunoglobulin production from immunologically relevant intestinal sites was quantified and the urinary (1)H NMR metabolic profile was obtained from each animal at post mortem (11 weeks).Results Different weaning diets induced divergent and sustained shifts in the metabolic phenotype, which resulted in the alteration of urinary gut microbial co-metabolites, even after 4 weeks of dietary standardisation. B lactis NCC2818 supplementation affected the systemic metabolism of the different weaning diet groups over and above the effects of diet. Additionally, production of gut mucosa-associated IgA and IgM was found to depend upon the weaning diet and on B lactis NCC2818 supplementation.ConclusionThe correlation of urinary (1)H NMR metabolic profile with mucosal immunoglobulin production was demonstrated, thus confirming the value of this multi-platform approach in uncovering non-invasive biomarkers of immunity. This has clear potential for translation into human healthcare with the development of urine testing as a means of assessing mucosal immune status. This might lead to early diagnosis of intestinal dysbiosis and with subsequent intervention, arrest disease development. This system enhances our overall understanding of pathologies under supra-organismal control.