Project description:Collection of HeLa maintenance and quality control runs for several years. The dataset was acquired to be used for exploration of deep learning models, initially in the scope of imputation. The repository for this archiv contains hints on how to use the three curated datasets and the single runs as filtered data. It provides links to the files on PRIDE.https://github.com/RasmussenLab/hela_qc_mnt_data The current pre-print of the data descriptor can be found here:https://doi.org/10.21203/rs.3.rs-3083547/v2
Project description:Curated collection of yeast transcription factor DNA binding specificity data reveals novel structural and gene regulatory insights
Project description:Despite various efforts to develop tools to detect and compare the activity and catabolic potential and activity for pollutant degradation of microorganisms in environmental samples, an open-source, curated and reliable method is still required. Here we report on a customize normalization system that can be applied to any microarray design, allowing the assessment of reliability of signals and enabling cross-experiment comparisons. Probes for the underlying catabolic gene array were designed based on manually curated databases for catabolic key genes. Signals were assigned to the respective catabolic protein subfamily that allows to inferring the functions and substrate specificity. The placement of probes for critical degradation nodes and subsequent metabolic steps allows the retrieval of information on the metabolic net. Information on gene localization from genome surveys was correlated to signals of putative hosts to generate phylogenetic community information. Hence, this novel array system was validated using genomic DNA of genome sequenced bacterial strains hosting biodegradation functions and applied to genomic DNA and RNA extracted from environmental samples under aromatic pollution pressure.
Project description:Under well-defined laboratory conditions, we grew R. pomeroyi DSS-3 and A. macleodii MIT1002 in batch cultures on a monosaccharide (glucose) and organic acid (acetate), provided either individually or in combination, and all at the same carbon equivalent. This batch culturing approach mimicked bacterial DOC assimilation in short-lived substrate ‘hot spots’, such as those formed by high phytoplankton extracellular release at peak photon availability. Measurements were made of bacterial metabolite uptake, respiration, and biomass accumulation through a growth cycle. Insights into bacterial core metabolism came from gene and protein expression measured at intervals during growth. Curated genome-scale models (flux balance analysis; FBA) were used to explore the metabolic foundation of CO2 production for insights into determinants of BGE and bCUE.
Project description:The development of reliable, mixed-culture biotechnological processes hinges on understanding how microbial ecosystems respond to disturbances. Here we reveal extensive phenotypic plasticity and niche complementarity in oleaginous microbial populations from a biological wastewater treatment plant. We perform meta-omics analyses (metagenomics, metatranscriptomics, metaproteomics and metabolomics) on in situ samples over 14 months at weekly intervals. Based on 1,364 de novo metagenome-assembled genomes, we uncover four distinct fundamental niche types. Throughout the time-series, we observe a major, transient shift in community structure, coinciding with substrate availability changes. Functional omics data reveals extensive variation in gene expression and substrate usage amongst community members. Ex situ bioreactor experiments confirm that responses occur within five hours of a pulse disturbance, demonstrating rapid adaptation by specific populations. Our results show that community resistance and resilience are a function of phenotypic plasticity and niche complementarity, and set the foundation for future ecological engineering efforts.
Project description:Targeted protein degradation is a novel pharmacology established by drugs that recruit target proteins to E3 ubiquitin ligases. Based on the structure of the degrader and the target, different E3 interfaces are critically involved, thus forming defined "functional hotspots". Understanding disruptive mutations in functional hotspots informs on the architecture of the assembly, and highlights residues susceptible to acquire resistance phenotypes. Here, we employ haploid genetics to show that hotspot mutations cluster in substrate receptors of hijacked ligases, where mutation type and frequency correlate with gene essentiality. A Hybrid capture assay reveals resistance-conferring mutations after degrader treatment. 29 putative target genes were selected to be sequenced. Target gene enrichment from gDNA of treated cells was performed, followed by amplification and sequencing to identify mutations.
Project description:Collection of adult mouse expression profiling covering main types of hematopoietic cells Aiming to identify HSC-specific genes, we have compiled 131 affymetrix MG430 2.0 arrays and re-processed data of third-party that were curated and quality-assured. This collection was built to include numerous progenitors’ subpopulations and balanced representation of major myeloid- and lymphoid cells. Result provided validated identification of genes that are highly specific to HSCs within the hematopoietic system. This dataset also enable direct identification of specific-genes for the other cell types represented.
Project description:Despite various efforts to develop tools to detect and compare the activity and catabolic potential and activity for pollutant degradation of microorganisms in environmental samples, an open-source, curated and reliable method is still required. Here we report on a customize normalization system that can be applied to any microarray design, allowing the assessment of reliability of signals and enabling cross-experiment comparisons. Probes for the underlying catabolic gene array were designed based on manually curated databases for catabolic key genes. Signals were assigned to the respective catabolic protein subfamily that allows to inferring the functions and substrate specificity. The placement of probes for critical degradation nodes and subsequent metabolic steps allows the retrieval of information on the metabolic net. Information on gene localization from genome surveys was correlated to signals of putative hosts to generate phylogenetic community information. Hence, this novel array system was validated using genomic DNA of genome sequenced bacterial strains hosting biodegradation functions and applied to genomic DNA and RNA extracted from environmental samples under aromatic pollution pressure. Catabolic microarray was optimized for detection and expression of catabolic genes involved in the degradation of pollutant compounds using genome genomic DNA of type strains: Burkholderia xenovorans LB400, Cupriavidus necator JMP134, Pseudomonas putida F1 and Sphingomonas wittichii RW1. Afterwards, this microarray was applied for environmental samples. For microcosm experiments, 200 ml of each groundwater were incubated in closed 1 l Erlenmeyer flasks at 20 degree C and 50 rpm. Second sets of 200 ml microcosms were supplemented with naphthalene (100 mg), which had above been identified as a contaminant present in both groundwaters in similar amounts. Naphthalene was supplied via the vapor phase and incubated under identical conditions as the control microcosms. After 4 days of incubations, 50 ml of each of the 4 microcosms were subjected to genomic DNA extraction and another 50 ml to RNA extraction.
Project description:Liao2011 - Genome-scale metabolic
reconstruction of Klebsiella pneumoniae (iYL1228)
This model is described in the article:
An experimentally validated
genome-scale metabolic reconstruction of Klebsiella pneumoniae
MGH 78578, iYL1228.
Liao YC, Huang TW, Chen FC,
Charusanti P, Hong JS, Chang HY, Tsai SF, Palsson BO, Hsiung
CA.
J. Bacteriol. 2011 Apr; 193(7):
1710-1717
Abstract:
Klebsiella pneumoniae is a Gram-negative bacterium of the
family Enterobacteriaceae that possesses diverse metabolic
capabilities: many strains are leading causes of
hospital-acquired infections that are often refractory to
multiple antibiotics, yet other strains are metabolically
engineered and used for production of commercially valuable
chemicals. To study its metabolism, we constructed a
genome-scale metabolic model (iYL1228) for strain MGH 78578,
experimentally determined its biomass composition,
experimentally determined its ability to grow on a broad range
of carbon, nitrogen, phosphorus and sulfur sources, and
assessed the ability of the model to accurately simulate growth
versus no growth on these substrates. The model contains 1,228
genes encoding 1,188 enzymes that catalyze 1,970 reactions and
accurately simulates growth on 84% of the substrates tested.
Furthermore, quantitative comparison of growth rates between
the model and experimental data for nine of the substrates also
showed good agreement. The genome-scale metabolic
reconstruction for K. pneumoniae presented here thus provides
an experimentally validated in silico platform for further
studies of this important industrial and biomedical
organism.
This model is hosted on
BioModels Database
and identified by:
MODEL1507180054.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
Project description:Circadian profiling improves target gene detection and pathway characterization in mouse models of NASH. Fatty livers show 3-hour advances in metabolic and clock gene transcript rhythms. Circadian profiling further reveals temporal changes in lipid, carbohydrate, and cholesterol metabolic transcripts.