908 research outputs found
Reconstruction and modeling protein translocation and compartmentalization in Escherichia coli at the genome-scale
BackgroundMembranes play a crucial role in cellular functions. Membranes provide a physical barrier, control the trafficking of substances entering and leaving the cell, and are a major determinant of cellular ultra-structure. In addition, components embedded within the membrane participate in cell signaling, energy transduction, and other critical cellular functions. All these processes must share the limited space in the membrane; thus it represents a notable constraint on cellular functions. Membrane- and location-based processes have not yet been reconstructed and explicitly integrated into genome-scale models.ResultsThe recent genome-scale model of metabolism and protein expression in Escherichia coli (called a ME-model) computes the complete composition of the proteome required to perform whole cell functions. Here we expand the ME-model to include (1) a reconstruction of protein translocation pathways, (2) assignment of all cellular proteins to one of four compartments (cytoplasm, inner membrane, periplasm, and outer membrane) and a translocation pathway, (3) experimentally determined translocase catalytic and porin diffusion rates, and (4) a novel membrane constraint that reflects cell morphology. Comparison of computations performed with this expanded ME-model, named iJL1678-ME, against available experimental data reveals that the model accurately describes translocation pathway expression and the functional proteome by compartmentalized mass.ConclusioniJL1678-ME enables the computation of cellular phenotypes through an integrated computation of proteome composition, abundance, and activity in four cellular compartments (cytoplasm, periplasm, inner and outer membrane). Reconstruction and validation of the model has demonstrated that the iJL1678-ME is capable of capturing the functional content of membranes, cellular compartment-specific composition, and that it can be utilized to examine the effect of perturbing an expanded set of network components. iJL1678-ME takes a notable step towards the inclusion of cellular ultra-structure in genome-scale models
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GABA-modulating bacteria of the human gut microbiota.
The gut microbiota affects many important host functions, including the immune response and the nervous system1. However, while substantial progress has been made in growing diverse microorganisms of the microbiota2, 23-65% of species residing in the human gut remain uncultured3,4, which is an obstacle for understanding their biological roles. A likely reason for this unculturability is the absence in artificial media of key growth factors that are provided by neighbouring bacteria in situ5,6. In the present study, we used co-culture to isolate KLE1738, which required the presence of Bacteroides fragilis to grow. Bioassay-driven purification of B. fragilis supernatant led to the isolation of the growth factor, which, surprisingly, is the major inhibitory neurotransmitter GABA (Îł-aminobutyric acid). GABA was the only tested nutrient that supported the growth of KLE1738, and a genome analysis supported a GABA-dependent metabolism mechanism. Using growth of KLE1738 as an indicator, we isolated a variety of GABA-producing bacteria, and found that Bacteroides ssp. produced large quantities of GABA. Genome-based metabolic modelling of the human gut microbiota revealed multiple genera with the predicted capability to produce or consume GABA. A transcriptome analysis of human stool samples from healthy individuals showed that GABA-producing pathways are actively expressed by Bacteroides, Parabacteroides and Escherichia species. By coupling 16S ribosmal RNA sequencing with functional magentic resonance imaging in patients with major depressive disorder, a disease associated with an altered GABA-mediated response, we found that the relative abundance levels of faecal Bacteroides are negatively correlated with brain signatures associated with depression
Recon 2.2: from reconstruction to model of human metabolism.
IntroductionThe human genome-scale metabolic reconstruction details all known metabolic reactions occurring in humans, and thereby holds substantial promise for studying complex diseases and phenotypes. Capturing the whole human metabolic reconstruction is an on-going task and since the last community effort generated a consensus reconstruction, several updates have been developed.ObjectivesWe report a new consensus version, Recon 2.2, which integrates various alternative versions with significant additional updates. In addition to re-establishing a consensus reconstruction, further key objectives included providing more comprehensive annotation of metabolites and genes, ensuring full mass and charge balance in all reactions, and developing a model that correctly predicts ATP production on a range of carbon sources.MethodsRecon 2.2 has been developed through a combination of manual curation and automated error checking. Specific and significant manual updates include a respecification of fatty acid metabolism, oxidative phosphorylation and a coupling of the electron transport chain to ATP synthase activity. All metabolites have definitive chemical formulae and charges specified, and these are used to ensure full mass and charge reaction balancing through an automated linear programming approach. Additionally, improved integration with transcriptomics and proteomics data has been facilitated with the updated curation of relationships between genes, proteins and reactions.ResultsRecon 2.2 now represents the most predictive model of human metabolism to date as demonstrated here. Extensive manual curation has increased the reconstruction size to 5324 metabolites, 7785 reactions and 1675 associated genes, which now are mapped to a single standard. The focus upon mass and charge balancing of all reactions, along with better representation of energy generation, has produced a flux model that correctly predicts ATP yield on different carbon sources.ConclusionThrough these updates we have achieved the most complete and best annotated consensus human metabolic reconstruction available, thereby increasing the ability of this resource to provide novel insights into normal and disease states in human. The model is freely available from the Biomodels database (http://identifiers.org/biomodels.db/MODEL1603150001)
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Enabling precision medicine in neonatology, an integrated repository for preterm birth research.
Preterm birth, or the delivery of an infant prior to 37 weeks of gestation, is a significant cause of infant morbidity and mortality. In the last decade, the advent and continued development of molecular profiling technologies has enabled researchers to generate vast amount of 'omics' data, which together with integrative computational approaches, can help refine the current knowledge about disease mechanisms, diagnostics, and therapeutics. Here we describe the March of Dimes' Database for Preterm Birth Research (http://www.immport.org/resources/mod), a unique resource that contains a variety of 'omics' datasets related to preterm birth. The database is open publicly, and as of January 2018, links 13 molecular studies with data across tens of thousands of patients from 6 measurement modalities. The data in the repository are highly diverse and include genomic, transcriptomic, immunological, and microbiome data. Relevant datasets are augmented with additional molecular characterizations of almost 25,000 biological samples from public databases. We believe our data-sharing efforts will lead to enhanced research collaborations and coordination accelerating the overall pace of discovery in preterm birth research
Effect of Pulsed or Continuous Delivery of Salt on Sensory Perception Over Short Time Intervals
Salt in the human diet is a major risk factor for hypertension and many countries have set targets to reduce
salt consumption. Technological solutions are being sought
to lower the salt content of processed foods without altering their taste. In this study, the approach was to deliver salt solutions in pulses of different concentrations to determine whether a pulsed delivery profile affected sensory perception of salt. Nine different salt profiles were delivered by a Dynataste device and a trained panel assessed their saltiness using time–intensity and single-score sensory techniques. The profile duration (15 s) was designed to match eating conditions and the effects of intensity and duration of the pulses on sensory perception were investigated. Sensory results from the profiles delivered in either water or in a bouillon base were not statistically different. Maximum perceived salt intensities and the area under the time–
intensity curves correlated well with the overall perceived
saltiness intensity despite the stimulus being delivered as
several pulses. The overall saltiness scores for profiles
delivering the same overall amount of sodium were statistically not different from one another suggesting that, in this system, pulsed delivery did not enhance salt
perception but the overall amount of salt delivered in each
profile did affect sensory perception
Mapping Cosmic Dawn and Reionization: Challenges and Synergies
Cosmic dawn and the Epoch of Reionization (EoR) are among the least explored
observational eras in cosmology: a time at which the first galaxies and
supermassive black holes formed and reionized the cold, neutral Universe of the
post-recombination era. With current instruments, only a handful of the
brightest galaxies and quasars from that time are detectable as individual
objects, due to their extreme distances. Fortunately, a multitude of
multi-wavelength intensity mapping measurements, ranging from the redshifted 21
cm background in the radio to the unresolved X-ray background, contain a
plethora of synergistic information about this elusive era. The coming decade
will likely see direct detections of inhomogenous reionization with CMB and 21
cm observations, and a slew of other probes covering overlapping areas and
complementary physical processes will provide crucial additional information
and cross-validation. To maximize scientific discovery and return on
investment, coordinated survey planning and joint data analysis should be a
high priority, closely coupled to computational models and theoretical
predictions.Comment: 5 pages, 1 figure, submitted to the Astro2020 Decadal Survey Science
White Paper cal
The evolutionary patterns of barley pericentromeric chromosome regions, as shaped by linkage disequilibrium and domestication
The distribution of recombination events along large cereal chromosomes is uneven and is generally restricted to gene-rich telomeric ends. To understand how the lack of recombination affects diversity in the large pericentromeric regions, we analysed deep exome capture data from a final panel of 815 Hordeum vulgare (barley) cultivars, landraces and wild barleys, sampled from across their eco-geographical ranges. We defined and compared variant data across the pericentromeric and non-pericentromeric regions, observing a clear partitioning of diversity both within and between chromosomes and germplasm groups. Dramatically reduced diversity was found in the pericentromeres of both cultivars and landraces when compared with wild barley. We observed a mixture of completely and partially differentiated single-nucleotide polymorphisms (SNPs) between domesticated and wild gene pools, suggesting that domesticated gene pools were derived from multiple wild ancestors. Patterns of genome-wide linkage disequilibrium, haplotype block size and number, and variant frequency within blocks showed clear contrasts among individual chromosomes and between cultivars and wild barleys. Although most cultivar chromosomes shared a single major pericentromeric haplotype, chromosome 7H clearly differentiated the two-row and six-row types associated with different geographical origins. Within the pericentromeric regions we identified 22 387 non-synonymous SNPs, 92 of which were fixed for alternative alleles in cultivar versus wild accessions. Surprisingly, only 29 SNPs found exclusively in the cultivars were predicted to be 'highly deleterious'. Overall, our data reveal an unconventional pericentromeric genetic landscape among distinct barley gene pools, with different evolutionary processes driving domestication and diversification.</p
Constraints on the Progenitor System of the Type Ia Supernova SN 2011fe/PTF11kly
Type Ia supernovae (SNe) serve as a fundamental pillar of modern cosmology,
owing to their large luminosity and a well-defined relationship between
light-curve shape and peak brightness. The precision distance measurements
enabled by SNe Ia first revealed the accelerating expansion of the universe,
now widely believed (though hardly understood) to require the presence of a
mysterious "dark" energy. General consensus holds that Type Ia SNe result from
thermonuclear explosions of a white dwarf (WD) in a binary system; however,
little is known of the precise nature of the companion star and the physical
properties of the progenitor system. Here we make use of extensive historical
imaging obtained at the location of SN 2011fe/PTF11kly, the closest SN Ia
discovered in the digital imaging era, to constrain the visible-light
luminosity of the progenitor to be 10-100 times fainter than previous limits on
other SN Ia progenitors. This directly rules out luminous red giants and the
vast majority of helium stars as the mass-donating companion to the exploding
white dwarf. Any evolved red companion must have been born with mass less than
3.5 times the mass of the Sun. These observations favour a scenario where the
exploding WD of SN 2011fe/PTF11kly, accreted matter either from another WD, or
by Roche-lobe overflow from a subgiant or main-sequence companion star.Comment: 22 pages, 6 figures, submitte
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