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To capture interplay between biological pathways, we analyzed the proteome from matched lung tissues and bronchoalveolar lavage fluid (BALF) of individual allergen-naïve and house dust mite (HDM)-challenged BALB/c mice, a model of allergic asthma. Unbiased label-free liquid chromatography with tandem mass spectrometry (LC-MS/MS) analysis quantified 2675 proteins from tissues and BALF of allergen-naïve and HDM-exposed mice. In comparing the four datasets, we found significantly greater diversity in proteins between lung tissues and BALF than in the changes induced by HDM challenge. The biological pathways enriched after allergen exposure were compartment-dependent. Lung tissues featured innate immune responses and oxidative stress, while BALF most strongly revealed changes in metabolism. We combined lung tissues and BALF proteomes, which principally highlighted oxidation reduction (redox) pathways, a finding influenced chiefly by the lung tissue dataset. Integrating lung and BALF proteomes also uncovered new proteins and biological pathways that may mediate lung tissue and BALF interactions after allergen challenge, for example, B-cell receptor signaling. We demonstrate that enhanced insight is fostered when different biological compartments from the lung are investigated in parallel. Integration of proteomes from lung tissues and BALF compartments reveals new information about protein networks in response to environmental challenge and interaction between intracellular and extracellular processes.

Summary Human induced pluripotent stem cells (hiPSCs) are used to study organogenesis and model disease as well as being developed for regenerative medicine. Endothelial cells are among the many cell types differentiated from hiPSCs, but their maturation and stabilization fall short of that in adult endothelium. We examined whether shear stress alone or in combination with pericyte co-culture would induce flow alignment and maturation of hiPSC-derived endothelial cells (hiPSC-ECs) but found no effects comparable with those in primary microvascular ECs. In addition, hiPSC-ECs lacked a luminal glycocalyx, critical for vasculature homeostasis, shear stress sensing, and signaling. We noted, however, that hiPSC-ECs have dysfunctional mitochondrial permeability transition pores, resulting in reduced mitochondrial function and increased reactive oxygen species. Closure of these pores by cyclosporine A improved EC mitochondrial function but also restored the glycocalyx such that alignment to flow took place. These results indicated that mitochondrial maturation is required for proper hiPSC-EC functionality., Graphical Abstract, Highlights • hiPSC-ECs lack a functional glycocalyx and fail to align to flow • hiPSC-ECs have reduced mitochondrial function and increased leakage of ROS • Closing the mPTP with cyclosporine A induces mitochondrial maturation • Improved mitochondrial function restores the glycocalyx and alignment to flow, Closure of the mitochondrial permeability transition pore by cyclosporine A improved mitochondrial function and maturation of hiPSC-ECs but also restored the glycocalyx such that alignment to flow took place. This functional glycocalyx, necessary for growth factor signaling and anticoagulation, is a prerequisite for future hiPSC-EC applications in tissue engineering, organoid vascularization and therapeutic use of hiPSC-ECs.

Cytotoxic T cells dynamically rewire their metabolism during the course of an immune response. While T-cell metabolism has been extensively studied at phenotypic endpoints of activation and differentiation, the underlying dynamics remain largely elusive. Here, we leverage on single-cell RNA-sequencing (scRNA-seq) measurements of in vitro activated and differentiated CD8+ T cells cultured in physiological media to resolve these metabolic dynamics. We find that our scRNA-seq analysis identifies most metabolic changes previously defined in in vivo experiments, such as a rewiring from an oxidative to an anabolism-promoting metabolic program during activation to an effector state, which is later reverted upon memory polarization. Importantly, our scRNA-seq data further provide a dynamic description of these changes. In this sense, our data predict a differential time-dependent reliance of CD8+ T cells on the synthesis versus uptake of various non-essential amino acids during T-cell activation, which we corroborate with additional functional in vitro experiments. We further exploit our scRNA-seq data to identify metabolic genes that could potentially dictate the outcome of T-cell differentiation, by ranking them based on their expression dynamics. Among the highest-ranked hits, we find asparagine synthetase (Asns), whose expression sharply peaks for effector CD8+ T cells and further decays towards memory polarization. We then confirm that these in vitro Asns expression dynamics are representative of an in vivo situation in a mouse model of viral infection. Moreover, we find that disrupting these expression dynamics in vitro, by depleting asparagine from the culture media, delays central-memory polarization. Accordingly, we find that preventing the decay of ASNS by stable overexpression at the protein level in vivo leads to a significant increase in effector CD8+ T-cell expansion, and a concomitant decrease in central-memory formation, in a mouse model of viral infection. This shows that ASNS expression dynamics dictate the fate of CD8+ T-cell differentiation. In conclusion, we provide a resource of dynamic expression changes during CD8+ T-cell activation and differentiation that is expected to increase our understanding of the dynamic metabolic requirements of T cells progressing along the immune response cascade.

Integrator is a key regulator of NEAT1 isoform switching and, thereby, paraspeckles biogenesis and chemosensitivity., RNA 3′ end processing provides a source of transcriptome diversification which affects various (patho)-physiological processes. A prime example is the transcript isoform switch that leads to the read-through expression of the long non-coding RNA NEAT1_2, at the expense of the shorter polyadenylated transcript NEAT1_1. NEAT1_2 is required for assembly of paraspeckles (PS), nuclear bodies that protect cancer cells from oncogene-induced replication stress and chemotherapy. Searching for proteins that modulate this event, we identified factors involved in the 3′ end processing of polyadenylated RNA and components of the Integrator complex. Perturbation experiments established that, by promoting the cleavage of NEAT1_2, Integrator forces NEAT1_2 to NEAT1_1 isoform switching and, thereby, restrains PS assembly. Consistently, low levels of Integrator subunits correlated with poorer prognosis of cancer patients exposed to chemotherapeutics. Our study establishes that Integrator regulates PS biogenesis and a link between Integrator, cancer biology, and chemosensitivity, which may be exploited therapeutically.

BACKGROUND: Renal endothelial cells from glomerular, cortical, and medullary kidney compartments are exposed to different microenvironmental conditions and support specific kidney processes. However, the heterogeneous phenotypes of these cells remain incompletely inventoried. Osmotic homeostasis is vitally important for regulating cell volume and function, and in mammals, osmotic equilibrium is regulated through the countercurrent system in the renal medulla, where water exchange through endothelium occurs against an osmotic pressure gradient. Dehydration exposes medullary renal endothelial cells to extreme hyperosmolarity, and how these cells adapt to and survive in this hypertonic milieu is unknown. METHODS: We inventoried renal endothelial cell heterogeneity by single-cell RNA sequencing >40,000 mouse renal endothelial cells, and studied transcriptome changes during osmotic adaptation upon water deprivation. We validated our findings by immunostaining and functionally by targeting oxidative phosphorylation in a hyperosmolarity model in vitro and in dehydrated mice in vivo. RESULTS: We identified 24 renal endothelial cell phenotypes (of which eight were novel), highlighting extensive heterogeneity of these cells between and within the cortex, glomeruli, and medulla. In response to dehydration and hypertonicity, medullary renal endothelial cells upregulated the expression of genes involved in the hypoxia response, glycolysis, and-surprisingly-oxidative phosphorylation. Endothelial cells increased oxygen consumption when exposed to hyperosmolarity, whereas blocking oxidative phosphorylation compromised endothelial cell viability during hyperosmotic stress and impaired urine concentration during dehydration. CONCLUSIONS: This study provides a high-resolution atlas of the renal endothelium and highlights extensive renal endothelial cell phenotypic heterogeneity, as well as a previously unrecognized role of oxidative phosphorylation in the metabolic adaptation of medullary renal endothelial cells to water deprivation. ispartof: JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY vol:31 issue:1 pages:118-138 ispartof: location:United States status: published

This study describes the application of the multivariate curve resolution (MCR) analysis technique for real-time analysis of culture fluorescence during recombinant Pichia pastoris cultivation in a bioreactor. Fluorescence spectra were acquired with an on-line dual excitation wavelength fluorometer and then used to develop a real time MCR-based bioprocess monitoring and diagnostics tool. Initial bioreactor experiments using two similar recombinant antibody secreting P. pastoris cell lines showed significant differences in protein production. To distinguish between the contributions of operating conditions and the specific cell line's genetic composition to the observed differences in protein production, the bioreactor experiments were repeated and accompanied by real time MCR analysis. The tests demonstrated high sensitivity of MCR-derived "pure concentration" profiles to growth as well as to initial conditions, thus enabling real-time cultivation process trend diagnostics and fault detection. © 2018 Her Majesty the Queen in Right of Canada © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2761, 2019.

Heterogeneity of lung tumor endothelial cell (TEC) phenotypes across patients, species (human/mouse), and models (in vivo/in vitro) remains poorly inventoried at the single-cell level. We single-cell RNA (scRNA)-sequenced 56,771 endothelial cells from human/mouse (peri)-tumoral lung and cultured human lung TECs, and detected 17 known and 16 previously unrecognized phenotypes, including TECs putatively regulating immune surveillance. We resolved the canonical tip TECs into a known migratory tip and a putative basement-membrane remodeling breach phenotype. Tip TEC signatures correlated with patient survival, and tip/breach TECs were most sensitive to vascular endothelial growth factor blockade. Only tip TECs were congruent across species/models and shared conserved markers. Integrated analysis of the scRNA-sequenced data with orthogonal multi-omics and meta-analysis data across different human tumors, validated by functional analysis, identified collagen modification as a candidate angiogenic pathway.

A method was developed to distinguish Vacci- nium species based on leaf extracts using nuclear magnetic resonance spectroscopy. Reference spectra were measured on leaf extracts from sev- eral species, including lowbush blueberry (Vacci- nium angustifolium), oval leaf huckleberry (Vacci- nium ovalifolium), and cranberry (Vaccinium mac- rocarpon). Using principal component analysis, these leaf extracts were resolved in the scores plot. Analysis of variance statistical tests demon- strated that the three groups differ significantly on PC2, establishing that the three species can be distinguished by nuclear magnetic resonance. Soft independent modeling of class analogies models for each species also showed discrimina- tion between species. To demonstrate the robust- ness of nuclear magnetic resonance spectroscopy for botanical identification, spectra of a sample of lowbush blueberry leaf extract were measured at five different sites, with different field strengths (600 versus 700 MHz), different probe types (cryogenic versus room temperature probes), dif- ferent sample diameters (1.7mm versus 5mm), and different consoles (Avance I versus Avance III). Each laboratory independently demonstrated the linearity of their NMR measurements by ac- quiring a standard curve for chlorogenic acid (R 2 =0.9782 to 0.9998). Spectra acquired on dif- ferent spectrometers atdifferent sites classifed in- to the expectedgroup for the Vaccinium spp., con- firming the utility of the method to distinguish Vaccinium species and demonstrating nuclear magnetic resonance fingerprinting for material validation of a natural health product. " NMR fingerprinting l " Vaccinium spp. l " Ericaceae

The interpretation of NMR spectroscopic information for structure elucidation involves decoding of complex resonance patterns that contain valuable molecular information (δ and J), which is not readily accessible otherwise. We introduce a new concept of 2D-NMR barcoding that uses clusters of fingerprint signals and their spatial relationships in the δ-δ coordinate space to facilitate the chemical identification of complex mixtures. Similar to widely used general barcoding technology, the structural information of individual compounds is encoded as a specifics pattern of their C,H correlation signals. Software-based recognition of these patterns enables the structural identification of the compounds and their discrimination in mixtures. Using the triterpenes from various Actaea (syn. Cimicifuga) species as a test case, heteronuclear multiple-bond correlation (HMBC) barcodes were generated on the basis of their structural subtypes from a statistical investigation of their δH and δC data in the literature. These reference barcodes allowed in silico identification of known triterpenes in enriched fractions obtained from an extract of A. racemosa (black cohosh). After dereplication, a differential analysis of heteronuclear single-quantum correlation (HSQC) spectra even allowed for the discovery of a new triterpene. The 2D barcoding concept has potential application in a natural product discovery project, allowing for the rapid dereplication of known compounds and as a tool in the search for structural novelty within compound classes with established barcodes. © 2014 American Chemical Society.

Modeling NMR-based metabolomics data often involves linear methods such as principal component analysis (PCA) and partial least squares (PLS). These methods have the objective of describing the main variance in the data and maximum covariance between the predictor variables and some response variable respectively. If the experiment is designed to investigate temporal biological fluctuations, however, the factors obtained become difficult to interpret in a biological context. Moreover, when these methods are applied to analyze data, an implicit assumption is made that the measurement errors exhibit an iid-normal distribution, often limiting the extent of the information recovered. A method for the linear decomposition of NMR-based metabolomics data by multivariate curve resolution (MCR), which has been used elsewhere for time course transcriptomics applications, is introduced and implemented via a weighted alternating least squares (ALS) approach. Measurement of error information is incorporated in the modeling process, allowing the least squares projections to be performed in a maximum likelihood fashion. As a result, noise heteroscedasticity resulting from pH-induced peak shifts can be modeled, eliminating the need for binning/bucketing. The utility of the method is demonstrated using two sets of temporal NMR metabolomics data, HgCl(2)-induced nephrotoxicity in rat, and fish (Japanese medaka, Oryzias latipes) embryogenesis. Profiles extracted for the nephrotoxicity data exhibit strong correlations with metabolites consistent with temporal fluctuations in glucosuria. The concentration of metabolites such as acetate, glucose, and alanine exhibit a steady increase, which peaks at Day 3 post dose and returns to basal levels at Day 8. Other metabolites including citrate and 2-oxoglutarate exhibit the opposite characteristics. Although the fish embryogenesis data are more complex, the profiles extracted by the algorithm display characteristics that depict temporal variation consistent with processes associated with embryogenesis.

The global analysis of metabolites can be used to define the phenotypes of cells, tissues or organisms. Classifying groups of samples based on their metabolic profile is one of the main topics of metabolomics research. Crisp clustering methods assign each feature to one cluster, thereby omitting information about the multiplicity of sample subtypes. Here, we present the application of fuzzy K-means clustering method for the classification of samples based on metabolomics 1D (1)H NMR fingerprints. The sample classification was performed on NMR spectra of cancer cell line extracts and of urine samples of type 2 diabetes patients and animal models. The cell line dataset included NMR spectra of lipophilic cell extracts for two normal and three cancer cell lines with cancer cell lines including two invasive and one non-invasive cancers. The second dataset included previously published NMR spectra of urine samples of human type 2 diabetics and healthy controls, mouse wild type and diabetes model and rat obese and lean phenotypes. The fuzzy K-means clustering method allowed more accurate sample classification in both datasets relative to the other tested methods including principal component analysis (PCA), hierarchical clustering (HCL) and K-means clustering. In the cell line samples, fuzzy clustering provided a clear separation of individual cell lines, groups of cancer and normal cell lines as well as non-invasive and invasive tumour cell lines. In the diabetes dataset, clear separation of healthy controls and diabetics in all three models was possible only by using the fuzzy clustering method.

NMR-based metabolomics is characterized by high throughput measurements of the signal intensities of complex mixtures of metabolites in biological samples by assaying, typically, bio-fluids or tissue homogenates. The ultimate goal is to obtain relevant biological information regarding the dissimilarity in patho-physiological conditions that the samples experience. For a long time now, this information has been obtained through the analysis of measured NMR signals via multivariate statistics. NMR data are quite complex and the use of such multivariate statistical methods as principal components analysis (PCA) for their analysis assumes that the data are multivariate normal with errors that are identical, independent and normally distributed (i.e. iid normal). There is a consensus that these assumptions are not always true for these data and, thus, several methods have been devised to transform the data or weight them prior to analysis by PCA. The structure of NMR measurement noise, or the extent to which violations of error homoscedasticity affect PCA results have neither been characterized nor investigated. A comprehensive characterization of measurement uncertainties in NMR based metabolomics was achieved in this work using an experiment designed to capture contributions of several sources of error to the total variance in the measurements. The noise structure was found to be heteroscedastic and highly correlated with spectral characteristics that are similar to the mean of the spectra and their standard deviation. A model was subsequently developed that potentially allows errors in NMR measurements to be accurately estimated without the need for extensive replication.

Stressors of various kinds constantly affect fish both in the wild and in culture, examples being acute water temperature and quality changes, predation, handling, and confinement. Known physiological responses of fish to stress such as increases in plasma cortisol and glucose levels, are considered to be adaptive, allowing the animal to cope in the short term. Prolonged exposure to stressors however, has the potential to affect growth, immune function, and survival. Nonetheless, little is known about the mechanisms underlying the long-term stress response. We have investigated the metabolic response of juvenile Atlantic salmon (Salmo salar) to long-term handling stress by analyzing fish plasma via 1H nuclear magnetic resonance spectroscopy and ultra high performance liquid chromatography–mass spectrometry (UPLC–MS), and comparing results with controls. Analysis of NMR data indicated a difference in the metabolic profiles of control and stressed fish after 1 week of stress with a maximum difference observed after 2 weeks. These differences were associated with stress-induced increases in phosphatidyl choline, lactate, carbohydrates, alanine, valine and trimethylamine-N-oxide, and decreases in low density lipoprotein, very low density lipoprotein, and lipid. UPLC-MS data showed differences at week 2, associated with another set of compounds, tentatively identified on the basis of their mass/charge. Overall the results provided a multi-faceted view of the response of fish to long-term handling stress, indicating that the metabolic disparity between the control and stress groups increased to week 2, but declined by weeks 3 and 4, and revealed several new molecular indicators of long-term stress.

Background Gastrointestinal microbial communities are diverse and are composed of both beneficial and pathogenic groups. Prebiotics, such as digestion-resistant fibers, influence the composition of gut microbiota, and can contribute to the improvement of host health. The red seaweed Chondrus crispus is rich in dietary fiber and oligosaccharides, however its prebiotic potential has not been studied to date. Methods Prebiotic effects were investigated with weaning rats fed a cultivated C. crispus-supplemented diet. Comparison standards included a fructo-oligo-saccharide (FOS) diet and a basal diet. The colonic microbiome was profiled with a 16S rRNA sequencing-based Phylochip array. Concentrations of short chain fatty acids (SCFAs) in the feacal samples were determined by gas chromatography with a flame ionization detector (GC-FID) analysis. Immunoglobulin levels in the blood plasma were analyzed with an enzyme-linked immunosorbent assay (ELISA). Histo-morphological parameters of the proximal colon tissue were characterized by hematoxylin and eosin (H&E) staining. Results Phylochip array analysis indicated differing microbiome composition among the diet-supplemented and the control groups, with the C. crispus group (2.5 % supplementation) showing larger separation from the control than other treatment groups. In the 2.5 % C. crispus group, the population of beneficial bacteria such as Bifidobacterium breve increased (4.9-fold, p = 0.001), and the abundance of pathogenic species such as Clostridium septicum and Streptococcus pneumonia decreased. Higher concentrations of short chain fatty acids (i.e., gut microbial metabolites), including acetic, propionic and butyric acids, were found in faecal samples of the C. crispus-fed rats. Furthermore, both C. crispus and FOS supplemented rats showed significant improvements in proximal colon histo-morphology . Higher faecal moisture was noted in the 2.5 % C. crispus group, and elevated plasma immunoglobulin (IgA and IgG) levels were observed in the 0.5 % C. crispus group, as compared to the basal feed group. Conclusions The results suggest multiple prebiotic effects, such as influencing the composition of gut microbial communities, improvement of gut health and immune modulation in rats supplemented with cultivated C. crispus. Electronic supplementary material The online version of this article (doi:10.1186/s12906-015-0802-5) contains supplementary material, which is available to authorized users.

Animal and human studies have indicated that fatty acids such as the conjugated linoleic acids (CLA) found in milk could potentially alter the risk of developing metabolic disorders including diabetes and cardiovascular disease (CVD). Using susceptible rodent models (apoE(-/-) and LDLr(-/-) mice) we investigated the interrelationship between mouse strain, dietary conjugated linoleic acids and metabolic markers of CVD. Despite an adverse metabolic risk profile, atherosclerosis (measured directly by lesion area), was significantly reduced with t-10, c-12 CLA and mixed isomer CLA (Mix) supplementation in both apoE(-/-) (p

The genus Actaea (including Cimicifuga) has been the source of ∼200 cycloartane triterpenes. While they are major bioactive constituents of complementary and alternative medicines, their structural similarity is a major dereplication problem. Moreover, their trivial names seldom indicate the actual structure. This project develops two new tools for Actaea triterpenes that enable rapid dereplication of more than 170 known triterpenes and facilitates elucidation of new compounds. A predictive computational model based on classification binary trees (CBTs) allows in silico determination of the aglycone type. This tool utilizes the Me (1)H NMR chemical shifts and has potential to be applicable to other natural products. Actaea triterpene dereplication is supported by a new systematic naming scheme. A combination of CBTs, (1)H NMR deconvolution, characteristic (1)H NMR signals, and quantitative (1)H NMR (qHNMR) led to the unambiguous identification of minor constituents in residually complex triterpene samples. Utilizing a 1.7 mm cryo-microprobe at 700 MHz, qHNMR enabled characterization of residual complexity at the 10-20 μg level in a 1-5 mg sample. The identification of five co-occurring minor constituents, belonging to four different triterpene skeleton types, in a repeatedly purified natural product emphasizes the critical need for the evaluation of residual complexity of reference materials, especially when used for biological assessment.

Urinary tract obstruction (UTO) results in renal compensatory mechanisms and may progress to irrecoverable functional loss and histologic alterations. The pathophysiology of this progression is poorly understood. We identified urinary metabolite alterations in a rodent model of partial and complete UTO using (1)H nuclear magnetic resonance ((1)H-NMR) spectroscopy. Principal component analysis (PCA) was used for classification and discovery of differentiating metabolites. UTO was associated with elevated urinary levels of alanine, succinate, dimethylglycine (DMG), creatinine, taurine, choline-like compounds, hippurate, and lactate. Decreased urinary levels of 2-oxoglutarate and citrate were noted. The patterns of alteration in partial and complete UTO were similar except that an absence of elevated urinary osmolytes (DMG and hippurate) was noted in complete UTO. This pattern of metabolite alteration indicates impaired oxidative metabolism of the mitochondria in renal proximal tubules and production of renal protective osmolytes by the medulla. Decreased production of osmolytes in complete obstruction better elucidates the pathophysiology of progression from renal compensatory mechanisms to irrecoverable changes. Further confirmation of these potential biomarkers in children with UTO is necessary.