Rebecca N. Culver

Bio: Rebecca N. Culver is an academic researcher from Stanford University. The author has contributed to research in topics: Microbiome & Metagenomics. The author has an hindex of 3, co-authored 5 publications receiving 41 citations.

Strain-resolved microbiome sequencing reveals mobile elements that drive bacterial competition on a clinical timescale.

Abstract: Populations of closely related microbial strains can be simultaneously present in bacterial communities such as the human gut microbiome. We recently developed a de novo genome assembly approach that uses read cloud sequencing to provide more complete microbial genome drafts, enabling precise differentiation and tracking of strain-level dynamics across metagenomic samples. In this case study, we present a proof-of-concept using read cloud sequencing to describe bacterial strain diversity in the gut microbiome of one hematopoietic cell transplantation patient over a 2-month time course and highlight temporal strain variation of gut microbes during therapy. The treatment was accompanied by diet changes and administration of multiple immunosuppressants and antimicrobials. We conducted short-read and read cloud metagenomic sequencing of DNA extracted from four longitudinal stool samples collected during the course of treatment of one hematopoietic cell transplantation (HCT) patient. After applying read cloud metagenomic assembly to discover strain-level sequence variants in these complex microbiome samples, we performed metatranscriptomic analysis to investigate differential expression of antibiotic resistance genes. Finally, we validated predictions from the genomic and metatranscriptomic findings through in vitro antibiotic susceptibility testing and whole genome sequencing of isolates derived from the patient stool samples. During the 56-day longitudinal time course that was studied, the patient’s microbiome was profoundly disrupted and eventually dominated by Bacteroides caccae. Comparative analysis of B. caccae genomes obtained using read cloud sequencing together with metagenomic RNA sequencing allowed us to identify differences in substrain populations over time. Based on this, we predicted that particular mobile element integrations likely resulted in increased antibiotic resistance, which we further supported using in vitro antibiotic susceptibility testing. We find read cloud assembly to be useful in identifying key structural genomic strain variants within a metagenomic sample. These strains have fluctuating relative abundance over relatively short time periods in human microbiomes. We also find specific structural genomic variations that are associated with increased antibiotic resistance over the course of clinical treatment.

Strain-resolved microbiome sequencing reveals mobile elements that drive bacterial competition on a clinical timescale

Abstract: Although shotgun short-read sequencing has facilitated the study of strain-level architecture within complex microbial communities, existing metagenomic approaches often cannot capture structural differences between closely related co-occurring strains. Recent methods, which employ read cloud sequencing and specialized assembly techniques, provide significantly improved genome drafts and show potential to capture these strain-level differences. Here, we apply this read cloud metagenomic approach to longitudinal stool samples from a patient undergoing hematopoietic cell transplantation. The patient9s microbiome is profoundly disrupted and is eventually dominated by Bacteroides caccae. Comparative analysis of B. caccae genomes obtained using read cloud sequencing together with metagenomic RNA sequencing allows us to predict that particular mobile element integrations result in increased antibiotic resistance, which we further support using in vitro antibiotic susceptibility testing. Thus, we find read cloud sequencing to be useful in identifying strain-level differences that underlie differential fitness.

Rapid ordering of barcoded transposon insertion libraries of anaerobic bacteria

Abstract: Commensal bacteria from the human intestinal microbiota play important roles in health and disease. Research into the mechanisms by which these bacteria exert their effects is hampered by the complexity of the microbiota and by the strict growth requirements of the individual species. The assembly of ordered transposon insertion libraries, in which nearly all nonessential genes have been disrupted and the strains stored as independent monocultures, would be a transformative resource for research into many microbiota members. However, assembly of these libraries must be fast and inexpensive in order to empower investigation of the large number of species that typically compose gut communities. The methods used to generate ordered libraries must also be adapted to the anaerobic growth requirements of most intestinal bacteria. We have developed a protocol to assemble ordered libraries of transposon insertion mutants that is fast, cheap, and effective for even strict anaerobes. The protocol differs from currently available methods by making use of cell sorting to order the library and barcoded transposons to facilitate the localization of ordered mutations in the library. By tracking transposon insertions using barcode sequencing, our approach increases the accuracy and reduces the time and effort required to locate mutants in the library. Ordered libraries can be sorted and characterized over the course of two weeks using this approach. We expect this protocol will lower the barrier to generating comprehensive, ordered mutant libraries for many species in the human microbiota, allowing for new investigations into genotype-phenotype relationships within this important microbial ecosystem.

Rapid ordering of barcoded transposon insertion libraries of anaerobic bacteria

Abstract: Commensal bacteria from the human intestinal microbiota play important roles in health and disease. Research into the mechanisms by which these bacteria exert their effects is hampered by the complexity of the microbiota, the strict growth requirements of the individual species and a lack of genetic tools and resources. The assembly of ordered transposon insertion libraries, in which nearly all nonessential genes have been disrupted and the strains stored as independent monocultures, would be a transformative resource for research into many microbiota members. However, assembly of these libraries must be fast and inexpensive in order to empower investigation of the large number of species that typically compose gut communities. The methods used to generate ordered libraries must also be adapted to the anaerobic growth requirements of most intestinal bacteria. We have developed a protocol to assemble ordered libraries of transposon insertion mutants that is fast, cheap and effective for even strict anaerobes. The protocol differs from currently available methods by making use of cell sorting to order the library and barcoded transposons to facilitate the localization of ordered mutations in the library. By tracking transposon insertions using barcode sequencing, our approach increases the accuracy and reduces the time and effort required to locate mutants in the library. Ordered libraries can be sorted and characterized over the course of 2 weeks using this approach. We expect this protocol will lower the barrier to generating comprehensive, ordered mutant libraries for many species in the human microbiota, allowing for new investigations into genotype–phenotype relationships within this important microbial ecosystem. This protocol assembles ordered libraries of transposon insertion mutants, even for strict anaerobes. It uses cell sorting to order the library and tracks transposon insertions using barcode sequencing to locate individual mutant strains in the ordered library.

Colons or semi-colons: punctuating the regional variation of intestinal microbial-immune interactions.

Abstract: The microbial communities that occupy the intestinal tract are shaped by a variety of different factors, including the immune system. A new study has observed and quantified, at unprecedented depth, regionally distinct microbial and immune niches along the human colon using simultaneous analyses of the gut microbiota and neighbouring immune cells.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

Integrative Genomics Viewer

Abstract: Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

Examining horizontal gene transfer in microbial communities.

Abstract: Bacteria acquire novel DNA through horizontal gene transfer (HGT), a process that enables an organism to rapidly adapt to changing environmental conditions, provides a competitive edge and potentially alters its relationship with its host. Although the HGT process is routinely exploited in laboratories, there is a surprising disconnect between what we know from laboratory experiments and what we know from natural environments, such as the human gut microbiome. Owing to a suite of newly available computational algorithms and experimental approaches, we have a broader understanding of the genes that are being transferred and are starting to understand the ecology of HGT in natural microbial communities. This Review focuses on these new technologies, the questions they can address and their limitations. As these methods are applied more broadly, we are beginning to recognize the full extent of HGT possible within a microbiome and the punctuated dynamics of HGT, specifically in response to external stimuli. Furthermore, we are better characterizing the complex selective pressures on mobile genetic elements and the mechanisms by which they interact with the bacterial host genome.

Autometa: automated extraction of microbial genomes from individual shotgun metagenomes.

Abstract: Shotgun metagenomics is a powerful, high-resolution technique enabling the study of microbial communities in situ. However, species-level resolution is only achieved after a process of 'binning' where contigs predicted to originate from the same genome are clustered. Such culture-independent sequencing frequently unearths novel microbes, and so various methods have been devised for reference-free binning. As novel microbiomes of increasing complexity are explored, sometimes associated with non-model hosts, robust automated binning methods are required. Existing methods struggle with eukaryotic contamination and cannot handle highly complex single metagenomes. We therefore developed an automated binning pipeline, termed 'Autometa', to address these issues. This command-line application integrates sequence homology, nucleotide composition, coverage and the presence of single-copy marker genes to separate microbial genomes from non-model host genomes and other eukaryotic contaminants, before deconvoluting individual genomes from single metagenomes. The method is able to effectively separate over 1000 genomes from a metagenome, allowing the study of previously intractably complex environments at the level of single species. Autometa is freely available at https://bitbucket.org/jason_c_kwan/autometa and as a docker image at https://hub.docker.com/r/jasonkwan/autometa under the GNU Affero General Public License 3 (AGPL 3).