Bacterial community composition in the Northern Gulf of Mexico intertidal sediment bioturbated by the ghost shrimp Lepidophthalmus louisianensis

Bioturbation plays an important role in structuring microbial communities in coastal sediments. This study investigates the bacterial community composition in sediment associated with the ghost shrimp Lepidophthalmus louisianensis at two locations in the Northern Gulf of Mexico (Bay St. Louis, MS, and Choctawhatchee Bay, FL). Bacteria were analysed for shrimp burrows and for three different depths of bioturbated intertidal sediment, using second-generation sequencing of the 16S rRNA gene. Burrow walls held a unique bacterial community, which was significantly different from those in the surrounding sediment communities. Communities in burrow walls and surrounding sediment communities also differed between the two geographic locations. The burrow wall communities from both locations were more similar to each other than to sediment communities from same location. Alpha- and Gammaproteobacteria were more abundant in burrows and surface sediment than in the subsurface, whereas Deltaproteobacteria were more abundant in burrows and subsurface sediment, suggesting sediment mixing by the bioturbator. However, abundance of individual ASVs was geographic location-specific for all samples. Therefore, it is suggested that the geographic location plays an important role in regional microbial communities distinctiveness. Bioturbation appears to be an important environmental driver in structuring the community around burrows. Sampling was conducted during times of the year and water salinity, tidal regime and temperature were variable, nevertheless the structure microbial communities appeared to remain realatively stable suggesting that these environmental variable played only a minor role.

Multi-factorial examination of amplicon sequencing workflows from sample preparation to bioinformatic analysis

BACKGROUND

The development of sequencing technologies to evaluate bacterial microbiota composition has allowed new insights into the importance of microbial ecology. However, the variety of methodologies used among amplicon sequencing workflows leads to uncertainty about best practices as well as reproducibility and replicability among microbiome studies. Using a bacterial mock community composed of 37 soil isolates, we performed a comprehensive methodological evaluation of workflows, each with a different combination of methodological factors spanning sample preparation to bioinformatic analysis to define sources of artifacts that affect coverage, accuracy, and biases in the resulting compositional profiles.

RESULTS

Of the workflows examined, those using the V4-V4 primer set enabled the highest level of concordance between the original mock community and resulting microbiome sequence composition. Use of a high-fidelity polymerase, or a lower-fidelity polymerase with an increased PCR elongation time, limited chimera formation. Bioinformatic pipelines presented a trade-off between the fraction of distinct community members identified (coverage) and fraction of correct sequences (accuracy). DADA2 and QIIME2 assembled V4-V4 reads amplified by Taq polymerase resulted in the highest accuracy (100%) but had a coverage of only 52%. Using mothur to assemble and denoise V4-V4 reads resulted in a coverage of 75%, albeit with marginally lower accuracy (99.5%).

CONCLUSIONS

Optimization of microbiome workflows is critical for accuracy and to support reproducibility and replicability among microbiome studies. These considerations will help reveal the guiding principles of microbial ecology and impact the translation of microbiome research to human and environmental health.

Amplicon Sequencing Pipelines in Metagenomics

Taxonomic profiling among a large number of samples is a fundamental task during amplicon sequencing analysis. The heterogeneity and technical noises in the sample handling, library preparation, and sequencing present a major challenge to how the biological conclusions are drawn from the data analysis, and accordingly, many tools have been developed to address specific issues related to each step of the data analysis. Nowadays, several sophisticated computational pipelines with flexible parameters are made available to provide one-stop comprehensive solutions by integrating various tools, which significantly mitigate the burden imposed by the complexity of the metagenomics data analysis. This chapter discusses the best practices related to the data generation and describes bioinformatics approaches to achieving greater accuracy from data processing. It offers two independent stepwise pipelines using mothur and DADA2 in a parallel way, presents the basic principles in the key steps of the analysis, and enables the comparisons between the two pipelines straightforwardly.

General Unified Microbiome Profiling Pipeline (GUMPP) for Large Scale, Streamlined and Reproducible Analysis of Bacterial 16S rRNA Data to Predicted Microbial Metagenomes, Enzymatic Reactions and Metabolic Pathways

General Unified Microbiome Profiling Pipeline (GUMPP) was developed for large scale, streamlined and reproducible analysis of bacterial 16S rRNA data and prediction of microbial metagenomes, enzymatic reactions and metabolic pathways from amplicon data. GUMPP workflow introduces reproducible data analyses at each of the three levels of resolution (genus; operational taxonomic units (OTUs); amplicon sequence variants (ASVs)). The ability to support reproducible analyses enables production of datasets that ultimately identify the biochemical pathways characteristic of disease pathology. These datasets coupled to biostatistics and mathematical approaches of machine learning can play a significant role in extraction of truly significant and meaningful information from a wide set of 16S rRNA datasets. The adoption of GUMPP in the gut-microbiota related research enables focusing on the generation of novel biomarkers that can lead to the development of mechanistic hypotheses applicable to the development of novel therapies in personalized medicine.

Spatio-temporal variations in chemical pollutants found among urban deposits match changes in thiopurine S-methyltransferase-harboring bacteria tracked by the tpm metabarcoding approach

The bTPMT (bacterial thiopurine S-methyltransferase), encoded by the tpm gene, can detoxify metalloid-containing oxyanions and xenobiotics. The hypothesis of significant relationships between tpm distribution patterns and chemical pollutants found in urban deposits was investigated. The tpm gene was found conserved among eight bacterial phyla with no sign of horizontal gene transfers but a predominance among gammaproteobacteria. A DNA metabarcoding approach was designed for tracking tpm-harboring bacteria among polluted urban deposits and sediments recovered for more than six years in a detention basin (DB). This DB recovers runoff waters and sediments from a zone of high commercial activities. The PCR products from DB samples led to more than 540,000 tpm reads after DADA2 or MOTHUR bio-informatic manipulations that were allocated to more than 88 and less than 634 sequence variants per sample. The tpm community patterns were significantly different between the recent urban deposits and those that had accumulated for more than 2 years in the DB, and between those of the DB surface and the DB settling pit. These groups of samples had distinct mixture of priority pollutants. Significant relationships between tpm ordination patterns, sediment accumulation time periods and location, and concentrations in PAH, chlorpyrifos, and 4-nonylphenols (NP) were observed. These correlations matched the higher occurrences of, among others, Aeromonas, Pseudomonas, and Xanthomonas tpm-harboring bacteria in recent urban DB deposits more contaminated with chrysene and alkylphenol ethoxylates. Highly significant drops in tpm reads allocated to Aeromonas species were recorded in the oldest DB sediments accumulating naphthalene and metallic pollutants. Degraders of urban pollutants such as P. aeruginosa and P. putida showed conserved distribution patterns over time but P. syringae phytopathogens were more abundant in the oldest sediments. TPMT-harboring bacteria can be used to assess the incidence of high risk priority pollutants on environmental systems.

Evaluation and update of cutoff values for methanotrophic pmoA gene sequences

The functional pmoA gene is frequently used to probe the diversity and phylogeny of methane-oxidizing bacteria (MOB) in various environments. Here, we compared the similarities between the pmoA gene and the corresponding 16S rRNA gene sequences of 77 described species covering gamma- and alphaproteobacterial methanotrophs (type I and type II MOB, respectively) as well as methanotrophs from the phylum Verrucomicrobia. We updated and established the weighted mean pmoA gene cutoff values on the nucleotide level at 86, 82, and 71 % corresponding to the 97, 95, and 90 % similarity of the 16S rRNA gene. Based on these cutoffs, the functional gene fragments can be entirely processed at the nucleotide level throughout software platforms such as Mothur or QIIME which provide a user-friendly and command-based alternative to amino acid-based pipelines. Type II methanotrophs are less divergent than type I both with regard to ribosomal and functional gene sequence similarity and GC content. We suggest that this agrees with the theory of different life strategies proposed for type I and type II MOB.