microbeMASST: a taxonomically informed mass spectrometry search tool for microbial metabolomics data

microbeMASST, a taxonomically informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbe-derived metabolites and relative producers without a priori knowledge will vastly enhance the understanding of microorganisms' role in ecology and human health.

A Taxonomically-informed Mass Spectrometry Search Tool for Microbial Metabolomics Data

MicrobeMASST, a taxonomically-informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbial-derived metabolites and relative producers, without a priori knowledge, will vastly enhance the understanding of microorganisms' role in ecology and human health.

Long-Read Metagenomics and CAZyme Discovery

Microorganisms play a primary role in regulating biogeochemical cycles and are a valuable source of enzymes that have biotechnological applications, such as carbohydrate-active enzymes (CAZymes). However, the inability to culture the majority of microorganisms that exist in natural ecosystems restricts access to potentially novel bacteria and beneficial CAZymes. While commonplace molecular-based culture-independent methods such as metagenomics enable researchers to study microbial communities directly from environmental samples, recent progress in long-read sequencing technologies are advancing the field. We outline key methodological stages that are required as well as describe specific protocols that are currently used for long-read metagenomic projects dedicated to CAZyme discovery.

"Candidatus Paraporphyromonas polyenzymogenes" encodes multi-modular cellulases linked to the type IX secretion system

BACKGROUND

In nature, obligate herbivorous ruminants have a close symbiotic relationship with their gastrointestinal microbiome, which proficiently deconstructs plant biomass. Despite decades of research, lignocellulose degradation in the rumen has thus far been attributed to a limited number of culturable microorganisms. Here, we combine meta-omics and enzymology to identify and describe a novel Bacteroidetes family ("Candidatus MH11") composed entirely of uncultivated strains that are predominant in ruminants and only distantly related to previously characterized taxa.

RESULTS

The first metabolic reconstruction of Ca. MH11-affiliated genome bins, with a particular focus on the provisionally named "Candidatus Paraporphyromonas polyenzymogenes", illustrated their capacity to degrade various lignocellulosic substrates via comprehensive inventories of singular and multi-modular carbohydrate active enzymes (CAZymes). Closer examination revealed an absence of archetypical polysaccharide utilization loci found in human gut microbiota. Instead, we identified many multi-modular CAZymes putatively secreted via the Bacteroidetes-specific type IX secretion system (T9SS). This included cellulases with two or more catalytic domains, which are modular arrangements that are unique to Bacteroidetes species studied to date. Core metabolic proteins from Ca. P. polyenzymogenes were detected in metaproteomic data and were enriched in rumen-incubated plant biomass, indicating that active saccharification and fermentation of complex carbohydrates could be assigned to members of this novel family. Biochemical analysis of selected Ca. P. polyenzymogenes CAZymes further iterated the cellulolytic activity of this hitherto uncultured bacterium towards linear polymers, such as amorphous and crystalline cellulose as well as mixed linkage β-glucans.

CONCLUSION

We propose that Ca. P. polyenzymogene genotypes and other Ca. MH11 members actively degrade plant biomass in the rumen of cows, sheep and most likely other ruminants, utilizing singular and multi-domain catalytic CAZymes secreted through the T9SS. The discovery of a prominent role of multi-modular cellulases in the Gram-negative Bacteroidetes, together with similar findings for Gram-positive cellulosomal bacteria (Ruminococcus flavefaciens) and anaerobic fungi (Orpinomyces sp.), suggests that complex enzymes are essential and have evolved within all major cellulolytic dominions inherent to the rumen.

Improved metagenome assemblies and taxonomic binning using long-read circular consensus sequence data

DNA assembly is a core methodological step in metagenomic pipelines used to study the structure and function within microbial communities. Here we investigate the utility of Pacific Biosciences long and high accuracy circular consensus sequencing (CCS) reads for metagenomic projects. We compared the application and performance of both PacBio CCS and Illumina HiSeq data with assembly and taxonomic binning algorithms using metagenomic samples representing a complex microbial community. Eight SMRT cells produced approximately 94 Mb of CCS reads from a biogas reactor microbiome sample that averaged 1319 nt in length and 99.7% accuracy. CCS data assembly generated a comparative number of large contigs greater than 1 kb, to those assembled from a ~190x larger HiSeq dataset (~18 Gb) produced from the same sample (i.e approximately 62% of total contigs). Hybrid assemblies using PacBio CCS and HiSeq contigs produced improvements in assembly statistics, including an increase in the average contig length and number of large contigs. The incorporation of CCS data produced significant enhancements in taxonomic binning and genome reconstruction of two dominant phylotypes, which assembled and binned poorly using HiSeq data alone. Collectively these results illustrate the value of PacBio CCS reads in certain metagenomics applications.