Improving cartilage phenotype from differentiated pericytes in tunable peptide hydrogels

Differentiation of stem cells to chondrocytes in vitro usually results in a heterogeneous phenotype. This is evident in the often detected over expression of type X collagen which, in hyaline cartilage structure is not characteristic of the mid-zone but of the deep-zone ossifying tissue. Methods to better match cartilage developed in vitro to characteristic in vivo features are therefore highly desirable in regenerative medicine. This study compares phenotype characteristics between pericytes, obtained from human adipose tissue, differentiated using diphenylalanine/serine (F2/S) peptide hydrogels with the more widely used chemical induced method for chondrogenesis. Significantly higher levels of type II collagen were noted when pericytes undergo chondrogenesis in the hydrogel in the absence of induction media. There is also a balanced expression of collagen relative to aggrecan production, a feature which was biased toward collagen production when cells were cultured with induction media. Lastly, metabolic profiles of each system show considerable overlap between both differentiation methods but subtle differences which potentially give rise to their resultant phenotype can be ascertained. The study highlights how material and chemical alterations in the cellular microenvironment have wide ranging effects on resultant tissue type

Nacre Topography Produces Higher Crystallinity in Bone than Chemically Induced Osteogenesis

It is counter-intuitive that invertebrate shells can induce bone formation yet nacre, or mother of pearl, from marine shells is both osteoinductive and osteointegrative. Nacre is composed of aragonite (calcium carbonate) and induces production of vertebrate bone (calcium phosphate). Exploited by the Mayans for dental implants, this remarkable phenomenon has been confirmed in vitro and in vivo yet the characteristic of nacre that induces bone formation remains unknown. By isolating nacre topography from its inherent chemistry in the production of polycaprolactone (PCL) nacre replica, we show that, for mesenchymal stem cells, nacre topography is osteoinductive. Gene expression of specific bone marker proteins, osteopontin, osteocalcin, osteonectin and osterix are increased 10-, 2- 1.7- and 1.8-fold respectively when compared to planar PCL. Furthermore, we demonstrate that bone tissue that forms in response to the physical topographical features of nacre has higher crystallinity than bone formed in response to chemical cues with full width half maximum for PO4 3- Raman shift of 7.6±0.7 for mineral produced in response to nacre replica compared to a much broader 34.6±10.1 in response to standard osteoinductive medium. These differences in mineral product are underpinned by differences in cellular metabolism. This observation can be exploited in the design of bone therapies; a matter that is most pressing in light of a rapidly ageing human population. Aragonite and calcite are the two calcium carbonate polymorphs that constitute the shell of molluscan bivalves conferring strength and resilience due to the nano- and microstructural assembly of the overall architecture. A small percentage of the invertebrate shell constitute the organic matrix which is responsible for the intricate processes of nucleation, growth and inhibition of calcium carbonate crystals resulting in the well-defined shell structure. The discovery of fully integrated shell dental implants in Mayan skulls initiated a number of studies showing that nacre, or mother of pearl, the aragonite calcium carbonate polymorph derived from the pearl oyster Pinctada maxima has good osteointegrative properties in vivo. Further exploration of this phenomenon in human jaw reconstructions and sheep femur implants confirm the osteointegrative properties of invertebrate shells. In addition, nacre initiates osteogenic differentiation in mesenchymal stem cells (MSCs) in vitro. This observation has led to a number of studies in which nacre and its chemistry have been incorporated into the design of existing biomaterials to induce bone formation. MSCs can be induced into undergoing osteogenesis in vitro by the use of pre-formulated soluble factors in the culture media, chemically defined surfaces, substrate matrix elasticity and the surface topography of the substrate. These approaches induce osteogenesis when presented in isolation or in combination. When these cues are presented in combination, surface patterning plays an important role and topography can have a stronger influence on cell behaviour when presented with effective surface chemistries. In vertebrate and invertebrate systems, the main requisites for forming hard tissue or biomineral structures are calcium phosphate and calcium carbonate respectively, both of which are assembled in a variety of ways generating an incredible amount of structural diversity. This juxtaposition of phosphate and carbonate is described as the “Bone-Shell Divide”. It is intriguing that mammalian cells respond to mineral on the shell side of the Bone-Shell Divide and this begs questions: which feature of nacre elicits this response and, in transcending the Bone-Shell Divide, do MSCs produce bone of similar or superior characteristics to that induced by other means? Addressing these questions has important implications in tissue engineering and biomaterial applications, especially with regards to orthopaedic applications where critical sized defects in trauma and reconstructive surgery demand large areas of intact bone usually acquired by creating a secondary injury site. By isolating the topographical features of nacre from its inherent chemistry, we show that the osteoinductive properties of nacre arise from the patterning of the surface presented to MSCs. Importantly, separating nacre topography from its inherent chemistry enhances the osteogenic response. In this report we dissect out the contribution of topography to nacre bioactivit

Topic modeling for untargeted substructure exploration in metabolomics

The potential of untargeted metabolomics to answer important questions across the life sciences is hindered due to a paucity of computational tools that enable extraction of key biochemically relevant information. Available tools focus on using mass spectrometry fragmentation spectra to identify molecules whose behavior suggests they are relevant to the system under study. Unfortunately, fragmentation spectra cannot identify molecules in isolation, but require authentic standards or databases of known fragmented molecules. Fragmentation spectra are, however, replete with information pertaining to the biochemical processes present; much of which is currently neglected. Here we present an analytical workflow that exploits all fragmentation data from a given experiment to extract biochemically-relevant features in an unsupervised manner. We demonstrate that an algorithm originally utilized for text-mining, Latent Dirichlet Allocation, can be adapted to handle metabolomics datasets. Our approach extracts biochemically-relevant molecular substructures (‘Mass2Motifs’) from spectra as sets of co-occurring molecular fragments and neutral losses. The analysis allows us to isolate molecular substructures, whose presence allows molecules to be grouped based on shared substructures regardless of classical spectral similarity. These substructures in turn support putative de novo structural annotation of molecules. Combining this spectral connectivity to orthogonal correlations (e.g. common abundance changes under system perturbation) significantly enhances our ability to provide mechanistic explanations for biological behavior

A novel targeted/untargeted GC-Orbitrap metabolomics methodology applied to Candida albicans and Staphylococcus aureus biofilms

Introduction: Combined infections from Candida albicans and Staphylococcus aureus are a leading cause of death in the developed world. Evidence suggests that Candida enhances the virulence of Staphylococcus—hyphae penetrate through tissue barriers, while S. aureus tightly associates with the hyphae to obtain entry to the host organism. Indeed, in a biofilm state, C. albicans enhances the antimicrobial resistance characteristics of S. aureus. The association of these microorganisms is also associated with significantly increased morbidity and mortality. Due to this tight association we hypothesised that metabolic effects were also in evidence. Objectives: To explore the interaction, we used a novel GC-Orbitrap-based mass spectrometer, the Q Exactive GC, which combines the high peak capacity and chromatographic resolution of gas chromatography with the sub-ppm mass accuracy of an Orbitrap system. This allows the capability to leverage the widely available electron ionisation libraries for untargeted applications, along with expanding accurate mass libraries and targeted matches based around authentic standards. Methods: Optimised C. albicans and S. aureus mono- and co-cultured biofilms were analysed using the new instrument in addition to the fresh and spent bacterial growth media. Results: The targeted analysis experiment was based around 36 sugars and sugar phosphates, 22 amino acids and five organic acids. Untargeted analysis resulted in the detection of 465 features from fresh and spent medium and 405 from biofilm samples. Three significantly changing compounds that matched to high scoring library fragment patterns were chosen for validation. Conclusion: Evaluation of the results demonstrates that the Q Exactive GC is suitable for metabolomics analysis using a targeted/untargeted methodology. Many of the results were as expected: e.g. rapid consumption of glucose and fructose from the medium regardless of the cell type. Modulation of sugar-phosphate levels also suggest that the pentose phosphate pathway could be enhanced in the cells from co-cultured biofilms. Untargeted metabolomics results suggested significant production of cell-wall biosynthesis components and the consumption of non-proteinaceous amino-acids

Unsupervised discovery and comparison of structural families across multiple samples in untargeted metabolomics

In untargeted metabolomics approaches, the inability to structurally annotate relevant features and map them to biochemical pathways is hampering the full exploitation of many metabolomics experiments. Furthermore, variable metabolic content across samples result in sparse feature matrices that are statistically hard to handle. Here, we introduce MS2LDA+ that tackles both above-mentioned problems. Previously, we presented MS2LDA, which extracts biochemically relevant molecular substructures (“Mass2Motifs”) from a collection of fragmentation spectra as sets of co-occurring molecular fragments and neutral losses, thereby recognizing building blocks of metabolomics. Here, we extend MS2LDA to handle multiple metabolomics experiments in one analysis, resulting in MS2LDA+. By linking Mass2Motifs across samples, we expose the variability in prevalence of structurally related metabolite families. We validate the differential prevalence of substructures between two distinct samples groups and apply it to fecal samples. Subsequently, within one sample group of urines, we rank the Mass2Motifs based on their variance to assess whether xenobiotic-derived substructures are among the most-variant Mass2Motifs. Indeed, we could ascribe 22 out of the 30 most-variant Mass2Motifs to xenobiotic-derived substructures including paracetamol/acetaminophen mercapturate and dimethylpyrogallol. In total, we structurally characterized 101 Mass2Motifs with biochemically or chemically relevant substructures. Finally, we combined the discovered metabolite families with full scan feature intensity information to obtain insight into core metabolites present in most samples and rare metabolites present in small subsets now linked through their common substructures. We conclude that by biochemical grouping of metabolites across samples MS2LDA+ aids in structural annotation of metabolites and guides prioritization of analysis by using Mass2Motif prevalence

Instances and connectors : issues for a second generation process language

This work is supported by UK EPSRC grants GR/L34433 and GR/L32699Over the past decade a variety of process languages have been defined, used and evaluated. It is now possible to consider second generation languages based on this experience. Rather than develop a second generation wish list this position paper explores two issues: instances and connectors. Instances relate to the relationship between a process model as a description and the, possibly multiple, enacting instances which are created from it. Connectors refers to the issue of concurrency control and achieving a higher level of abstraction in how parts of a model interact. We believe that these issues are key to developing systems which can effectively support business processes, and that they have not received sufficient attention within the process modelling community. Through exploring these issues we also illustrate our approach to designing a second generation process language.Postprin

A novel metabolomic approach used for the comparison of Staphylococcus aureus planktonic cells and biofilm samples

Introduction: Bacterial cell characteristics change significantly during differentiation between planktonic and biofilm states. While established methods exist to detect and identify transcriptional and proteomic changes, metabolic fluctuations that distinguish these developmental stages have been less amenable to investigation. Objectives: The objectives of the study were to develop a robust reproducible sample preparation methodology for high throughput biofilm analysis and to determine differences between Staphylococcus aureus in planktonic and biofilm states. Methods: The method uses bead beating in a chloroform/methanol/water extraction solvent to both disrupt cells and quench metabolism. Verification of the method was performed using liquid-chromatography-mass spectrometry. Raw mass-spectrometry data was analysed using an in-house bioinformatics pipe-line incorporating XCMS, MzMatch and in-house R-scripts, with identifications matched to internal standards and metabolite data-base entries. Results: We have demonstrated a novel mechanical bead beating method that has been optimised for the extraction of the metabolome from cells of a clinical Staphylococcus aureus strain existing in a planktonic or biofilm state. This high-throughput method is fast and reproducible, allowing for direct comparison between different bacterial growth states. Significant changes in arginine biosynthesis were identified between the two cell populations. Conclusions: The method described herein represents a valuable tool in studying microbial biochemistry at a molecular level. While the methodology is generally applicable to the lysis and extraction of metabolites from Gram positive bacteria, it is particularly applicable to biofilms. Bacteria that exist as a biofilm are shown to be highly distinct metabolically from their ‘free living’ counterparts, thus highlighting the need to study microbes in different growth states. Metabolomics can successfully distinguish between a planktonic and biofilm growth state. Importantly, this study design, incorporating metabolomics, could be optimised for studying the effects of antimicrobials and drug modes of action, potentially providing explanations and mechanisms of antibiotic resistance and to help devise new antimicrobials

High connectivity of the Crocodile Shark between the Atlantic and Southwest Indian Oceans: highlights for conservation

Among the various shark species that are captured as bycatch in commercial fishing operations, the group of pelagic sharks is still one of the least studied and known. Within those, the crocodile shark, Pseudocarcharias kamoharai, a small-sized lamnid shark, is occasionally caught by longline vessels in certain regions of the tropical oceans worldwide. However, the population dynamics of this species, as well as the impact of fishing mortality on its stocks, are still unknown, with the crocodile shark currently one of the least studied of all pelagic sharks. Given this, the present study aimed to assess the population structure of P. kamoharai in several regions of the Atlantic and Indian Oceans using genetic molecular markers. The nucleotide composition of the mitochondrial DNA control region of 255 individuals was analyzed, and 31 haplotypes were found, with an estimated diversity Hd = 0.627, and a nucleotide diversity pi = 0.00167. An analysis of molecular variance (AMOVA) revealed a fixation index phi(ST) = -0.01118, representing an absence of population structure among the sampled regions of the Atlantic Ocean, and between the Atlantic and Indian Oceans. These results show a high degree of gene flow between the studied areas, with a single genetic stock and reduced population variability. In panmictic populations, conservation efforts can be concentrated in more restricted areas, being these representative of the total biodiversity of the species. When necessary, this strategy could be applied to the genetic maintenance of P. kamoharai.Foundation for Research Support of the Sao Paulo State - FAPESP [2011/23787-0, 2010/51903-2]; Portuguese Foundation for Science and Technology (FCT) [SFRH/BPD/93936/2013]; Foundation for Research Support of the Sao Paulo State - FAPESP [2011/23787-0, 2010/51903-2]; Portuguese Foundation for Science and Technology (FCT) [SFRH/BPD/93936/2013]info:eu-repo/semantics/publishedVersio

PLoS Pathog

Metabolomics coupled with heavy-atom isotope-labelled glucose has been used to probe the metabolic pathways active in cultured bloodstream form trypomastigotes of Trypanosoma brucei, a parasite responsible for human African trypanosomiasis. Glucose enters many branches of metabolism beyond glycolysis, which has been widely held to be the sole route of glucose metabolism. Whilst pyruvate is the major end-product of glucose catabolism, its transamination product, alanine, is also produced in significant quantities. The oxidative branch of the pentose phosphate pathway is operative, although the non-oxidative branch is not. Ribose 5-phosphate generated through this pathway distributes widely into nucleotide synthesis and other branches of metabolism. Acetate, derived from glucose, is found associated with a range of acetylated amino acids and, to a lesser extent, fatty acids; while labelled glycerol is found in many glycerophospholipids. Glucose also enters inositol and several sugar nucleotides that serve as precursors to macromolecule biosynthesis. Although a Krebs cycle is not operative, malate, fumarate and succinate, primarily labelled in three carbons, were present, indicating an origin from phosphoenolpyruvate via oxaloacetate. Interestingly, the enzyme responsible for conversion of phosphoenolpyruvate to oxaloacetate, phosphoenolpyruvate carboxykinase, was shown to be essential to the bloodstream form trypanosomes, as demonstrated by the lethal phenotype induced by RNAi-mediated downregulation of its expression. In addition, glucose derivatives enter pyrimidine biosynthesis via oxaloacetate as a precursor to aspartate and orotate

Urinary antihypertensive drug metabolite screening using molecular networking coupled to high-resolution mass spectrometry fragmentation

Introduction Mass spectrometry is the current technique of choice in studying drug metabolism. High-resolution mass spectrometry in combination with MS/MS gas-phase experiments has the potential to contribute to rapid advances in this field. However, the data emerging from such fragmentation spectral files pose challenges to downstream analysis, given their complexity and size. Objectives This study aims to detect and visualize antihypertensive drug metabolites in untargeted metabolomics experiments based on the spectral similarity of their fragmentation spectra. Furthermore, spectral clusters of endogenous metabolites were also examined. Methods Here we apply a molecular networking approach to seek drugs and their metabolites, in fragmentation spectra from urine derived from a cohort of 26 patients on antihypertensive therapy. The mass spectrometry data was collected on a Thermo Q-Exactive coupled to pHILIC chromatography using data dependent analysis (DDA) MS/MS gas-phase experiments. Results In total, 165 separate drug metabolites were found and structurally annotated (17 by spectral matching and 122 by classification based on a clustered fragmentation pattern). The clusters could be traced to 13 drugs including the known antihypertensives verapamil, losartan and amlodipine. The molecular networking approach also generated clusters of endogenous metabolites, including carnitine derivatives, and conjugates containing glutamine, glutamate and trigonelline. Conclusions The approach offers unprecedented capability in the untargeted identification of drugs and their metabolites at the population level and has great potential to contribute to understanding stratified responses to drugs where differences in drug metabolism may determine treatment outcome