Thermodynamic analysis of protein unfolding in aqueous solutions as a multisite reaction of protein with water and solute molecules

Thermal unfolding of ribonuclease A, lysozyme, and chymotrypsinogen A was analyzed as a multisite reaction of a protein molecule with water and solute molecules. The protein unfolding process in various solutions of sugars and denaturants was described well by the van't Hoff equation. The reciprocal form of the Wyman-Tanford equation, which describes the unfolded-to-folded protein ratio as a function of water activity, was successfully applied to obtain a good linear relationship. From this analysis, the role of water activity on protein stability was clearly explained and the contributions of hydration and solute binding to protein molecule were separately discussed in protein unfolding. General solution for the free energy of protein stability was obtained as a simple function of solute concentration.     

Burst-phase expansion of native protein prior to global unfolding in SDS

Although numerous studies have been directed at understanding early folding events through the characterization of folding intermediates, there are few reports on the very late folding events, i.e. on the events taking place on the native side of the folding barrier and on alternative conformations of the folded state. To shed further light on these issues, we have characterized by protein engineering the structure of an expanded but native-like intermediate that accumulates transiently in the unfolding reaction of the small protein S6 in the presence of SDS. The results show that the SDS micelles attack the native protein in the dead-time of the denaturation experiment, causing an expansion of the hydrophobic core prior to the major unfolding transition. We distinguish two forms of the unfolding intermediate that are correlated with the micellar structure. With spherical micelles, the expansion is seen mainly as a weakening of the interactions which anchor the two alpha-helices to the core of the S6 structure. With cylindrical micelles, prevalent at higher SDS concentrations, the expansion is more global and produces a species which closely resembles the transition-state structure for unfolding in GdmCl. Despite the highly weakened core, the micelle-associated intermediate displays cooperative unfolding, indicating a significant structural plasticity of the species on the native side of the folding barrier in the presence of SDS.     

A new method for the improvement of data production in phytochemical analysis

Introduction – The use of the average analytical signal for the construction of curves by the least squares method (LSM) over the standard addition method (SAM) is widespread. It would be advantageous, however, to find a way to avoid intermediary averages, which are known to be the cause of significant increases in standard deviations (SD). Objective – To develop a protocol that uses all gathered data to create curves by LSM over SAM. To use Excel^® for the estimation of y = mx + b and R² rather than using LSM equations for the SD of m, x and b. Methodology – The level of lead (II) in the bark (cork) of Quercus suber Linnaeus was determined using differential pulse anodic stripping voltammetry (DPASV). Three current samples were taken for each of the four standard additions. These signals were combined for adjustment by LSM. The results were compared with those obtained after averaging the current for each addition, and the expression of uncertainty in the measurements determined. Results – The new method shows an expanded uncertainty of ± 0.3321 μg/g (nearly 1.42%). The difference between the results obtained by the new and the old method is 0.01 μg/g (23.41 and 23.40 μg/g). The limit of detection changed approximately from 4.8 to 4 μg/g and the relative SD approximately from 9 to 6%. Conclusion – The absence of intermediary averages in curves improved the determination of lead (II) in cork by DPASV. Estimation of SD only with LSM equations produced results that were significantly worse. The changes are large enough to transform an apparently internally non‐validated procedure (repeatability for precision) into an internally validated procedure. Copyright © 2009 John Wiley & Sons, Ltd.     

Analysis of multitemperature isothermal titration calorimetry data at very low c: Global beats van't Hoff

Isothermal titration calorimetry data for very low c (≡K[M]₀) must normally be analyzed with the stoichiometry parameter n fixed — at its known value or at any reasonable value if the system is not well characterized. In the latter case, ΔH° (and hence n) can be estimated from the T-dependence of the binding constant K, using the van't Hoff (vH) relation. An alternative is global or simultaneous fitting of data at multiple temperatures. In this Note, global analysis of low-c data at two temperatures is shown to estimate ΔH° and n with double the precision of the vH method.     

Global analysis of fluorescence fluctuation data

Over the last decade the number of applications of fluorescence correlation spectroscopy (FCS) has grown rapidly. Here we describe the development and application of a software package, FCS Data Processor, to analyse the acquired correlation curves. The algorithms combine strong analytical power with flexibility in use. It is possible to generate initial guesses, link and constrain fit parameters to improve the accuracy and speed of analysis. A global analysis approach, which is most effective in analysing autocorrelation curves determined from fluorescence fluctuations of complex biophysical systems, can also be implemented. The software contains a library of frequently used models that can be easily extended to include user-defined models. The use of the software is illustrated by analysis of different experimental fluorescence fluctuation data sets obtained with Rhodamine Green in aqueous solution and enhanced green fluorescent protein in vitro and in vivo.An erratum to this article can be found at Victor V. Skakun, Mark A. Hink and Anatoli V. Digris contributed equally to this work.     

The interrelationship between ligand binding and thermal unfolding of the folate binding protein. The role of self-association and pH

The present study utilized a combination of DLS (dynamic light scattering) and DSC (differential scanning calorimetry) to address thermostability of high-affinity folate binding protein (FBP), a transport protein and cellular receptor for the vitamin folate. At pH 7.4 (pI = 7–8) ligand binding increased concentration-dependent self-association of FBP into stable multimers of holo-FBP. DSC of 3.3 μM holo-FBP showed Tm (76 °C) and molar enthalpy (146 kcal M^− 1) values increasing to 78 °C and 163 kcal M^− 1 at 10 μM holo-FBP, while those of apo-FBP were 55 °C and 105 kcal M^− 1. Besides ligand binding, intermolecular forces involved in concentration-dependent multimerization thus contribute to the thermostability of holo-FBP. Hence, thermal unfolding and dissociation of holo-FBP multimers occur simultaneously consistent with a gradual decrease from octameric to monomeric holo-FBP (10 μM) in DLS after a step-wise rise in temperature to 78 °C ≈ Tm. Stable holo-FBP multimers may protect naturally occurring labile folates against decomposition or bacterial utilization. DSC established an interrelationship between diminished folate binding at pH 5, especially in NaCl-free buffers, and low thermostability. Positively charged apo-FBP was almost completely unfolded and aggregated at pH 5 (Tm 38 °C) and holo-FBP, albeit more thermostable, was labile with aggregation tendency. Addition of 0.15 M NaCl increased thermostability of apo-FBP drastically, and even more so that of holo-FBP. Electrostatic forces thus seem to contribute to a diminished thermostability at low pH. Fluorescence spectroscopy after irreversible thermal unfolding of FBP revealed a weak-affinity folate binding.     

Statistical uncertainty and its propagation in the analysis of quantitative polymerase chain reaction data: Comparison of methods

Most methods for analyzing real-time quantitative polymerase chain reaction (qPCR) data for single experiments estimate the hypothetical cycle 0 signal y₀ by first estimating the quantification cycle (C_q) and amplification efficiency (E) from least-squares fits of fluorescence intensity data for cycles near the onset of the growth phase. The resulting y₀ values are statistically equivalent to the corresponding C_q if and only if E is taken to be error free. But uncertainty in E usually dominates the total uncertainty in y₀, making the latter much degraded in precision compared with C_q. Bias in E can be an even greater source of error in y₀. So-called mechanistic models achieve higher precision in estimating y₀ by tacitly assuming E = 2 in the baseline region and so are subject to this bias error. When used in calibration, the mechanistic y₀ is statistically comparable to C_q from the other methods. When a signal threshold y_q is used to define C_q, best estimation precision is obtained by setting y_q near the maximum signal in the range of fitted cycles, in conflict with common practice in the y₀ estimation algorithms.     

MicroRNA-33a functions as a bone metastasis suppressor in lung cancer by targeting parathyroid hormone related protein

Background

Bone is a common site of metastasis for lung cancer, and is associated with significant morbidity and a dismal prognosis. MicroRNAs (miRNAs) are increasingly implicated in regulating the progression of malignancies.

Methods

The efficacy of miR-33a or anti-miR-33a plasmid was assessed by Real-time PCR. Luciferase assays were using One-Glo Luciferase Assay System. Measurement of secreted factors was determined by ELISA kit.

Results

We have found that miR-33a, which is downregulated in lung cancer cells, directly targets PTHrP (parathyroid hormone-related protein), a potent stimulator of osteoclastic bone resorption, leading to decreased osteolytic bone metastasis. We also found that miR-33a levels are inversely correlated with PTHrP expression between human normal bronchial cell line and lung cancer cell lines. The reintroduction of miR-33a reduces the stimulatory effect of A549 on the production of osteoclastogenesis activator RANKL (receptor activator of nuclear factor kappa-B ligand) and M-CSF (macrophage colony-stimulating factor) on osteoblasts, while the expression of PTHrP is decreased in A549 cells. miR-33a overexpression also reduces the inhibitory activity of A549 on the production of OPG (osteoprotegerin), an osteoclastogenesis inhibitor. In addition, miR-33a-mediated PTHrP downregulation results in decreased IL-8 secretion in A549, which contributes to decreased lung cancer-mediated osteoclast differentiation and bone resorption.

Conclusions

These findings have led us to conclude that miR-33a may be a potent tumor suppressor, which inhibits direct and indirect osteoclastogenesis through repression of PTHrP.

General significance

miR-33a may even predict a poor prognosis for lung cancer patients.     

Fingerprint detection and process prediction by multivariate analysis of fed‐batch monoclonal antibody cell culture data

This work presents a sequential data analysis path, which was successfully applied to identify important patterns (fingerprints) in mammalian cell culture process data regarding process variables, time evolution and process response. The data set incorporates 116 fed‐batch cultivation experiments for the production of a Fc‐Fusion protein. Having precharacterized the evolutions of the investigated variables and manipulated parameters with univariate analysis, principal component analysis (PCA) and partial least squares regression (PLSR) are used for further investigation. The first major objective is to capture and understand the interaction structure and dynamic behavior of the process variables and the titer (process response) using different models. The second major objective is to evaluate those models regarding their capability to characterize and predict the titer production. Moreover, the effects of data unfolding, imputation of missing data, phase separation, and variable transformation on the performance of the models are evaluated. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1633–1644, 2015     

Chemical strategies for the global analysis of protein function

As the human genome project nears completion, biological research is entering a new era in which experimental focus will shift from identifying novel genes to determining the function of gene products. Rising to this challenge, several technologies have emerged that aim to characterise genes and/or proteins collectively rather than individually. Of particular interest is a new breed of strategies that employs synthetic chemistry to enrich our understanding of protein function on a global scale.     

大肠杆菌全局调控转录因子环腺苷酸受体蛋白质在代谢工程中的应用

环腺苷酸受体蛋白质(Cyclic amp receptor protein,CRP)是原核生物共有的一类全局转录因子,调控原核生物大肠杆菌Escherichia coli中近一半基因的转录。通过易错PCR或DNA shuffling的方法可以获得CRP突变体文库,然后经过筛选可以得到目的细胞表型——"抗逆性"增强。本研究综述了突变CRP在细胞表型:耐氧化压力、耐渗透胁迫、耐有机溶剂(甲苯)、发酵中耐醋酸盐类和生物醇生产中耐生物醇中的应用。推论出CRP同样可以应用于相似微生物的表型培育,并展望了CRP的巨大应用潜力。     

Principal components analysis of protein structure ensembles calculated using NMR data

One important problem when calculating structures of biomolecules from NMR data is distinguishing converged structures from outlier structures. This paper describes how Principal Components Analysis (PCA) has the potential to classify calculated structures automatically, according to correlated structural variation across the population. PCA analysis has the additional advantage that it highlights regions of proteins which are varying across the population. To apply PCA, protein structures have to be reduced in complexity and this paper describes two different representations of protein structures which achieve this. The calculated structures of a 28 amino acid peptide are used to demonstrate the methods. The two different representations of protein structure are shown to give equivalent results, and correct results are obtained even though the ensemble of structures used as an example contains two different protein conformations. The PCA analysis also correctly identifies the structural differences between the two conformations.     

Multivariate statistical analysis of quantitative serum protein data in populations of Rwanda

Data on serum protein levels of four populations from Rwanda were analyzed by multivariate statistical methods to assess their utility as an anthropological tool. These populations consisted of two ethnic groups in two different environments. Seven proteins were considered in the analysis. The total concentration of proteins is intermediate between Italian levels and those of the Binga pygmies of the Republic of Central Africa (RCA). Discrimination between the populations was possible with a 25% misclassification. The major principal components can be interpreted from a medical viewpoint, and show significant differences between the populations.     

PKB: a program system and data base for analysis of protein structure

PKB is a computer program system that combines a data base of three-dimensional protein structures with a series of algorithms for pattern recognition, data analysis, and graphics. By typing relatively simple commands the user may search the data base for instances of a structural motif and analyze in detail the set of individual structures that are found. The application of PKB to the study of protein folding is illustrated in three examples. The first analysis compares the conformations observed for a short sequential motif, sequences similar to the cell-attachment signal Arg-Gly-Asp. The second compares sequences observed for a conformational motif, a 16-residue beta alpha beta unit. The third analysis considers a population of substructures containing ion-pair interactions, examining the relationship of frequency of occurrence to calculated electrostatic energy.     

Rational design of crystal contact‐free space in protein crystals for analyzing spatial distribution of motions within protein molecules

Contacts with neighboring molecules in protein crystals inevitably restrict the internal motions of intrinsically flexible proteins. The resultant clear electron densities permit model building, as crystallographic snapshot structures. Although these still images are informative, they could provide biased pictures of the protein motions. If the mobile parts are located at a site lacking direct contacts in rationally designed crystals, then the amplitude of the movements can be experimentally analyzed. We propose a fusion protein method, to create crystal contact‐free space (CCFS) in protein crystals and to place the mobile parts in the CCFS. Conventional model building fails when large amplitude motions exist. In this study, the mobile parts appear as smeared electron densities in the CCFS, by suitable processing of the X‐ray diffraction data. We applied the CCFS method to a highly mobile presequence peptide bound to the mitochondrial import receptor, Tom20, and a catalytically relevant flexible segment in the oligosaccharyltransferase, AglB. These two examples demonstrated the general applicability of the CCFS method to the analysis of the spatial distribution of motions within protein molecules.     

Advanced multivariate data analysis to determine the root cause of trisulfide bond formation in a novel antibody–peptide fusion

Product quality heterogeneities, such as a trisulfide bond (TSB) formation, can be influenced by multiple interacting process parameters. Identifying their root cause is a major challenge in biopharmaceutical production. To address this issue, this paper describes the novel application of advanced multivariate data analysis (MVDA) techniques to identify the process parameters influencing TSB formation in a novel recombinant antibody–peptide fusion expressed in mammalian cell culture. The screening dataset was generated with a high‐throughput (HT) micro‐bioreactor system (Ambr^TM 15) using a design of experiments (DoE) approach. The complex dataset was firstly analyzed through the development of a multiple linear regression model focusing solely on the DoE inputs and identified the temperature, pH and initial nutrient feed day as important process parameters influencing this quality attribute. To further scrutinize the dataset, a partial least squares model was subsequently built incorporating both on‐line and off‐line process parameters and enabled accurate predictions of the TSB concentration at harvest. Process parameters identified by the models to promote and suppress TSB formation were implemented on five 7 L bioreactors and the resultant TSB concentrations were comparable to the model predictions. This study demonstrates the ability of MVDA to enable predictions of the key performance drivers influencing TSB formation that are valid also upon scale‐up. Biotechnol. Bioeng. 2017;114: 2222–2234. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.     

A suite of Mathematica notebooks for the analysis of protein main chain 15N NMR relaxation data

A suite of Mathematica notebooks has been designed to ease the analysis of protein main chain ¹⁵N NMR relaxation data collected at a single magnetic field strength. Individual notebooks were developed to perform the following tasks: nonlinear fitting of ¹⁵N-T ₁ and -T ₂ relaxation decays to a two parameter exponential decay, calculation of the principal components of the inertia tensor from protein structural coordinates, nonlinear optimization of the principal components and orientation of the axially symmetric rotational diffusion tensor, model-free analysis of ¹⁵N-T ₁, -T ₂, and {¹H}–¹⁵N NOE data, and reduced spectral density analysis of the relaxation data. The principle features of the notebooks include use of a minimal number of input files, integrated notebook data management, ease of use, cross-platform compatibility, automatic visualization of results and generation of high-quality graphics, and output of analyses in text format.L. Spyracopoulos is an AHFMR Medical Research Senior Scholar     

Bioinformatic prediction and analysis of eukaryotic protein kinases in the rat genome

Eukaryotic protein kinases, containing a conserved catalytic domain, represent one of the largest superfamilies of the eukaryotic proteins and play distinct roles in cell signaling and diseases. Near completion of rat genome sequencing project enables the evaluation of a near complete set of rat protein kinases. Publicly accessible genetic sequence databases were searched for rat protein kinases, and 515 eukaryotic protein kinases, 40 atypical protein kinases and 45 kinase pseudogenes were identified. The rat has 509 putative protein kinases orthologous to human kinases. Unlike microtubule affinity-regulating kinases, the rat has a few more kinases, in addition to the orthologous pairs of mouse kinases. The comparison of 11 different eukaryotic species revealed the evolutionary conservation of this diverse family of proteins. The evolutionary rate studies of human disease and non-disease associated kinases suggested that relatively uniform selective pressures have been applied to these kinase classes. This bioinformatic study of the rat protein kinases provides a suitable framework for further characterization of the functional and structural properties of these protein kinases.