Current Biotechnology (v.4, #1)

Preface: Message from Our New Editor-in-Chief by Pabulo Henrique Rampelotto (1-1).

Use of Smartphone Accelerometers and Signal Energy for Estimating Energy Expenditure in Daily-Living Conditions by Martine Duclos, Gerard Fleury, Romain Guidoux, Philippe Lacomme, Nicolas Lamaudiere, Pierre-Henri Manenq, Ludivine Paris, Libo Ren, Sylvie Rousset (4-15).
This paper aims to introduce an efficient predictive function for total energy expenditure (TEE) in everyday life using dedicated mass-market sensors similar to those found in widespread smartphones and tablets. Our research encompasses the design of a TEE estimation model using the smartphone accelerometer with a new signal-to-energy transformation function. The main idea of this study consists in using the signal intensity instead of the activity recognition, since the signal intensity of the accelerometer is related to the amplitude of activities. The performance of the proposed function is estimated using a smartphone-based implementation and evaluated compared to references (the scenario associated with compendium MET values, Armband® and Actiheart®) under controlled conditions (CC) for 3.5 hours, and to both devices in free-living conditions (FLC) over a 12-hour monitoring period. The experiments were carried out with 12 volunteers in CC and 30 volunteers in FLC. The TEE mean gap in absolute value between the function and the three references (scenario, Armband® and Actiheart®) was 3.5%, 6.6% and 14.1% in CC, and 14.1% and 15.0% according to Armband® and Actiheart® in FLC, respectively.

In the multiple sequence alignment (MSA) of the members of a protein family some positions are highly conserved, while others vary. The conserved positions are clearly important, but the non-conserved positions are also important because the destabilizing effects of a given amino acid at one position can be compensated by the stabilizing effect of a certain amino acid at another position: in other words, two (or more) positions in a protein family can coevolve. Information about coevolving positions is valuable to understand the protein mechanism and dynamic properties, and to design mutagenesis studies. Several methods are available for the identification of coevolving positions from the analysis of MSAs. If an MSA contains a large number of sequences, information about the proximities between residues derived from coevolution maps can be sufficient to predict a protein fold. Conversely, if the structure of at least one representative member of a protein family is known, coevolution maps obtained by different methods can be validated against the distance map derived from the structure. In the absence of a reference structure, validation of the results obtained with the experimental MSA can be obtained by evaluating the performance of different methods with synthetic MSAs that mimic the features of the experimental one, and in which the covarying positions are known. Using a single protein family as an example, we review here the steps involved in the derivation and validation of coevolution maps from MSAs.

Transcription factors control the flow of genetic information from DNA to messenger RNA rendering understanding of their function highly important for the modulation and optimization of protein expression. Molecular and structural biology have provided a wealth of information for transcription factors, however, the dynamic processes underlying their activation are yet not fully understood. In this context, molecular dynamics (MD) simulations represent a computational method that is capable to supplement experimental data by providing atomistic information on protein dynamics. We applied MD simulations to supplement the structural information available for the transcription factor RfaH from Escherichia coli. RfaH consists of an N-terminal domain (NTD) and a C-terminal domain (CTD), which tightly interact with each other in the autoinhibited conformation of RfaH. Upon activation the CTD is released and undergoes a large-scale α a†' β structural transition. Investigation of RfaH under different environmental conditions revealed that not only high temperatures, but also a decrease in ionic strength significantly enhances CTD dynamics. Despite this enhanced dynamics, none of the conditions investigated caused CTD dissociation suggesting that this process needs to be triggered by the interaction with DNA or other proteins of the transcription machinery. Further, the N-terminus of the first CTD helix, which contains two glycines, was identified to exhibit rather large motions and we propose a set of mutations affecting the local dynamics and/or the strength of the NTD-CTD interactions. Taken together, this study presents computational strategies, which complement experimental approaches by providing detailed information about the dynamics of biomolecules.

Automated Extraction of Proteotypic Peptides by Shotgun Proteomic Experiments: A New Computational Tool and Two Actual Cases by Dario Di Silvestre, Pietro Brunetti, Danila Vella, Francesca Brambilla, Antonella De Palma, Pierluigi Mauri (39-45).
The rapid development of mass spectrometry-based proteomic technologies has allowed the quantification and validation of protein biomarkers toward detection of signature molecules, called proteotypic peptides. To facilitate their extraction from experimental protein and peptide lists, we present here a friendly computational tool called Experimental Proteotypic Peptides Investigator (EPPI). In this study, it was used for extracting proteotypic peptides from two collections of experimental data obtained by MudPIT analysis of adipose and gut human tissue. In particular, EPPI allows the selection of peptides presenting higher occurrence, evaluates their uniqueness by molecular weight and amino-acid sequence, and takes into consideration combinations of multiple proteotypic peptides (proteotypic peptide sets) for evaluating their capacity to target a single protein. In fact, in combination with high-resolution MS instruments, it could be a starting point for targeting proteins by following only precursor ions in full MS scan mode. The software is available under the permissive Apache 2.0 open-source license, and the code can be accessed from https://github.com/ITB-ProtMet/eppi.git.

With the advancement in proteomics and bioinformatics, it is paramount to predict the causes of aggregation in all Human Hydrolase Enzymes (HHE), which have more tendencies to aggregate. Protein aggregation is associated with manifold pathological and neurodegenerative diseases because of amyloid fibrillation. Physico-chemical factors responsible for aggregation were studied in details. The positional dependencies of amylogenic regions in active participation for aggregation in HHE were correlated and brought into limelight through this study. Novel deductions from several studies in this research revealed that helical regions in the N-Terminal amylogenic regions mainly contributed for aggregation in HHE, especially for the ones having acidic theoretical pI. The presence of aggregation-prone highly fluctuating amino acid residues mainly in N-Terminal amylogenic regions was also explored. Withal, mutational alterations in the active sites, that could reduce net aggregation propensity and free energy of folding of entire HHE family leading to better foldability and reduction in the chances for the neurodegenerative disorders to be caused were also discerned with supportive statistical significance.

Stevioside, a glycoside present in the leaves of Stevia rebaudiana Bertoni, offers therapeutic benefits such as anti-hyperglycemic, anti-hypertensive, antiinflammatory, anti-tumor, diuretic and immune influencing properties. In this work antimicrobial activity of stevioside against Bacillus cereus, a major source of milk contamination was investigated. The isolate was confirmed by various biochemical and 16S rRNA gene sequencing. The effect of temperature, incubation time and concentration of stevioside was optimized from a central composite response surface design. The standard plate count (SPC) of pasteurized milk was drastically reduced in comparison to toned and fresh milk. The optimal temperature, incubation time and stevioside concentration were observed to be 60.23A°C, 21 h, and 275 μg/ mL respectively. The synergism of stevioside with the external factors (temperature and time) against B. cereus was observed. Our studies showed that addition of stevioside in fresh as well as pasteurised milk would control growth of B. cereus in milk.

Novel short-chain-length-long-chain-length polyhydroxyalkanoate (SCL-LCL-PHA) copolymer production was examined with Pseudomonas aeruginosa MTCC 7925 under supplementation of non-edible oils such as karanja, jatropha, mahua, and castor oils, and their respective cakes for cost reduction. Polymer yield reached up to 4.66 g/l (63.7% dry cell wt., dcw) with a mol fraction of 89.7:4.2:2.7:3.4 of 3- hydroxybutyric acid (3HB): 3-hydroxyvaleric acid (3HV): 3-hydroxyhexadecanoic acid (3HHD): 3-hydroxyoctadecanoic acid (3HOD) units under the interactive condition of low nitrogen concentration with 0.5% (v/v) jatropha oil in combination with its cake extract, followed by 3.94 g/l (59.6% dcw) with a mol fraction of 91.6:3.3:2.5:2.6 of 3HB: 3HV: 3HHD: 3HOD with castor oil and its cake extracts. The novel co-polymer not only depicted material properties analogous to the common plastics but also better melting temperature (Tm), glass-transition temperature (Tg), elongation-to-break value and Young's modulus than the homopolymer of poly-3-hydroxybutyrate (PHB). As compared to our previous report where palm oil and its cakes were used, a cost reduction of 54% was observed with the non-edible jatropha oil with its cakes. This opens up possibility for further study at pilot-scale level for low-cost production and future recommendations.