Targeting the microbiome to promote health and end cancer
by prof. Jennifer Wargo
aMeta: a computational method for data-driven ancient metagenomic analysis
Analysis of microbial data from archaeological samples is a growing field with great potential for understanding ancient environments, lifestyles, and diseases. However, high error rates have been a challenge in ancient metagenomics, and the availability of computational frameworks that meet the demands of the field is limited. Here, we propose aMeta , an accurate metagenomic profiling workflow for ancient DNA designed to minimize the amount of false discoveries and computer memory requirements. Using simulated data, we benchmark aMeta against a current state-of-the-art workflow and demonstrate its superiority in microbial detection and authentication, as well as substantially lower usage of computer memory.
Biology Department, Science for Life Laboratory, National Bioinformatics Infrastructure Sweden, Lund University, Lund, Sweden
Comparing invasive and noninvasive fecal sampling in wildlife microbiome studies: a case study on wild common cranes
In ecological and conservation studies, responsible researchers strive to obtain rich data while minimizing disturbance to wildlife and ecosystems. We assessed if samples collected noninvasively, in this case, from common cranes (Grus grus), can be used for fecal microbiome research, comparing microbiota of noninvasively collected fecal samples to those collected from trapped common cranes at the same sites over the same period.
We found significant differences in fecal microbial composition (alpha and beta diversity), which likely did not result from noninvasive samples’ exposure to soil contaminants, as assessed by comparing bacterial oxygen use profiles. Differences might result from trapped birds’ exposure to sedatives or stress. We conclude that if all samples are collected in the same manner, comparative analyses are valid, and noninvasive sampling may better represent host fecal microbiota because there are no trapping effects.
To illustrate this point, combining movement data from GPS-tagged cranes with noninvasively sampled fecal microbiota samples of birds spatiotemporally overlapping with the tagged birds, we find evidence that supports the role of diet in structuring bacterial communities. We also show that the wild bird gut microbiota undergoes not only seasonal shifts but is also affected by management schemes and local agricultural practices.
Experiments with fresh and delayed sample collection can elucidate effects of environmental exposures on microbiota. Further, controlled tests of stressing or sedation may unravel how trapping affects wildlife microbiota, but our application already shows how valuable this method can be.
Link to OA paper: https://onlinelibrary.wiley.com/doi/10.1111/1755-0998.13708
Azrieli Faculty of Medicine, Bar-Ilan University, Israel
Neuroblastoma is associated with alterations in gut microbiome composition subsequent to maternal microbial seeding
Neuroblastoma is the most frequent extracranial solid tumour in children, accounting for ~15% of deaths due to cancer in childhood. The most common clinical presentation are abdominal tumours. An altered gut microbiome composition has been linked to multiple cancer types, and reported in murine models of neuroblastoma. However, whether children with neuroblastoma display alterations in gut microbiome composition remains unexplored.
Here, we assessed gut microbiome composition by shotgun metagenomic profiling in an observational cross-sectional study on 288 individuals, consisting of patients with a diagnosis of neuroblastoma at disease onset (N=63), healthy controls matching the patients on the main covariates of microbiome composition (N=94), healthy siblings of the patients (N=13), mothers of patients (N=59), and mothers of the controls (N=59). We examined taxonomic and functional microbiome composition and mother-infant strain transmission patterns. Patients with neuroblastoma displayed alterations in gut microbiome composition characterised by reduced microbiome richness, decreased relative abundances of 18 species (including Phocaeicola dorei and Bifidobacterium bifidum), enriched protein fermentation and reduced carbohydrate fermentation potential. Using machine learning, we could successfully discriminate patients from controls (AUC = 82%). Healthy siblings did not display such alterations but resembled the healthy control group. No significant differences in maternal microbiome composition nor mother-to-offspring transmission were detected.
Therefore, the alterations in taxonomic and functional gut microbiome composition we described in patients with neuroblastoma, cannot be traced to differential maternal seeding and might arise subsequently.
MELIS Department, Pompeu Fabra University, Barcelona, Spain