DNA clue to honey bee deaths

Scientists say that mass bee deaths may be caused by viruses that disrupt gene expression.

The team analysed which genes were turned on and which were turned off in healthy bees and those from hives with colony collapse disorder (CCD).

Since 2006, CCD has caused the catastrophic loss of US bee hives and is implicated in bee deaths elsewhere.

Writing in PNAS journal, the team say they used "whole genome microarrays" to compare cells from bees' guts.

Lead scientist May Berenbaum from the University of Illinois told BBC News that the research was made possible by publication of the bee genome in 2006.

We talk about a smoking gun. We have the bullet hole! Professor May Berenbaum

"It's an incredibly useful repository of information which allowed the construction of the microarray - a slide which has all 10,000 bee genes on it," she said.

"We used it to compare colony collapse disorder bees with healthy ones and looked at the differences. There are of course 10,000 genes. So there were a whole lot of differences but we could rule out many of them."

Gut feeling

The team concentrated on analysing gene expression from cells in the bees' guts because this is the primary site of pesticide detoxification and immune defence.

Previous theories for CCD have included pesticide poisoning as well as infection and mite infestation.

But the team's genetic analysis of the bees' guts failed to reveal elevated expression of pesticide response genes.

In addition, genes involved in immune response showed no clear expression pattern despite the increased prevalence of viruses and other pathogens in CCD colonies.

What did show up in the guts of the CCD bees was an abundance of fragments from the ribosome, a structure which is the cell's protein making factory.

According to the researchers, this finding suggests that protein production is likely to be compromised in bees from CCD hives.

Previous research shows that the viruses that bees carry all attack the ribosome.

Little problem

The microbes in question are known as "picorna-like" viruses. The word derives from pico, which means little, and RNA (ribonucleic acid).

"These picorna-like viruses all attack at the same spot," said Professor Berenbaum.

"What they do is to work their way into the ribosome and instead of making honey bee protein they make virus proteins.

"So maybe what's happening is basically the ribosome wears out. So we looked to see if the CCD bees have more of these viruses than healthy bees. And they do.

The viruses in question include "deformed wing virus" and "Israeli acute paralysis virus".

The scientists believe that if a number of similar picorna-like viruses attack simultaneously, they may be able to overwhelm the ribosome.

"We talk about a smoking gun. We have the bullet hole!" said May Berenbaum.

"We now need to look for how multiple viruses might interact on the ribosome."

The honey bee is the US's key agricultural pollinator. As such it is worth $14bn to the country's economy.

CCD was first identified in 2006. In the winter of 2007-8 more than a third of US bees were lost.

Similar losses have been reported in Europe, giving rise to fears that CCD is a global problem.

http://news.bbc.co.uk/1/hi/sci/tech/8219202.stm

Understanding Microarrays

Ever tried to understand DNA Microarrays and how they work? Well, here is a brilliant multimedia animation to explain the process:

http://gcat.davidson.edu/Pirelli/index.htm

Microarrays are used to measure the gene expression of cells in different conditions. When a cell becomes cancerous, for example, some genes are induced (transcription increases), other genes are repressed (transcription is decreased) and with other genes nothing changes. Cells respond to different conditions, some environmental (e.g. sun burn) and some chemically induced (e.g. taking heroin). Medicines and their affects on gene expression are prime candidates for micro-array analysis so they can find out why people respond differently to the same drug - which genes are up-regulated/down-regulated in the presence of the drug.

Part 1

We'll use the experiment mentioned in the above multimedia example... Yeast cells can grow with or without oxygen. But in order to survive-in or adapt-to these conditions they have to create new proteins and also stop the production of other proteins that are not so useful in that condition.

If we place some cells in one condition (with oxygen) and then extract the mRNA from them we can tell which proteins are being made. Cells in oxygen is our control condition.
If we extract the mRNA from the cells in the other condition (sans oxygen) then we know what proteins are being expressed for this specific state. Cells without oxygen is the experimental condition.

If we compare the proteins being made (or not being made) in the two conditions we can discover what transcription has started or stopped in the anaerobic state.

We use DNA microarrays to do find this out. The microarray chip (glass slide) contains the mRNA of the whole yeast genome attached to it. To make a microarray we need to get the mRNA strands from both samples and use them to make mRNA probes which are attached to the surface of the microarray. This is a long process which we won't go into. Often, a ready-to-use microarray chip is available to buy from a company like Affymetrix.

Part 2

In order to find out which proteins have been transcribed we have to attach the mRNA of the samples in each condition to the microarray and we have to label them in a way to identify which mRNA came from which sample.

Since both the microarray mRNA probes and the mRNA strands from the cells are the same they cannot combine so we have to make complimentary DNA (cDNA) strands from the mRNA of each sample.

The enzyme reverse transcriptase converts the mRNA to cDNA. The cDNA is made with flourescently-labelled nucleotides so under the correct light the cDNA will glow. The cDNA has the complementary sequence of the mRNA, so if the mRNA was as shown below, thecDNA would be:

CUUUUUAUCCCCCGGGC - mRNA
GAAAAATAGGGGGCCCG - cDNA

Sample 1, the control, in aerobic conditions is labelled green. The second sample, the experimental condition, anaerobic, is labelled with a red flourescent. The mRNA is dissolved using RNAse so we end up with pure cDNA.

The red and green cDNA is complementary to the mRNA of the microarray so when it is squirted on to the microarray slide from both samples they quickly bind to their complimentary strands. Anything that didn't attach is washed off.

Part 3

The microarray is scanned using a machine that has two lasers that iduce flourescence from red and green labelled strands. Pictures for each color are stored on the computer and processed to measure the intensity of the flourescence - the greater the intensity, the more cDNA is attached to the probes and this tells us that a particular gene is highly expressed. Or the intensity is really weak so we can tell that that particular gene is barely expressed.The pictures/data can be combined to compare both conditions:

If a gene was expressed only in the control cells then a spot on the microarray would glow green.
If a gene was expressed only in the experimental cells (anaerobic) then a spot on the microarray would glow red.
If the gene was expressed in both conditions the colors green and red would mix to form a yellowy shade.
Genes that aren't expressed in either condition show as black since no light is emitted.

Since each gene of the yeast genome is a spot on the microarray, we know what gene each color-spot represents on the microarray so we can easily find out which genes are induced or repressed after the scan.

Simple sort-of :) . Data retrieved from microarray analysis is usually processed using complex programs like R using the bioconductor module. There's a lot of statistics behind the analysis of the data so most people who deal with this stuff are specialists.