Platform-agnostic electrochemical sensing app and companion potentiostat.

Electrochemical sensing is ubiquitous in a number of fields ranging from biosensing, to environmental monitoring through to food safety and battery or corrosion characterisation. Whereas conventional potentiostats are ideal to develop assays in laboratory settings, they are in general, not well-suited for field work due to their size and power requirements. To address this need, a number of portable battery-operated potentiostats have been proposed over the years. However, most open source solutions do not take full advantage of integrated circuit (IC) potentiostats, a rapidly evolving field. This is partly due to the constraining requirements inherent to the development of dedicated interfaces, such as apps, to address and control a set of common electrochemical sensing parameters. Here we propose the PocketEC, a universal app that has all the functionalities to interface with potentiostat ICs through a user defined property file. The versatility of PocketEC, developed with an assay developer mindset, was demonstrated by interfacing it, via Bluetooth, to the ADuCM355 evaluation board, the open-source DStat potentiostat and the Voyager board, a custom-built, small footprint potentiostat based around the LMP91000 chip. The Voyager board is presented here for the first time. Data obtained using a standard redox probe, Ferrocene Carboxylic Acid (FCA) and a silver ion assay using anodic stripping multi-step amperometry were in good agreement with analogous measurements using a bench top potentiostat. Combined with its Voyager board companion, the PocketEC app can be used directly for a number of wearable or portable electrochemical sensing applications. Importantly, the versatility of the app makes it a candidate of choice for the development of future portable potentiostats. Finally, the app is available to download on the Google Play store and the source codes and design files for the PocketEC app and the Voyager board are shared via Creative Commons license (CC BY-NC 3.0) to promote the development of novel portable or wearable applications based on electrochemical sensing.

Angiotensin Converting Enzyme (ACE): A Marker for Personalized Feedback on Dieting.

Angiotensin Converting Enzyme (ACE) expression and activity is associated with obesity. ACE is a circulating factor that predicts sustained weight loss over a time frame of months. Here, we evaluate whether ACE might also be an early marker (over a 24-hour period) for weight loss. 32 participants (78% females; BMI 28.47 ± 4.87kg/m2) followed a 1200KCal diet with an optional daily (<250KCal) snack and were asked to use an in-house generated health platform to provide recordings of food intake, physical activity and urine collection time and volume. Following a day of dieting, ACE levels in urine negatively correlated with weight loss (p = 0.015 ). This reduction in ACE levels was significantly more robust in individuals with a BMI > 25 (p = 0.0025 ). This study demonstrated that ACE levels correlate with BMI and weight loss as early as after 1 day of dieting, and thus ACE could be a potential early "biofeedback" marker for weight loss and diet efficiency.

Towards personalised molecular feedback for weight loss.

BACKGROUND: Numerous diets, apps and websites help guide and monitor dietary behaviour with the goal of losing weight, yet dieting success is highly dependent on personal preferences and circumstances. To enable a more quantitative approach to dieting, we developed an integrated platform that allows tracking of life-style information alongside molecular biofeedback measurements (lactate and insulin). METHODS: To facilitate weight loss, participants (≥18 years) omitted one main meal from the usual three-meal routine. Daily caloric intake was restricted to ~1200KCal with one optional snack ≤250KCal. A mobile health platform (personalhealth.warwick.ac.uk) was developed and used to maintain diaries of food intake, weight, urine collection and volume. A survey was conducted to understand participants' willingness to collect samples, motivation for taking part in the study and reasons for dropout. RESULTS: Meal skipping resulted in weight loss after a 24 h period in contrast to 3-meal control days regardless of the meal that was skipped, breakfast, lunch or dinner (p < 0.001). Common reasons for engagement were interest in losing weight and personal metabolic profile. Total insulin and lactate values varied significantly between healthy and obese individuals at p = 0.01 and 0.05 respectively. CONCLUSION: In a proof of concept study with a meal-skipping diet, we show that insulin and lactate values in urine correlate with weight loss, making these molecules potential candidates for quantitative feedback on food intake behaviour to people dieting.

Selective inhibition of microRNA accessibility by RBM38 is required for p53 activity.

MicroRNAs (miRNAs) interact with 3'-untranslated regions of messenger RNAs to restrict expression of most protein-coding genes during normal development and cancer. RNA-binding proteins (RBPs) can control the biogenesis, stability and activity of miRNAs. Here we identify RBM38 in a genetic screen for RBPs whose expression controls miRNA access to target mRNAs. RBM38 is induced by p53 and its ability to modulate miRNA-mediated repression is required for proper p53 function. In contrast, RBM38 shows lower propensity to block the action of the p53-controlled miR-34a on SIRT1. Target selectivity is determined by the interaction of RBM38 with uridine-rich regions near miRNA target sequences. Furthermore, in large cohorts of human breast cancer, reduced RBM38 expression by promoter hypermethylation correlates with wild-type p53 status. Thus, our results indicate a novel layer of p53 gene regulation, which is required for its tumour suppressive function.

Metal-induced folding of Diels-Alderase ribozymes studied by static and time-resolved NMR spectroscopy.

The metal ion-induced folding of the Diels-Alder ribozyme into a catalytically active form with a complex RNA pseudoknot has been characterized by static and time-resolved NMR spectroscopy. The conformations of two sequences from the Diels-Alder ribozyme family, A27 WT and G27 MUT, were studied in the absence and presence of metal ions and of ligand. The single nucleotide mutant G27 MUT in the absence of metal ions displayed conformational heterogeneity which greatly influences its folding trajectory. Time-resolved NMR experiments were applied using a sample-mixing technique to rapidly add Ca(2+) ions to induce folding in situ. The folding rates observed for the G27 MUT ribozyme differed by 3 orders of magnitude from the A27 WT folding rates determined previously by FRET experiments. A model based on the characterization of the free and metal-bound forms of the ribozymes is proposed to account for the difference in the folding rates of the two ribozymes. Evidence is provided that the reactivity is modulated due to local dynamics around the catalytic pocket for the G27 MUT ribozyme.

Flexibility of the cytoplasmic domain of the phototaxis transducer II from Natronomonas pharaonis.

Chemo- and phototaxis systems in bacteria and archaea serve as models for more complex signal transduction mechanisms in higher eukaryotes. Previous studies of the cytoplasmic fragment of the phototaxis transducer (pHtrII-cyt) from the halophilic archaeon Natronomonas pharaonis showed that it takes the shape of a monomeric or dimeric rod under low or high salt conditions, respectively. CD spectra revealed only approximately 24% helical structure, even in 4 M KCl, leaving it an open question how the rod-like shape is achieved. Here, we conducted CD, FTIR, and NMR spectroscopic studies under different conditions to address this question. We provide evidence that pHtrII-cyt is highly dynamic with strong helical propensity, which allows it to change from monomeric to dimeric helical coiled-coil states without undergoing dramatic shape changes. A statistical analysis of predicted disorder for homologous sequences suggests that structural flexibility is evolutionarily conserved within the methyl-accepting chemotaxis protein family.

Time-resolved NMR studies of RNA folding.

The application of real-time NMR experiments to the study of RNA folding, as reviewed in this article, is relatively new. For many RNA folding events, current investigations suggest that the time scales are in the second to minute regime. In addition, the initial investigations suggest that different folding rates are observed for one structural transition may be due to the hierarchical folding units of RNA. Many of the experiments developed in the field of NMR of protein folding cannot directly be transferred to RNA: hydrogen exchange experiments outside the spectrometer cannot be applied since the intrinsic exchange rates are too fast in RNA, relaxation dispersion experiments on the other require faster structural transitions than those observed in RNA. On the other hand, information derived from time-resolved NMR experiments, namely the acquisition of native chemical shifts, can be readily interpreted in light of formation of a single long-range hydrogen bonding interaction. Together with mutational data that can readily be obtained for RNA and new ligation technologies that enhance site resolution even further, time-resolved NMR may become a powerful tool to decipher RNA folding. Such understanding will be of importance to understand the functions of coding and non-coding RNAs in cells.

BLMT: statistical sequence analysis using N-grams.

UNLABELLED: Statistical analysis of amino acid and nucleotide sequences, especially sequence alignment, is one of the most commonly performed tasks in modern molecular biology. However, for many tasks in bioinformatics, the requirement for the features in an alignment to be consecutive is restrictive and "n-grams" (aka k-tuples) have been used as features instead. N-grams are usually short nucleotide or amino acid sequences of length n, but the unit for a gram may be chosen arbitrarily. The n-gram concept is borrowed from language technologies where n-grams of words form the fundamental units in statistical language models. Despite the demonstrated utility of n-gram statistics for the biology domain, there is currently no publicly accessible generic tool for the efficient calculation of such statistics. Most sequence analysis tools will disregard matches because of the lack of statistical significance in finding short sequences. This article presents the integrated Biological Language Modeling Toolkit (BLMT) that allows efficient calculation of n-gram statistics for arbitrary sequence datasets. AVAILABILITY: BLMT can be downloaded from http://www.cs.cmu.edu/~blmt/source and installed for standalone use on any Unix platform or Unix shell emulation such as Cygwin on the Windows platform. Specific tools and usage details are described in a "readme" file. The n-gram computations carried out by the BLMT are part of a broader set of tools borrowed from language technologies and modified for statistical analysis of biological sequences; these are available at http://flan.blm.cs.cmu.edu/.