Mechanisms of substrate selection by the signal recognition particle

The signal recognition particle (SRP) targets membrane and secretory proteins to their correct cellular destination with remarkably high fidelity. Previous studies have shown that multiple checkpoints exist within this targeting pathway that allows ‘correct cargo’ to be quickly and efficiently targeted and for ‘incorrect cargo’ to be promptly rejected. In this work, we delved further into understanding the mechanisms of how substrates are selected or discarded by the SRP. First, we discovered the role of the SRP fingerloop and how it activates the SRP and SRP receptor (SR) GTPases to target and unload cargo in response to signal sequence binding. Second, we learned how an ‘avoidance signal’ found in the bacterial autotransporter, EspP, allows this protein to escape the SRP pathway by causing the SRP and SR to form a ‘distorted’ complex that is inefficient in delivering the cargo to the membrane. Lastly, we determined how Trigger Factor, a co-translational chaperone, helps SRP discriminate against ‘incorrect cargo’ at three distinct stages: SRP binding to RNC; targeting of RNC to the membrane via SRP-FtsY assembly; and stronger antagonism of SRP targeting of ribosomes bearing nascent polypeptides that exceed a critical length. Overall, results delineate the rich underlying mechanisms by which SRP recognizes its substrates, which in turn activates the targeting pathway and provides a conceptual foundation to understand how timely and accurate selection of substrates is achieved by this protein targeting machinery.

Burrowing behaviour of signal crayfish, Pacifastacus leniusculus (Dana), in the River Great Ouse, England

Observations were made on crayfish burrows in five locations on the Great Ouse River. The burrow densities and the relative abundance of crayfish were observed. Also, laboratory experiments were carried out in order to study the characteristics and mechanisms of burrowing.

The home range of the signal crayfish in a British lowland river

The signal crayfish Pacifastacus leniusculus (Dana), a native of north-western North America, is now a common resident in some British fresh waters following its introduction to England in 1976 (Lowery & Holdich 1988). In 1984, signal crayfish were introduced into the River Great Ouse, the major lowland river in southern central England, where they have established a large breeding population. This study examines two sites near Thornborough Weir. For the measurement and description of home range a new eletronic microchip system and a modified capture-mark-recapture method were employed. Signal crayfish were marked or tagged to see if they gradually moved away from their burrows. This method proved to be successful for estimating population densities when a section of river is divided into several equidistant linear ”locations”.

Convex Relaxation for Low-Dimensional Representation: Phase Transitions and Limitations

There is a growing interest in taking advantage of possible patterns and structures in data so as to extract the desired information and overcome the curse of dimensionality. In a wide range of applications, including computer vision, machine learning, medical imaging, and social networks, the signal that gives rise to the observations can be modeled to be approximately sparse and exploiting this fact can be very beneficial. This has led to an immense interest in the problem of efficiently reconstructing a sparse signal from limited linear observations. More recently, low-rank approximation techniques have become prominent tools to approach problems arising in machine learning, system identification and quantum tomography.

In sparse and low-rank estimation problems, the challenge is the inherent intractability of the objective function, and one needs efficient methods to capture the low-dimensionality of these models. Convex optimization is often a promising tool to attack such problems. An intractable problem with a combinatorial objective can often be "relaxed" to obtain a tractable but almost as powerful convex optimization problem. This dissertation studies convex optimization techniques that can take advantage of low-dimensional representations of the underlying high-dimensional data. We provide provable guarantees that ensure that the proposed algorithms will succeed under reasonable conditions, and answer questions of the following flavor:

More specifically, i) Focusing on linear inverse problems, we generalize the classical error bounds known for the least-squares technique to the lasso formulation, which incorporates the signal model. ii) We show that intuitive convex approaches do not perform as well as expected when it comes to signals that have multiple low-dimensional structures simultaneously. iii) Finally, we propose convex relaxations for the graph clustering problem and give sharp performance guarantees for a family of graphs arising from the so-called stochastic block model. We pay particular attention to the following aspects. For i) and ii), we aim to provide a general geometric framework, in which the results on sparse and low-rank estimation can be obtained as special cases. For i) and iii), we investigate the precise performance characterization, which yields the right constants in our bounds and the true dependence between the problem parameters.

The current distribution of signal and native crayfish in the Broadmead Brook, Wiltshire

Signal crayfish (Pacifastacus leniusculus) have existed in the upper reaches of Broadmead Brook in Wiltshire since 200 individuals were introduced at West Kington in 1981. The population has expanded upstream and downstream since this introduction, however, giving rise to concerns that it may potentially threaten the native crayfish population further downstream. Signal crayfish can act as a vector of crayfish plague - a disease caused by the fungus Aphanomyces astaci Schikora which results in almost complete mortality to the native, white-clawed crayfish Austropotamobius pallipes. The native crayfish in Broadmead Brook have not yet succumbed to crayfish plague and are currently free of the disease. However, as signal crayfish appear to out-compete the native species, the native population could still be under threat. In this article, we highlight the findings of previous crayfish surveys on Broadmead Brook and describe work undertaken in summer 2001 to map the current distribution of native and signal crayfish. Finally, options for controlling the spread of signal crayfish are discussed.