BackgroundThe accuracy of microbial community surveys based on marker-gene and metagenomic sequencing (MGS) suffers from the presence of contaminants—DNA sequences not truly present in the sample. Contaminants come from various sources, including reagents. Appropriate laboratory practices can reduce contamination, but do not eliminate it. Here we introduce decontam (https://github.com/benjjneb/decontam), an open-source R package that implements a statistical classification procedure that identifies contaminants in MGS data based on two widely reproduced patterns: contaminants appear at higher frequencies in low-concentration samples and are often found in negative controls.ResultsDecontam classified amplicon sequence variants (ASVs) in a human oral dataset consistently with prior microscopic observations of the microbial taxa inhabiting that environment and previous reports of contaminant taxa. In metagenomics and marker-gene measurements of a dilution series, decontam substantially reduced technical variation arising from different sequencing protocols. The application of decontam to two recently published datasets corroborated and extended their conclusions that little evidence existed for an indigenous placenta microbiome and that some low-frequency taxa seemingly associated with preterm birth were contaminants.ConclusionsDecontam improves the quality of metagenomic and marker-gene sequencing by identifying and removing contaminant DNA sequences. Decontam integrates easily with existing MGS workflows and allows researchers to generate more accurate profiles of microbial communities at little to no additional cost.Electronic supplementary materialThe online version of this article (10.1186/s40168-018-0605-2) contains supplementary material, which is available to authorized users.

Bacteriophages typically have small genomes 1 and depend on their bacterial hosts for replication 2 . Here we sequenced DNA from diverse ecosystems and found hundreds of phage genomes with lengths of more than 200 kilobases (kb), including a genome of 735 kb, which is-to our knowledge-the largest phage genome to be described to date. Thirty-five genomes were manually curated to completion (circular and no gaps). Expanded genetic repertoires include diverse and previously undescribed CRISPR-Cas systems, transfer RNAs (tRNAs), tRNA synthetases, tRNA-modification enzymes, translation-initiation and elongation factors, and ribosomal proteins. The CRISPR-Cas systems of phages have the capacity to silence host transcription factors and translational genes, potentially as part of a larger interaction network that intercepts translation to redirect biosynthesis to phage-encoded functions. In addition, some phages may repurpose bacterial CRISPR-Cas systems to eliminate competing phages. We phylogenetically define the major clades of huge phages from human and other animal microbiomes, as well as from oceans, lakes, sediments, soils and the built environment. We conclude that the large gene inventories of huge phages reflect a conserved biological strategy, and that the phages are distributed across a broad bacterial host range and across Earth's ecosystems.Phages-viruses that infect bacteria-are considered distinct from cellular life owing to their inability to carry out most biological processes required for reproduction. They are agents of ecosystem change because they prey on specific bacterial populations, mediate lateral gene transfer, alter host metabolism and redistribute bacterially derived compounds through cell lysis 2-4 . They spread antibiotic resistance 5 and disperse pathogenicity factors that cause disease in humans and animals 6,7 . Most knowledge about phages is based on laboratorystudied examples, the vast majority of which have genomes that are a few tens of kb in length. Widely used isolation-based methods select against large phage particles, and they can be excluded from phage concentrates obtained by passage through 100-nm or 200-nm filters 1 . In 2017, only 93 isolated phages with genomes that were more than 200 kb in length were published 1 . Sequencing of whole-community DNA can uncover phage-derived fragments; however, large genomes can still escape detection owing to fragmentation 8 . A new clade of human-and animal-associated megaphages was recently described on the basis of genomes that were manually curated to completion from metagenomic datasets 9 . This finding prompted us to carry out a more-comprehensive analysis of microbial communities to evaluate the prevalence, diversity and ecosystem distribution of phages with large genomes. Previously, phages with genomes of more than 200 kb have been referred to as 'jumbophages' 1 or, in the case of phages with genomes of more than 500 kb, as megaphages 9 . As the set reconstructed here span both size ranges we refer to them simply as 'huge phage...

Over 100 years ago, Robert Koch introduced his ideas about how to prove a causal relationship between a microorganism and a disease. Koch's postulates created a scientific standard for causal evidence that established the credibility of microbes as pathogens and led to the development of modern microbiology. In more recent times, Koch's postulates have evolved to accommodate a broader understanding of the host-parasite relationship as well as experimental advances. Techniques such as in situ hybridization, PCR, and representational difference analysis reveal previously uncharacterized, fastidious or uncultivated, microbial pathogens that resist the application of Koch's original postulates, but they also provide new approaches for proving disease causation. In particular, the increasing reliance on sequence-based methods for microbial identification requires a reassessment of the original postulates and the rationale that guided Koch and later revisionists. Recent investigations of Whipple's disease, human ehrlichiosis, hepatitis C, hantavirus pulmonary syndrome, and Kaposi's sarcoma illustrate some of these issues. A set of molecular guidelines for establishing disease causation with sequence-based technology is proposed, and the importance of the scientific concordance of evidence in supporting causal associations is emphasized.

Understanding how microbial communities develop is essential for predicting and directing their future states. Ecological theory suggests that community development is often influenced by priority effects, in which the order and timing of species arrival determine how species affect one another. Priority effects can have long-lasting consequences, particularly if species arrival history varies during the early stage of community development, but their importance to the human gut microbiota and host health remains largely unknown. Here, we explore how priority effects might influence microbial communities in the gastrointestinal tract during early childhood and how the strength of priority effects can be estimated from the composition of the microbial species pool. We also discuss factors that alter microbial transmission, such as delivery mode, diet and parenting behaviours such as breastfeeding, which can influence the likelihood of priority effects. An improved knowledge of priority effects has the potential to inform microorganism-based therapies, such as prebiotics and probiotics, which are aimed at guiding the microbiota towards a healthy state.