Robert Mansourian

Germ-free C57BL/6J mice are resistant to high-fat-diet-induced insulin resistance and have altered cholesterol metabolism

Recent studies showed that germ-free (GF) mice are resistant to obesity when consuming a high-fat, high-carbohydrate Western diet. However, it remains unclear what mechanisms are involved in the antiobesity phenotype and whether GF mice develop insulin resistance and dyslipidemia with high-fat (HF) feeding. In the present study, we compared the metabolic consequences of HF feeding on GF and conventional (conv) C57BL/6J mice. GF mice consumed fewer calories, excreted more fecal lipids, and weighed significantly less than conv mice. GF/HF animals also showed enhanced insulin sensitivity with improved glucose tolerance, reduced fasting and nonfasting insulinemia, and increased phospho-Akt((Ser-473)) in adipose tissue. In association with enhanced insulin sensitivity, GF/HF mice had reduced plasma TNF-α and total serum amyloid A concentrations. Reduced hypercholesterolemia, a moderate accretion of hepatic cholesterol, and an increase in fecal cholesterol excretion suggest an altered cholesterol metabolism in GF/HF mice. Pronounced nucleus SREBP2 proteins and up-regulation of cholesterol biosynthesis genes indicate that enhanced cholesterol biosynthesis contributed to the cholesterol homeostasis in GF/HF mice. Our results demonstrate that fewer calorie consumption and increased lipid excretion contributed to the obesity-resistant phenotype of GF/HF mice and reveal that insulin sensitivity and cholesterol metabolism are metabolic targets influenced by the gut microbiota.

The limit fold change model: A practical approach for selecting differentially expressed genes from microarray data

BackgroundThe biomedical community is developing new methods of data analysis to more efficiently process the massive data sets produced by microarray experiments. Systematic and global mathematical approaches that can be readily applied to a large number of experimental designs become fundamental to correctly handle the otherwise overwhelming data sets.ResultsThe gene selection model presented herein is based on the observation that: (1) variance of gene expression is a function of absolute expression; (2) one can model this relationship in order to set an appropriate lower fold change limit of significance; and (3) this relationship defines a function that can be used to select differentially expressed genes. The model first evaluates fold change (FC) across the entire range of absolute expression levels for any number of experimental conditions. Genes are systematically binned, and those genes within the top X% of highest FCs for each bin are evaluated both with and without the use of replicates. A function is fitted through the top X% of each bin, thereby defining a limit fold change. All genes selected by the 5% FC model lie above measurement variability using a within standard deviation (SDwithin) confidence level of 99.9%. Real time-PCR (RT-PCR) analysis demonstrated 85.7% concordance with microarray data selected by the limit function.ConclusionThe FC model can confidently select differentially expressed genes as corroborated by variance data and RT-PCR. The simplicity of the overall process permits selecting model limits that best describe experimental data by extracting information on gene expression patterns across the range of expression levels. Genes selected by this process can be consistently compared between experiments and enables the user to globally extract information with a high degree of confidence.

Chronic wound healing by fetal cell therapy may be explained by differential gene profiling observed in fetal versus old skin cells

Engineering of fetal tissue has a high potential for the treatment of acute and chronic wounds of the skin in humans as these cells have high expansion capacity under simple culture conditions and one organ donation can produce Master Cell Banks which can fabricate over 900 million biological bandages (9 x 12cm). In a Phase 1 clinical safety study, cases are presented for the treatment of therapy resistant leg ulcers. All eight patients, representing 13 ulcers, tolerated multiple treatments with fetal biological bandages showing no negative secondary effects and repair processes similar to that seen in 3rd degree burns. Differential gene profiling using Affymetrix gene chips (analyzing 12,500 genes) were accomplished on these banked fetal dermal skin cells compared to banked dermal skin cells of an aged donor in order to point to potential indicators of wound healing. Families of genes involved in cell adhesion and extracellular matrix, cell cycle, cellular signaling, development and immune response show significant differences in regulation between banked fetal and those from banked old skin cells: with approximately 47.0% of genes over-expressed in fetal fibroblasts. It is perhaps these differences which contribute to efficient tissue repair seen in the clinic with fetal cell therapy.

Time-resolved Quantitative Proteome Analysis of In Vivo Intestinal Development

Postnatal intestinal development is a very dynamic process characterized by substantial morphological changes that coincide with functional adaption to the nutritional change from a diet rich in fat (milk) to a diet rich in carbohydrates on from weaning. Time-resolved studies of intestinal development have so far been limited to investigation at the transcription level or to single or few proteins at a time. In the present study, we elucidate proteomic changes of primary intestinal epithelial cells from jejunum during early suckling (1–7 days of age), middle suckling (7–14 days), and weaning period (14–35 days) in mice, using a label-free proteomics approach. We show differential expression of 520 proteins during intestinal development and a pronounced change of the proteome during the middle suckling period and weaning. Proteins involved in several metabolic processes were found differentially expressed along the development. The temporal expression profiles of enzymes of the glycolysis were found to correlate with the increase in carbohydrate uptake at weaning, whereas the abundance changes of proteins involved in fatty acid metabolism as well as lactose metabolism indicated a nondiet driven preparation for the nutritional change at weaning. Further, we report the developmental abundance changes of proteins playing a vital role in the neonatal acquisition of passive immunity. In addition, different isoforms of several proteins were quantified, which may contribute to a better understanding of the roles of the specific isoforms in the small intestine. In summary, we provide a first, time-resolved proteome profile of intestinal epithelial cells along postnatal intestinal development.

Microarray data analysis: a practical approach for selecting differentially expressed genes

BackgroundThe biomedical community is rapidly developing new methods of data analysis for microarray experiments, with the goal of establishing new standards to objectively process the massive datasets produced from functional genomic experiments. Each microarray experiment measures thousands of genes simultaneously producing an unprecedented amount of biological information across increasingly numerous experiments; however, in general, only a very small percentage of the genes present on any given array are identified as differentially regulated. The challenge then is to process this information objectively and efficiently in order to obtain knowledge of the biological system under study and by which to compare information gained across multiple experiments. In this context, systematic and objective mathematical approaches, which are simple to apply across a large number of experimental designs, become fundamental to correctly handle the mass of data and to understand the true complexity of the biological systems under study.ResultsThe present report develops a method of extracting differentially expressed genes across any number of experimental samples by first evaluating the maximum fold change (FC) across all experimental parameters and across the entire range of absolute expression levels. The model developed works by first evaluating the FC across the entire range of absolute expression levels in any number of experimental conditions. The selection of those genes within the top X% of highest FCs observed within absolute expression bins was evaluated both with and without the use of replicates. Lastly, the FC model was validated by both real time polymerase chain reaction (RT-PCR) and variance data. Semi-quantitative RT-PCR analysis demonstrated 73% concordance with the microarray data from Mu11K Affymetrix GeneChips. Furthermore, 94.1% of those genes selected by the 5% FC model were found to lie above measurement variability using a SDwithin confidence level of 99.9%.ConclusionAs evidenced by the high rate of validation, the FC model has the potential to minimize the number of required replicates in expensive microarray experiments by extracting information on gene expression patterns (e.g. characterizing biological and/or measurement variance) within an experiment. The simplicity of the overall process allows the analyst to easily select model limits which best describe the data. The genes selected by this process can be compared between experiments and are shown to objectively extract information which is biologically & statistically significant.

The Global Error Assessment (GEA) model for the selection of differentially expressed genes in microarray data

MOTIVATION Microarray technology has become a powerful research tool in many fields of study; however, the cost of microarrays often results in the use of a low number of replicates (k). Under circumstances where k is low, it becomes difficult to perform standard statistical tests to extract the most biologically significant experimental results. Other more advanced statistical tests have been developed; however, their use and interpretation often remain difficult to implement in routine biological research. The present work outlines a method that achieves sufficient statistical power for selecting differentially expressed genes under conditions of low k, while remaining as an intuitive and computationally efficient procedure. RESULTS The present study describes a Global Error Assessment (GEA) methodology to select differentially expressed genes in microarray datasets, and was developed using an in vitro experiment that compared control and interferon-gamma treated skin cells. In this experiment, up to nine replicates were used to confidently estimate error, thereby enabling methods of different statistical power to be compared. Gene expression results of a similar absolute expression are binned, so as to enable a highly accurate local estimate of the mean squared error within conditions. The model then relates variability of gene expression in each bin to absolute expression levels and uses this in a test derived from the classical ANOVA. The GEA selection method is compared with both the classical and permutational ANOVA tests, and demonstrates an increased stability, robustness and confidence in gene selection. A subset of the selected genes were validated by real-time reverse transcription-polymerase chain reaction (RT-PCR). All these results suggest that GEA methodology is (i) suitable for selection of differentially expressed genes in microarray data, (ii) intuitive and computationally efficient and (iii) especially advantageous under conditions of low k. AVAILABILITY The GEA code for R software is freely available upon request to authors.

Transcriptome and translational signaling following endurance exercise in trained skeletal muscle: impact of dietary protein

Postexercise protein feeding regulates the skeletal muscle adaptive response to endurance exercise, but the transcriptome guiding these adaptations in well-trained human skeletal muscle is uncharacterized. In a crossover design, eight cyclists ingested beverages containing protein, carbohydrate and fat (PTN: 0.4, 1.2, 0.2 g/kg, respectively) or isocaloric carbohydrate and fat (CON: 1.6, 0.2 g/kg) at 0 and 1 h following 100 min of cycling. Biopsies of the vastus lateralis were collected at 3 and 48 h following to determine the early and late transcriptome and regulatory signaling responses via microarray and immunoblot. The top gene ontology enriched by PTN were: muscle contraction, extracellular matrix--signaling and structure, and nucleoside, nucleotide, and nucleic acid metabolism (3 and 48 h); developmental processes, immunity, and defense (3 h); glycolysis, lipid and fatty acid metabolism (48 h). The transcriptome was also enriched within axonal guidance, actin cytoskeletal, Ca2+, cAMP, MAPK, and PPAR canonical pathways linking protein nutrition to exercise-stimulated signaling regulating extracellular matrix, slow-myofibril, and metabolic gene expression. At 3 h, PTN attenuated AMPKα1Thr172 phosphorylation but increased mTORC1Ser2448, rps6Ser240/244, and 4E-BP1-γ phosphorylation, suggesting increased translation initiation, while at 48 h AMPKα1Thr172 phosphorylation and PPARG and PPARGC1A expression increased, supporting the late metabolic transcriptome, relative to CON. To conclude, protein feeding following endurance exercise affects signaling associated with cell energy status and translation initiation and the transcriptome involved in skeletal muscle development, slow-myofibril remodeling, immunity and defense, and energy metabolism. Further research should determine the time course and posttranscriptional regulation of this transcriptome and the phenotype responding to chronic postexercise protein feeding.

Influence of gut microbiota on mouse B2 B cell ontogeny and function

A complex interplay between the microbiota and the host immune system is evidenced to shape the immune system throughout life, but little is known about the microbial effect on key players of the adaptive immune system, the B2 B cells. In the presented study, we have evaluated the effect of commensal bacteria on B cell ontogeny and function, with the focus on B2 B cells of spleen and Peyers patches. We have compared germ-free mice to mice that are exposed to a normal complex bacterial community from the day of birth and combined classical immunological assessment with advanced genome-wide expression profiling. Despite a preservation of all B cell subsets and phenotype, our results show that microbiota strongly impact mucosal B cell physiology and lead to higher serum Ig concentrations. We show that this microbial influence comprises downregulation of transcription factors involved in early B cell activation steps and upregulation of genes and proteins involved in later stages of B cell response. In summary, we show an influence of the gut microbiota on function of mucosal B2 B cells, involving mechanisms downstream of B cell activation and proliferation.

Effect of dietary phytic acid on zinc absorption in the healthy elderly, as assessed by serum concentration curve tests

Zn absorption was investigated in healthy elderly subjects aged 71-78 years and in young subjects aged 23-43 years using serum concentration curve (SCC) tests. Both groups had similar Zn and protein status. The increase in serum Zn was monitored for 180 min after ingestion of 200 ml of soya milk enriched with 50 mg of Zn. Three levels of phytic acid were used: 0 g/200 ml (totally dephytinized soya milk), 0.13 g/200 ml (half dephytinized), and 0.26 g/200 ml (natural phytic acid content). In a first study the effect of 0 v. 0.26 g/200 ml phytic acid was compared in 10 elderly and 10 young subjects, each subject receiving both treatments. In a second study soya milks with 0 and 0.13 g/200 ml were tested in nine elderly and ten young subjects, again receiving both treatments. Mean areas under the curve of the SCC tests conducted with the 0 g/200 ml soya milk were found to be the same in both studies. Phytic acid strongly depressed Zn absorption in both studies (P < or = 0.05), but to a greater extent at the 0.26 g/200 ml level. No difference was found between the groups of young and elderly subjects. Therefore, no significant effect of aging on Zn absorption, as evaluated by the SCC test, or on the inhibitory effect of phytic acid was detected.

Protein-leucine ingestion activates a regenerative inflammo-myogenic transcriptome in skeletal muscle following intense endurance exercise

Protein-leucine supplement ingestion following strenuous endurance exercise accentuates skeletal-muscle protein synthesis and adaptive molecular responses, but the underlying transcriptome is uncharacterized. In a randomized single-blind triple-crossover design, 12 trained men completed 100 min of high-intensity cycling then ingested 70/15/180/30 g protein-leucine-carbohydrate-fat (15LEU), 23/5/180/30 g (5LEU), or 0/0/274/30 g (CON) beverages during the first 90 min of a 240 min recovery period. Vastus lateralis muscle samples (30 and 240 min postexercise) underwent transcriptome analysis by microarray followed by bioinformatic analysis. Gene expression was regulated by protein-leucine in a dose-dependent manner affecting the inflammatory response and muscle growth and development. At 30 min, 15LEU and 5LEU vs. CON activated transcriptome networks with gene-set functions involving cell-cycle arrest (Z-score 2.0-2.7, P < 0.01), leukocyte maturation (1.7, P = 0.007), cell viability (2.4, P = 0.005), promyogenic networks encompassing myocyte differentiation and myogenin (MYOD1, MYOG), and a proteinaceous extracellular matrix, adhesion, and development program correlated with plasma lysine, arginine, tyrosine, taurine, glutamic acid, and asparagine concentrations. High protein-leucine dose (15LEU-5LEU) activated an IL-1I-centered proinflammatory network and leukocyte migration, differentiation, and survival functions (2.0-2.6, <0.001). By 240 min, the protein-leucine transcriptome was anti-inflammatory and promyogenic (IL-6, NF- β, SMAD, STAT3 network inhibition), with overrepresented functions including decreased leukocyte migration and connective tissue development (-1.8-2.4, P < 0.01), increased apoptosis of myeloid and muscle cells (2.2-3.0, P < 0.002), and cell metabolism (2.0-2.4, P < 0.01). The analysis suggests protein-leucine ingestion modulates inflammatory-myogenic regenerative processes during skeletal muscle recovery from endurance exercise. Further cellular and translational research is warranted to validate amino acid-mediated myeloid and myocellular mechanisms within skeletal-muscle functional plasticity.