Living in a microbial world

Supervised Machine Learning Enables Geospatial Microbial Provenance

The recent increase in publicly available metagenomic datasets with geospatial metadata has made it possible to determine location-specific, microbial fingerprints from around the world. Such fingerprints can be useful for comparing microbial niches for environmental research, as well as for applications within forensic science and public health. To determine the regional specificity for environmental metagenomes, we examined 4305 shotgun-sequenced samples from the MetaSUB Consortium dataset-the most extensive public collection of urban microbiomes, spanning 60 different cities, 30 countries, and 6 continents. We were able to identify city-specific microbial fingerprints using supervised machine learning (SML) on the taxonomic classifications, and we also compared the performance of ten SML classifiers. We then further evaluated the five algorithms with the highest accuracy, with the city and continental accuracy ranging from 85-89% to 90-94%, respectively. Thereafter, we used these results to develop Cassandra, a random-forest-based classifier that identifies bioindicator species to aid in fingerprinting and can infer higher-order microbial interactions at each site. We further tested the Cassandra algorithm on the Tara Oceans dataset, the largest collection of marine-based microbial genomes, where it classified the oceanic sample locations with 83% accuracy. These results and code show the utility of SML methods and Cassandra to identify bioindicator species across both oceanic and urban environments, which can help guide ongoing efforts in biotracing, environmental monitoring, and microbial forensics (MF).

Microbial Pyrrolnitrin: Natural Metabolite with Immense Practical Utility

Pyrrolnitrin (PRN) is a microbial pyrrole halometabolite of immense antimicrobial significance for agricultural, pharmaceutical and industrial implications. The compound and its derivatives have been isolated from rhizospheric fluorescent or non-fluorescent pseudomonads, Serratia and Burkholderia. They are known to confer biological control against a wide range of phytopathogenic fungi, and thus offer strong plant protection prospects against soil and seed-borne phytopathogenic diseases. Although chemical synthesis of PRN has been obtained using different steps, microbial production is still the most useful option for producing this metabolite. In many of the plant-associated isolates of Serratia and Burkholderia, production of PRN is dependent on the quorum-sensing regulation that usually involves N-acylhomoserine lactone (AHL) autoinducer signals. When applied on the organisms as antimicrobial agent, the molecule impedes synthesis of key biomolecules (DNA, RNA and protein), uncouples with oxidative phosphorylation, inhibits mitotic division and hampers several biological mechanisms. With its potential broad-spectrum activities, low phototoxicity, non-toxic nature and specificity for impacts on non-target organisms, the metabolite has emerged as a lead molecule of industrial importance, which has led to developing cost-effective methods for the biosynthesis of PRN using microbial fermentation. Quantum of work narrating focused research efforts in the emergence of this potential microbial metabolite is summarized here to present a consolidated, sequential and updated insight into the chemistry, biology and applicability of this natural molecule.

Metagenomic Approaches for Understanding New Concepts in Microbial Science

Over the past thirty years, since the dawn of metagenomic studies, a completely new (micro) universe was revealed, with the potential to have profound impacts on many aspects of the society. Remarkably, the study of human microbiome provided a new perspective on a myriad of human traits previously regarded as solely (epi-) genetically encoded, such as disease susceptibility, immunological response, and social and nutritional behaviors. In this context, metagenomics has established a powerful framework for understanding the intricate connections between human societies and microbial communities, ultimately allowing for the optimization of both human health and productivity. Thus, we have shifted from the old concept of microbes as harmful organisms to a broader panorama, in which the signal of the relationship between humans and microbes is flexible and directly dependent on our own decisions and practices. In parallel, metagenomics has also been playing a major role in the prospection of "hidden" genetic features and the development of biotechnological applications, through the discovery of novel genes, enzymes, pathways, and bioactive molecules with completely new or improved biochemical functions. Therefore, this review highlights the major milestones over the last three decades of metagenomics, providing insights into both its potentialities and current challenges.

MetaBinG2: a fast and accurate metagenomic sequence classification system for samples with many unknown organisms

BACKGROUND

Many methods have been developed for metagenomic sequence classification, and most of them depend heavily on genome sequences of the known organisms. A large portion of sequencing sequences may be classified as unknown, which greatly impairs our understanding of the whole sample.

RESULT

Here we present MetaBinG2, a fast method for metagenomic sequence classification, especially for samples with a large number of unknown organisms. MetaBinG2 is based on sequence composition, and uses GPUs to accelerate its speed. A million 100 bp Illumina sequences can be classified in about 1 min on a computer with one GPU card. We evaluated MetaBinG2 by comparing it to multiple popular existing methods. We then applied MetaBinG2 to the dataset of MetaSUB Inter-City Challenge provided by CAMDA data analysis contest and compared community composition structures for environmental samples from different public places across cities.

CONCLUSION

Compared to existing methods, MetaBinG2 is fast and accurate, especially for those samples with significant proportions of unknown organisms.

REVIEWERS

This article was reviewed by Drs. Eran Elhaik, Nicolas Rascovan, and Serghei Mangul.

Communicating the promise, risks, and ethics of large-scale, open space microbiome and metagenome research

The public commonly associates microorganisms with pathogens. This suspicion of microorganisms is understandable, as historically microorganisms have killed more humans than any other agent while remaining largely unknown until the late seventeenth century with the works of van Leeuwenhoek and Kircher. Despite our improved understanding regarding microorganisms, the general public are apt to think of diseases rather than of the majority of harmless or beneficial species that inhabit our bodies and the built and natural environment. As long as microbiome research was confined to labs, the public's exposure to microbiology was limited. The recent launch of global microbiome surveys, such as the Earth Microbiome Project and MetaSUB (Metagenomics and Metadesign of Subways and Urban Biomes) project, has raised ethical, financial, feasibility, and sustainability concerns as to the public's level of understanding and potential reaction to the findings, which, done improperly, risk negative implications for ongoing and future investigations, but done correctly, can facilitate a new vision of "smart cities." To facilitate improved future research, we describe here the major concerns that our discussions with ethics committees, community leaders, and government officials have raised, and we expound on how to address them. We further discuss ethical considerations of microbiome surveys and provide practical recommendations for public engagement.