Monthly Archives: January 2019

Magnetotaxis: A Bacterial Superpower

The idea of bacterial superpowers is perhaps most associated with superbugs: the terrifying, drug-resistant bacterial strains that appear ever more frequently in news reports. While the notion of a world where antibiotics no longer work is chilling, this blog post will focus on a more positive aspect of the bacterial domain.

One of the more “niche” bacterial superpowers is magnetotaxis: the ability of certain bacteria to align their motion to the Earth’s magnetic field. This phenomenon was first reported in 1963 by Salvatore Bellini in the University of Pavia. While observing bog sediment under the microscope, he noticed a set of bacteria orienting themselves in the same direction: towards the Earth’s magnetic North pole. He dubbed these gram-negative bacteria “magnetosensitive”, or “batteri magnetosensibili”, but the discovery went largely unnoticed by the international scientific community [1]. The name “magnetotactic bacteria” (MTB) was introduced about a decade later, when Richard Blakemore reported the same phenomenon for bacteria found in marine sediments [2]. Through transmission electron microscopy, Blakemore was also able to capture the cellular feature that gives MTBs their unusual abilities: a rod-like structure of membrane-bound, iron-rich inorganic crystals, called magnetosomes. Later it was revealed that this structure is supported by a dedicated cytoskeletal system, which keeps it rod-shaped and prevents the aggregation of magnetosomes [4]. Magnetotaxis then results from the combination of the passive alignment of the cell to the Earth’s magnetic field, and flagellar motion. Continue reading

Making the most of your CPUs when using python

Over the last decade, single-threaded CPU performance has begun to plateau, whilst the number of logical cores has been increasing exponentially.

Like it or loathe it, for the last few years, python has featured as one of the top ten most popular languages [tiobe / PYPL].   That being said however, python has an issue which makes life harder for the user wanting to take advantage of this parallelism windfall.  That issue is called the GIL (Global Interpreter Lock).  The GIL can be thought of as the conch shell from Lord of the Flies.  You have to hold the conch (GIL) for your thread to be computed.  With only one conch, no matter how beautifully written and multithreaded your code, there will still only be one thread will be executed at any point in time.

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Non-alcoholic fatty liver disease

In my new research project, I investigate Non-alcoholic fatty liver disease (NAFLD). This term describes a variety of conditions that are associated with fatty livers. While the early stages of this disease are not harmful, it can lead to cirrhosis (Cirrhosis is the scaring of liver tissue that prevents a liver to function properly). Ultimately, if a liver stops working it can be fatal unless treated, for example, with a liver transplant. NAFLD is the most common liver disease in developed countries and is expected to become the leading cause of liver transplant by 2020 [1].

The disease progresses in four stages: Continue reading

Graph-based Methods for Cheminformatics

In cheminformatics, there are many possible ways to encode chemical data represented by small molecules and proteins, such as SMILES, fingerprints, chemical descriptors etc. Recently, utilising graph-based methods for machine learning have become more prominent. In this post, we will explore why representing molecules as graphs is a natural and suitable encoding. Continue reading