Gut Bacteria in Young Diabetic Kids Show Differences

and DNA microarray principle

analyzes

• New research published in Diabetologia (the journal ofthe European Association for the Study of Diabetes)shows that children diagnosed with type 1 diabetes have aless balanced composition of gut bacteria compared withchildren of the same age without diabetes.

• The research is by Dr Marcus de Goffau and Dr HermieHarmsen, University Medical Center Groningen, theNetherlands, and colleagues.

• The incidence of type 1 diabetes is increasing worldwide,showing a particularly sharp increase among childrenunder the age of 5 years.

• Recent studies indicate that adverse changes in gutmicrobiota are associated with the development of type 1diabetes, but little is known about the microbiota inchildren who have diabetes at an early age.

• Thus in this new study the microbiota of children aged 1years with new-onset type 1 diabetes was compared withthe microbiota of age-matched healthy controls.

• A deep global analysis of the gut microbiota composition

was done by phylogenetic microarray analysis using a

Human Intestinal Tract Chip (HITChip), an analytical

device designed specifically for studying gut bacteria ( I

will give summary about this technique in the next slide).

• Patients were recruited into two research projects – the

DIPP (Finnish Type 1 Diabetes Prediction and Prevention)

study in Finland and the international VirDiab (Viruses in

Diabetes) study, which included cases and control children

from seven European countries.

• Faecal samples were collected from children newly

diagnosed with type 1 diabetes and controls. DNA was

successfully isolated from 28 diabetic children: four from

France, one from Greece, three from Estonia, two from

Lithuania and 18 from Finland.

• The diabetic children were matched with controlchildren according to age; DNA was isolatedsuccessfully from 27 control children.

• One of the control children was from Lithuaniaand the rest were from Finland.

• The samples were collected from the diabeticchildren within 4 weeks of the diagnosis ofdiabetes and were coupled with samples from age-matched controls.

• Samples were collected by the parents at homeand shipped by mail at ambient temperature tothe laboratory, where they were subsequentlystored at -75°C.

• The researchers found that in childrenyounger than three years, the combinedabundance of the class Bacilli (notablystreptococci) and the phylum Bacteroideteswere higher in diabetic children, whereas thecombined abundance of the important(usually beneficial) Clostridium clusters IVand XIVa was higher in the healthycontrols(Clostridium Clusters IV and XIVa ThatCan Promote the Induction of Foxp3+

Regulatory Treg Cells in Gut as a Novel Strategyto Prevent and Treat Inflammatory BowelDiseases).

• Controls aged three years and older werecharacterized by a higher fraction of butyrate-producing species within Clostridium clustersIV and XIVa than was seen in thecorresponding diabetic children or in childrenfrom the younger age groups, while thediabetic children older than three years couldbe differentiated by having an unusually highmicrobial diversity.

• An increased diversity is often associated withunstable or with unusual bacterial networks; inchildren with celiac disease or adults withcolorectal cancer an abnormally high microbialdiversity is found.

• The authors discuss that the ideal scenario for thegut is to have the right balance of bacteria toproduce the fermentation product butyrate, which isreadily absorbed by the human gut and turned intoenergy.

• Production of sufficient butyrate by bacteria in thegut leads to optimal gut function andprevents/minimizes inflammation and othermetabolic problems.

• The authors explain that, as the gut microbiota ofvery young children (1-3 years) is still developingvery rapidly, the proper kind of balance to producebutyrate is not yet exactly the same as it is whenchildren are older than 3 years.

• The authors also recalculated their results withoutthe non-Finnish children to adjust for anygeographical differences, and their main findingsremained unchanged.

• They say: "The results from both age groups suggestthat non-diabetic children have a more balancedmicrobiota in which butyrate-producing speciesappear to hold a pivotal position.

• Although distinct differences have been found ineach age category between the healthy and diabeticchildren, the main differences with regard toClostridium clusters IV and XIVa appear torepresent two sides of the same coin, as theytogether emphasize the importance of developingbalanced bacterial cross-feeding complexes thathave sufficient potential for butyrate formation."

• They add: "Dietary interventions aimed atachieving or maintaining optimal butyrateproduction levels might measurably reduce the riskof developing type 1 diabetes, especially in childrenwith genetic risk for developing type 1 diabetes."

• The authors say more work needs to be done on establishing

exactly what foods are best for promoting ideal gut

conditions, however they conclude: "We think a diet high in

fruits and vegetables is best as these are rich in fibre/complex

carbohydrates, which are important because butyrate-

producing species are dependent upon them indirectly via

cross-feeding relations with fibre degraders.

• Simple sugars, on the other hand, cause an overabundance of

species which are very proficient in quickly utilizing sugars—

Streptococci for example—thus outcompeting or limiting the

amount of species which are beneficial for human health.

• Excessive protein and animal fat consumption might

similarly indirectly negatively affect butyrate production as

they stimulate non-butyrate-producing species which are very

good in utilizing this type of food source (such as

Bacteroides).”

DNA microarray principle analyzes

• Introduction to the transcriptome platform

• The Transcriptome Platform form the Biology Department GenomicService (SGDB) at the E. coli Normal Superior has been created in 1998by laboratories from ENS, Curie Institute and ESPCI, during the Ile deFrance genopole development.

• The transcriptome platform is currently proposing DNA microarraysfrom "yeast and guts bacteria " (pan-genomic) and "mouse" (pan-genmoci and dedicated to nervous system development).

• Platform produced slides distribution is done according to a scientificcollaboration which terms are described in an agreement and a protocol

• Although the transcriptome platform does not offer systematically toproduce DNA microarrays to order, we are open to every project aiming atproducing new types of microarrays (from other organisms or for arestricted collection of genes).

• At this prospect, access conditions to the production facilities have to bediscussed case by case with the platform head.

• DNA microarrays principle

• This slides shortly explain the various steps involved in a typical DNAmicroarray experiment.

• DNA microarray principle

• DNA microarrays allow for rapid measurement and visualization of differential expression between genes at the whole genome scale.

• If technique implementation is quite complicated, it’s principle is very easy.

• Here are described the major steps involved in this process

• Microarray production process

• Target preparation

• Hybridization

• Slide scanning

• Data analysis Expression profile clustering

• Microarray production process:

• DNA fragments amplified by PCR technique are spotted ona microscopic glass slide coated with polylysine prior tospotting process.

• The polylysine coating goal is to ensure DNA fixationthrough electrostatic interactions.

• PCR fragments are in this case the expressed part (ORF) ofthe 6200 Saccharomyces cerevisae genes (baker yeast).

• Slide preparation is achieved by blocking the polylysine notfixed to DNA in order to avoid target binding.

• Prior to hybridization, DNA is denatured to obtained asingle strand DNA on the microarray, this will allow theprobe to bind to the complementary strand from the target.

• Apart from glass slide microarray other types of chips exist:

• Target preparation:• RNA are extracted from two yeast cultures from which we

want to compare expression level.• Messengers RNA are then transformed in cDNA by reverse

transcription.• On this stage, DNA from the first culture with a green dye,

whereas DNA from the second culture is labeled with a reddye.

• Hybridization:• Green labeled cDNA and red labeled ones are mixed

together (call the target) and put on the matrix of spottedsingle strand DNA (call the probe).

• The chip is then incubated one night at 60 degrees.• At this temperature, a DNA strand that encounter the

complementary strand and match together to create adouble strand DNA.

• The fluorescent DNA will then hybridize on the spotted ones.

•If replace grey scales by green scales for the first image and red

scales for the second one, It obtained by superimposing the two

images one image composed of spots going from green ones

(where only DNA from the first condition is fixed) to red (where

only DNA from the second condition is fixed) passing through

the yellow color (where DNA from the two conditions are fixed

on equal amount).

•Slide scanning: A laser

excites each spot and the

fluorescent emission gather

through a photo- multiplicator

(PMT) coupled to a confocal

microscope.

• Then obtained two images

where grey scales represent

fluorescent intensities read

• Data analysis:• Obtained now two microarray images from which we have to

calculate the number of DNA molecules in each experimentalcondition.

• To do so, we measure the signal amount in the green dye emissionwavelength and the signal amount in the red dye emission wavelength.

• Then normalize these amount according to various parameters (yeastamount in each culture condition, emission power of each dye, …).

• It suppose that the amount of fluorescent DNA fixed is proportional tothe mRNA amount present in each cell at the beginning and wecalculate the red/green fluorescence ratio.

• If this ratio is greater than 1 (red on the image), the gene expression isgreater in the second experimental condition, if this ration is smallerthan 1 (green on the image), the gene expression is greater in the firstcondition.

• It can visualize these differences in expression using software as theone developed in the laboratory call ArrayPlot (cf below image).

• This software allows from the intensities list of spot to display the redintensities of each spot as a function of the green intensities.

• Expression profile clustering:• Then we can try to gather genes that share the same

expression profile on several experiments.

• This clustering can be done gradually as forphylogenetic analysis, which consist in calculatingsimilarity criteria between expression profiles andgather the most similar ones.

• It can also use more complex techniques as principalcomponent analysis or neuronal networks.

• At the end hierarchical clustering is usually displayedas a matrix where each column represent oneexperiment and each row a gene.

• Ratios are displayed thanks to a color scale goingfrom green (repressed genes) to red (induced genes).