Osmolyte-induced folding of an intrinsically disordered protein: folding mechanism in the absence of ligand.

Understanding the interconversion between thermodynamically distinguishable states present in a protein folding pathway provides not only the kinetics and energetics of protein folding but also insights into the functional roles of these states in biological systems. The protein component of the bacterial RNase P holoenzyme from Bacillus subtilis (P protein) was previously shown to be unfolded in the absence of its cognate RNA or other anionic ligands. P protein was used in this study as a model system to explore general features of intrinsically disordered protein (IDP) folding mechanisms. The use of trimethylamine N-oxide (TMAO), an osmolyte that stabilizes the unliganded folded form of the protein, enabled us to study the folding process of P protein in the absence of ligand. Transient stopped-flow kinetic traces at various final TMAO concentrations exhibited multiphasic kinetics. Equilibrium "cotitration" experiments were performed using both TMAO and urea during the titration to produce a urea-TMAO titration surface of P protein. Both kinetic and equilibrium studies show evidence of a previously undetected intermediate state in the P protein folding process. The intermediate state is significantly populated, and the folding rate constants are relatively slow compared to those of intrinsically folded proteins similar in size and topology. The experiments and analysis described serve as a useful example for mechanistic folding studies of other IDPs.

Oscillations by minimal bacterial suicide circuits reveal hidden facets of host-circuit physiology.

Synthetic biology seeks to enable programmed control of cellular behavior though engineered biological systems. These systems typically consist of synthetic circuits that function inside, and interact with, complex host cells possessing pre-existing metabolic and regulatory networks. Nevertheless, while designing systems, a simple well-defined interface between the synthetic gene circuit and the host is frequently assumed. We describe the generation of robust but unexpected oscillations in the densities of bacterium Escherichia coli populations by simple synthetic suicide circuits containing quorum components and a lysis gene. Contrary to design expectations, oscillations required neither the quorum sensing genes (luxR and luxI) nor known regulatory elements in the P(luxI) promoter. Instead, oscillations were likely due to density-dependent plasmid amplification that established a population-level negative feedback. A mathematical model based on this mechanism captures the key characteristics of oscillations, and model predictions regarding perturbations to plasmid amplification were experimentally validated. Our results underscore the importance of plasmid copy number and potential impact of "hidden interactions" on the behavior of engineered gene circuits - a major challenge for standardizing biological parts. As synthetic biology grows as a discipline, increasing value may be derived from tools that enable the assessment of parts in their final context.

Mapping the semantic structure of cognitive neuroscience.

Cognitive neuroscience, as a discipline, links the biological systems studied by neuroscience to the processing constructs studied by psychology. By mapping these relations throughout the literature of cognitive neuroscience, we visualize the semantic structure of the discipline and point to directions for future research that will advance its integrative goal. For this purpose, network text analyses were applied to an exhaustive corpus of abstracts collected from five major journals over a 30-month period, including every study that used fMRI to investigate psychological processes. From this, we generate network maps that illustrate the relationships among psychological and anatomical terms, along with centrality statistics that guide inferences about network structure. Three terms--prefrontal cortex, amygdala, and anterior cingulate cortex--dominate the network structure with their high frequency in the literature and the density of their connections with other neuroanatomical terms. From network statistics, we identify terms that are understudied compared with their importance in the network (e.g., insula and thalamus), are underspecified in the language of the discipline (e.g., terms associated with executive function), or are imperfectly integrated with other concepts (e.g., subdisciplines like decision neuroscience that are disconnected from the main network). Taking these results as the basis for prescriptive recommendations, we conclude that semantic analyses provide useful guidance for cognitive neuroscience as a discipline, both by illustrating systematic biases in the conduct and presentation of research and by identifying directions that may be most productive for future research.

Engineering emergence for cluster configuration

Distributed applications are being deployed on ever-increasing scale and with ever-increasing functionality. Due to the accompanying increase in behavioural complexity, self-management abilities, such as self-healing, have become core requirements. A key challenge is the smooth embedding of such functionality into our systems. Natural distributed systems such as ant colonies have evolved highly efficient behaviour. These emergent systems achieve high scalability through the use of low complexity communication strategies and are highly robust through large-scale replication of simple, anonymous entities. Ways to engineer this fundamentally non-deterministic behaviour for use in distributed applications are being explored. An emergent, dynamic, cluster management scheme, which forms part of a hierarchical resource management architecture, is presented. Natural biological systems, which embed self-healing behaviour at several levels, have influenced the architecture. The resulting system is a simple, lightweight and highly robust platform on which cluster-based autonomic applications can be deployed.

Sequence and Structure Based Protein Folding Studies With Implications

As the expression of the genetic blueprint, proteins are at the heart of all biological systems. The ever increasing set of available protein structures has taught us that diversity is the hallmark of their architecture, a fundamental characteristic that enables them to perform the vast array of functionality upon which all of life depends. This diversity, however, is central to one of the most challenging problems in molecular biology: how does a folding polypeptide chain navigate its way through all of the myriad of possible conformations to find its own particular biologically active form? With few overarching structural principles to draw upon that can be applied to all protein architecture, the search for a solution to the protein folding problem has yet to produce an algorithm that can explain and duplicate this fundamental biological process. In this thesis, we take a two-pronged approach for investigating the protein folding process. Our initial statistical studies of the distributions of hydrophobic and hydrophilic residues within α-helices and β-sheets suggest (i) that hydrophobicity plays a critical role in helix and sheet formation; and (ii) that the nucleation of these motifs may result in largely unidirectional growth. Most tellingly, from an examination of the amino acids found in the smallest β-sheets, we do not find any evidence of a β-nucleating code in the primary protein sequence. Complementing these statistical analyses, we have analyzed the structural environments of several ever-widening aspects of protein topology. Our examination of the gaps between strands in the smallest β-sheets reveals a common organizational principle underlying β-formation involving strands separated by large sequential gaps: with very few exceptions, these large gaps fold into single, compact structural modules, bringing the β-strands that are otherwise far apart in the sequence close together in space. We conclude, therefore, that β-nucleation in the smallest sheets results from the co-location of two strands that are either local in sequence, or local in space following prior folding events. A second study of larger β-sheets both corroborates and extends these findings: virtually all large sequential gaps between pairs of β-strands organize themselves into an hierarchical arrangement, creating a bread-crumb model of go-and-come-back structural organization that ultimately juxtaposes two strands of a parental β-structure that are far apart in the sequence in close spatial proximity. In a final study, we have formalized this go-and-come-back notion into the concept of anti-parallel double-strandedness (DS), and measure this property across protein architecture in general. With over 90% of all residues in a large, non-redundant set of protein structures classified as DS, we conclude that DS is a unifying structural principle that underpins all globular proteins. We postulate, moreover, that this one simple principle, anti-parallel double-strandedness, unites protein structure, protein folding and protein evolution.

Information processing in the transcriptional regulatory network of yeast: Functional robustness

Background: Gene networks are considered to represent various aspects of molecular biological systems meaningfully because they naturally provide a systems perspective of molecular interactions. In this respect, the functional understanding of the transcriptional regulatory network is considered as key to elucidate the functional organization of an organism.

Quantification of nanoparticle uptake by cells using microscopical and analytical techniques

Quantification of nanoparticles in biological systems (i.e., cells, tissues and organs) is becoming a vital part of nanotoxicological and nanomedical fields. Dose is a key parameter when assessing behavior and any potential risk of nanomaterials. Various techniques for nanoparticle quantification in cells and tissues already exist but will need further development in order to make measurements reliable, reproducible and intercomparable between different techniques. Microscopy allows detection and location of nanoparticles in cells and has been used extensively in recent years to characterize nanoparticles and their pathways in living systems. Besides microscopical techniques (light microscopy and electron microscopy mainly), analytical techniques such as mass spectrometry, an established technique in trace element analysis, have been used in nanoparticle research. Other techniques require 'labeled particles, fluorescently, radioactively or magnetically. However, these techniques lack spatial resolution and subcellular localization is not possible. To date, only electron microscopy offers the resolving power to determine accumulation of nanoparticles in cells due to its ability to image particles individually. So-called super-resolution light microscopy techniques are emerging to provide sufficient resolution on the light microscopy level to image or 'see particles as individual particles. Nevertheless, all microscopy techniques require statistically sound sampling strategies in order to provide quantitative results. Stereology is a well-known sampling technique in various areas and, in combination with electron microscopy, proves highly successful with regard to quantification of nanoparticle uptake by cells. © 2010 Future Medicine Ltd.

Hydrophobic substances induce water stress in microbial cells

Ubiquitous noxious hydrophobic substances, such as hydrocarbons, pesticides and diverse industrial chemicals, stress biological systems and thereby affect their ability to mediate biosphere functions like element and energy cycling vital to biosphere health. Such chemically diverse compounds may have distinct toxic activities for cellular systems; they may also share a common mechanism of stress induction mediated by their hydrophobicity. We hypothesized that the stressful effects of, and cellular adaptations to, hydrophobic stressors operate at the level of water : macromolecule interactions. Here, we present evidence that: (i) hydrocarbons reduce structural interactions within and between cellular macromolecules, (ii) organic compatible solutes-metabolites that protect against osmotic and chaotrope-induced stresses-ameliorate this effect, (iii) toxic hydrophobic substances induce a potent form of water stress in macromolecular and cellular systems, and (iv) the stress mechanism of, and cellular responses to, hydrophobic substances are remarkably similar to those associated with chaotrope-induced water stress. These findings suggest that it may be possible to devise new interventions for microbial processes in both natural environments and industrial reactors to expand microbial tolerance of hydrophobic substances, and hence the biotic windows for such processes.

Metamaterials Nanosensor for Label-free Analysis of Conformation and Molecular Interaction of Biomolecules

Analysis of molecular interaction and conformational dynamics of biomolecules is of paramount importance in understanding of their vital functions in complex biological systems, disease detection, and new drug development. Plasmonic biosensors based upon surface plasmon resonance and localized surface plasmon resonance have become the predominant workhorse for detecting accumulated biomass caused by molecular binding events. However, unlike surface-enhanced Raman spectroscopy (SERS), the plasmonic biosensors indeed are not suitable tools to interrogate vibrational signatures of conformational transitions required for biomolecules to interact. Here, we show that plasmonic metamaterials can offer two transducing channels for parallel acquisition of optical transmission and sensitive SERS spectra at the biointerface, simultaneously probing the conformational states and binding affinity of biomolecules, e.g. G-quadruplexes, in different environments (Fig. 1). We further demonstrate the use of the metamaterials for fingerprinting and detection of arginine-glycine-glycine domain of nucleolin, a cancer biomarker which specifically binds to a G-quadruplex, with the picomolar sensitivity. The dual-mode nanosensor will significantly contribute to unraveling the complexes of the conformational dynamics of biomolecules as well as to improving specificity of biodetection assays.

Label-free Analysis of Conformational Dynamics and Molecular Interaction of Biomolecules by Vis-NIR Metasensor

Analysis of binding recognition and conformation of biomolecules is of paramount important in understanding of their vital functions in complex biological systems. By enabling sub-wavelength light localization and strong local field enhancement, plasmonic biosensors have become dominant tools used for such analysis owing to their label-free and real-time attributes1,2. However, the plasmonic biosensors are not well-suited to provide information regarding conformation or chemical fingerprint of biomolecules. Here, we show that plasmonic metamaterials, consisting of periodic arrays of artificial split-ring resonators (SRRs)3, can enable capabilities of both sensing and fingerprinting of biomolecules. We demonstrate that by engineering geometry of individual SRRs, localized surface plasmon resonance (LSPR) frequency of the metamaterials could be tuned to visible-near infrared regimes (Vis-NIR) such that they possess high local field enhancement for surface-enhanced Raman scattering spectroscopy (SERS). This will provide the basis for the development of a dual mode label-free conformational-resolving and quantitative detection platform. We present here the ability of each sensing mode to independently detect binding adsorption and to identify different conformational states of Guanine (G)-rich DNA monolayers in different environment milieu. Also shown is the use of the nanosensor for fingerprinting and detection of Arginine-Glycine-Glycine (RGG) peptide binding to the G-quadruplex aptamer. The dual-mode nanosensor will significantly contribute to unraveling the complexes of the conformational dynamics of biomolecules as well as to improving specificity of biodetection assays that the conventional, population-averaged plasmonic biosensors cannot achieve.

Metamaterials-Based Label-Free Nanosensor for Conformation and Affinity Biosensing

Analysis of molecular interaction and conformational dynamics of biomolecules is of paramount importance in understanding of their vital functions in complex biological systems, disease detection, and new drug development. Plasmonic biosensors based upon surface plasmon resonance and localized surface plasmon resonance have become the predominant workhorse for detecting accumulated biomass caused by molecular binding events. However, unlike surface-enhanced Raman spectroscopy (SERS), the plasmonic biosensors indeed are not suitable tools to interrogate vibrational signatures of conformational transitions required for biomolecules to interact. Here, we show that highly tunable plasmonic metamaterials can offer two transducing channels for parallel acquisition of optical transmission and sensitive SERS spectra at the biointerface, simultaneously probing the conformational states and binding affinity of biomolecules, e.g. G-quadruplexes, in different environments. We further demonstrate the use of the metamaterials for fingerprinting and detection of arginine-glycine-glycine domain of nucleolin, a cancer biomarker which specifically binds to a G-quadruplex, with the picomolar sensitivity.

Radiosensitising Nanoparticles as Novel Cancer Therapeutics — Pipe Dream or Realistic Prospect?

The field of high atomic number nanoparticle radiosensitising agents is reviewed. After a brief discussion of the new mode of physicochemical action implied by irradiation of high atomic number nanoparticles embedded in biological systems, a series of exemplars are discussed. Silver-, gadolinium- and gold-based nanoparticles are discussed in order of increasing atomic number with functionalisation strategies being outlined. In vitro and in vivo evidence for radio-enhancement and the mechanisms attributed to the increased biological effect are discussed.

Development of Novel Activity-Based Probes for the Detection of Serine Proteases

Cystic Fibrosis (CF) is a genetic disease featuring a chronic cycle of inflammation and infection in the airways of sufferers. Mutations lead to altered ion transport, which in turn causes dehydrated airways and reduced mucociliary clearance which predisposes the patient to infection, resulting in a severe immune response and tissue destruction (1). Airway dehydration is primarily caused by the hyperabsorption of sodium by the epithelial sodium channel (ENaC) (2). ENaC is activated by the action of a number of predominantly trypsin-like Channel Activating Proteases (CAPs) including prostasin, matriptase and furin (3). Additional proteases known to activate ENaC include human airway trypsin (3), plasmin, neutrophil elastase and chymotrypsin (4).

Activity profiling is a valuable technique which involves the use of small inhibitory molecules called Activity-Based Probes (ABPs) which can be used to covalently label the active site of proteases and provide a range of information regarding its structure, catalytic mechanism, location and function within biological systems. The development of novel ABPs for CAPs, would enhance understanding of the role of these proteases in CF airways disease and in particular their role in ENaC activation and airway dehydration. This project investigates the application of a range of novel broad-spectrum ABPs targeting the various subclasses of serine proteases, to include those proteases involved in ENaC activation. Additionally, the application of more selective ABPs in detecting specific serine proteases is investigated.

Compounds were synthesised by Solid-Phase Peptide Synthesis (SPPS) using a standard Fmoc/tBu strategy. Kinetic evaluation of synthesised ABPs against various serine proteases was determined by fluorogenic steady-state enzyme assays. Furthermore, application of ABPs and confirmation of irreversible nature of the compounds was carried out through SDS-PAGE and electroblotting techniques.

Synthesised compounds showed potent irreversible inhibition of serine proteases within their respective targeting class (NAP855 vs Trypsin k3/Ki = 2.60 x 106 M-1 min-1, NFP849 vs Chymotrypsin k3/Ki = 1.28 x 106 M-1 min-1 and NVP800 vs Neutrophil Elastase k3/Ki = 6.41 x 104 M-1 min-1). Furthermore ABPs showed little to no cross-reactivity between classes and so display selectivity between classes. The irreversible nature of compounds was further demonstrated through labelling of proteases, followed by separation and detection via SDS-PAGE and electroblotting techniques. Targeted labelling of active proteases only, was demonstrated by failure of ABPs to detect previously inactivated proteases. Extension of the substrate recognition site within probes resulted in an increased potency and selectivity in the detection of the target proteases. Successful detection of neutrophil elastase from CF sputum samples by NVP800, demonstrated the application of compounds within biological samples and their potential use in identifying further proteases involved in ENaC activation and airway dehydration in CF patients.