Monocytes re-enter the bone marrow during fasting and alter the host response to infection
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE217597 | GEO | 2023/03/07
REPOSITORIES: GEO
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Project description:One of the key functions of the mammalian liver is lipid metabolism. During fasting, lipid storage in the liver increases in order to reserve and provide energy for cellular functions. Upon re-feeding, this reserve of lipids is rapidly depleted; this change is visible, as the organelles responsible for lipid storage – lipid droplets (LDs) – drastically decrease in size following re-feeding. Little is known regarding LD proteome, or how it changes during the fasting/re-feeding transition. Our study investigated the hepatic LD proteome and how it changes between fasting and re-feeding conditions. For this purpose, LDs were isolated from 4 month-old C57BL/6 mice after a 24 hour fasting period, or a 24 hour fasting period followed by 6 hours of re-feeding. Proteins isolated from these LDs were subject to SDS-PAGE followed by in-gel trypsinization and LC-MS/MS. We identified a combined total of 941 proteins on hepatic LDs, of which 817 had quantifiable extracted ion chromatograms in at least 2 samples (n=6 total) and were not deemed contaminants. 777 of the 817 proteins were observed in both energetic states, with 33 being uniquely observed in fasted LDs, and 7 being uniquely observed in re-fed LDs.
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Project description:This study integrates global transcriptional profiling and the metabolic perturbation induced by fasting and re-feeding. Genetic control of growth and development should be revealed by systematic modeling of metabolic and regulatory pathways. Chicken oligo arrays were used for transcriptional profiling in two time-course experiments. Two critical developmental stages were chosen: immediately after hatchling (Wk1) and prior to marketing of broiler chickens (Wk6). Only male chickens were used to simplify the experimental design. A RNA reference design was employed for microarray hybridization using two reference RNA pools derived from all individuals sampled at either Wk1 or Wk6. Microarray data was acquired using GenePix Pro software. Loess normalization and a linear mixed model were applied in data processing using the R statistical package with LIMMA software [Smyth, G. K. (2004) Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Statistical Applications in Genetics and Molecular Biology, Vol. 3, No. 1, Article 3]. The results show hundreds of differentially expressed genes, which are regulated by age and the metabolic perturbation of fasting and re-feeding. Numerous common genes were found at both developmental stages (Wk1 and Wk6) that could be candidates for controlling growth and development of chickens. Differential expression revealed by either microarray or qRT-PCR analyses of selected genes was highly consistent. QRT-PCR verification of genes acutely depressed by fasting includes AGO1, ANGTPL3, ATPCL, FASN, FAT, ME1, PPARG, SCD1, SREBP1 and THRSPA. Genes up-regulated by fasting were ALDOB, IL-15, LDHB, LIPIN2, PANK1, PPARA and UPP2. These genes are functionally assigned to metabolic enzymes, transcription factors, acute phase proteins, immune factors and involved in various pathways (i.e., fatty acid and amino acid metabolism, glycolysis, growth factor signaling and immune defense). Keywords: Hepatic transcripts, oligo-array, chicken, metabolic perturbation, fasting and re-feeding
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Project description:This study integrates global transcriptional profiling and the metabolic perturbation induced by fasting and re-feeding. Genetic control of growth and development should be revealed by systematic modeling of metabolic and regulatory pathways. Chicken oligo arrays were used for transcriptional profiling in two time-course experiments. Two critical developmental stages were chosen: immediately after hatchling (Wk1) and prior to marketing of broiler chickens (Wk6). Only male chickens were used to simplify the experimental design. A RNA reference design was employed for microarray hybridization using two reference RNA pools derived from all individuals sampled at either Wk1 or Wk6. Microarray data was acquired using GenePix Pro software. Loess normalization and a linear mixed model were applied in data processing using the R statistical package with LIMMA software [Smyth, G. K. (2004) Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Statistical Applications in Genetics and Molecular Biology, Vol. 3, No. 1, Article 3]. The results show hundreds of differentially expressed genes, which are regulated by age and the metabolic perturbation of fasting and re-feeding. Numerous common genes were found at both developmental stages (Wk1 and Wk6) that could be candidates for controlling growth and development of chickens. Differential expression revealed by either microarray or qRT-PCR analyses of selected genes was highly consistent. QRT-PCR verification of genes acutely depressed by fasting includes AGO1, ANGTPL3, ATPCL, FASN, FAT, ME1, PPARG, SCD1, SREBP1 and THRSPA. Genes up-regulated by fasting were ALDOB, IL-15, LDHB, LIPIN2, PANK1, PPARA and UPP2. These genes are functionally assigned to metabolic enzymes, transcription factors, acute phase proteins, immune factors and involved in various pathways (i.e., fatty acid and amino acid metabolism, glycolysis, growth factor signaling and immune defense). A reference RNA design was used for microarray hybridizations, where the same reference RNA pool was co-hybridized to each target sample on an microarray. The reference RNA pool was made from an equal amount of high-quality amplified RNA (aRNA), derived from all liver samples within each experiment (Wk1 = 50 samples and Wk6 = 30 samples). The reference RNA pool was labeled with Alexa 647 while each target sample was labeled with Alexa 555.
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