Concurrent Scientific Session (Genomics): Metagenomics
Ultra-long read nanopore sequencing methods for metagenomics
At present, most metagenomic surveys rely on high-output platforms such as Illumina. However, the short reads generated by these platforms limit specificity of taxonomic assignment and result in highly fragmented assemblies. Single molecule sequencing platforms are able to sequence much longer molecules and the output of these platforms, particular the PromethION from Oxford Nanopore now supports the study of complex microbial communities using shotgun metagenomics. We assessed a variety of commercially available and manual extraction methods using both a ten-species mock community and clinical samples seeking to find a method capable of generating ultra-long reads (>100 kb) from these samples. The results presented here demonstrate the importance of having lysis methods capable of extracting high-molecular weight DNA from recalcitrant organisms such as Gram-positive bacteria and fungi. Development of these methods is critical to support the growing field of clinical microbiome research including the ability to perform strain tracking and produce high-quality metagenome assembled genomes (MAGs) from metagenomic samples
Combining high resolution whole genome mapping with long read DNA sequencing for microbial genome assembly
De novo whole genome assemblies based on short-read sequencing data are often incomplete and highly fragmented. The development of long-read, single-molecule technologies, like those produced by Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT), were driven by the need for longer read lengths to span repeat regions and complex events. While significant improvements in assembly have been observed with the application of these technologies, both are unable to achieve sufficient read length to observe all genomic structural changes. When genomes are too complex to assemble using multiple sequencing platforms, the need for high resolution genomic mapping is required to supplement, correct, and verify sequence assemblies. By mapping reads that are hundreds of kilobases in length, electronic detection preserves long-range information while simultaneously achieving unparalleled resolution and accuracy. We will describe the application of Nabsys data to provide maps for Pseudoaltermonas haloplanktis used in the ABRF microbial control. The maps were used to identify sequence assembly errors in both PacBio and ONT assemblies and to determine when sequence assembly was correct and complete.
Microbes in Space
In light of an upcoming new era of human expansion in the universe, such as future space travel to Mars, the microbiome of the closed space environment needs to be examined thoroughly to identify the types of microorganisms that can accumulate in this unique environment, how long they persist and survive and their impact on human health and spacecraft infrastructure. As part of this NASA initiative, the viable microbial communities on ISS surfaces from eight different locations over three flight missions, spanning 14 months, were characterized using culture-based techniques, qPCR and amplicon sequencing of the 16S rRNA gene and internal transcribed spacer region using the Illumina platform. Across three flight samplings, K. pneumoniae reads, an opportunistic BSL-2 pathogen, were retrieved during Flight 1 and successively its reads persisted in Flight 2. Subsequently, in Flight 3, most of the locations were inflicted with the presence of this opportunistic pathogen. Other noticeable opportunistic pathogens of all flights were, A. baumannii, E. cloacae, S. enterica, and S. sonnei as well as some fungi. None of the pathogenic fungi were persistent in any of the locations sampled.
Finding NEMO: discovering Novel Endemic Micro-Organisms in the gut microbiome using a genome-centric metagenomics analysis
The human gut microbiome is a rich ocean of biological diversity. However, the methods used to profile microbial communities often lack the resolution needed to catch and define novel organisms, and they can end up lost in the sea of data. Shotgun metagenomic profiling and genome-centric analysis of microbiomes can overcome these issues, resulting in accurate identification or organisms while avoiding false positive results. Analysis of the metagenomes from more than 1,000 fecal microbiome samples from an Australian population discovered over 800 novel species (using the recently proposed genome-based taxonomy GTDB). Surprisingly, some of these novel species are commonly observed in the population, with many found in >50% of people. This metagenomics approach couples the discovery of these species with the annotation of their metabolic functions, enabling predictions of the roles the novel organisms have in the gut . Population-wide metagenomic analysis linked with medical questionnaires has revealed correlations between many of these novel species and disease states. These organisms and their metabolites are potential candidates for biotherapeutic development. This work highlights the utility of genome-centric metagenomics analysis in finding these novel species.
Understanding Permafrost Dynamics Using Metagenomics and Systems Biology
Permafrost underlies 25% of earth’s land surface. As temperatures warm, particularly in Alaska and across the Arctic, permafrost will thaw, dramatically altering landscapes and ecosystems. As permafrost thaws, soil microbes activate and through their metabolic processes, release carbon back into the atmosphere. In the laboratory, we subjected Alaskan permafrost samples to warming temperatures to mimic thaw. DNA was extracted from samples across the thaw regime and sequenced on an Illumina HiSeq. Shotgun sequencing revealed that the composition of microbes from the frozen state were different from those in the thawed state. Furthermore, the temperature, rather than the starting inoculum, influenced the thawed community composition. This has important implications for predictions of biochemical processes under warming conditions because different sets of permafrost will likely respond differently and these trajectories should be accounted for in the current models.