Posts Tagged ‘Podcast’

Coronavirus Chatter [podcast]

Thursday, June 20th, 2013

MERS-CoV

Play this podcast:
http://bit.ly/mb240613mp3

 

Coronaviruses belong to the order Nidovirales, family Coronaviridae, and are enveloped viruses with a positive-sense single-stranded RNA genome. They are classified into four genera: Alphacoronavirus, Betacoronavirus, Gammacoronavirus, and Deltacoronavirus. Coronaviruses cause a range of infections in humans and animals, for the most part not too serious.

In the aftermath of the severe acute respiratory syndrome (SARS)-epidemic in 2002/2003 caused by a coronavirus probably originally from bats, a large number of novel bat coronaviruses was described. In addition to SARS-CoV, four human coronaviruses (HCoVs), termed HCoV-OC43, -229E, -NL63, and -HKU1 are known. Recently, a sixth HCoV was described, now known as MERS-CoV – Middle East respiratory syndrome, see: 10 things you should know about novel coronavirus (MERS-CoV).

Bat species are surprisingly numerous and compared with other animals we know relatively little about them. For example, a recent paper in JGV looked at 1,868 specimens from 1,562 individual bats collected between 2008 and 2012 in Costa Rica, Panama, Ecuador and Brazil. In three out of the four countries (except Ecuador), bat coronaviruses were detected (Highly diversified coronaviruses in neotropical bats. J Gen Virol. 12 Jun 2013).

Carl Zimmer: Listen Closely To The Bats and You Can Hear the Viral Chatter

A recent perspective into the spread of MERS appeared recently in the NY Times: Investigation Follows Trail of a Virus in Hospitals.

 

 

Good Bugs, Bad Bugs: Fun Kids Guide to Microbiology

Tuesday, December 11th, 2012

Dive into the exciting world of Microbiology, narrated by one nice, helpful microbe called Benny and one not very nice germ called Mal. In this episode they introduce us to some of their microbe friends!
Podcast Episode 1 (10 December 2012):
https://itunes.apple.com/gb/podcast/good-bugs-bad-bugs-fun-kids/id586289570

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MicrobiologyBytes Podcasts

Monday, August 31st, 2009

MicrobiologyBytes For more than three years (since April 2006) I’ve been experimenting with podcasts covering all aspects of microbiology. I decided to have a break over the last month, and during that time I have been thinking about the future. On balance, I feel that the audio format of the podcasts does not add much value to the content beyond what could be achieved with text and images in the style of standard posts on this site. In some circumstances though, a video can add significant value, so I have decided not to post any more audio podcasts for the foreseeable future and to invest the time in producing occasional videos which you will be able to view on this site. All of the old podcast files will remain available here.

Thanks for listening, and here’s the first of the new videos:

The structure of hepatitis E virus

Monday, July 27th, 2009

Viral hepatitis is mostly caused by five distinct viruses named hepatitis A–E. Despite their names, the five viruses are unrelated, with totally different genome structures and replication mechanisms. Hepatitis E virus (HEV) is responsible for endemic hepatitis as well as sporadic epidemics of acute, enterically transmitted hepatitis in the developing world. HEV accounts for more than 50% of acute viral hepatitis in young adults in these regions, with a case fatality of 1–2% in regular patients and up to 20% in pregnant women. Because there is no robust cell culture system for this virus, and because it is not closely related to any other well-characterized virus, little is known about the molecular biology of HEV or its strategy for replication.

HEV is a small, non-enveloped, icosahedral virus with a positive-sense RNA genome of 7.2 kb. Its genomic RNA is polyadenylated and contains three open reading frames (ORFs). HEV was originally classified in the Caliciviridae family because of its structural similarity to other caliciviruses. However, it is now regarded as the sole member of the Hepevirus genus. The genomic RNA of HEV exhibits several distinct features compared to the genomic RNA of caliciviruses, including a methylated cap at the 5′-end and an ORF1 with functional domains arranged in a different order.

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A recent paper in PNAS describes the crystal structure of HEV at 3.5-Å resolution (Structure of the hepatitis E virus-like particle suggests mechanisms for virus assembly and receptor binding. PNAS USA July 21, 2009). The capsid protein of this virus contains three linear domains that form distinct structural elements:

  • S, the continuous capsid
  • P1, three-fold protrusions
  • P2, two-fold spikes

Each domain possesses a potential polysaccharide-binding site that may function in receptor binding. Receptor binding to P1 at the capsid protein interface may lead to capsid disassembly and cell entry. These findings significantly advance the understanding of HEV and are useful for the development of vaccines and antiviral medications.

Super-Resolution Light Microscopy of Escherichia coli

Monday, July 20th, 2009

Cells arrange their components – proteins, lipids, and nucleic acids – in organized and reproducible ways to optimize their activities and to improve cell efficiency and survival. Eukaryotic cells have a complex arrangement of subcellular structures such as membrane-bound organelles and cytoskeletal transport systems. However, subcellular organization is also important in prokaryotic cells, including rod-shaped bacteria such as E. coli, most of which lack such well-developed systems of organelles and motor proteins for transporting cellular cargoes. In fact, it has remained somewhat mysterious how bacteria are able to organize and spatially segregate their interiors.

The E. coli chemotaxis network, a system important for the bacterial response to environmental cues, is one of the best-understood biological signal transduction pathways and serves as a useful model for studying bacterial spatial organization because its components display a nonrandom, periodic distribution in mature cells. Chemotaxis receptors aggregate and cluster into large sensory complexes that localize to the poles of bacteria. To understand how these clusters form and what controls their size and density, a recent study used ultrahigh-resolution light microscopy, called photoactivated localization microscopy, to visualize individual chemoreceptors in single E. coli cells. From these high-resolution images, the authors were able to determine that receptors are not actively distributed or attached to specific locations in cells. Instead, it appears that random receptor diffusion and receptor–receptor interactions are sufficient to generate the observed complex, ordered pattern. This simple mechanism, termed stochastic self-assembly, may prove to be widespread in both prokaryotic and eukaryotic cells.

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Self-Organization of the Escherichia coli Chemotaxis Network Imaged with Super-Resolution Light Microscopy. 2009 PLoS Biol 7(6): e1000137 doi:10.1371/journal.pbio.1000137
The Escherichia coli chemotaxis network is a model system for biological signal processing. In E. coli, transmembrane receptors responsible for signal transduction assemble into large clusters containing several thousand proteins. These sensory clusters have been observed at cell poles and future division sites. Despite extensive study, it remains unclear how chemotaxis clusters form, what controls cluster size and density, and how the cellular location of clusters is robustly maintained in growing and dividing cells. Here, we use photoactivated localization microscopy (PALM) to map the cellular locations of three proteins central to bacterial chemotaxis (the Tar receptor, CheY, and CheW) with a precision of 15 nm. We find that cluster sizes are approximately exponentially distributed, with no characteristic cluster size. One-third of Tar receptors are part of smaller lateral clusters and not of the large polar clusters. Analysis of the relative cellular locations of 1.1 million individual proteins (from 326 cells) suggests that clusters form via stochastic self-assembly. The super-resolution PALM maps of E. coli receptors support the notion that stochastic self-assembly can create and maintain approximately periodic structures in biological membranes, without direct cytoskeletal involvement or active transport.

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How smart are bacteria?

Monday, July 6th, 2009

A recent article in New Scientist entitled Why microbes are smarter than you thought looks at six behaviours that seem remarkably intelligent for single celled organisms. Single-celled organisms don’t have nervous systems, let alone brains, but they could be viewed as “biological computers” with internal machinery that can process and respond to information.

On MicrobiologyBytes I’ve often discussed bacterial communication – the ways in which bacteria talk to each other using chemical signals. If Bacillus subtilis cells are growing in a nutrient-poor area, they release chemicals into their surroundings which tell their neighbours “There’s not much food here, so clear off or we’ll both starve.” In response to these chemical messages, the other bacteria move away, changing the shape of the colony.

Many single-celled organisms can work out how many other bacteria of their own species are in their vicinity – something known as “quorum sensing“. Each individual bacterium releases a small amount of a chemical into the surrounding medium. If there are lots of other bacteria around, all releasing the same chemical, levels can reach a critical point and trigger a change in behaviour of the whole population. This “voting system” can be used to decide when to launch an attack on a host. Once they have grown to sufficient numbers to overwhelm the immune system, they collectively launch an assault on the body. Jamming these signals might provide us with a way to fight back.

Bacteria form communities known as biofilms, familiar as the thin layer of slime that coats the insides of water pipes, or surgical implants. Many different species live side by side in these “bacterial cities”, consuming each other’s wastes, cooperating to exploit food sources, and safeguarding one another from external threats such as antibiotics.

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Many microbes can accelerate the rate at which their genes mutate. This allows them to obtain new abilities that may be helpful when conditions get tough. Escherichia coli mutates more rapidly when under stress (Stress-induced mutagenesis in bacteria. Science. 2003 300(5624): 1404-9), and yeast can perform the same trick (Adaptive mutation in Saccharomyces cerevisiae. Crit Rev Biochem Mol Biol. 2007 42(4): 285-31).

Microbes are also pretty good at navigation. The single-celled algae Chlamydomonas swim towards light, but only if it is of a wavelength that they can use for photosynthesis. Some bacteria move according to the presence of chemicals in their environment – a behaviour called chemotaxis. Another group of bacteria align themselves to the Earth’s magnetic field, allowing them to head directly north or south, and more importantly, up or down for optimum photosynthesis.

When the amoeba Dictyostelium searches the surface of a Petri dish for food, it makes frequent turns. But it does not do so randomly. If it has just turned right, it is twice as likely to turn left as right on its next turn, and vice versa. It remembers which direction it last turned.

Remarkable though these behaviours are, we have probably only scratched the surface of what single-celled organisms can do. With so many still entirely unknown to science, there must be plenty more surprises in store.

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Manuka honey

Monday, June 29th, 2009

Manuka On MicrobiologyBytes I’ve often discussed dangerous antibiotic-resistant superbugs such as Staphylococcus aureus MRSA and Clostridium difficile, and what can be done about them. Manuka honey is gathered in New Zealand and Australia from bees which have fed on the manuka bush, Leptospermum scoparium. Recent research has shown that this particular honey has antibacterial activity due primarily to the presence of methylglyoxal (Identification and quantification of methylglyoxal as the dominant antibacterial constituent of Manuka (Leptospermum scoparium) honeys from New Zealand. Mol Nutr Food Res. 2008 Apr;52(4):483-9). This substance originates from dihydroxyacetone, which is present in the nectar of manuka flowers in varying amounts (The origin of methylglyoxal in New Zealand manuka (Leptospermum scoparium) honey. Carbohydr Res. 2009 May 26;344(8):1050-3). Nectar washed from manuka flowers contained high levels of dihydroxyacetone and no detectable methylglyoxal. Storage of manuka honey at 37°C leads to a decrease in the dihydroxyacetone content and a related increase in methylglyoxal. Addition of dihydroxyacetone to clover honey followed by incubation results in methylglyoxal levels similar to those found in manuka honey.

So why the fuss? Dressings containing manuka honey have been shown to be clinically effective against a wide range of bacteria which cause skin ulcers and chronic wound infections, a big problem in hospitals (PubMed: latest research). But manuka honey is in relatively short supply, and so expensive. Manuka honey is now being made in the UK from bushes brought to the Tregothnan Estate near Truro, Cornwall, in 1888. It goes well with a Cornish cream tea, but at £55 a pot, it’s still not cheap.

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Toxins for microbial attack and plant defence

Monday, June 22nd, 2009

Pythium aphanidermatum Millions of years of coevolution of plants and microbial pathogens have shaped both the abilities of microbial pathogens to overcome plant disease resistance and the abilities of plants to cope with microbial invasion. Phytopathogens from different taxonomic origins secrete structurally unrelated effectors into plants to establish infection and to suppress host defences. In addition, phytopathogenic micro-organisms produce a wide range of cytolytic toxins that function as virulence determinants.

Microbial pattern recognition is a prerequisite for the initiation of antimicrobial defenses in all multicellular organisms, including plants. The bipartite plant immune system is based upon recognition of pathogen-associated molecular patterns by pattern-recognition receptors as well as upon the activities of resistance proteins that have evolved to recognize the presence or activities of microbial effectors. In addition to the recognition of microbial patterns and effectors, plants also possess capacities to sense host-derived damage patterns that originate, for example, from the degradation of the plant cell wall by microbial hydrolytic enzymes.

Paradoxically, some phytopathogenic microbe-derived cytolytic toxins have also been reported to elicit plant defences. However, for virtually all microbial toxins with plant defence-stimulating potential, it is unknown whether activation of plant defences results from toxin-induced cellular distress or, independently of toxin action, from recognition of toxins as microbial patterns by plant pattern-recognition receptors.

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NLPs are a superfamily of proteins that are produced by various phytopathogenic micro-organisms, both prokaryotes and eukaryotes. Necrosis and ethylene-inducing peptide 1 (Nep1)-like proteins (NLPs) trigger leaf necrosis that is genetically distinct from immunity-associated programmed cell death and stimulate immunity associated defences in all dicotyledonous plants tested, but not in monocotyledons such as grasses. Hence, NLPs were proposed to have dual functions in plant pathogen interactions, acting both as triggers of immune responses and as toxin-like virulence factors. The broad taxonomic distribution of NLPs, in particular their occurrence in both prokaryotic and eukaryotic species, is unusual for known microbial phytotoxins, the production of which is restricted to a narrow range of microbial species.

Recent work has determined the crystal structure of an NLP from a phytopathogenic fungus (A common toxin fold mediates microbial attack and plant defense. PNAS USA June 11 2009, doi: 10.1073/pnas.0902362106). Computational modeling of the three-dimensional structure of NLPs from another fungus and from a phytopathogenic bacterium reveals a high degree of conservation. Expression of the fungus NLPs in an NLP-deficient phytopathogenic bacteria restored bacterial virulence.

Mutation analysis revealed that identical structural properties were required to cause plasma membrane permeabilization and cytolysis in plant cells, as well as to restore bacterial virulence. The conclusion is that NLPs are conserved virulence factors whose wide taxonomic distribution is exceptional for microbial phytotoxins, and that contribute to host infection by plasma membrane destruction and cytolysis. Phytotoxin-induced cellular damage-associated activation of plant defenses is reminiscent of microbial toxin-induced inflammatory activation in vertebrates and may constitute another conserved element in animal and plant innate immunity.

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Hungry for hosts – gene flow in influenza virus

Monday, June 15th, 2009

Fulmar Wild waterfowl and seabirds are major natural reservoirs of influenza A viruses. Genetic analysis has revealed that influenza A viruses found in all other host species, including humans, were ultimately derived from avian viruses. Geographical separation of host species has shaped the influenza gene pool into largely independently evolving Eurasian and American lineages, although some gene flow between these regions has been documented.

Reassortment between Eurasian and North American lineage viruses have also been documented in wild aquatic bird populations indicating that in these two geographically segregated lineages there is some mixing of viruses. However, the possible effects of virus gene flow between the Eurasian and American gene pools on influenza virus evolution and population structure had not been fully explored until recently. A new study shows that virus gene flow from Eurasia has led to the exclusion of some viruses from North America, most likely mediated by competition for susceptible hosts (Gene flow and competitive exclusion of avian influenza A virus in natural reservoir hosts. Virology, 5 June 2009 doi:10.1016/j.virol.2009.05.002).

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The researchers found that intercontinental gene flow is frequently mediated through seabirds, highlighting the need for increased surveillance of influenza viruses in a broader spectrum of potential host species. Such selection is only likely to occur in cases where the viruses in question are sufficiently antigenically similar to induce a cross-protective immune response.

Population genetics offers a number of concepts and principles to explain the evolutionary behavior of RNA viruses. For example, the competitive exclusion principle states that when two species compete for limited resources one species will eventually outcompete the other and become dominant. In the case of RNA viruses, a combination of high replication numbers and high nucleotide substitution rates makes the prolonged co-existence of two or more genetically distinct virus populations unlikely. In theory, the competitive pressure exerted by an invading influenza virus will select for viruses with increased reproduction and transmissibility. Therefore the adaptive advantage conferred through competition may contribute to influenza disease emergence.

Increased genome surveillance of influenza viruses in bird populations is critical for understanding the effects of gene flow between populations. The extent of virus competition in avian populations infected with influenza remains unknown. In Asia, the long-term endemicity of H5N1 influenza appears to have replaced, most probably through competitive selection, low pathogenic H5 subtype viruses that have been only rarely isolated from poultry in Asia since 2000 when compared to previous surveillance in the 1970′s. This new work provides a possible mechanism for disease emergence and transmission from natural reservoir hosts.

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