Biology subjects

Patrick D Schloss

Publications and source records attributed to Patrick D Schloss.

3 recordsLinked to original sources

bioRxiv2016

Looking for a Signal in the Noise: Revisiting Obesity and the Microbiome

Two recent studies have re-analyzed published data and found that when datasets are analyzed independently there was limited support for the widely accepted hypothesis that changes in the microbiome are associated with obesity. This hypothesis was reconsidered by increasing the number of datasets and pooling the results across the individual datasets. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were applied to identify 10 studies for an updated and more synthetic analysis. Alpha diversity metrics and the relative risk of obesity based on those metrics were used to identify a limited number of significant associations with obesity; however, when the results of the studies were pooled using a random effects model significant associations were observed between Shannon diversity, number of observed OTUs, and Shannon evenness and obesity status. They were not observed for the ratio of Bacteroidetes and Firmicutes or their individual relative abundances. Although these tests yielded small P-values, the difference between the Shannon diversity index of non-obese and obese individuals was 2.07%. A power analysis demonstrated that only one of the studies had sufficient power to detect a 5% difference in diversity. When Random Forest machine learning models were trained on one dataset and then tested using the other 9 datasets, the median accuracy varied between 33.01 and 64.77% (median=56.67%). Although there was support for a relationship between the microbial communities found in human feces and obesity status, this association is relatively weak and its detection is confounded by large interpersonal variation and insufficient sample sizes.

Microbiology↗

bioRxiv2016

Application of database-independent approach to assess the quality of OTU picking methods

Assigning 16S rRNA gene sequences to operational taxonomic units (OTUs) allows microbial ecologists to overcome the inconsistencies and biases within bacterial taxonomy and provides a strategy for clustering similar sequences that do not have representatives in a reference database. I have applied the Matthews correlation coefficient to assess the ability of 15 reference-independent and -dependent clustering algorithms to assign sequences to OTUs. This metric quantifies the ability of an algorithm to reflect the relationships between sequences without the use of a reference and can be applied to any dataset or method. The most consistently robust method was the average neighbor algorithm; however, for some datasets other algorithms matched its performance.

Microbiology↗

bioRxiv2016

The status of the microbial census: an update

A census is typically carried out for people at a national level; however, microbial ecologists have implemented a molecular census of bacteria and archaea by sequencing their 16S rRNA genes. We assessed how well the microbial census of full-length 16S rRNA gene sequences is proceeding in the context of recent advances in high throughput sequencing technologies. Among the 1,411,234 and 53,546 full-length bacterial and archaeal sequences sequences, 94.5% and 95.1% of the bacterial and archeaeal sequences, respectively, belonged to operational taxonomic units (OTUs) that have been observed more than once. Although these metrics suggest that the census is approaching completion, 29.2% of the bacterial and 38.5% of the archaeal OTUs have been observed more than once. Thus, there is still considerable microbial diversity to be explored. Unfortunately, the rate of new full-length sequences has been declining and new sequences are primarily being deposited by a small number of studies. Furthermore, sequences from soil and aquatic environments, which are known to be rich in bacterial diversity, only represent 7.8 and 16.5% of the census while sequences associated with zoonotic environments represent 55.0% of the census. Continued use of traditional approaches and new technologies such as single cell genomics and short read assembly are likely to improve our ability to sample rare OTUs if it is possible to overcome this sampling bias. The success of ongoing efforts to use short read sequencing to characterize microbial communities requires that researchers strive to expand the depth and breadth of the microbial census.\n\nImportanceThe biodiversity contained within the bacterial and archaeal domains dwarfs that of the eukaryotes and the services these organisms provide to the biosphere are critical. Surprisingly, we have done a relatively poor job of keeping track of the ongoing effort to characterize the biodiversity as represented in full-length 16S rRNA genes. By understanding how this census is proceeding, it is possible to suggest the best allocation of resources for advancing the census. We found that the ongoing effort has done an excellent job of sampling the most abundant organisms, but struggles to sample the more rare organisms. Through the use of new sequencing technologies we should be able to obtain full-length sequences from these rare organisms. Furthermore, we suggest that by allocating more resources to sampling environments known to have the greatest biodiversity we will be able to make significant advances in our characterization of microbial diversity.

Microbiology↗