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June 1, 2021  |  

SMRT Sequencing of whole mitochondrial genomes and its utility in association studies of metabolic disease.

In this study we demonstrate the utility of Single-Molecule Real Time SMRT sequencing to detect variants and to recapitulate whole mitochondrial genomes in an association study of Metabolic syndrome using samples from a well-studied cohort from Micronesia. The Micronesian island of Kosrae is a rare genetic isolate that offers significant advantages for genetic studies of human disease. Kosrae suffers from one of the highest rates of MetS (41%), obesity (52%), and diabetes (17%) globally and has a homogeneous environment making this an excellent population in which to study these significant health problems. We are conducting family-based association analyses aimed at identifying specific mitochondrial variants that contribute to obesity and other co-morbid conditions. We sequenced whole mitochondrial genomes from 10 Kosraen individuals who represent greater than 25 % of the mitochondrial genetic diversity for the entire Kosraen population. Using Pacific Biosciences C2 chemistry, SMRTbell libraries were constructed from pooled, full-length, unsheared 5 kb PCR amplicons, tiling the entire 16.6 kb mtDNA genome. Average read lengths for each sample were between 2500-3000 bp, with 5% of reads between 6,000-8,000 bases, depending on movie lengths. The data generated in this study serve as proof of principle that SMRT Sequencing data can be utilized for identification of high-quality variants and complete mitochondrial genome sequences. These data will be leveraged to identify causative variants for Metabolic syndrome and associated disorders.


June 1, 2021  |  

Comparative genomics of Shiga toxin-producing Escherichia coli O145:H28 strains associated with the 2007 Belgium and 2010 US outbreaks.

Shiga toxin-producing Escherichia coli (STEC) is an emerging pathogen. Recently there has been a global in the number of outbreaks caused by non-O157 STECs, typically involving six serogroups O26, O45, 0103, 0111, and 0145. STEC O145:H28 has been associated with severe human disease including hemolytic-uremic syndrome (HUS), and is demonstrated by the 2007 Belgian ice-cream-associated outbreak and 2010 US lettuce-associated outbreak, with over 10% of patients developing HUS in each. The goal of this work was to do comparative genomics of strains, clinical and environmental, to investigate genome diversity and virulence evolution of this important foodborne pathogen.


June 1, 2021  |  

Complete HIV-1 genomes from single molecules: Diversity estimates in two linked transmission pairs using clustering and mutual information.

We sequenced complete HIV-1 genomes from single molecules using Single Molecule, Real- Time (SMRT) Sequencing and derive de novo full-length genome sequences. SMRT sequencing yields long-read sequencing results from individual DNA molecules with a rapid time-to-result. These attributes make it a useful tool for continuous monitoring of viral populations. The single-molecule nature of the sequencing method allows us to estimate variant subspecies and relative abundances by counting methods. We detail mathematical techniques used in viral variant subspecies identification including clustering distance metrics and mutual information. Sequencing was performed in order to better understand the relationships between the specific sequences of transmitted viruses in linked transmission pairs. Samples representing HIV transmission pairs were selected from the Zambia Emory HIV Research Project (Lusaka, Zambia) and sequenced. We examine Single Genome Amplification (SGA) prepped samples and samples containing complex mixtures of genomes. Whole genome consensus estimates for each of the samples were made. Genome reads were clustered using a simple distance metric on aligned reads. Appropriate thresholds were chosen to yield distinct clusters of HIV genomes within samples. Mutual information between columns in the genome alignments was used to measure dependence. In silico mixtures of reads from the SGA samples were made to simulate samples containing exactly controlled complex mixtures of genomes and our clustering methods were applied to these complex mixtures. SMRT Sequencing data contained multiple full-length (greater than 9 kb) continuous reads for each sample. Simple whole genome consensus estimates easily identified transmission pairs. The clustering of the genome reads showed diversity differences between the samples, allowing us to characterize the diversity of the individual quasi-species comprising the patient viral populations across the full genome. Mutual information identified possible dependencies of different positions across the full HIV-1 genome. The SGA consensus genomes agreed with prior Sanger sequencing. Our clustering methods correctly segregated reads to their correct originating genome for the synthetic SGA mixtures. The results open up the potential for reference-agnostic and cost effective full genome sequencing of HIV-1.


June 1, 2021  |  

Advances in sequence consensus and clustering algorithms for effective de novo assembly and haplotyping applications.

One of the major applications of DNA sequencing technology is to bring together information that is distant in sequence space so that understanding genome structure and function becomes easier on a large scale. The Single Molecule Real Time (SMRT) Sequencing platform provides direct sequencing data that can span several thousand bases to tens of thousands of bases in a high-throughput fashion. In contrast to solving genomic puzzles by patching together smaller piece of information, long sequence reads can decrease potential computation complexity by reducing combinatorial factors significantly. We demonstrate algorithmic approaches to construct accurate consensus when the differences between reads are dominated by insertions and deletions. High-performance implementations of such algorithms allow more efficient de novo assembly with a pre-assembly step that generates highly accurate, consensus-based reads which can be used as input for existing genome assemblers. In contrast to recent hybrid assembly approach, only a single ~10 kb or longer SMRTbell library is necessary for the hierarchical genome assembly process (HGAP). Meanwhile, with a sensitive read-clustering algorithm with the consensus algorithms, one is able to discern haplotypes that differ by less than 1% different from each other over a large region. One of the related applications is to generate accurate haplotype sequences for HLA loci. Long sequence reads that can cover the whole 3 kb to 4 kb diploid genomic regions will simplify the haplotyping process. These algorithms can also be applied to resolve individual populations within mixed pools of DNA molecules that are similar to each, e.g., by sequencing viral quasi-species samples.


June 1, 2021  |  

Automated, non-hybrid de novo genome assemblies and epigenomes of bacterial pathogens.

Understanding the genetic basis of infectious diseases is critical to enacting effective treatments, and several large-scale sequencing initiatives are underway to collect this information. Sequencing bacterial samples is typically performed by mapping sequence reads against genomes of known reference strains. While such resequencing informs on the spectrum of single-nucleotide differences relative to the chosen reference, it can miss numerous other forms of variation known to influence pathogenicity: structural variations (duplications, inversions), acquisition of mobile elements (phages, plasmids), homonucleotide length variation causing phase variation, and epigenetic marks (methylation, phosphorothioation) that influence gene expression to switch bacteria from non- pathogenic to pathogenic states. Therefore, sequencing methods which provide complete, de novo genome assemblies and epigenomes are necessary to fully characterize infectious disease agents in an unbiased, hypothesis-free manner. Hybrid assembly methods have been described that combine long sequence reads from SMRT DNA Sequencing with short reads (SMRT CCS (circular consensus) or second-generation reads), wherein the short reads are used to error-correct the long reads which are then used for assembly. We have developed a new paradigm for microbial de novo assemblies in which SMRT sequencing reads from a single long insert library are used exclusively to close the genome through a hierarchical genome assembly process, thereby obviating the need for a second sample preparation, sequencing run, and data set. We have applied this method to achieve closed de novo genomes with accuracies exceeding QV50 (>99.999%) for numerous disease outbreak samples, including E. coli, Salmonella, Campylobacter, Listeria, Neisseria, and H. pylori. The kinetic information from the same SMRT Sequencing reads is utilized to determine epigenomes. Approximately 70% of all methyltransferase specificities we have determined to date represent previously unknown bacterial epigenetic signatures. With relatively short sequencing run times and automated analysis pipelines, it is possible to go from an unknown DNA sample to its complete de novo genome and epigenome in about a day.


June 1, 2021  |  

Automated, non-hybrid de novo genome assemblies and epigenomes of bacterial pathogens

Understanding the genetic basis of infectious diseases is critical to enacting effective treatments, and several large-scale sequencing initiatives are underway to collect this information. Sequencing bacterial samples is typically performed by mapping sequence reads against genomes of known reference strains. While such resequencing informs on the spectrum of single nucleotide differences relative to the chosen reference, it can miss numerous other forms of variation known to influence pathogenicity: structural variations (duplications, inversions), acquisition of mobile elements (phages, plasmids), homonucleotide length variation causing phase variation, and epigenetic marks (methylation, phosphorothioation) that influence gene expression to switch bacteria from non-pathogenic to pathogenic states. Therefore, sequencing methods which provide complete, de novo genome assemblies and epigenomes are necessary to fully characterize infectious disease agents in an unbiased, hypothesis-free manner. Hybrid assembly methods have been described that combine long sequence reads from SMRT DNA sequencing with short, high-accuracy reads (SMRT (circular consensus sequencing) CCS or second-generation reads) to generate long, highly accurate reads that are then used for assembly. We have developed a new paradigm for microbial de novo assemblies in which long SMRT sequencing reads (average readlengths >5,000 bases) are used exclusively to close the genome through a hierarchical genome assembly process, thereby obviating the need for a second sample preparation, sequencing run and data set. We have applied this method to achieve closed de novo genomes with accuracies exceeding QV50 (>99.999%) to numerous disease outbreak samples, including E. coli, Salmonella, Campylobacter, Listeria, Neisseria, and H. pylori. The kinetic information from the same SMRT sequencing reads is utilized to determine epigenomes. Approximately 70% of all methyltransferase specificities we have determined to date represent previously unknown bacterial epigenetic signatures. The process has been automated and requires less than 1 day from an unknown DNA sample to its complete de novo genome and epigenome.


June 1, 2021  |  

Rapid sequencing of HIV-1 genomes as single molecules from simple and complex samples.

Background: To better understand the relationships among HIV-1 viruses in linked transmission pairs, we sequenced several samples representing HIV transmission pairs from the Zambia Emory HIV Research Project (Lusaka, Zambia) using Single Molecule, Real-Time (SMRT) Sequencing. Methods: Single molecules were sequenced as full-length (9.6 kb) amplicons directly from PCR products without shearing. This resulted in multiple, fully-phased, complete HIV-1 genomes for each patient. We examined Single Genome Amplification (SGA) prepped samples, as well as samples containing complex mixtures of genomes. We detail mathematical techniques used in viral variant subspecies identification, including clustering distance metrics and mutual information, which were used to derive multiple de novo full-length genome sequences for each patient. Whole genome consensus estimates for each sample were made. Genome reads were clustered using a simple distance metric on aligned reads. Appropriate thresholds were chosen to yield distinct clusters of HIV-1 genomes within samples. Mutual information between columns in the genome alignments was used to measure dependence. In silico mixtures of reads from the SGA samples were made to simulate samples containing exactly controlled complex mixtures of genomes and our clustering methods were applied to these complex mixtures. Results: SMRT Sequencing data contained multiple full-length (>9 kb) continuous reads for each sample. Simple whole-genome consensus estimates easily identified transmission pairs. Clustering of genome reads showed diversity differences between samples, allowing characterization of the quasi-species diversity comprising the patient viral populations across the full genome. Mutual information identified possible dependencies of different positions across the full HIV-1 genome. The SGA consensus genomes agreed with prior Sanger sequencing. Our clustering methods correctly segregated reads to their correct originating genome for the synthetic SGA mixtures. Conclusions: SMRT Sequencing yields long-read sequencing results from individual DNA molecules with a rapid time-to-result. These attributes make it a useful tool for continuous monitoring of viral populations. The single-molecule nature of the sequencing method allows us to estimate variant subspecies and relative abundances by counting methods. The results open up the potential for reference-agnostic and cost effective full genome sequencing of HIV-1.


June 1, 2021  |  

Using whole exome sequencing and bacterial pathogen sequencing to investigate the genetic basis of pulmonary non-tuberculous mycobacterial infections.

Pulmonary non-tuberculous mycobacterial (PNTM) infections occur in patients with chronic lung disease, but also in a distinct group of elderly women without lung defects who share a common body morphology: tall and lean with scoliosis, pectus excavatum, and mitral valve prolapse. In order to characterize the human host susceptibility to PNTM, we performed whole exome sequencing (WES) of 44 individuals in extended families of patients with active PNTM as well as 55 additional unrelated individuals with PNTM. This unique collection of familial cohorts in PNTM represents an important opportunity for a high yield search for genes that regulate mucosal immunity. An average of 58 million 100bp paired-end Illumina reads per exome were generated and mapped to the hg19 reference genome. Following variant detection and classification, we identified 58,422 potentially high-impact SNPs, 97.3% of which were missense mutations. Segregating variants using the family pedigrees as well as comparisons to the unrelated individuals identified multiple potential variants associated with PNTM. Validations of these candidate variants in a larger PNTM cohort are underway. In addition to WES, we sequenced the genomes of 52 mycobacterial isolates, including 9 from these PNTM patients, to integrate host PNTM susceptibility with mycobacterial genotypes and gain insights into the key factors involved in this devastating disease. These genomes were sequenced using a combination of 454, Illumina, and PacBio platforms and assembled using multiple genome assemblers. The resulting genome sequences were used to identify mycobacterial genotypes associated with virulence, invasion, and drug resistance.


June 1, 2021  |  

New discoveries from closing Salmonella genomes using Pacific Biosciences continuous long reads.

The newer hierarchical genome assembly process (HGAP) performs de novo assembly using data from a single PacBio long insert library. To assess the benefits of this method, DNA from several Salmonella enterica serovars was isolated from a pure culture. Genome sequencing was performed using Pacific Biosciences RS sequencing technology. The HGAP process enabled us to close sixteen Salmonella subsp. enterica genomes and their associated mobile elements: The ten serotypes include: Salmonella enterica subsp. enterica serovar Enteritidis (S. Enteritidis) S. Bareilly, S. Heidelberg, S. Cubana, S. Javiana and S. Typhimurium, S. Newport, S. Montevideo, S. Agona, and S. Tennessee. In addition, we were able to detect novel methyltransferases (MTases) by using the Pacific Biosciences kinetic score distributions showing that each serovar appears to have a novel methylation pattern. For example while all Salmonella serovars examined so far have methylase specific activity for 5’-GATC-3’/3’-CTAG-5’ and 5’-CAGAG-3’/3’-GTCTC-5’ (underlined base indicates a modification), S. Heidelberg is uniquely specific for 5’-ACCANCC-3’/3’-TGGTNGG-5’, while S. Typhimurium has uniquely methylase specific for 5′-GATCAG-3’/3′- CTAGTC-5′ sites, for the samples examined so far. We believe that this may be due to the unique environments and phages that these serotypes have been exposed to. Furthermore, our analysis identified and closed a variety of plasmids such as mobilization plasmids, antimicrobial resistance plasmids and IncX plasmids carrying a Type IV secretion system (T4SS). The VirB/D4 T4SS apparatus is important in that it assists with rapid dissemination of antibiotic resistance and virulence determinants. Presently, only limited information exists regarding the genotypic characterization of drug resistance in S. Heidelberg isolates derived from various host species. Here, we characterize two S. Heidelberg outbreak isolates from two different outbreaks. Both isolates contain the IncX plasmid of approximately 35 kb, and carried the genes virB1, virB2, virB3/4, virB5, virB6, virB7, virB8, virB9, virB10, virB11, virD2, and virD4, that are associated with the T4SS. In addition, the outbreak isolate associated with ground turkey carries a 4,473 bp mobilization plasmid and an incompatibility group (Inc) I1 antimicrobial resistance plasmid encoding resistance to gentamicin (aacC2), beta-lactam (bl2b_tem), streptomycin (aadAI) and tetracycline (tetA, tetR) while the outbreak isolate associated with chicken breast carries the IncI1 plasmid encoding resistance to gentamicin (aacC2), streptomycin (aadAI) and sulfisoxazole (sul1). Using this new technology we explored the genetic elements present in resistant pathogens which will achieve a better understanding of the evolution of Salmonella.


June 1, 2021  |  

Characterization of NNRTI mutations in HIV-1 RT using Single Molecule, Real-Time SMRT Sequencing.

Background: Genotypic testing of chronic viral infections is an important part of patient therapy and requires assays capable of detecting the entire spectrum of viral mutations. Single Molecule, Real-Time (SMRT) sequencing offers several advantages to other sequencing technologies, including superior resolution of mixed populations and long read lengths capable of spanning entire viral protein coding regions. We examined detection sensitivity of SMRT sequencing using a mixture of HIV-1 RT gene coding regions containing single NNRTI mutations. Methodology: SMRTbell templates were prepared from PCR products generated from a prospective reference material being developed by BC Center of Excellence for HIV/AIDS, and contained a mixture of fifteen infectious viruses containing single NNRTI resistance mutations (viz V90I, K101E, K103N, V108I, E138A/G/K/Q, V179D, Y181C, Y188C, G190A/S, M230L and P236L) built upon the HIV-1LAI molecular clone. Templates were sequenced on the PacBio RS II to obtain single molecule long reads using P4/C2 chemistry, using 180 minute movie collection without stage start. The relative abundances of the mutant viruses were then estimated using codon-aware analysis methods. Results: Sequencing of these templates produced average read lengths of 5.0 KB, comprising 40,000-fold coverage across the entire amplicon per SMRT Cell. All the expected mutations in the mixture of mutant viruses were accurately identified. Frequencies of NNRTI variants estimated ranged from 0.5% to 12.5%. Conclusions: Codon analysis revealed a number of variants across the amplicon with highly consistent results across SMRT Cells. From a single SMRT Cell, variants were accurately and reliably detected down to 0.5% with simple analyses. Long polymerase reads and high accuracy reads make it possible to call variants from just a few molecules. SMRT Sequencing can identify species comprising a mixed viral population, with granularity and low cost of consumables allowing for smaller multiplexing of samples and first-in-first-out processing.


June 1, 2021  |  

Next generation sequencing of full-length HIV-1 env during primary infection.

Background: The use of next generation sequencing (NGS) to examine circulating HIV env variants has been limited due to env’s length (2.6 kb), extensive indel polymorphism, GC deficiency, and long homopolymeric regions. We developed and standardized protocols for isolation, RT-PCR amplification, single molecule real-time (SMRT) sequencing, and haplotype analysis of circulating HIV-1 env variants to evaluate viral diversity in primary infection. Methodology: HIV RNA was extracted from 7 blood plasma samples (1 mL) collected from 5 subjects (one individual sampled and sequenced at 3 time points) in the San Diego Primary Infection Cohort between 3-33 months from their estimated date of infection (EDI). Median viral load per sample was 50,118 HIV RNA copies/mL (range: 22,387-446,683). Full-length (3.2 kb) env amplicons were constructed into SMRTbell templates without shearing, and sequenced on the PacBio RS II using P4/C2 chemistry and 180 minute movie collection without stage start. To examine viral diversity in each sample, we determined haplotypes by clustering circular consensus sequences (CCS), and reconstructing a cluster consensus sequence using a partial order alignment approach. We measured sample diversity both as the mean pairwise distance among reads, and the fraction of reads containing indel polymorphisms. Results: We collected a median of 8,775 CCS reads per SMRT Cell (range: 4243-12234). A median of 7 haplotypes per subject (range: 1-55) were inferred at baseline. For the one subject with longitudinal samples analyzed, we observed an increasing number of distinct haplotypes (8 to 55 haplotypes over the course of 30 months), and an increasing mean pairwise distance among reads (from 0.8% to 1.6%, Tamura-Nei 93). We also observed significant indel polymorphism, with 16% of reads from one sample later in infection (33 months post-EDI) exhibiting deletions of more than 10% of env with respect to the reference strain, HXB2. Conclusions: This study developed a standardized NGS procedure (PacBio SMRT) to deep sequence full-length HIV RNA env variants from the circulating viral population, achieving good coverage, confirming low env diversity during primary infection that increased over time, and revealing significant indel polymorphism that highlights structural variation as important to env evolution. The long, accurate reads greatly simplified downstream bioinformatics analyses, especially haplotype phasing, increasing our confidence in the results. The sequencing methodology and analysis tools developed here could be successfully applied to any area for which full-length HIV env analysis would be useful.


June 1, 2021  |  

High-throughput analysis of full-length proviral HIV-1 genomes from PBMCs.

Background: HIV-1 proviruses in peripheral blood mononuclear cells (PBMCs) are felt to be an important reservoir of HIV-1 infection. Given that this pool represents an archival library, it can be used to study virus evolution and CD4+ T cell survival. Accurate study of this pool is burdened by difficulties encountered in sequencing a full-length proviral genome, typically accomplished by assembling overlapping pieces and imputing the full genome. Methodology: Cryopreserved PBMCs collected from a total of 8 HIV+ patients from 1997-2001 were used for genomic DNA extraction. Patients had been receiving cART for 2-8 years at the time samples were obtained. 7 patients had pVL >50 copies/mL (mean: 312,282, range: 18,372-683,400) and 1 had pVL <50. Genomic DNA was subjected to limiting dilution prior to amplification of near-full-length genomes by a newly developed nested PCR. The predicted size of the PCR product was 9.0 kb, spanning from the 5’ LTR through the 3’ LTR. Single molecules were sequenced as near-full-length amplicons directly from PCR products without shearing using commercially available P4-C2 reagents and standard protocols on a PacBio RS II instrument. Quality of the genomes was validated by clonal positive controls and synthetic mixtures. Results: Near-full-length provirus genome sequences were successfully obtained from all 8 patients as continuous long reads from single molecules. PacBio sequencing required approximately 10% of the PCR product needed for Sanger sequencing and generated 325 MB per 3-hour run including 1,800 full-length intact genome reads on average. One patient’s sample was not at a limiting dilution and analysis revealed multiple subspecies. For 8 near-fulllength provirus genomes derived from the other 7 patients, large internal deletions were noted in 2 proviruses; APOBEC-mediated hypermutations were seen in 2 proviruses; and 4 proviruses appeared to be intact genomes. All of the defective proviruses showed a complete absence of resistance mutations in either RT or protease, even after 2-8 years of cART. On the contrary, all of the intact proviruses contained evidence of ART-resistance associated mutations suggesting that they represented relatively recent variants. Conclusions: Combining a novel protocol for full-length limiting dilution amplification of proviruses with PacBio SMRT sequencing allowed for the generation of near-full-length genomes with good quality and an ability to detect minor variants at the 1-10% level. Preliminary data analyses suggest that defective proviruses may represent archival variants that persist long-term in host cells, while intact proviruses within the PBMC pool showing evidence of active virus replication may represent more recent variants.


June 1, 2021  |  

Accurately surveying uncultured microbial species with SMRT Sequencing

Background: Microbial ecology is reshaping our understanding of the natural world by revealing the large phylogenetic and functional diversity of microbial life. However the vast majority of these microorganisms remain poorly understood, as most cultivated representatives belong to just four phylogenetic groups and more than half of all identified phyla remain uncultivated. Characterization of this microbial ‘dark matter’ will thus greatly benefit from new metagenomic methods for in situ analysis. For example, sensitive high throughput methods for the characterization of community composition and structure from the sequencing of conserved marker genes. Methods: Here we utilize Single Molecule Real-Time (SMRT) sequencing of full-length 16S rRNA amplicons to phylogenetically profile microbial communities to below the genus-level. We test this method on a mock community of known composition, as well as a previously studied microbial community from a lake known to predominantly contain poorly characterized phyla. These results are compared to traditional 16S tag sequencing from short-read technologies and subsets of the full-length data corresponding to the same regions of the 16S gene. Results: We explore the benefits of using full-length amplicons for estimating community structure and diversity. In addition, we investigate the possible effects of context-specific and GC-content biases known to affect short-read sequencing technologies on the predicted community structure. We characterize the potential benefits of profiling metagenomic communities with full-length 16S rRNA genes from SMRT sequencing relative to standard methods.


June 1, 2021  |  

SMRT Sequencing and assembly of the human microbiome project Mock Community sample – a feasibility project.

While the utility of Single Molecule, Real-Time (SMRT) Sequencing for de novo assembly and finishing of bacterial isolates is well established, this technology has not yet been widely applied to shotgun sequencing of microbial communities. In order to demonstrate the feasibility of this approach, we sequenced genomic DNA from the Microbial Mock Community B of the Human Microbiome Project


June 1, 2021  |  

An interactive workflow for the analysis of contigs from the metagenomic shotgun assembly of SMRT Sequencing data.

The data throughput of next-generation sequencing allows whole microbial communities to be analyzed using a shotgun sequencing approach. Because a key task in taking advantage of these data is the ability to cluster reads that belong to the same member in a community, single-molecule long reads of up to 30 kb from SMRT Sequencing provide a unique capability in identifying those relationships and pave the way towards finished assemblies of community members. Long reads become even more valuable as samples get more complex with lower intra-species variation, a larger number of closely related species, or high intra-species variation. Here we present a collection of tools tailored for PacBio data for the analysis of these fragmented metagenomic assembles, allowing improvements in the assembly results, and greater insight into the communities themselves. Supervised classification is applied to a large set of sequence characteristics, e.g., GC content, raw-read coverage, k-mer frequency, and gene prediction information, allowing the clustering of contigs from single or highly related species. A unique feature of SMRT Sequencing data is the availability of base modification / methylation information, which can be used to further analyze clustered contigs expected to be comprised of single or very closely related species. Here we show base modification information can be used to further study variation, based on differences in the methylated DNA motifs involved in the restriction modification system. Application of these techniques is demonstrated on a monkey intestinal microbiome sample and an in silico mix of real sequencing data from distinct bacterial samples.


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