Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Optimization of a Sample Preparation Workflow for Proteomics Analysis of the Mouse Feces

ABSTRACT: We evaluated different protein different extraction protocols (using different lysis buffers) and contaminant removal strategies during bottom-up proteomics analysis of mouse feces to maximize quantitative reproducibility and the number of identified proteins.

INSTRUMENT(S): timsTOF Pro

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Feces

SUBMITTER: Maryam Baniasad

LAB HEAD: Vicki Wysocki

PROVIDER: PXD027788 | Pride | 2022-08-22

REPOSITORIES: Pride

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	Filter_FASP_10k_1.msf	Msf
	Filter_FASP_10k_1.mzML	Mzml
	Filter_FASP_10k_2.msf	Msf
	Filter_FASP_10k_2.mzML	Mzml
	Filter_FASP_10k_3.msf	Msf

Items per page:

1 - 5 of 90

Publications

Optimization of proteomics sample preparation for identification of host and bacterial proteins in mouse feces.

Baniasad Maryam M Kim Yongseok Y Shaffer Michael M Sabag-Daigle Anice A Leleiwi Ikaia I Daly Rebecca A RA Ahmer Brian M M BMM Wrighton Kelly C KC Wysocki Vicki H VH

Analytical and bioanalytical chemistry 20220201 7

Bottom-up proteomics is a powerful method for the functional characterization of mouse gut microbiota. To date, most of the bottom-up proteomics studies of the mouse gut rely on limited amounts of fecal samples. With mass-limited samples, the performance of such analyses is highly dependent on the protein extraction protocols and contaminant removal strategies. Here, protein extraction protocols (using different lysis buffers) and contaminant removal strategies (using different types of filters ...[more]

PMID: 35106611

Similar Datasets

Impact of fecal microbiota transplantation (FMT) in 3 days-ABX-treated recipient mice using feces from 6 NSCLC patients at diagnosis.

Project description:This study aimed to analyze changes in gut microbiota composition in mice after transplantation of fecal microbiota (FMT, N = 6) from the feces of NSCLC patients by analyzing fecal content using 16S rRNA sequencing, 10 days after transplantation. Specific-pathogen-free (SPF) mice were used for each experiments (N=4) as controls.

2023-07-01 | E-MTAB-12812 | biostudies-arrayexpress

Proteome data on the microbial microbiome of grasshopper feces

Project description:For phytophagous insects, the efficiency of utilization of hemicellulose and cellulose depends on the gut microbiota. Shifts in environmental and management conditions alter the presence and abundance of plant species which may induce adaptations in the diversity of gut microbiota. To test the adaptation of the microbiota to a shift from a natural diverse to a monocultural meadow with Dactylis glomerata the highly abundant grasshopper species, Chorthippus dorsatus, was taken from the wild and kept in captivity and were fed with Dactylis glomerata for five days. The feces were collected and analyzed by metaproteomics. After the diet shift from a diverse source to the single source, the microbiota composition stays relatively stable. The Bacilli as the group of highest abundance did not change on the functional level. In contrast, pronounced shifts of amino acid and carbohydrate metabolism in Clostridia and Proteobacteria were observed. Hence, the adaptation upon short-term change of food source in this grasshopper species is dominated by functional adaptations and not by shifts in the community structure of the microbiota. This suggests that the microbiota of grasshoppers is capable to cope also with the loss of diverse feeding plants at least for a shorter time period.

2017-01-02 | PXD005126 | Pride

High-throughput miRNA sequencing and identification of biomarkers for forensically relevant biological fluids

Project description:In this study, small RNAs were isolated from individual donations of eight forensically relevant biological fluids (blood, semen, vaginal fluid, menstrual blood, saliva, urine, feces, and perspiration) and subjected to next generation sequencing using the IlluminaÂ® Hi-Seq platform. Sequencing reads were aligned and annotated against miRbase release 21, resulting in a list of miRNAs and their relative expression levels for each sample analyzed. Body fluids with high bacterial loads (vaginal fluid, saliva, and feces) yielded relatively low annotated miRNA counts, likely due to oversaturation of small RNAs from the endogenous bacteria. Both body-fluid specific and potential normalization miRNAs were identified for further analysis as potential body fluid identification tools for each body fluid. 32 samples - 3-5 replicates of each human biological fluid: venous blood, urine, semen (normal and vasectomized), vaginal secretions, menstrual secretions, perspiration, feces, saliva

2016-08-20 | E-GEOD-85830 | biostudies-arrayexpress

16s rRNA-young and old mouse gut microbiota-stroke

Project description:To explore the effects of gut microbiota of young (8 weeks) or old mice (18～20 months) on stroke, feces of young (Y1-Y9) and old mice (O6-O16) were collected and analyzed by 16s rRNA sequencing. Then stroke model was established on young mouse receive feces from old mouse (DOT1-15) and young mouse receive feces from young mouse (DYT1-15). 16s rRNA sequencing were also performed for those young mice received feces from young and old mice.

2021-10-15 | E-MTAB-10837 | biostudies-arrayexpress

Extracellular miRNAs in serum and feces of mice exposed to high-dose radiation

Project description:Exposure to high-dose radiation causes life-threatening serious intestinal damage. Histological analysis is the most accurate method for judging the extent of intestinal damage after death. However, it is difficult to predict the extent of intestinal damage to body samples. Here we focused on extracellular microRNAs (miRNAs) released from cells and investigated miRNA species that increased or decreased in serum and feces using a radiation-induced intestinal injury mouse model. A peak of small RNA of 25–200 nucleotides was detected in mouse serum and feces 72 h after radiation exposure, and miRNA presence in serum and feces was inferred. MiRNAs expressed in the small intestine and were increased by more than 2.0-fold in serum or feces following a 10 Gy radiation exposure were detected by microarray analysis and were 4 in serum and 19 in feces. In this study, miR-375-3p, detected in serum and feces, was identified as the strongest candidate for a high-dose radiation biomarker in serum and/or feces using a radiation-induced intestinal injury model.

2023-12-15 | GSE247876 | GEO

Metagenome sequencing of feces of mouse treated D-galactose or not

Project description:D-galactose orally intake ameliorate DNCB-induced atopic dermatitis by modulating microbiota composition and quorum sensing. The increased abundance of bacteroidetes and decreased abundance of firmicutes was confirmed. By D-galactose treatment, Bacteroides population was increased and prevotella, ruminococcus was decreased which is related to atopic dermatitis.

2022-04-29 | E-MTAB-11632 | biostudies-arrayexpress

Feces 16S rRNA seq of mice treated by AZ1 with 2.5% DSS or H2O

Project description:Feces 16s rRNA seq experiments is required to demonstrate the AZ1 doesn’t impact the intestinal microbiota.

2020-02-14 | GSE143003 | GEO

pig microbiota ob/le - Intestinal Microbiota and Microbial Metabolites Are Changed in a Pig Model Fed a High-Fat/Low-Fiber or a Low-Fat/High-Fiber Diet

Project description:Feces samples from pigs with two different diets were analysed. Proteins from the microbiota was extracted and analysed by LC-MS/MS. Differences along the time and between the diets were observed.

2016-04-22 | PXD003447 | Pride

16S rRNA gene sequence analysis of feces samples from rats treated with paclitaxel or vehicle controls

Project description:To address the role of gut microbiota in the development of paclitaxel-induced peripheral neuropathy (PIPN), we performed 16S rRNA sequencing analysis of feces samples at 14 days and 28 days after the initiation of paclitaxel or vehicle injections.

2023-10-16 | E-MTAB-13426 | biostudies-arrayexpress

Fecal proteomics as a novel method to study mammalian behavior and physiology

Project description:Mammalian feces can be collected non-invasively during field research and provides valuable information on the ecology and evolution of the host individuals. Undigested food objects, genome/metagenome, steroid hormones, and stable isotopes obtained from fecal samples provide evidence on diet, host/symbiont genetics, and physiological status of the individuals. However, proteins in mammalian feces have hardly been studied, which hampers the molecular investigations into the behavior and physiology of the host individuals. Here, we apply mass spectrometry-based proteomics to fecal samples (n = 10) that were collected from infant, juvenile, and adult captive Japanese macaques (Macaca fuscata) to describe the proteomes of the host, food, and intestinal microbes. The results show that fecal proteomics is a useful method to investigate dietary changes along with breastfeeding and weaning, to reveal the organ/tissue and taxonomy of dietary items, and to estimate physiological status inside intestinal tracts. These types of insights are difficult or impossible to obtain through other molecular approaches. Most mammalian species are facing extinction risk and there is an urgent need to obtain knowledge on their ecology and evolution for better conservation strategy. The fecal proteomics framework we present here is easily applicable to wild settings and other mammalian species, and provides direct evidence of their behavior and physiology.

2021-03-18 | PXD021098 | Pride

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data