Microbiome profiling by Illumina sequencing of combinatorial sequence-tagged PCR products

We developed a low-cost, high-throughput microbiome profiling method that uses combinatorial sequence tags attached to PCR primers that amplify the rRNA V6 region. Amplified PCR products are sequenced using an Illumina paired-end protocol to generate millions of overlapping reads. Combinatorial sequence tagging can be used to examine hundreds of samples with far fewer primers than is required when sequence tags are incorporated at only a single end. The number of reads generated permitted saturating or near-saturating analysis of samples of the vaginal microbiome. The large number of reads al- lowed an in-depth analysis of errors, and we found that PCR-induced errors composed the vast majority of non-organism derived species variants, an ob- servation that has significant implications for sequence clustering of similar high-throughput data. We show that the short reads are sufficient to assign organisms to the genus or species level in most cases. We suggest that this method will be useful for the deep sequencing of any short nucleotide region that is taxonomically informative; these include the V3, V5 regions of the bac- terial 16S rRNA genes and the eukaryotic V9 region that is gaining popularity for sampling protist diversity.Comment: 28 pages, 13 figure

Two-Stage Clustering (TSC): A Pipeline for Selecting Operational Taxonomic Units for the High-Throughput Sequencing of PCR Amplicons

Clustering 16S/18S rRNA amplicon sequences into operational taxonomic units (OTUs) is a critical step for the bioinformatic analysis of microbial diversity. Here, we report a pipeline for selecting OTUs with a relatively low computational demand and a high degree of accuracy. This pipeline is referred to as two-stage clustering (TSC) because it divides tags into two groups according to their abundance and clusters them sequentially. The more abundant group is clustered using a hierarchical algorithm similar to that in ESPRIT, which has a high degree of accuracy but is computationally costly for large datasets. The rarer group, which includes the majority of tags, is then heuristically clustered to improve efficiency. To further improve the computational efficiency and accuracy, two preclustering steps are implemented. To maintain clustering accuracy, all tags are grouped into an OTU depending on their pairwise Needleman-Wunsch distance. This method not only improved the computational efficiency but also mitigated the spurious OTU estimation from ‘noise’ sequences. In addition, OTUs clustered using TSC showed comparable or improved performance in beta-diversity comparisons compared to existing OTU selection methods. This study suggests that the distribution of sequencing datasets is a useful property for improving the computational efficiency and increasing the clustering accuracy of the high-throughput sequencing of PCR amplicons. The software and user guide are freely available at http://hwzhoulab.smu.edu.cn/paperdata/

Photosynthetic quantum efficiency in south‐eastern Amazonian trees may be already affected by climate change

Tropical forests are experiencing unprecedented high‐temperature conditions due to climate change that could limit their photosynthetic functions. We studied the high‐temperature sensitivity of photosynthesis in a rainforest site in southern Amazonia, where some of the highest temperatures and most rapid warming in the Tropics have been recorded. The quantum yield (F v /F m ) of photosystem II was measured in seven dominant tree species using leaf discs exposed to varying levels of heat stress. T 50 was calculated as the temperature at which F v /F m was half the maximum value. T 5 is defined as the breakpoint temperature, at which F v /F m decline was initiated. Leaf thermotolerance in the rapidly warming southern Amazonia was the highest recorded for forest tree species globally. T 50 and T 5 varied between species, with one mid‐storey species, Amaioua guianensis , exhibiting particularly high T 50 and T 5 values. While the T 50 values of the species sampled were several degrees above the maximum air temperatures experienced in southern Amazonia, the T 5 values of several species are now exceeded under present‐day maximum air temperatures

Slip-Sliding Away: Serial Changes and Homoplasy in Repeat Number in the Drosophila yakuba Homolog of Human Cancer Susceptibility Gene BRCA2

Several recent studies have examined the function and evolution of a Drosophila homolog to the human breast cancer susceptibility gene BRCA2, named dmbrca2. We previously identified what appeared to be a recent expansion in the RAD51-binding BRC-repeat array in the ancestor of Drosophila yakuba. In this study, we examine patterns of variation and evolution of the dmbrca2 BRC-repeat array within D. yakuba and its close relatives. We develop a model of how unequal crossing over may have produced the expanded form, but we also observe short repeat forms, typical of other species in the D. melanogaster group, segregating within D. yakuba and D. santomea. These short forms do not appear to be identical-by-descent, suggesting that the history of dmbrca2 in the D. melanogaster subgroup has involved repeat unit contractions resulting in homoplasious forms. We conclude that the evolutionary history of dmbrca2 in D. yakuba and perhaps in other Drosophila species may be more complicated than can be inferred from examination of the published single genome sequences per species

EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data

Recovery of ribosomal small subunit genes by assembly of short read community DNA sequence data generally fails, making taxonomic characterization difficult. Here, we solve this problem with a novel iterative method, based on the expectation maximization algorithm, that reconstructs full-length small subunit gene sequences and provides estimates of relative taxon abundances. We apply the method to natural and simulated microbial communities, and correctly recover community structure from known and previously unreported rRNA gene sequences. An implementation of the method is freely available at https://github.com/csmiller/EMIRGE

Deep Sequencing of the Vaginal Microbiota of Women with HIV

BACKGROUND: Women living with HIV and co-infected with bacterial vaginosis (BV) are at higher risk for transmitting HIV to a partner or newborn. It is poorly understood which bacterial communities constitute BV or the normal vaginal microbiota among this population and how the microbiota associated with BV responds to antibiotic treatment. METHODS AND FINDINGS: The vaginal microbiota of 132 HIV positive Tanzanian women, including 39 who received metronidazole treatment for BV, were profiled using Illumina to sequence the V6 region of the 16S rRNA gene. Of note, Gardnerella vaginalis and Lactobacillus iners were detected in each sample constituting core members of the vaginal microbiota. Eight major clusters were detected with relatively uniform microbiota compositions. Two clusters dominated by L. iners or L. crispatus were strongly associated with a normal microbiota. The L. crispatus dominated microbiota were associated with low pH, but when L. crispatus was not present, a large fraction of L. iners was required to predict a low pH. Four clusters were strongly associated with BV, and were dominated by Prevotella bivia, Lachnospiraceae, or a mixture of different species. Metronidazole treatment reduced the microbial diversity and perturbed the BV-associated microbiota, but rarely resulted in the establishment of a lactobacilli-dominated microbiota. CONCLUSIONS: Illumina based microbial profiling enabled high though-put analyses of microbial samples at a high phylogenetic resolution. The vaginal microbiota among women living with HIV in Sub-Saharan Africa constitutes several profiles associated with a normal microbiota or BV. Recurrence of BV frequently constitutes a different BV-associated profile than before antibiotic treatment

Coevolution of amino acid residues in the key photosynthetic enzyme Rubisco

<p>Abstract</p> <p>Background</p> <p>One of the key forces shaping proteins is coevolution of amino acid residues. Knowing which residues coevolve in a particular protein may facilitate our understanding of protein evolution, structure and function, and help to identify substitutions that may lead to desired changes in enzyme kinetics. Rubisco, the most abundant enzyme in biosphere, plays an essential role in the process of carbon fixation through photosynthesis, thus facilitating life on Earth. This makes Rubisco an important model system for studying the dynamics of protein fitness optimization on the evolutionary landscape. In this study we investigated the selective and coevolutionary forces acting on large subunit of land plants Rubisco using Markov models of codon substitution and clustering approaches applied to amino acid substitution histories.</p> <p>Results</p> <p>We found that both selection and coevolution shape Rubisco, and that positively selected and coevolving residues have their specifically favored amino acid composition and pairing preference. The mapping of these residues on the known Rubisco tertiary structures showed that the coevolving residues tend to be in closer proximity with each other compared to the background, while positively selected residues tend to be further away from each other. This study also reveals that the residues under positive selection or coevolutionary force are located within functionally important regions and that some residues are targets of both positive selection and coevolution at the same time.</p> <p>Conclusion</p> <p>Our results demonstrate that coevolution of residues is common in Rubisco of land plants and that there is an overlap between coevolving and positively selected residues. Knowledge of which Rubisco residues are coevolving and positively selected could be used for further work on structural modeling and identification of substitutions that may be changed in order to improve efficiency of this important enzyme in crops.</p

Cellular injury and neuroinflammation in children with chronic intractable epilepsy

<p>Abstract</p> <p>Objective</p> <p>To elucidate the presence and potential involvement of brain inflammation and cell death in neurological morbidity and intractable seizures in childhood epilepsy, we quantified cell death, astrocyte proliferation, microglial activation and cytokine release in brain tissue from patients who underwent epilepsy surgery.</p> <p>Methods</p> <p>Cortical tissue was collected from thirteen patients with intractable epilepsy due to focal cortical dysplasia (6), encephalomalacia (5), Rasmussen's encephalitis (1) or mesial temporal lobe epilepsy (1). Sections were processed for immunohistochemistry using markers for neuron, astrocyte, microglia or cellular injury. Cytokine assay was performed on frozen cortices. Controls were autopsy brains from eight patients without history of neurological diseases.</p> <p>Results</p> <p>Marked activation of microglia and astrocytes and diffuse cell death were observed in epileptogenic tissue. Numerous fibrillary astrocytes and their processes covered the entire cortex and converged on to blood vessels, neurons and microglia. An overwhelming number of neurons and astrocytes showed DNA fragmentation and its magnitude significantly correlated with seizure frequency. Majority of our patients with abundant cell death in the cortex have mental retardation. IL-1beta, IL-8, IL-12p70 and MIP-1beta were significantly increased in the epileptogenic cortex; IL-6 and MCP-1 were significantly higher in patients with family history of epilepsy.</p> <p>Conclusions</p> <p>Our results suggest that active neuroinflammation and marked cellular injury occur in pediatric epilepsy and may play a common pathogenic role or consequences in childhood epilepsy of diverse etiologies. Our findings support the concept that immunomodulation targeting activated microglia and astrocytes may be a novel therapeutic strategy to reduce neurological morbidity and prevent intractable epilepsy.</p

H2r: Identification of evolutionary important residues by means of an entropy based analysis of multiple sequence alignments

BACKGROUND: A multiple sequence alignment (MSA) generated for a protein can be used to characterise residues by means of a statistical analysis of single columns. In addition to the examination of individual positions, the investigation of co-variation of amino acid frequencies offers insights into function and evolution of the protein and residues. RESULTS: We introduce conn(k), a novel parameter for the characterisation of individual residues. For each residue k, conn(k) is the number of most extreme signals of co-evolution. These signals were deduced from a normalised mutual information (MI) value U(k, l) computed for all pairs of residues k, l. We demonstrate that conn(k) is a more robust indicator than an individual MI-value for the prediction of residues most plausibly important for the evolution of a protein. This proposition was inferred by means of statistical methods. It was further confirmed by the analysis of several proteins. A server, which computes conn(k)-values is available at http://www-bioinf.uni-regensburg.de. CONCLUSION: The algorithms H2r, which analyses MSAs and computes conn(k)-values, characterises a specific class of residues. In contrast to strictly conserved ones, these residues possess some flexibility in the composition of side chains. However, their allocation is sensibly balanced with several other positions, as indicated by conn(k)

Correlated Mutations: A Hallmark of Phenotypic Amino Acid Substitutions

Point mutations resulting in the substitution of a single amino acid can cause severe functional consequences, but can also be completely harmless. Understanding what determines the phenotypical impact is important both for planning targeted mutation experiments in the laboratory and for analyzing naturally occurring mutations found in patients. Common wisdom suggests using the extent of evolutionary conservation of a residue or a sequence motif as an indicator of its functional importance and thus vulnerability in case of mutation. In this work, we put forward the hypothesis that in addition to conservation, co-evolution of residues in a protein influences the likelihood of a residue to be functionally important and thus associated with disease. While the basic idea of a relation between co-evolution and functional sites has been explored before, we have conducted the first systematic and comprehensive analysis of point mutations causing disease in humans with respect to correlated mutations. We included 14,211 distinct positions with known disease-causing point mutations in 1,153 human proteins in our analysis. Our data show that (1) correlated positions are significantly more likely to be disease-associated than expected by chance, and that (2) this signal cannot be explained by conservation patterns of individual sequence positions. Although correlated residues have primarily been used to predict contact sites, our data are in agreement with previous observations that (3) many such correlations do not relate to physical contacts between amino acid residues. Access to our analysis results are provided at http://webclu.bio.wzw.tum.de/~pagel/supplements/correlated-positions/