Luiz Fernando Wurdig Roesch

Pyrosequencing enumerates and contrasts soil microbial diversity.

Estimates of the number of species of bacteria per gram of soil vary between 2000 and 8.3 million (Gans et al., 2005; Schloss and Handelsman, 2006). The highest estimate suggests that the number may be so large as to be impractical to test by amplification and sequencing of the highly conserved 16S rRNA gene from soil DNA (Gans et al., 2005). Here we present the use of high throughput DNA pyrosequencing and statistical inference to assess bacterial diversity in four soils across a large transect of the western hemisphere. The number of bacterial 16S rRNA sequences obtained from each site varied from 26 140 to 53 533. The most abundant bacterial groups in all four soils were the Bacteroidetes, Betaproteobacteria and Alphaproteobacteria. Using three estimators of diversity, the maximum number of unique sequences (operational taxonomic units roughly corresponding to the species level) never exceeded 52 000 in these soils at the lowest level of dissimilarity. Furthermore, the bacterial diversity of the forest soil was phylum rich compared to the agricultural soils, which are species rich but phylum poor. The forest site also showed far less diversity of the Archaea with only 0.009% of all sequences from that site being from this group as opposed to 4%–12% of the sequences from the three agricultural sites. This work is the most comprehensive examination to date of bacterial diversity in soil and suggests that agricultural management of soil may significantly influence the diversity of bacteria and archaea.

Complete Genome Sequence of the N2-Fixing Broad Host Range Endophyte Klebsiella pneumoniae 342 and Virulence Predictions Verified in Mice

We report here the sequencing and analysis of the genome of the nitrogen-fixing endophyte, Klebsiella pneumoniae 342. Although K. pneumoniae 342 is a member of the enteric bacteria, it serves as a model for studies of endophytic, plant-bacterial associations due to its efficient colonization of plant tissues (including maize and wheat, two of the most important crops in the world), while maintaining a mutualistic relationship that encompasses supplying organic nitrogen to the host plant. Genomic analysis examined K. pneumoniae 342 for the presence of previously identified genes from other bacteria involved in colonization of, or growth in, plants. From this set, approximately one-third were identified in K. pneumoniae 342, suggesting additional factors most likely contribute to its endophytic lifestyle. Comparative genome analyses were used to provide new insights into this question. Results included the identification of metabolic pathways and other features devoted to processing plant-derived cellulosic and aromatic compounds, and a robust complement of transport genes (15.4%), one of the highest percentages in bacterial genomes sequenced. Although virulence and antibiotic resistance genes were predicted, experiments conducted using mouse models showed pathogenicity to be attenuated in this strain. Comparative genomic analyses with the presumed human pathogen K. pneumoniae MGH78578 revealed that MGH78578 apparently cannot fix nitrogen, and the distribution of genes essential to surface attachment, secretion, transport, and regulation and signaling varied between each genome, which may indicate critical divergences between the strains that influence their preferred host ranges and lifestyles (endophytic plant associations for K. pneumoniae 342 and presumably human pathogenesis for MGH78578). Little genome information is available concerning endophytic bacteria. The K. pneumoniae 342 genome will drive new research into this less-understood, but important category of bacterial-plant host relationships, which could ultimately enhance growth and nutrition of important agricultural crops and development of plant-derived products and biofuels.

Distantly sampled soils carry few species in common

The bacterial phylogenetic structure of soils from four distinctly different sites in South and North America was analyzed. One hundred and thirty-nine thousand sequences of the V9 region of the small subunit of the bacterial ribosomal RNA gene generated for a previous study were used for this work. Whereas the previous work estimated levels of species richness, this study details the degree of bacterial community overlap between the four soils. Sequences from the four soils were classified and grouped into different phyla and then assigned to operational taxonomic units (OTUs) as defined by 97 or 100% sequence similarity. Pairwise Jaccard and θ similarity indices averaged over all phyla equalled 6 and 12% respectively at the 97% similarity level, and 15% for both at the 100% similarity level. At 100 and 97% sequence similarity, 1.5 and 4.1% of OTUs were found in all four soils respectively, and 87.9 and 74.4%, respectively were a unique particular soil. These analyses, based on the largest soil bacterial sequence retrieval to date, establish the high degree of community structure difference for randomly sampled dissimilar soils and support the idea that wide sampling is important for bioprospecting. The 10 most abundant cultured genera were determined in each soil. These 10 genera comprised a significant proportion of the reads obtained from each soil (31.3–37.4%). Chitinophaga was the most abundant or the second most abundant genus in all four soils with 7.5–13.8% of the total bacterial sequences in these soils. The striking result is that several culturable genera, whose roles in soil are virtually unknown, were found among these dominant sequences.

Rethinking microbial diversity analysis in the high throughput sequencing era

The analysis of amplified and sequenced 16S rRNA genes has become the most important single approach for microbial diversity studies. The new sequencing technologies allow for sequencing thousands of reads in a single run and a cost-effective option is split into a single run across many samples. However for this type of investigation the key question that needs to be answered is how many samples can be sequenced without biasing the results due to lack of sequence representativeness? In this work we demonstrated that the level of sequencing effort used for analyzing soil microbial communities biases the results and determines the most effective type of analysis for small and large datasets. Many simulations were performed with four independent pyrosequencing-generated 16S rRNA gene libraries from different environments. The analysis performed here illustrates the lack of resolution of OTU-based approaches for datasets with low sequence coverage. This analysis should be performed with at least 90% of sequence coverage. Diversity index values increase with sample size making normalization of the number of sequences in all samples crucial. An important finding of this study was the advantage of phylogenetic approaches for examining microbial communities with low sequence coverage. However, if the environments being compared were closely related, a deeper sequencing would be necessary to detect the variation in the microbial composition.

Biodiversity of diazotrophic bacteria within the soil, root and stem of field-grown maize

Recent studies suggest a high diversity of diazotrophic bacteria in maize. However, none of these works have been based on a sufficient number of samples to provide reasonable quantitative estimates of diazotrophic bacterial diversity. Here we present the use of molecular tools and statistical inference to assess diazotrophic bacterial diversity within rhizosphere soils, roots and stems of field grown maize. DNA was isolated from the latter collected from six maize growing regions within the southern most state in Brazil, Rio Grande do Sul. Using conserved primers, nifH Cluster I gene fragments were amplified from each of the three zones, and the products cloned and sequenced. The majority of the sequences were classified within the Proteobacteria with the α-proteobacteria and β-proteobacteria being the most abundant in the rhizosphere soil and stem samples. The γ-proteobacteria were most abundant in rhizosphere soils, less so in roots, and least in the stem samples. According to three different diversity measures, the rhizosphere soil samples possessed greater diazotrophic bacterial diversity than the roots and stems of the maize plants. Only two genera, Azospirillum and Azotobacter, were found in virtually all samples at an abundance of over 1% of the total nifH sequences obtained. Other genera were largely restricted to soil (Methylocystis, Beijerinckia, Geobacter, Rhodovulum, Methylobacterium, Gluconacetobacter, Methylocella, and Delftia), roots (Dechloromonas), or stems (Methylosinus, Raoultella, and Rhizobium). Three genera, Herbaspirillum, Ideonella, and Klebsiella, appeared to dominate in the interior of the plant but were much rarer in soil.

Data analysis for 16S microbial profiling from different benchtop sequencing platforms

Progress in microbial ecology is confounded by problems when evaluating results from different sequencing methodologies. Contrary to existing expectations, here we demonstrate that the same biological conclusion is reached using different NGS technologies when stringent sequence quality filtering and accurate clustering algorithms are applied.

Influence of Fecal Sample Storage on Bacterial Community Diversity

Previous studies have identified a correlation, either positive or negative, between specific stool bacteria strains and certain autoimmune diseases. These conflicting data may relate to sample collection. The aim of this work was to evaluate the influence of the collection parameters of time and temperature on bacterial community composition. Samples were taken from healthy children and immediately divided in 5 sub-samples. One sample was frozen immediately at -80°C, while the other aliquots were frozen 12, 24, 48, and 72h later DNA extracted from each sample was used to amplify the 16S rRNA with barcoded primers. The amplified products were pooled and partial 16S rRNA sequences were obtained by pyrosequencing. Person-to-person variability in community diversity was high. A list of those taxa that comprise at least 1% of the community was made for each individual. None of these were present in high numbers in all individuals. The Bacteroides were present in the highest abundance in three of four subjects. A total of 23,701 16S rRNA sequences were obtained with an average of 1,185 reads per sample with an average length of 200 bases. Although pyrosequencing of amplified 16S rRNA identified changes in community composition over time (~10%), little diversity change was observed at 12 hours (3.06%) with gradual changes occurring after 24 (8.61%), 48 (9.72%), and 72 h (10.14%), post collection.

Network topology reveals high connectance levels and few key microbial genera within soils

Microbes have a central role in soil global biogeochemical process, yet specific microbe-microbe relationships are largely unknown. Analytical approaches as network analysis may shed new lights in understanding of microbial ecology and environmental microbiology. We investigated the soil bacterial community interactions through cultivation-independent methods in several land uses common in two Brazilian biomes. Using correlation network analysis we identified bacterial genera that presented important microbial associations within the soil community. The associations revealed nonrandomly structured microbial communities and clusters of operational taxonomic units (OTUs) that reflected relevant bacterial relationships. Possible keystone genera were found in each soil. Irrespective of the biome or land use studied only a small portion of OTUs showed positive or negative interaction with other members of the soil bacterial community. The more interactive genera were also more abundant however, within those genera, the abundance was not related to taxon importance as measured by the Betweenness Centrality. Most of the soil bacterial genera were important to the overall connectance of the network, whereas only few genera play a key role as connectors, mainly belonged to phyla Proteobacteria and Actinobacteria. Finally it was observed that each land use presented a different set of keystone genera and that no keystone genus presented a generalized distribution. Taking into account that species interactions could be more important to soil processes than species richness and abundance, especially in complex ecosystems, this approach might represent a step forward in microbial ecology beyond the conventional studies of microbial richness and abundance.

Brazilian Microbiome Project: revealing the unexplored microbial diversity--challenges and prospects.

The Brazilian Microbiome Project (BMP) aims to assemble a Brazilian Metagenomic Consortium/Database. At present, many metagenomic projects underway in Brazil are widely known. Our goal in this initiative is to co-ordinate and standardize these together with new projects to come. It is estimated that Brazil hosts approximately 20 % of the entire world’s macroorganism biological diversity. It is 1 of the 17 countries that share nearly 70 % of the world’s catalogued animal and plant species, and is recognized as one of the most megadiverse countries. At the end of 2012, Brazil has joined GBIF (Global Biodiversity Information Facility), as associated member, to improve the access to the Brazilian biodiversity data in a free and open way. This was an important step toward increasing international collaboration and clearly shows the commitment of the Brazilian government in directing national policies toward sustainable development. Despite its importance, the Brazilian microbial diversity is still considered to be largely unknown, and it is clear that to maintain ecosystem dynamics and to sustainably manage land use, it is crucial to understand the biological and functional diversity of the system. This is the first attempt to collect and collate information about Brazilian microbial genetic and functional diversity in a systematic and holistic manner. The success of the BMP depends on a massive collaborative effort of both the Brazilian and international scientific communities, and therefore, we invite all colleagues to participate in this project.

Shifts in soil bacterial community after eight years of land-use change.

The interaction between plants, soil and microorganisms is considered to be the major driver of ecosystem functions and any modification of plant cover and/or soil properties might affect the microbial structure, which, in turn, will influence ecological processes. Assuming that soil properties are the major drivers of soil bacterial diversity and structure within the same soil type, it can be postulated whether plant cover causes significant shifts in soil bacterial community composition. To address this question, this study used 16S rRNA pyrosequencing to detect differences in diversity, composition and/or relative abundance of bacterial taxa from an area covered by pristine forest, as well as eight-year-old grassland surrounded by the same forest. It was shown that a total of 69% of the operational taxonomic units (OTUs) were shared between environments. Overall, forest and grassland samples presented the same diversity and the clustering analysis did not show the occurrence of very distinctive bacterial communities between environments. However, 11 OTUs were detected in statistically significant higher abundance in the forest samples but in lower abundance in the grassland samples, whereas 12 OTUs occurred in statistically significant higher abundance in the grassland samples but in lower abundance in the forest samples. The results suggested the prevalence of a resilient core microbial community that did not suffer any change related to land use, soil type or edaphic conditions. The results illustrated that the history of land use might influence present-day community structure.