Hydrophobic interaction chromatography

Most proteins and large polypeptides have hydrophobic regions at their surface. These hydrophobic ‘patches’ are due to the presence of the side chains of hydrophobic or non-polar amino acids such as phenylalanine, tryptophan, alanine and methionine. These surface hydrophobic regions are interspersed between more hydrophilic or polar regions and the number, size and distribution of them is a specific characteristic of each protein. Hydrophobic Interaction Chromatography (HIC) is a commonly used technique that exploits these hydrophobic features of proteins as a basis for their separation even in complex biological mixtures (1) (2). In general the conditions under which hydrophobic interaction chromatography is used are relatively mild and ‘protein friendly’ resulting in good biological recoveries. Hydrophobic binding is relatively strong and is maintained even in the presence of chaotrophic agents, organic solvents and detergents. For these reasons this technique has a widespread use for the purification of proteins and large polypeptides

Ion exchange chromatography – basic principles and application

Ion-Exchange Chromatography (IEC) allows for the separation of ionizable molecules on the basis of differences in charge properties. Its large sample-handling capacity, broad applicability (particularly to proteins and enzymes), moderate cost, powerful resolving ability, and ease of scale-up and automation have led to it becoming one of the most versatile and widely used of all liquid chromatography (LC) techniques. In this chapter, we review the basic principles of IEC, as well as the broader criteria for selecting IEC conditions. By way of further illustration, we outline protocols necessary to partially purify a serine peptidase from bovine whole brain cytosolic fraction, covering crude tissue extract preparation through to partial purification of the target enzyme using anion-exchange chromatography. Protocols for assaying total protein and enzyme activity in both pre- and post-IEC fractions are also described. The target serine peptidase, prolyl oligopeptidase (POP, EC3.4.21.26), is an 80 kDa enzyme with endopeptidase activity towards peptide substrates of ≤30 amino acids. POP is a ubiquitous post-proline cleaving enzyme with particularly high expression levels in the mammalian brain, where it participates in the metabolism of neuroactive peptides and peptide-like hormones (e.g. thyroliberin, gonadotropin-releasing hormone)

Gel filtration chromatography

Gel-filtration chromatography is a popular and versatile technique that permits the effective separation of proteins and other biological molecules in high yield. Here, the basis of the method is described and typical matrix types are contrasted. The selection of suitable operating conditions and applications of the method are also discussed

Irrigation and the Palu landslides

Wet rice cultivation in the Palu Valley, Indonesia, prepared the ground for the devastating liquefaction-induced landslides that were triggered by the Mw 7.5 earthquake in 2018, suggest two studies of the spatial relationship between landslide morphology and irrigation

Time reverse imaging for far-field tsunami forecasting: 2011 Tohoku earthquake case study

This paper describes a new method for forecasting far-field tsunamis by combining aspects of least squares tsunami source inversion (LSQ) with time reverse imaging (TRI). This method has the same source representation as LSQ but uses TRI to estimate initial sea surface displacement. We apply this method to the 2011 Japan tsunami, and the results show that the method produces tsunami waveforms of excellent agreement with observed waveforms at both near- and far-field stations not used in the source estimation. The spatial distribution of cumulative sea surface displacement agrees well with other models obtained in more sophisticated inversions, but resolve source kinematics are not well resolved. The method has potential for application in tsunami warning systems, as it is computationally efficient and can be used to estimate the initial source model by applying precomputed Green's functions in order to provide more accurate and realistic tsunami predictions

Efficient Bayesian uncertainty estimation in linear finite fault inversion with positivity constraints by employing a log-normal prior

Obtaining slip distributions for earthquakes results in an ill-posed inverse problem. While this implies that only limited and uncertain information can be recovered from the data, inferences are typically made based only on a single regularized model. Here, we develop an inversion approach that can quantify uncertainties in a Bayesian probabilistic framework for the finite fault inversion (FFI) problem. The approach is suitably efficient for rapid source characterization and includes positivity constraints for model parameters, a common practice in FFI, via coordinate transformation to logarithmic space. The resulting inverse problem is nonlinear and the most probable solution can be obtained by iterative linearization. In addition, model uncertainties are quantified by approximating the posterior probability distribution by a Gaussian distribution in logarithmic space. This procedure is straightforward since an analytic expression for the Hessian of the objective function is obtained. In addition to positivity, we apply smoothness regularization to the model in logarithmic space. Simulations based on surface wave data show that smoothing in logarithmic space penalizes abrupt slip changes less than smoothing in linear space. Even so, the main slip features of models that are smooth in linear space are recovered well with logarithmic smoothing. Our synthetic experiments also show that, for the data set we consider, uncertainty is low at the shallow portion of the fault and increases with depth. In addition, a simulation with a large station azimuthal gap of 180° significantly increases the slip uncertainties. Further, the marginal posterior probabilities obtained from our approximate method are compared with numerical Markov Chain Monte Carlo sampling. We conclude that the Gaussian approximation is reasonable and meaningful inferences can be obtained from it. Finally, we apply the new approach to observed surface wave records from the great Illapel earthquake (Chile, 2015, Mw = 8.3). The location and amplitude of our inferred peak slip is consistent with other published solutions but the spatial slip distribution is more compact, likely because of the logarithmic regularization. We also find a minor slip patch downdip, mainly in an oblique direction, which is poorly resolved compared to the main slip patch and may be an artefact. We conclude that quantifying uncertainties of finite slip models is crucial for their meaningful interpretation, and therefore rapid uncertainty quantification can be critical if such models are to be used for emergency response

The 1674 Ambon Tsunami: Extreme Run-Up Caused by an Earthquake-Triggered Landslide

We present an analysis of the oldest detailed account of tsunami run-up in Indonesia, that of the 1674 Ambon tsunami (Rumphius in Waerachtigh Verhael van de Schuckelijcke Aerdbebinge, BATAVIA, Dutch East Indies, 1675). At 100 m this is the largest run-up height ever documented in Indonesia, and with over 2300 fatalities even in 1674, it ranks as one of Indonesia's most deadly tsunami disasters. We consider the plausible sources of earthquakes near Ambon that could generate a large, destructive tsunami, including the Seram Megathrust, the South Seram Thrust, and faults local to Ambon. We conclude that the only explanation for the extreme run-up observed on the north coast of Amon is a tsunami generated by an earthquake-triggered coastal landslide. We use a two-layer tsunami model to show that a submarine landslide, with an approximate volume of 1 km3, offshore the area on Ambon's northern coast, between Seith and Hila, where dramatic changes in coastal landscape were observed can explain the observed tsunami run-up along the coast. Thus, the 1674 Ambon tsunami adds weight to the evidence from recent tsunamis, including the 1992 Flores, 2018 Palu and Sunda Strait tsunamis, that landslides are an important source of tsunami hazard in Indonesia

Western Java Ambient Noise Tomography: A Preliminary Result

Western Java, Indonesia, has at least three important active faults: the Cimandiri, Lembang, and Baribis Faults, which pose a great danger for the cities near them. It is crucial to have a better understanding of shallow crustal structure to delineate active faults and deep basins in order to support seismic hazard and disaster mitigation efforts in Indonesia. In this study, we perform ambient seismic noise tomography which can give better resolution of the shallow structure beneath western Java. We have deployed a seismometer network in the western to central Java region through a research collaboration program between the Bandung Institute of Technology (ITB) and the Australian National University (ANU). We deployed 70 seismometer stations from June to January 2017 to acquire ambient seismic noise data. As the first stage of the data processing, we will focus on conducting single data preparation and cross-correlation to retrieve an estimate of Green's functions between station pairs. We also use the frequency-time analysis technique to obtain dispersion curves to measure the interstation group velocity. The group velocity is use as an input in tomography inversion. Our preliminary results show low velocity anomalies associated with sedimentary basins and a high velocity anomaly associated with the southern mountains