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We demonstrate on-chip, differential DNA and RNA extraction from a single cell using a microfluidic chip and a two-stage lysis protocol. This method enables direct use of the whole extract, without additional washing steps, reducing sample loss. Using this method, the tumor driving pathway in individual cells from a colorectal cancer cell line was determined by applying a Bayesian computational pathway model to sequences obtained from the RNA fraction of a single cell and, the mutations driving the pathway were determined by analyzing sequences obtained from the DNA fraction of the same single cell. This combined functional and mutational pathway assessment of a single cell could be of significant value for dissecting cellular heterogeneity in tumors and analyzing single circulating tumor cells.

To elucidate cellular diversity and clonal evolution in tissues and tumors, one must resolve genomic heterogeneity in single cells. To this end, we have developed low-cost, mass-producible micro-/nanofluidic chips for DNA extraction from individual cells. These chips have modules that collect genomic DNA for sequencing or map genomic structure directly, on-chip, with denaturation-renaturation (D-R) optical mapping [Marie R, et al. (2013) Proc Natl Acad Sci USA 110:4893-4898]. Processing of single cells from the LS174T colorectal cancer cell line showed that D-R mapping of single molecules can reveal structural variation (SV) in the genome of single cells. In one experiment, we processed 17 fragments covering 19.8 Mb of the cell's genome. One megabase-large fragment aligned well to chromosome 19 with half its length, while the other half showed variable alignment. Paired-end single-cell sequencing supported this finding, revealing a region of complexity and a 50-kb deletion. Sequencing struggled, however, to detect a 20-kb gap that D-R mapping showed clearly in a megabase fragment that otherwise mapped well to the reference at the pericentromeric region of chromosome 4. Pericentromeric regions are complex and show substantial sequence homology between different chromosomes, making mapping of sequence reads ambiguous. Thus, D-R mapping directly, from a single molecule, revealed characteristics of the single-cell genome that were challenging for short-read sequencing.

Background: Lung transplantation (LT) is a recognized treatment for end-stage pulmonary disease. Bacteria from the recipient nasopharynx seed the new lungs leading to infections and allograft damage. Understanding the characteristics and topological variations of the microbiota may be important to apprehend the pathophysiology of allograft dysfunction. Objectives: To examine the characteristics and relationship of bacterial compositions between conducting and respiratory zones of the allograft. Methods: We performed 16S rRNA gene sequencing on bronchial aspirates (BAs) and bronchoalveolar lavages (BALs) collected in pairs in 19 patients at several time-points post-LT. Results: The respiratory zone was characterized independently of the time post-LT by a higher bacterial richness than the conducting zone (p = 0.041). The phyla Firmicutes and Proteobacteria dominated both sampling zones, with an inverse correlation between these two phyla (Spearman r = -0.830). Samples of the same pair, as well as pairs from the same individual clustered together (Pseudo-F = 3.8652, p < 0.01). Microbiota of BA and BAL were more closely related in samples from the same patient than each sample type across different patients, with variation in community structure being mainly inter-individual (p < 0.01). Both number of antibiotics administered (p < 0.01) and time interval post-LT (p < 0.01) contributed to the variation in global microbiota structure. Longitudinal analysis of BA-BAL pairs of two patients showed dynamic wave like fluctuations of the microbiota. Conclusions: Our results show that post-transplant respiratory zones harbor higher bacterial richness, but overall similar bacterial profiles as compared to conductive zones. They further support an individual microbial signature following LT.

In eukaryotes, diverse small RNA (sRNA) populations including miRNAs, siRNAs and piRNAs regulate gene expression and repress transposons, transgenes and viruses. Functional sRNAs are associated with effector proteins based on their size and nucleotide composition. The sRNA populations are currently analyzed by deep sequencing that generates millions of reads which are then mapped to a reference sequence or database. Here we developed a tool called MISIS to view and analyze sRNA maps of genomic loci and viruses which spawn multiple sRNAs. MISIS displays sRNA reads as a histogram where the x-axis indicates positions of the 5'- or 3'-terminal nucleotide of sense and antisense sRNAs, respectively, along a given reference sequence or its selected region and the y-axis the number of reads starting (for sense sRNA) or ending (for antisense sRNA) at each position. Size-classes of sRNAs can be visualized and compared separately or in combination. Thus, MISIS gives an overview of sRNA distribution along the reference sequence as well as detailed information on single sRNA species of different size-classes and abundances. MISIS reads standard BAM/SAM files outputted by mapping tools and generates table files containing counts of sRNA reads at each position of the reference sequence forward and reverse strand and for each of the chosen size-classes of sRNAs. These table files can be used by other tools such as Excel for further quantitative analysis and visualization. MISIS is a Java standalone program. It is freely available along with the source code at the following website: http://www.fasteris.com/apps.

Toxic metals polluting aquatic ecosystems are taken up by inhabitants and accumulate in the food web, affecting species at all trophic levels. It is therefore important to have good tools to assess the level of risk represented by toxic metals in the environment. Macrophytes are potential organisms for the identification of metal-responsive biomarkers but are still underrepresented in ecotoxicology. In the present study, we used next-generation sequencing to investigate the transcriptomic response of Elodea nuttallii exposed to enhanced concentrations of Hg and Cd. We de novo assembled more than 60 000 contigs, of which we found 170 to be regulated dose-dependently by Hg and 212 by Cd. Functional analysis showed that these genes were notably related to energy and metal homeostasis. Expression analysis using nCounter of a subset of genes showed that the gene expression pattern was able to assess toxic metal exposure in complex environmental samples and was more sensitive than other end points (e.g., bioaccumulation, photosynthesis, etc.). In conclusion, we demonstrate the feasibility of using gene expression signatures for the assessment of environmental contamination, using an organism without previous genetic information. This is of interest to ecotoxicology in a wider sense given the possibility to develop specific and sensitive bioassays.

Recently developed genomics tools have a promising potential to identify early biomarkers of exposure to toxicants. In the present work we used transcriptome analysis (RNA-seq) of Elodea nuttallii –an invasive rooted macrophyte that is able to accumulate large amounts of metals- to identify biomarkers of Hg exposure. RNA-seq allowed identification of genes affected by Hg exposure and also unraveled plant response to the toxic metal: a change in energy/reserve metabolism caused by the inhibition of photosynthesis, and an adaptation of homeostasis networks to control accumulation of Hg. Data were validated by RT-qPCR and selected genes were further tested as biomarkers. Samples exposed in the field and to natural contaminated sediments clustered well with samples exposed to low metal concentrations under laboratory conditions. Our data suggest that this plant and/or this approach could be useful to develop new tests for water and sediment quality assessment.

International audience; Deep-sea floors represent one of the largest and most complex ecosystems on Earth but remain essentially unexplored. The vastness and remoteness of this ecosystem make deep-sea sampling difficult, hampering traditional taxonomic observations and diversity assessment. This problem is particularly true in the case of the deep-sea meiofauna, which largely comprises small-sized, fragile , and difficult-to-identify metazoans and protists. Here, we introduce an ultra-deep sequencing-based metagenetic approach to examine the richness of benthic foraminifera, a principal component of deep-sea meiofauna. We used Illumina sequencing technology to assess foraminiferal richness in 31 unsieved deep-sea sediment samples from five distinct oceanic regions. We sequenced an extremely short fragment (36 bases) of the small subunit ribo-somal DNA hypervariable region 37f, which has been shown to accurately distinguish foraminiferal species. In total, we obtained 495,978 unique sequences that were grouped into 1,643 operational taxonomic units, of which about half (841) could be reliably assigned to foraminifera. The vast majority of the operational tax-onomic units (nearly 90%) were either assigned to early (ancient) lineages of soft-walled, single-chambered (monothalamous) fora-minifera or remained undetermined and yet possibly belong to unknown early lineages. Contrasting with the classical view of multichambered taxa dominating foraminiferal assemblages, our work reflects an unexpected diversity of monothalamous lineages that are as yet unknown using conventional micropaleontological observations. Although we can only speculate about their morphology , the immense richness of deep-sea phylotypes revealed by this study suggests that ultra-deep sequencing can improve understanding of deep-sea benthic diversity considered until now as unknowable based on a traditional taxonomic approach.

Trans-splicing of leader sequences onto the 5′ends of mRNAs is a widespread phenomenon in protozoa, nematodes and some chordates. Using parallel sequencing we have developed a method to simultaneously map 5′splice sites and analyze the corresponding gene expression profile, that we term spliced leader trapping (SLT). The method can be applied to any organism with a sequenced genome and trans-splicing of a conserved leader sequence. We analyzed the expression profiles and splicing patterns of bloodstream and insect forms of the parasite Trypanosoma brucei. We detected the 5′ splice sites of 85% of the annotated protein-coding genes and, contrary to previous reports, found up to 40% of transcripts to be differentially expressed. Furthermore, we discovered more than 2500 alternative splicing events, many of which appear to be stage-regulated. Based on our findings we hypothesize that alternatively spliced transcripts present a new means of regulating gene expression and could potentially contribute to protein diversity in the parasite. The entire dataset can be accessed online at TriTrypDB or through: http://splicer.unibe.ch/., Author Summary Some organisms like the human and animal parasite Trypanosoma brucei add a leader sequence to their mRNAs through a reaction called trans-splicing. Until now the splice sites for most mRNAs were unknown in T. brucei. Using high throughput sequencing we have developed a method to identify the splice sites and at the same time measure the abundance of the corresponding mRNAs. Analyzing three different life cycle stages of the parasite we identified the vast majority of splice sites in the organism and, to our great surprise, uncovered more than 2500 alternative splicing events, many of which appeared to be specific for one of the life cycle stages. Alternative splicing is a result of the addition of the leader sequence to different positions on the mRNA, leading to mixed mRNA populations that can encode for proteins with varying properties. One of the most obvious changes caused by alternative splicing is the gain or loss of targeting signals, leading to differential localization of the corresponding proteins. Based on our findings we hypothesize that alternative splicing is a major mechanism to regulate gene expression in T. brucei and could contribute to protein diversity in the parasite.

In recent years, unprecedented DNA sequencing capacity provided by next generation sequencing (NGS) has revolutionized genomic research. Combining the Illumina sequencing platform and a scFv library designed to confine diversity to both CDR3, >1.9 × 10(7) sequences have been generated. This approach allowed for in depth analysis of the library's diversity, provided sequence information on virtually all scFv during selection for binding to two targets and a global view of these enrichment processes. Using the most frequent heavy chain CDR3 sequences, primers were designed to rescue scFv from the third selection round. Identification, based on sequence frequency, retrieved the most potent scFv and valuable candidates that were missed using classical in vitro screening. Thus, by combining NGS with display technologies, laborious and time consuming upfront screening can be by-passed or complemented and valuable insights into the selection process can be obtained to improve library design and understanding of antibody repertoires.