KOMB: K-core based de novo characterization of copy number variation in microbiomes.

Characterizing metagenomes via kmer-based, database-dependent taxonomic classification has yielded key insights into underlying microbiome dynamics. However, novel approaches are needed to track community dynamics and genomic flux within metagenomes, particularly in response to perturbations. We describe KOMB, a novel method for tracking genome level dynamics within microbiomes. KOMB utilizes K-core decomposition to identify Structural variations (SVs), specifically, population-level Copy Number Variation (CNV) within microbiomes. K-core decomposition partitions the graph into shells containing nodes of induced degree at least K, yielding reduced computational complexity compared to prior approaches. Through validation on a synthetic community, we show that KOMB recovers and profiles repetitive genomic regions in the sample. KOMB is shown to identify functionally-important regions in Human Microbiome Project datasets, and was used to analyze longitudinal data and identify keystone taxa in Fecal Microbiota Transplantation (FMT) samples. In summary, KOMB represents a novel graph-based, taxonomy-oblivious, and reference-free approach for tracking CNV within microbiomes. KOMB is open source and available for download at https://gitlab.com/treangenlab/komb.

Prolonged use of a proton pump inhibitor reduces microbial diversity: implications for Clostridium difficile susceptibility.

BACKGROUND: The role of the gut microbiome in arresting pathogen colonization and growth is important for protection against Clostridium difficile infection (CDI). Observational studies associate proton pump inhibitor (PPI) use and CDI incidence. We hypothesized that PPI use affected the distal gut microbiome over time, an effect that would be best explored by time-longitudinal study of healthy subjects on PPI in comparison to treatment-naïve CDI subjects. This study enrolled nine healthy human subjects and five subjects with treatment-naïve CDI. After random assignment to a low (20 mg/day) or high (2× 20 mg/day) dose group, fecal samples were collected from the nine healthy subjects before, during, and after 28 days of PPI use. This was done in conjunction with pre-treatment fecal collection from CDI subjects. High-throughput sequencing (16S rRNA) was performed on time-longitudinal samples to assess changes to the healthy gut microbiome associated with prolonged PPI usage. The healthy samples were then compared to the CDI subjects to explore changes over time to the gut microbiome associated with PPI use and potentially related to CDI. RESULTS: We report that PPI usage at low and high dosages, administered for 28 days, resulted in decreases to observed operational taxonomic unit (OTU) counts after both 1 week and 1 month. This decrease resulted in observed OTU levels that were similar to those found in treatment-naïve CDI patients, which was partly reversible after a 1 month recovery period. We did not detect a dose-dependent difference in OTU levels nor did we detect significant changes in taxa previously reported to be affected by PPI treatment. CONCLUSION: While our observation of diminishing observed OTU counts during PPI therapy is a preliminary finding in a small cohort, our hypothesis that PPIs disrupt the healthy human gut microbiome is supported in this group. We conclude that decreases in observed species counts were reversible after cessation of PPI usage within 1 month. This finding may be a potential explanation for the association between prolonged PPI usage and CDI incidence.

Genomic rearrangements define lineage relationships between adjacent lepidic and invasive components in lung adenocarcinoma.

The development of adenocarcinoma of the lung is believed to proceed from in situ disease (adenocarcinoma in situ, AIS) to minimally invasive disease with prominent lepidic growth (minimally invasive adenocarcinoma, MIA), then to fully invasive adenocarcinoma (AD), but direct evidence for this model has been lacking. Because some lung adenocarcinomas show prominent lepidic growth (AD-L), we designed a study to address the lineage relationship between the lepidic (noninvasive) component (L) and the adjacent nonlepidic growth component representing invasive disease within individual tumors. Lineage relationships were evaluated by next-generation DNA sequencing to define large genomic rearrangements in microdissected tissue specimens collected by laser capture. We found a strong lineage relationship between the majority of adjacent lepidic and invasive components, supporting a putative AIS-AD transition. Notably, many rearrangements were detected in the less aggressive lepidic component, although the invasive component exhibited an overall higher rate of genomic rearrangement. Furthermore, a significant number of genomic rearrangements were present in histologically normal lung adjacent to tumor, but not in host germline DNA, suggesting field defects restricted to zonal regions near a tumor. Our results offer a perspective on the genetic pathogenesis underlying adenocarcinoma development and its clinical management.