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Circular DNA is ubiquitous in nature in the form of plasmids, circular DNA viruses, and extrachromosomal circular DNA (eccDNA) in eukaryotes. Sequencing of such molecules is essential to profiling virus distributions, discovering new viruses and understanding the roles of eccDNAs in eukaryotic cells. Circular DNA enrichment sequencing (CIDER-Seq) is a technique to enrich and accurately sequence circular DNA without the need for polymerase chain reaction amplification, cloning, and computational sequence assembly. The approach is based on randomly primed circular DNA amplification, which is followed by several enzymatic DNA repair steps and then by long-read sequencing. CIDER-Seq includes a custom data analysis package (CIDER-Seq Data Analysis Software 2) that implements the DeConcat algorithm to deconcatenate the long sequencing products of random circular DNA amplification into the intact sequences of the input circular DNA. The CIDER-Seq data analysis package can generate full-length annotated virus genomes, as well as circular DNA sequences of novel viruses. Applications of CIDER-Seq also include profiling of eccDNA molecules such as transposable elements (TEs) from biological samples. The method takes ~2 weeks to complete, depending on the computational resources available. Owing to the present constraints of long-read single-molecule sequencing, the accuracy of circular virus and eccDNA sequences generated by the CIDER-Seq method scales with sequence length, and the greatest accuracy is obtained for molecules <10 kb long. Size-selected and amplified circular DNA molecules are sequenced on the PacBio platform and processed with a custom pipeline, resulting in full-length annotated genomes of circular DNA viruses and sequences of extrachromosomal circular DNA at single-molecule resolution.

Background The gut is the most extensively studied niche of the human microbiome. The aim of this study was to characterise the initial gut microbiota development of a cohort of breastfed infants ( n  = 192) from 1 to 24 weeks of age. Methods V4-V5 region 16S rRNA amplicon Illumina sequencing and, in parallel, bacteriological culture. The metabolomic profile of infant urine at 4 weeks of age was also examined by LC-MS. Results Full-term (FT), spontaneous vaginally delivered (SVD) infants’ microbiota remained stable at both phylum and genus levels during the 24-week period examined. FT Caesarean section (CS) infants displayed an increased faecal abundance of Firmicutes ( p  < 0.01) and lower abundance of Actinobacteria ( p  < 0.001) after the first week of life compared to FT-SVD infants. FT-CS infants gradually progressed to harbouring a microbiota closely resembling FT-SVD (which remained stable) by week 8 of life, which was maintained at week 24. The gut microbiota of preterm (PT) infants displayed a significantly greater abundance of Proteobacteria compared to FT infants ( p  < 0.001) at week 1. Metabolomic analysis of urine at week 4 indicated PT-CS infants have a functionally different metabolite profile than FT (both CS and SVD) infants. Co-inertia analysis showed co-variation between the urine metabolome and the faecal microbiota of the infants. Tryptophan and tyrosine metabolic pathways, as well as fatty acid and bile acid metabolism, were found to be affected by delivery mode and gestational age. Conclusions These findings confirm that mode of delivery and gestational age both have significant effects on early neonatal microbiota composition. There is also a significant difference between the metabolite profile of FT and PT infants. Prolonged breastfeeding was shown to have a significant effect on the microbiota composition of FT-CS infants at 24 weeks of age, but interestingly not on that of FT-SVD infants. Twins had more similar microbiota to one another than between two random infants, reflecting the influence of similarities in both host genetics and the environment on the microbiota.

Breast cancer is characterised by genomic alterations. We did a multicentre molecular screening study to identify abnormalities in individual patients with the aim of providing targeted therapy matched to individuals' genomic alterations. From June 16, 2011, to July 30, 2012, we recruited patients who had breast cancer with a metastasis accessible for biopsy in 18 centres in France. Comparative genomic hybridisation (CGH) array and Sanger sequencing on PIK3CA (exon 10 and 21) and AKT1 (exon 4) were used to assess metastatic biopsy samples in five centres. Therapeutic targets were decided on the basis of identified genomic alterations. The primary objective was to include 30% of patients in clinical trials testing a targeted therapy and, therefore, the primary outcome was the proportion of patients to whom a targeted therapy could be offered. For the primary endpoint, the analyses were done on the overall population registered for the trial. This trial is registered with ClinicalTrials.gov, number NCT01414933. 423 patients were included, and biopsy samples were obtained from 407 (metastatic breast cancer was not found in four). CGH array and Sanger sequencing were feasible in 283 (67%) and 297 (70%) patients, respectively. A targetable genomic alteration was identified in 195 (46%) patients, most frequently in PIK3CA (74 [25%] of 297 identified genomic alterations), CCND1 (53 [19%]), and FGFR1 (36 [13%]). 117 (39%) of 297 patients with genomic tests available presented with rare genomic alterations (defined as occurring in less than 5% of the general population), including AKT1 mutations, and EGFR, MDM2, FGFR2, AKT2, IGF1R, and MET high-level amplifications. Therapy could be personalised in 55 (13%) of 423 patients. Of the 43 patients who were assessable and received targeted therapy, four (9%) had an objective response, and nine others (21%) had stable disease for more than 16 weeks. Serious (grade 3 or higher) adverse events related to biopsy were reported in four (1%) of enrolled patients, including pneumothorax (grade 3, one patient), pain (grade 3, one patient), haematoma (grade 3, one patient), and haemorrhagic shock (grade 3, one patient). Personalisation of medicine for metastatic breast cancer is feasible, including for rare genomic alterations. French National Cancer Institute, Breast Cancer Research Foundation, Odyssea, Operation Parrains Chercheurs.

We have found that intestinal bacteria and their metabolites, short‐chain fatty acids (SCFAs), promote cancer growth in prostate cancer (PCa) mouse models. To clarify the association between gut microbiota and PCa in humans, we analyzed the gut microbiota profiles of men with suspected PCa. One hundred and fifty‐two Japanese men undergoing prostate biopsies (96 with cancer and 56 without cancer) were included in the study and randomly divided into two cohorts: a discovery cohort (114 samples) and a test cohort (38 samples). The gut microbiota was compared between two groups, a high‐risk group (men with Grade group 2 or higher PCa) and a negative + low‐risk group (men with negative biopsy or Grade group 1 PCa), using 16S rRNA gene sequencing. The relative abundances of Rikenellaceae, Alistipes, and Lachnospira, all SCFA‐producing bacteria, were significantly increased in high‐risk group. In receiver operating characteristic curve analysis, the index calculated from the abundance of 18 bacterial genera which were selected by least absolute shrinkage and selection operator regression detected high‐risk PCa in the discovery cohort with higher accuracy than the prostate specific antigen test (area under the curve [AUC] = 0.85 vs 0.74). Validation of the index in the test cohort showed similar results (AUC = 0.81 vs 0.67). The specific bacterial taxa were associated with high‐risk PCa. The gut microbiota profile could be a novel useful marker for the detection of high‐risk PCa and could contribute to the carcinogenesis of PCa. To clarify the association between the gut microbiota and prostate cancer, we analyzed the gut microbiota profiles of 152 men undergoing prostate biopsy. The abundances of Rikenellaceae, Alistipes, and Lachnospira were significantly increased in men with high‐risk cancer. The index calculated from the abundance of 18 bacterial genera detected high‐risk cancer with higher accuracy than the prostate specific antigen test.

Background The rapid evolution of 454 GS-FLX sequencing technology has not been accompanied by a reassessment of the quality and accuracy of the sequences obtained. Current strategies for decision-making and error-correction are based on an initial analysis by Huse et al. in 2007, for the older GS20 system based on experimental sequences. We analyze here the quality of 454 sequencing data and identify factors playing a role in sequencing error, through the use of an extensive dataset for Roche control DNA fragments. Results We obtained a mean error rate for 454 sequences of 1.07%. More importantly, the error rate is not randomly distributed; it occasionally rose to more than 50% in certain positions, and its distribution was linked to several experimental variables. The main factors related to error are the presence of homopolymers, position in the sequence, size of the sequence and spatial localization in PT plates for insertion and deletion errors. These factors can be described by considering seven variables. No single variable can account for the error rate distribution, but most of the variation is explained by the combination of all seven variables. Conclusions The pattern identified here calls for the use of internal controls and error-correcting base callers, to correct for errors, when available (e.g. when sequencing amplicons). For shotgun libraries, the use of both sequencing primers and deep coverage, combined with the use of random sequencing primer sites should partly compensate for even high error rates, although it may prove more difficult than previous thought to distinguish between low-frequency alleles and errors.

Sequencing 16S rRNA gene fragments has become a fundamental tool for understanding the diversity of microbial communities and the factors that affect their diversity. Due to technical challenges, it is common to observe wide variation in the number of sequences that are collected from different samples within the same study. However, the diversity metrics used by microbial ecologists are sensitive to differences in sequencing effort. Therefore, tools are needed to control for the uneven levels of sequencing. This simulation-based analysis shows that despite a longstanding controversy, rarefaction is the most robust approach to control for uneven sequencing effort. The controversy started because of confusion over the definition of rarefaction and violation of assumptions that are made by methods that have been borrowed from other fields. Microbial ecologists should use rarefaction.

Introduction Molecular-matched therapies have revolutionized cancer treatment. We evaluated the improvement in clinical outcomes of applying an in-house customized Next Generation Sequencing panel in a single institution. Methods Patients with advanced solid tumors were molecularly selected to receive a molecular-matched treatment into early phase clinical trials versus best investigators choice, according to the evaluation of a multidisciplinary molecular tumor board. The primary endpoint was progression-free survival (PFS) assessed by the ratio of patients presenting 1.3-fold longer PFS on matched therapy (PFS2) than with prior therapy (PFS1). Results Of a total of 231 molecularly screened patients, 87 were eligible for analysis. Patients who received matched therapy had a higher median PFS2 (6.47 months; 95% CI, 2.24–14.43) compared to those who received standard therapy (2.76 months; 95% CI, 2.14–3.91, Log-rank p = 0.022). The proportion of patients with a PFS2/PFS1 ratio over 1.3 was significantly higher in the experimental arm (0.33 vs 0.08; p = 0.008). Discussion We demonstrate the pivotal role of the institutional molecular tumor board in evaluating the results of a customized NGS panel. This process optimizes the selection of available therapies, improving disease control. Prospective randomized trials are needed to confirm this approach and open the door to expanded drug access.

Cell identity is determined by the selective activation or silencing of specific genes via transcription factor binding and epigenetic modifications on the genome. Chromatin immunoprecipitation (ChIP) has been the standard technique for mapping the sites of transcription factor binding and histone modification. Recently, alternative methods to ChIP have been developed for addressing the increasing demands for low-input epigenomic profiling. Chromatin integration labeling (ChIL) followed by sequencing (ChIL-seq) has been demonstrated to be particularly useful for epigenomic profiling of low-input samples or even single cells because the technique amplifies the target genomic sequence before cell lysis. After labeling the target protein or modification in situ with an oligonucleotide-conjugated antibody (ChIL probe), the nearby genome sequence is amplified by Tn5 transposase-mediated transposition followed by T7 RNA polymerase-mediated transcription. ChIL-seq enables the detection of the antibody target localization under a fluorescence microscope and at the genomic level. Here we describe the detailed protocol of ChIL-seq with assessment methods for the key steps, including ChIL probe reaction, transposition, in situ transcription and sequencing library preparation. The protocol usually takes 3 d to prepare the sequencing library, including overnight incubations for the ChIL probe reaction and in situ transcription. The ChIL probe can be separately prepared and stored for several months, and its preparation and evaluation protocols are also documented in detail. An optional analysis for multiple targets (multitarget ChIL-seq) is also described. We anticipate that the protocol presented here will make the ChIL technique more widely accessible for analyzing precious samples and facilitate further applications. The authors describe detailed procedures for an epigenomic profiling method suitable for low-input samples that is based on in situ labeling with an oligonucleotide-conjugated antibody.

Protozoa have long been considered undesirable residents of the human gut, but recent findings suggest that some of them may positively affect the gut ecosystem. To better understand the role and ecological dynamics of these commensal and potentially beneficial protozoan symbionts, we need efficient methods to detect them, as well as accurate estimates of their prevalence across human populations. Metagenomics provides such an opportunity, allowing simultaneous detection of multiple symbionts in a single analytical procedure. In this study, we collected fecal samples of 68 individuals from three Cameroonian populations with different subsistence modes and compared metagenomics-based and targeted methods of detection for two common protozoan genera: Blastocystis and Entamoeba. In addition, we analyzed our data along with publicly available fecal metagenomes from various worldwide populations to explore the prevalence and association patterns of ten protozoan genera. Regarding the detection method, microscopy was much less sensitive than metagenomics for Entamoeba, whereas qPCR was at least as sensitive as metagenomics for Blastocystis sp. However, metagenomics was more likely to detect co-colonizations by multiple subtypes. Out of the ten examined genera in 127 individuals from Cameroon, Tanzania, Peru, Italy or USA, only three (Blastocystis, Entamoeba and Enteromonas) had an overall prevalence exceeding 10%. All three genera were more common in less industrialized populations and their prevalence differed between continents and subsistence modes, albeit not in a straightforward manner. The majority (72.5%) of colonized individuals carried at least two protozoan species, indicating that mixed-species colonizations are common. In addition, we detected only positive and no negative association patterns between different protozoa. Despite the pitfalls of the metagenomic approach, ranging from the availability of good-quality sequencing data to the lack of standard analytical procedures, we demonstrated its utility in simultaneous detection of multiple protozoan genera, and especially its ability to efficiently detect mixed-species colonizations. Our study corroborates and expands prevalence results previously obtained for Blastocystis sp. and provides novel data for Entamoeba spp. and several other protozoan genera. Furthermore, it indicates that multiple protozoa are common residents of the healthy human gut worldwide.