Here, we present the complete genome sequence of Actinomyces naeslundii strain ATCC 27039, isolated from an abdominal wound abscess. This strain is genetically transformable and will thus provide valuable information related to its crucial role in oral multispecies biofilm development. Copyright © 2016 Mashimo et al.
Borrelia mayonii, a Borrelia burgdorferi sensu lato (Bbsl) genospecies, was recently identified as a cause of Lyme borreliosis (LB) among patients from the upper midwestern United States. By microscopy and PCR, spirochete/genome loads in infected patients were estimated at 105 to 106 per milliliter of blood. Here, we present the full chromosome and plasmid sequences of two B. mayonii isolates, MN14-1420 and MN14-1539, cultured from blood of two of these patients. Whole genome sequencing and assembly was conducted using PacBio long read sequencing (Pacific Biosciences RSII instrument) followed by hierarchical genome-assembly process (HGAP). The B. mayonii genome is ~1.31 Mbp in size (26.9% average GC content) and is comprised of a linear chromosome, 8 linear and 7 circular plasmids. Consistent with its taxonomic designation as a new Bbsl genospecies, the B. mayonii linear chromosome shares only 93.83% average nucleotide identity with other genospecies. Both B. mayonii genomes contain plasmids similar to B. burgdorferi sensu stricto lp54, lp36, lp28-3, lp28-4, lp25, lp17, lp5, 5 cp32s, cp26, and cp9. The vls locus present on lp28-10 of B. mayonii MN14-1420 is remarkably long, being comprised of 24 silent vls cassettes. Genetic differences between the two B. mayonii genomes are limited and include 15 single nucleotide variations as well as 7 fewer silent vls cassettes and a lack of the lp5 plasmid in MN14-1539. Notably, 68 homologs to proteins present in B. burgdorferi sensu stricto appear to be lacking from the B. mayonii genomes. These include the complement inhibitor, CspZ (BB_H06), the fibronectin binding protein, BB_K32, as well as multiple lipoproteins and proteins of unknown function. This study shows the utility of long read sequencing for full genome assembly of Bbsl genomes, identifies putative genome regions of B. mayonii that may be linked to clinical manifestation or tissue tropism, and provides a valuable resource for pathogenicity, diagnostic and vaccine studies.
Escherichia coli serotype O25b:H4 is involved in human urinary tract infections.In this study, we sequenced and analyzed E. coli O25b:H4 isolated from a patient sufferingfrom recurring UTI infections in an intensive care unit at Hera General Hospital inMakkah, Saudi Arabia. We aimed to determine the virulence genes for pathogenesis anddrug resistance of this isolate compared to other E. coli strains. We sequenced and analyzedthe E. coli O25b:H4 Saudi strain clinical isolate using next generation sequencing. Usingthe ERGO genome analysis platform, we performed annotations and identified virulenceand antibiotic resistance determinants of this clinical isolate. The E. coli O25b:H4 genomewas assembled into four contigs representing a total chromosome size of 5.28 Mb, andthree contigs were identified, including a 130.9 kb (virulence plasmid) contig bearing thebla-CTX gene and 32 kb and 29 kb contigs. In comparing this genome to otheruropathogenic E. coli genomes, we identified unique drug resistance and pathogenicityfactors. In this work, whole-genome sequencing and targeted comparative analysis of aclinical isolate of uropathogenic Escherichia coli O25b:H4 was performed. This strainencodes virulence genes linked with extraintestinal pathogenic E. coli (ExPEC) that areexpressed constitutively in E. coli ST131. We identified the genes responsible forpathogenesis and drug resistance and performed comparative analyses of the virulenceand antibiotic resistance determinants with those of other E. coli UPEC isolates. This isthe first report of genome sequencing and analysis of a UPEC strain from Saudi Arabia.
With next-generation sequencing (NGS) technologies, the life sciences face a deluge of raw data. Classical analysis processes for such data often begin with an assembly step, needing large amounts of computing resources, and potentially removing or modifying parts of the biological information contained in the data. Our approach proposes to focus directly on biological questions, by considering raw unassembled NGS data, through a suite of six command-line tools.
In the estimation of repeat numbers in a short tandem repeat (STR) region from high-throughput sequencing data, two types of strategies are mainly taken: a strategy based on counting repeat patterns included in sequence reads spanning the region and a strategy based on estimating the difference between the actual insert size and the insert size inferred from paired-end reads. The quality of sequence alignment is crucial, especially in the former approaches although usual alignment methods have difficulty in STR regions due to insertions and deletions caused by the variations of repeat numbers.We proposed a new dynamic programming based realignment method named STR-realigner that considers repeat patterns in STR regions as prior knowledge. By allowing the size change of repeat patterns with low penalty in STR regions, accurate realignment is expected. For the performance evaluation, publicly available STR variant calling tools were applied to three types of aligned reads: synthetically generated sequencing reads aligned with BWA-MEM, those realigned with STR-realigner, those realigned with ReviSTER, and those realigned with GATK IndelRealigner. From the comparison of root mean squared errors between estimated and true STR region size, the results for the dataset realigned with STR-realigner are better than those for other cases. For real data analysis, we used a real sequencing dataset from Illumina HiSeq 2000 for a parent-offspring trio. RepeatSeq and lobSTR were applied to the sequence reads for these individuals aligned with BWA-MEM, those realigned with STR-realigner, ReviSTER, and GATK IndelRealigner. STR-realigner shows the best performance in terms of consistency of the size of estimated STR regions in Mendelian inheritance. Root mean squared error values were also calculated from the comparison of these estimated results with STR region sizes obtained from high coverage PacBio sequencing data, and the results from the realigned sequencing data with STR-realigner showed the least (the best) root mean squared error value.The effectiveness of the proposed realignment method for STR regions was verified from the comparison with an existing method on both simulation datasets and real whole genome sequencing dataset.
Genome assembly depends critically on read length. Two recent technologies, from Pacific Biosciences (PacBio) and Oxford Nanopore, produce read lengths >20 kb, which yield de novo genome assemblies with vastly greater contiguity than those based on Sanger, Illumina, or other technologies. However, the very high error rates of these two new technologies (~15% per base) makes assembly imprecise at repeats longer than the read length and computationally expensive. Here we show that the contiguity and quality of the assembly of these noisy long reads can be significantly improved at a minimal cost, by leveraging on the low error rate and low cost of Illumina short reads. Namely, k-mers from the PacBio raw reads that are not present in Illumina reads (which account for ~95% of the distinct k-mers) are deemed sequencing errors and ignored at the seed alignment step. By focusing on the ~5% of k-mers that are error free, read overlap sensitivity is dramatically increased. Of equal importance, the validation procedure can be extended to exclude repetitive k-mers, which prevents read miscorrection at repeats and further improves the resulting assemblies. We tested the k-mer validation procedure using one long-read technology (PacBio) and one assembler (MHAP/Celera Assembler), but it is very likely to yield analogous improvements with alternative long-read technologies and assemblers, such as Oxford Nanopore and BLASR/DALIGNER/Falcon, respectively.© 2016 Carvalho et al.; Published by Cold Spring Harbor Laboratory Press.
An inexpensive, magnetic thermoplastic nanomaterial is developed utilizing a hierarchical layering of micro- and nanoscale silica lamellae to create a high-surface-area and low-shear substrate capable of capturing vast amounts of ultrahigh-molecular-weight DNA. Extraction is performed via a simple 45 min process and is capable of achieving binding capacities up to 1 000 000 times greater than silica microparticles. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Single-molecule, real-time sequencing (SMRT) developed by Pacific BioSciences produces longer reads than secondary generation sequencing technologies such as Illumina. The long read length enables PacBio sequencing to close gaps in genome assembly, reveal structural variations, and identify gene isoforms with higher accuracy in transcriptomic sequencing. However, PacBio data has high sequencing error rate and most of the errors are insertion or deletion errors. During alignment-based homology search, insertion or deletion errors in genes will cause frameshifts and may only lead to marginal alignment scores and short alignments. As a result, it is hard to distinguish true alignments from random alignments and the ambiguity will incur errors in structural and functional annotation. Existing frameshift correction tools are designed for data with much lower error rate and are not optimized for PacBio data. As an increasing number of groups are using SMRT, there is an urgent need for dedicated homology search tools for PacBio data.In this work, we introduce Frame-Pro, a profile homology search tool for PacBio reads. Our tool corrects sequencing errors and also outputs the profile alignments of the corrected sequences against characterized protein families. We applied our tool to both simulated and real PacBio data. The results showed that our method enables more sensitive homology search, especially for PacBio data sets of low sequencing coverage. In addition, we can correct more errors when comparing with a popular error correction tool that does not rely on hybrid sequencing.The source code is freely available at https://sourceforge.net/projects/frame-pro/yannisun@msu.edu. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
In the context of third-generation long-read sequencing technologies, read-overlap-based approaches are expected to play a central role in the assembly step. A fundamental challenge in assembling from a read-overlap graph is that the true sequence corresponds to a Hamiltonian path on the graph, and, under most formulations, the assembly problem becomes NP-hard, restricting practical approaches to heuristics. In this work, we avoid this seemingly fundamental barrier by first setting the computational complexity issue aside, and seeking an algorithm that targets information limits In particular, we consider a basic feasibility question: when does the set of reads contain enough information to allow unambiguous reconstruction of the true sequence?Based on insights from this information feasibility question, we present an algorithm-the Not-So-Greedy algorithm-to construct a sparse read-overlap graph. Unlike most other assembly algorithms, Not-So-Greedy comes with a performance guarantee: whenever information feasibility conditions are satisfied, the algorithm reduces the assembly problem to an Eulerian path problem on the resulting graph, and can thus be solved in linear time. In practice, this theoretical guarantee translates into assemblies of higher quality. Evaluations on both simulated reads from real genomes and a PacBio Escherichia coli K12 dataset demonstrate that Not-So-Greedy compares favorably with standard string graph approaches in terms of accuracy of the resulting read-overlap graph and contig N50.Available at github.com/samhykim/nsgcourtade@eecs.berkeley.edu or dntse@stanford.eduSupplementary data are available at Bioinformatics online.© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Rapid development in sequencing technologies has dramatically improved our ability to detect genetic variants in human genome. However, current methods have variable sensitivities in detecting different types of genetic variants. One type of such genetic variants that is especially hard to detect is inversions. Analysis of public databases showed that few short inversions have been reported so far. Unlike reads that contain small insertions or deletions, which will be considered through gap alignment, reads carrying short inversions often have poor mapping quality or are unmapped, thus are often not further considered. As a result, the majority of short inversions might have been overlooked and require special algorithms for their detection.Here, we introduce SRinversion, a framework to analyze poorly mapped or unmapped reads by splitting and re-aligning them for the purpose of inversion detection. SRinversion is very sensitive to small inversions and can detect those less than 10?bp in size. We applied SRinversion to both simulated data and high-coverage sequencing data from the 1000 Genomes Project and compared the results with those from Pindel, BreakDancer, DELLY, Gustaf and MID. A better performance of SRinversion was achieved for both datasets for the detection of small inversions.SRinversion is implemented in Perl and is publicly available at http://paed.hku.hk/genome/software/SRinversion/index.html CONTACT: yangwl@hku.hkSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
We have developed a high-throughput sequencing approach that enables us to determine terminal telomere sequences from tens of thousands of individual Schizosaccharomyces pombe telomeres. This method provides unprecedented coverage of telomeric sequence complexity in fission yeast. S. pombe telomeres are composed of modular degenerate repeats that can be explained by variation in usage of the TER1 RNA template during reverse transcription. Taking advantage of this deep sequencing approach, we find that ‘like’ repeat modules are highly correlated within individual telomeres. Moreover, repeat module preference varies with telomere length, suggesting that existing repeats promote the incorporation of like repeats and/or that specific conformations of the telomerase holoenzyme efficiently and/or processively add repeats of like nature. After the loss of telomerase activity, this sequencing and analysis pipeline defines a population of telomeres with altered sequence content. This approach will be adaptable to study telomeric repeats in other organisms and also to interrogate repetitive sequences throughout the genome that are inaccessible to other sequencing methods.© 2016 Federation of European Biochemical Societies.
Second generation sequencing technologies paved the way to an exceptional increase in the number of sequenced genomes, both prokaryotic and eukaryotic. However, short reads are difficult to assemble and often lead to highly fragmented assemblies. The recent developments in long reads sequencing methods offer a promising way to address this issue. However, so far long reads are characterized by a high error rate, and assembling from long reads require a high depth of coverage. This motivates the development of hybrid approaches that leverage the high quality of short reads to correct errors in long reads.We introduce CoLoRMap, a hybrid method for correcting noisy long reads, such as the ones produced by PacBio sequencing technology, using high-quality Illumina paired-end reads mapped onto the long reads. Our algorithm is based on two novel ideas: using a classical shortest path algorithm to find a sequence of overlapping short reads that minimizes the edit score to a long read and extending corrected regions by local assembly of unmapped mates of mapped short reads. Our results on bacterial, fungal and insect data sets show that CoLoRMap compares well with existing hybrid correction methods.The source code of CoLoRMap is freely available for non-commercial use at https://github.com/sfu-compbio/colormapehaghshe@sfu.ca or cedric.chauve@sfu.caSupplementary data are available at Bioinformatics online.© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
The human microbiota and epigenetic processes have both been shown to play a crucial role in health and disease. However, there is extremely scarce information on epigenetic modulation of microbiota members except for a few pathogens. Mainly DNA adenine methylation has been described extensively in modulating the virulence of pathogenic bacteria in particular. It would thus appear likely that such mechanisms are widespread for most bacterial members of the microbiota. This review will present briefly the current knowledge on epigenetic processes in bacteria, give examples of known methylation processes in microbial members of the human microbiota and summarize the knowledge on regulation of host epigenetic processes by the human microbiota.
To investigate the potential evolutionary obstacles in the sustainable therapeutic use of plasmid-dependent phages to control the clinically important conjugative plasmid-mediated dissemination of antibiotic resistance genes to pathogenic bacteria.The lytic plasmid-dependent phage PRD1 and the multiresistance conferring plasmid RP4 in an Escherichia coli host were utilized to assess the genetic and phenotypic changes induced by combined phage and antibiotic selection.Resistance to PRD1 was always coupled with either completely lost or greatly reduced conjugation ability. Reversion to full conjugation efficiency was found to be rare, and it also restored the susceptibility to plasmid-dependent phages. Consequently, plasmid-dependent phages constitute an interesting candidate for development of sustainable anticonjugation/antiresistance therapeutic applications.
Protection against enteric infections, also termed colonization resistance, results from mutualistic interactions of the host and its indigenous microbes. The gut microbiota of humans and mice is highly diverse and it is therefore challenging to assign specific properties to its individual members. Here, we have used a collection of murine bacterial strains and a modular design approach to create a minimal bacterial community that, once established in germ-free mice, provided colonization resistance against the human enteric pathogen Salmonella enterica serovar Typhimurium (S. Tm). Initially, a community of 12 strains, termed Oligo-Mouse-Microbiota (Oligo-MM(12)), representing members of the major bacterial phyla in the murine gut, was selected. This community was stable over consecutive mouse generations and provided colonization resistance against S. Tm infection, albeit not to the degree of a conventional complex microbiota. Comparative (meta)genome analyses identified functions represented in a conventional microbiome but absent from the Oligo-MM(12). By genome-informed design, we created an improved version of the Oligo-MM community harbouring three facultative anaerobic bacteria from the mouse intestinal bacterial collection (miBC) that provided conventional-like colonization resistance. In conclusion, we have established a highly versatile experimental system that showed efficacy in an enteric infection model. Thus, in combination with exhaustive bacterial strain collections and systems-based approaches, genome-guided design can be used to generate insights into microbe-microbe and microbe-host interactions for the investigation of ecological and disease-relevant mechanisms in the intestine.
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