Project description:In a prior report, we observed two distinct lung microbiomes in healthy subjects that we termed â??pneumotypesâ??: pneumotypeSPT, characterized by high bacterial load and supraglottic predominant taxa (SPT) such as the anaerobes Prevotella and Veillonella; and pneumotypeBPT, with low bacterial burden and background predominant taxa (BPT) found in the saline lavage and bronchoscope. Here, we determined the prevalence of these two contrasting lung microbiome types, in a multi-center study of healthy subjects. We confirmed that a lower airway microbiome enriched with upper airway microbes (pneumotypeSPT) was present in ~45% of healthy individuals. Cross-sectional Multicenter cohort. BAL of 49 healthy subjects from three cohort had their lower airway microbiome assessed by 16S rDNA sequencing and microbial gene content (metagenome) was computationally inferred from taxonomic assignments. The amplicons from total 100 samples are barcoded; the barcode and other clinical characteristics (e.g. inflammatory biomarkers and metabolome data) for each sample are provided in the 'Pneumotype.sep.Map.A1.txt' file.
Project description:Secreted metabolites are an important class of bio-process analytical technology (PAT) targets that can correlate to cell conditions. However, current strategies for measuring metabolites are limited to discrete measurements, resulting in limited understanding and ability for feedback control strategies. Herein, a continuous metabolite monitoring strategy is demonstrated using a single-use metabolite absorbing resonant transducer (SMART) to correlate with cell growth. Polyacrylate is shown to absorb secreted metabolites from living cells containing hydroxyl and alkenyl groups such as terpenoids, that act as a plasticizer. Upon softening, the polyacrylate irreversibly conformed into engineered voids above a resonant sensor, changing the local permittivity which is interrogated, contact-free, with a vector network analyzer. Compared to sensing using the intrinsic permittivity of cells, the SMART approach yields a 20-fold improvement in sensitivity. Tracking growth of many cell types such as Chinese hamster ovary, HEK293, K562, HeLa, and E. coli cells as well as perturbations in cell proliferation during drug screening assays are demonstrated. The sensor is benchmarked to show continuous measurement over six days, ability to track different growth conditions, selectivity to transducing active cell growth metabolites against other components found in the media, and feasibility to scale out for high throughput campaigns.
Project description:Classically, phenotype is what is observed, and genotype is the genetic makeup. Statistical studies aim to project phenotypic likelihoods of genotypic patterns. The traditional genotype-to-phenotype theory embraces the view that the encoded protein shape together with gene expression level largely determines the resulting phenotypic trait. Here, we point out that the molecular biology revolution at the turn of the century explained that the gene encodes not one but ensembles of conformations, which in turn spell all possible gene-associated phenotypes. The significance of a dynamic ensemble view is in understanding the linkage between genetic change and the gained observable physical or biochemical characteristics. Thus, despite the transformative shift in our understanding of the basis of protein structure and function, the literature still commonly relates to the classical genotype-phenotype paradigm. This is important because an ensemble view clarifies how even seemingly small genetic alterations can lead to pleiotropic traits in adaptive evolution and in disease, why cellular pathways can be modified in monogenic and polygenic traits, and how the environment may tweak protein function.
Project description:BackgroundHyaluronan (HA) has previously been identified as an integral component of the limbal stem cell niche in vivo. In this study, we investigated whether a similar HA matrix is also expressed in vitro providing a niche supporting limbal epithelial stem cells (LESCs) during ex vivo expansion. We also investigated whether providing exogenous HA in vitro is beneficial to LESCs during ex vivo expansion.MethodHuman LESCs (hLESCs) were isolated from donor corneas and a mouse corneal epithelial progenitor cell line (TKE2) was obtained. The HA matrix was identified surrounding LESCs in vitro using immunocytochemistry, flow cytometry and red blood exclusion assay. Thereafter, LESCs were maintained on HA coated dishes or in the presence of HA supplemented in the media, and viability, proliferation, cell size, colony formation capabilities and expression of putative stem cell markers were compared with cells maintained on commonly used coated dishes.ResultshLESCs and TKE2 cells express an HA-rich matrix in vitro, and this matrix is essential for maintaining LESCs. Further supplying exogenous HA, as a substrate and supplemented to the media, increases LESC proliferation, colony formation capabilities and the expression levels of putative limbal stem cell markers.ConclusionOur data show that both exogenous and endogenous HA help to maintain the LESC phenotype. Exogenous HA provides improved culture conditions for LESC during ex vivo expansion. Thus, HA forms a favorable microenvironment for LESCs during ex vivo expansion and, therefore, could be considered as an easy and cost-effective substrate and/or supplement for culturing LESCs in the clinic.
Project description:Understanding the interplay between environmental conditions and phenotypes is a fundamental goal of biology. Unfortunately, data that include observations on phenotype and environment are highly heterogeneous and thus difficult to find and integrate. One approach that is likely to improve the status quo involves the use of ontologies to standardize and link data about phenotypes and environments. Specifying and linking data through ontologies will allow researchers to increase the scope and flexibility of large-scale analyses aided by modern computing methods. Investments in this area would advance diverse fields such as ecology, phylogenetics, and conservation biology. While several biological ontologies are well-developed, using them to link phenotypes and environments is rare because of gaps in ontological coverage and limits to interoperability among ontologies and disciplines. In this manuscript, we present (1) use cases from diverse disciplines to illustrate questions that could be answered more efficiently using a robust linkage between phenotypes and environments, (2) two proof-of-concept analyses that show the value of linking phenotypes to environments in fishes and amphibians, and (3) two proposed example data models for linking phenotypes and environments using the extensible observation ontology (OBOE) and the Biological Collections Ontology (BCO); these provide a starting point for the development of a data model linking phenotypes and environments.
Project description:Enterovirus 71 (EV71) is a member of the species Human enterovirus A within the family Picornaviridae and is a major causative agent of epidemics of hand, foot and mouth disease associated with severe neurological disease. Three EV71 genogroups, designated A, B and C, have been identified, with 75-84 % nucleotide sequence similarity between them. Two strains, EV71-26M (genogroup B) and EV71-6F (genogroup C), were found to have distinct cell-culture growth (26M, rapid; 6F, slow) and plaque-formation (26M, large; 6F, small) phenotypes. To identify the genome regions responsible for the growth phenotypes of the two strains, a series of chimeric viruses was constructed by exchanging the 5' untranslated region (UTR), P1 structural protein or P2/P3 non-structural protein gene regions plus the 3'UTR using infectious cDNA clones of both virus strains. Analysis of reciprocal virus chimeras revealed that the 5'UTRs of both strains were compatible, but not responsible for the observed phenotypes. Introduction of the EV71-6F P1 region into the EV71-26M clone resulted in a small-plaque and slow-growth phenotype similar to that of EV71-6F, whereas the reciprocal chimera displayed intermediate-growth and intermediate-sized plaque phenotypes. Introduction of the EV71-26M P2-P3-3'UTR regions into the EV71-6F clone resulted in a large-plaque and rapid-growth phenotype identical to that of strain EV71-26M, whereas the reciprocal chimera retained the background strain large-plaque phenotype. These results indicate that, although both the P1 and P2-P3-3'UTR genome regions influence the EV71 growth phenotype in cell culture, phenotype expression is dependent on specific genome-segment combinations and is not reciprocal.
Project description:Cell culture systems for studying the combined effects of matrix proteins and mechanical forces on the behavior of soft tissue cells have not been well developed. Here, we describe a new biomimetic cell culture system that allows for the study of mixtures of matrix proteins while controlling mechanical stiffness in a range that is physiological for soft tissues. This system consists of layer-by-layer (LbL)-assembled films of native matrix proteins atop mechanically tunable soft supports. We used hepatic stellate cells, which differentiate to myofibroblasts in liver fibrosis, for proof-of-concept studies. By culturing cells on collagen and lumican LbL-modified hydrogels, we demonstrate that this system is noncytotoxic and offers a valid control substrate, that the hydrogel determines the overall system mechanics, and that the addition of lumican to collagen influences the stellate cell phenotype. LbL-modified hydrogels offer the potential to study the influence of complex environmental factors on soft-tissue cells in culture.
Project description:MicroRNAs are important negative regulators of protein coding gene expression, and have been studied intensively over the last few years. To this purpose, different measurement platforms to determine their RNA abundance levels in biological samples have been developed. In this study, we have systematically compared 12 commercially available microRNA expression platforms by measuring an identical set of 20 standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples, and synthetic spikes from homologous microRNA family members. We developed novel quality metrics in order to objectively assess platform performance of very different technologies such as small RNA sequencing, RT-qPCR and (microarray) hybridization. We assessed reproducibility, sensitivity, quantitative performance, and specificity. The results indicate that each method has its strengths and weaknesses, which helps guiding informed selection of a quantitative microRNA gene expression platform in function of particular study goals.
Project description:The function of microbial interactions is to enable microorganisms to survive by establishing a homeostasis between microbial neighbors and local environments. A microorganism can respond to environmental stimuli using metabolic exchange-the transfer of molecular factors, including small molecules and proteins. Microbial interactions not only influence the survival of the microbes but also have roles in morphological and developmental processes of the organisms themselves and their neighbors. This, in turn, shapes the entire habitat of these organisms. Here we highlight our current understanding of metabolic exchange as well as the emergence of new technologies that are allowing us to eavesdrop on microbial conversations comprising dozens to hundreds of secreted metabolites that control the behavior, survival and differentiation of members of the community. The goal of the rapidly advancing field studying multifactorial metabolic exchange is to devise a microbial 'Rosetta stone' in order to understand the language by which microbial interactions are negotiated and, ultimately, to control the outcome of these conversations.