Phenotypic signatures arising from unbalanced bacterial growth.
Ontology highlight
ABSTRACT:
SUBMITTER: Tan C
PROVIDER: S-EPMC4125075 | biostudies-literature | 2014 Aug
REPOSITORIES: biostudies-literature
Publications
Phenotypic signatures arising from unbalanced bacterial growth.
Tan Cheemeng C Smith Robert Phillip RP Tsai Ming-Chi MC Schwartz Russell R You Lingchong L
PLoS computational biology 20140807 8
Fluctuations in the growth rate of a bacterial culture during unbalanced growth are generally considered undesirable in quantitative studies of bacterial physiology. Under well-controlled experimental conditions, however, these fluctuations are not random but instead reflect the interplay between intra-cellular networks underlying bacterial growth and the growth environment. Therefore, these fluctuations could be considered quantitative phenotypes of the bacteria under a specific growth conditio ...[more]
Similar Datasets
Project description:The scarce knowledge on phenotypic characterization restricts the usage of genetic diversity of plant genetic resources in research and breeding. We describe original and ready-to-use processed data for approximately 60% of ~22,000 barley accessions hosted at the Federal ex situ Genebank for Agricultural and Horticultural Plant Species. The dataset gathers records for three traits with agronomic relevance: flowering time, plant height and thousand grain weight. This information was collected for seven decades for winter and spring barley during the seed regeneration routine. The curated data represent a source for research on genetics and genomics of adaptive and yield related traits in cereals due to the importance of barley as model organism. This data could be used to predict the performance of non-phenotyped individuals in other collections through genomic prediction. Moreover, the dataset empowers the utilization of phenotypic diversity of genetic resources for crop improvement.
| S-EPMC6278694 | biostudies-literature
Project description:Background: Arbovirus infections have steadily become a major pandemic threat. This study aimed at investigating the existence of host epigenetic markers arising from the principal arboviruses infections impacting on human health. We set to systematically review all published evidence describing any epigenetic modifications associated with infections from arboviruses, including, but not limited to, microRNAs, DNA methylation, and histone modifications. Methods: A comprehensive search was conducted using the electronic databases PubMed, Science Direct and Cochrane Library from inception to January 4th, 2018. We included reports describing original in vivo or in vitro studies investigating epigenetic changes related to arbovirus infections in either clinical subjects or human cell lines. Studies investigating epigenetic modifications related to the virus or the arthropod vector were excluded. A narrative synthesis of the findings was conducted, contextualizing comparative evidence from in vitro and in vivo studies. Results: A total of 853 unique references were identified and screened by two independent researchers. Thirty-two studies met the inclusion criteria and were reviewed. The evidence was centered mainly on microRNA and DNA methylation signatures implicated with secondary Dengue fever. Evidence for recent epidemic threats, such as the infections by Zika or Chikungunya viruses is still scant. Conclusions: Major epigenetic alterations found on arboviruses infections were miR-146, miR-30e and the Dicer complex. However, existing studies frequently tested distinct hypotheses resulting in a heterogeneity of methodological approaches. Whilst epigenetic signatures associated with arbovirus infections have been reported, existing studies have largely focused on a small number of diseases, particularly dengue. Validation of epigenetic signatures have an untapped potential, but concerted investigations are certainly required to deliver robust candidates of clinical utility for diagnosis, staging and prognosis of specific arboviral diseases.
| S-EPMC6554415 | biostudies-literature
Project description:Monosomy 1p36 syndrome is one of the most common submicroscopic deletion syndromes, which is characterized by the presence of delayed developmental milestones, intellectual disability, and clinically recognizable dysmorphic craniofacial features. The syndrome comprises 4 cytogenetic groups including pure terminal deletions, interstitial deletions, complex rearrangements, and derivative chromosomes 1 due to unbalanced translocations, where unbalanced translocations represent the least percentage of all cases of monosomy 1p36 (7%). Most patients with monosomy 1p36 due to an unbalanced translocation can be cytogenetically diagnosed using conventional techniques. However, chromosomal microarray analysis is mandatory in these cases to detect copy number variance and size of the deletion and allows for setting a phenotype-genotype correlation. Here, we studied a 1.5-year-old female patient who showed intellectual disability, delayed milestones, hypotonia, seizures, and characteristic dysmorphic features including brachycephaly, straight eyebrows, deep-set eyes, downslanting palpebral fissures, midface hypoplasia, depressed nasal bridge, long philtrum, and pointed chin. Conventional cytogenetic analysis (CCA), microarray study, and fluorescence in situ hybridization (FISH) analysis were performed. CCA showed a translocation involving chromosomes 1 and 21, 45,XX,der(1)t(1;21)(p36.32;q21.1)dn. Microarray analysis revealed copy number losses at both 1p36 and proximal 21q. FISH confirmed the presence of the 1p36 deletion, but was not performed for 21q. We have concluded that phenotype-genotype correlation for monosomy 1p36 syndrome can be performed for the fundamental clinical manifestations; however, the final aspect of the syndrome depends on composite factors. Monosomy 1p36 due to unbalanced translocation may present either classically or with additional altered features of various severity based on the copy number variations involving different chromosomes.
| S-EPMC7802438 | biostudies-literature
Project description:UNLABELLED:Bacterial vaginosis (BV) is characterized by shifts in the vaginal microbiota from Lactobacillus dominant to a microbiota with diverse anaerobic bacteria. Few studies have linked specific metabolites with bacteria found in the human vagina. Here, we report dramatic differences in metabolite compositions and concentrations associated with BV using a global metabolomics approach. We further validated important metabolites using samples from a second cohort of women and a different platform to measure metabolites. In the primary study, we compared metabolite profiles in cervicovaginal lavage fluid from 40 women with BV and 20 women without BV. Vaginal bacterial representation was determined using broad-range PCR with pyrosequencing and concentrations of bacteria by quantitative PCR. We detected 279 named biochemicals; levels of 62% of metabolites were significantly different in women with BV. Unsupervised clustering of metabolites separated women with and without BV. Women with BV have metabolite profiles marked by lower concentrations of amino acids and dipeptides, concomitant with higher levels of amino acid catabolites and polyamines. Higher levels of the signaling eicosanoid 12-hydroxyeicosatetraenoic acid (12-HETE), a biomarker for inflammation, were noted in BV. Lactobacillus crispatus and Lactobacillus jensenii exhibited similar metabolite correlation patterns, which were distinct from correlation patterns exhibited by BV-associated bacteria. Several metabolites were significantly associated with clinical signs and symptoms (Amsel criteria) used to diagnose BV, and no metabolite was associated with all four clinical criteria. BV has strong metabolic signatures across multiple metabolic pathways, and these signatures are associated with the presence and concentrations of particular bacteria. IMPORTANCE:Bacterial vaginosis (BV) is a common but highly enigmatic condition that is associated with adverse outcomes for women and their neonates. Small molecule metabolites in the vagina may influence host physiology, affect microbial community composition, and impact risk of adverse health outcomes, but few studies have comprehensively studied the metabolomics profile of BV. Here, we used mass spectrometry to link specific metabolites with particular bacteria detected in the human vagina by PCR. BV was associated with strong metabolic signatures across multiple pathways affecting amino acid, carbohydrate, and lipid metabolism, highlighting the profound metabolic changes in BV. These signatures were associated with the presence and concentrations of particular vaginal bacteria, including some bacteria yet to be cultivated, thereby providing clues as to the microbial origin of many metabolites. Insights from this study provide opportunities for developing new diagnostic markers of BV and novel approaches for treatment or prevention of BV.
| S-EPMC4453549 | biostudies-literature
Project description:Rett syndrome (RTT), a neurodevelopmental disorder affecting mostly females, is caused by mutations in the X-linked gene encoding methyl-CpG-binding protein 2 (MeCP2). Although the majority of girls with classic RTT have a random pattern of X-chromosome inactivation (XCI), nonbalanced patterns have been observed in patients carrying mutant MECP2 and, in some cases, account for variability of phenotypic manifestations. We have generated an RTT mouse model that recapitulates all major aspects of the human disease, but we found that females exhibit a high degree of phenotypic variability beyond what is observed in human patients with similar mutations. To evaluate whether XCI influences the phenotypic outcome of Mecp2 mutation in the mouse, we studied the pattern of XCI at the single-cell level in brains of heterozygous females. We found that XCI patterns were unbalanced, favoring expression of the wild-type allele, in most mutant females. It is notable that none of the animals had nonrandom XCI favoring the mutant allele. To explore why the XCI patterns favored expression of the wild-type allele, we studied primary neuronal cultures from Mecp2-mutant mice and found selective survival of neurons in which the wild-type X chromosome was active. Quantitative analysis indicated that fewer phenotypes are observed when a large percentage of neurons have the mutant X chromosome inactivated. The study of neuronal XCI patterns in a large number of female mice carrying a mutant Mecp2 allele highlights the importance of MeCP2 for neuronal viability. These findings also raise the possibility that there are human females who carry mutant MECP2 alleles but are not recognized because their phenotypes are subdued owing to favorable XCI patterns.
| S-EPMC1182264 | biostudies-literature
Project description:BackgroundCranial neural crest cells (NCCs) are a unique embryonic cell type which give rise to a diverse array of derivatives extending from neurons and glia through to bone and cartilage. Depending on their point of origin along the antero-posterior axis cranial NCCs are rapidly sorted into distinct migratory streams that give rise to axial specific structures. These migratory streams mirror the underlying segmentation of the brain with NCCs exiting the diencephalon and midbrain following distinct paths compared to those exiting the hindbrain rhombomeres (r). The genetic landscape of cranial NCCs arising at different axial levels remains unknown.ResultsHere we have used RNA sequencing to uncover the transcriptional profiles of mouse cranial NCCs arising at different axial levels. Whole transcriptome analysis identified over 120 transcripts differentially expressed between NCCs arising anterior to r3 (referred to as r1-r2 migratory stream for simplicity) and the r4 migratory stream. Eight of the genes differentially expressed between these populations were validated by RT-PCR with 2 being further validated by in situ hybridisation. We also explored the expression of the Neuropilins (Nrp1 and Nrp2) and their co-receptors and show that the A-type Plexins are differentially expressed in different cranial NCC streams.ConclusionsOur analyses identify a large number of genes differentially regulated between cranial NCCs arising at different axial levels. This data provides a comprehensive description of the genetic landscape driving diversity of distinct cranial NCC streams and provides novel insight into the regulatory networks controlling the formation of specific skeletal elements and the mechanisms promoting migration along different paths.
| S-EPMC5390458 | biostudies-literature
Project description:The explosion of sequence information in bacteria makes developing high-throughput, cost-effective approaches to matching genes with phenotypes imperative. Using E. coli as proof of principle, we show that combining large-scale chemical genomics with quantitative fitness measurements provides a high-quality data set rich in discovery. Probing growth profiles of a mutant library in hundreds of conditions in parallel yielded > 10,000 phenotypes that allowed us to study gene essentiality, discover leads for gene function and drug action, and understand higher-order organization of the bacterial chromosome. We highlight new information derived from the study, including insights into a gene involved in multiple antibiotic resistance and the synergy between a broadly used combinatory antibiotic therapy, trimethoprim and sulfonamides. This data set, publicly available at http://ecoliwiki.net/tools/chemgen/, is a valuable resource for both the microbiological and bioinformatic communities, as it provides high-confidence associations between hundreds of annotated and uncharacterized genes as well as inferences about the mode of action of several poorly understood drugs.
| S-EPMC3060659 | biostudies-literature
Project description:Application of a genome-wide linkage method to identify genotype-phenotype relationships between distantly related strains of E. coli. Each hybridization compares transposon footprinting results from a linkage library under a selective condition with those under a nonselective condition. For each of three conditions, we compare transposon footprinting for a library selected under that condition with those under a reference condition (glucose minimal media). Each experiment was performed in duplicate.
2013-11-30 | E-GEOD-45421 | biostudies-arrayexpress
Project description:Although the relationship between phenotypic plasticity and evolutionary dynamics has attracted large interest, very little is known about the contribution of phenotypic plasticity to adaptive evolution. In this study, we analyzed phenotypic and genotypic changes in E. coli cells during adaptive evolution to ethanol stress. To quantify the phenotypic changes, transcriptome analyses were performed. We previously obtained 6 independently evolved ethanol tolerant E. coli strains, strains A through F, by culturing cells under 5% ethanol stress for about 1000 generations and found a significantly larger growth rate than the parent strains (Horinouchi et al, 2010, PMID: 20955615). To elucidate the phenotypic changes that occurred during adaptive evolution, we quantified the time-series of the expression changes by microarray analysis. Starting from frozen stocks obtained at 6 time points (0, 384, 744, 1224, 1824 and 2496 hours) in laboratory evolution, cells were cultured under 5% ethanol stress, and mRNA samples were obtained in the exponential growth phase for microarray analysis.
2014-07-21 | E-GEOD-59050 | biostudies-arrayexpress
Project description:Musculoskeletal pain conditions, such as fibromyalgia and low back pain, tend to coexist in affected individuals and are characterized by a report of pain greater than expected based on the results of a standard physical evaluation. The pathophysiology of these conditions is largely unknown, we lack biological markers for accurate diagnosis, and conventional therapeutics have limited effectiveness. Growing evidence suggests that chronic pain conditions are associated with both physical and psychological triggers, which initiate pain amplification and psychological distress; thus, susceptibility is dictated by complex interactions between genetic and environmental factors. Herein, we review phenotypic and genetic markers of common musculoskeletal pain conditions, selected based on their association with musculoskeletal pain in previous research. The phenotypic markers of greatest interest include measures of pain amplification and 'psychological' measures (such as emotional distress, somatic awareness, psychosocial stress and catastrophizing). Genetic polymorphisms reproducibly linked with musculoskeletal pain are found in genes contributing to serotonergic and adrenergic pathways. Elucidation of the biological mechanisms by which these markers contribute to the perception of pain in these patients will enable the development of novel effective drugs and methodologies that permit better diagnoses and approaches to personalized medicine.
| S-EPMC3991785 | biostudies-literature