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This blog is a special place for analize different papers regarding genetics and bioinformatics.

Monday, December 6, 2010

Urban aerosols harbor diverse and dynamic bacterial populations

Urban aerosols harbor diverse and dynamic bacterial populations
Eoin L. Brodie, Todd Z. DeSantis, Jordan P. Moberg Parker, Ingrid X. Zubietta, Yvette M. Piceno, and Gary L. Andersen*
Ecology Department, Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720
Edited by Steven E. Lindow, University of California, Berkeley, CA, and approved November 7, 2006 (received for review September 20, 2006)


Considering the importance of its potential implications for human health, agricultural productivity, and ecosystem stability, surprisingly little is known regarding the composition or dynamics of the atmosphere’s microbial inhabitants. Using a custom high-density DNA microarray, we detected and monitored bacterial populations in two U.S. cities over 17 weeks. These urban aerosols contained at least 1,800 diverse bacterial types, a richness approaching that of some soil bacterial communities. We also reveal the consistent presence of bacterial families with pathogenic members including environmental relatives of select agents of bioterrorism significance. Finally, using multivariate regression techniques, we demonstrate that temporal and meteorological influences can be stronger factors than location in shaping the biological composition of the air we breathe.

What to remember

Background: It is very poor knowledge about the bacterial composition in the atmosphere and his variation on different weather or locations. This bacterias on the atmosphere con allow the propagation of certain diseases depending of hte composition of such bacteria community.
The traditional method to detect bacterias are culture based, so it has been difficult to know wich is the composition of this communities.
This paper talks about the design of a microarray (PhyloChip) which could give a comprehensive identification of bacteria and archeal organisms.
They used 16S rRNA. The main problem of develop a microarray from 16S rRNA is the natural diversity of the sequences and also cross-hybridization.

Sequences diversity problems:
  • new environment can have many undocumented organisms, this new organisms sequences can be very similar to the sequences used for array design.
  • Microarray that use single probes may be ineffective for detect environmental sequences with one or several polymorphisms.
They design 11 probes, for each taxonomic group. This allows the failure of some of them.

Samples were taken from Austin and San Antonio. It was made a PCR amplification of 16S rRNA because the samples were to low.
Amplification products from 4 days within a 7 days period, were pooled representing 1 week, and 17 consecutive weekly samples beginning May 2003 were analyzed from both cities for bacterial composition.


PhyloChip results for sample San Antonio July 2003 week 14-20 were compared with clone library sequences results from the same pool of amplified 16S r RNA

Phylochip correctly detect 90% of cloned subfamilies (below family and above species) and detect 2.5 fold more diversity at the phylum level.

The most frequently sequences found on air clone library:

Bacilli (Bacillus batavienses and bacillus spp)
The rest of sequences were very diverse, with a majority of clones representing distinctive 16S RNA gene sequences.

Fig 1: Representative phylogenetic tree showing all known bacterial phyla (and individual classes in the case of proteobacteria) annotated to show 16S rRNA gene sequences detected in an urban aerosol by both microarray and cloning. Also annotated are phyla detected by microarray only that subsequently were confirmed by targeted PCR and sequencing. The Archaea are used as an outgroup. (Scale bar: 0.1 changes per nucleotide.)

Due to the few information regarding diversity on this kind of samples, it was compared the diversity detected on this sample with the diversity found in a farm soil from previous studies.
Soil samples are known to be highly diverse, and the rarefaction curves indicate similar level of diversity between the soil and air samples.

Richness study (chao1 and ACE) of the aerosol sample indicate between 1500 to 1800 rRNA phylotypes. However, that curves are nonasymptotic, could be underestimated this values (insufficient clone sampling).

Fig. 2. Rarefaction curves comparing bacterial diversity in a Minnesota farm soil (20) and the urban aerosol in this study. (Inset) Complete rarefaction curve for 1,874 sequences from the Minnesota farm soil library.

It is expected that this microbial community by dynamic. Latin Square type study was used to test the ability of the PhyloChip to track 16SRNA amplicon dynamics quantitatively.
The Latin Square study contains mixtures of amplicons from diverse bacterial species applied to the PhyloChip in rotating concentrations.
It was demonstrated a strong linear relationship between PhyloChip intensities and quantities of 16S RNA gene signatures applied to PhyloChip (detection of changes in biomarkers quantities, Phylochips detection capacity of found changes on the 16RNA types).

Then was analysed the intensity of the data (changes on the 16SRNA) for both cities, during the 17 weeks.
Also they collect meteorological parameters, in order to see the correlation between them and the bacterial population. Regression tree analysis was used.

For both cities it was a positive correlation with temperature, air pressure, visibility.

For both cities it was a negative correlation with wind speed and particulate matter.

There were changes in bacterial composition in spore-forming bacteria due to the weather. Actinomicetes shows positive correlation with temperature.
The most significant correlation was observed between gammaproteobacterium Pseudomonas oleovorans and week

Fig. 3. Multivariate regression tree analysis of the interaction between aerosol bacterial dynamics (array intensity) and environmental parameters. The model explains 89.1% of variance in SI Data Set 1. Bars plotted under each cluster represent mean of normalized array intensities of phylogenetically related bacteria shown to be significantly correlated with environmental/temporal parameters.

Some bacterias were detected consistently every week. San Antonio shows 80 subfamilies and Austin shows 43 subfamilies. This bacterias are soil associated,(acidobacteria, Verrucomicrobia) so maybe from there.
Also was found consistently Sphingomonas, psychrotolerant (ound on antarctic), spore formers (endospore-forming Bacilli and Clostridia and the exospore-forming Actinomicetes. Also was found Cyanobacteria.
Epsilon proteobacteria were detected in both cities (Campylobacteraceae and Helicobacteraceae)which are human and animal pathogens.

Due to the presence of pathogens bacteria, the US homeland security monitoring systems made a study for potential reservoirs of environmental relatives. It was observed a diversity of Francisella like organisms that can be triggering for the aerosols detectors monitoring systems. The same study was made for this 2 cities, and they only found related Francisella in one week on each city, but never was observed the Francisella Tularensis which is the agent of Tularemia. Also was found related Bacillus anthracis Bacteria one week in San Antonio. Rickettsia and CLostridium botulinum types C and G, Burkholderia mallei and Bu. pseudomalei were detected regularly.

On this study we can know about the dynamic and composition of these two bacterial communities.
It was demonstrated that the diversity of bacteria is related to the climatic regulation.
It is necessary to have a global scale study of this community in order to have baseline levels of the bacteria populations.

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