Recent work has underscored the importance of the microbiome in human health, largely attributing differences in phenotype to differences in the species present across individuals1,2,3,4,5. But mobile genes can confer profoundly different phenotypes on different strains of the same species. Little is known about the function and distribution of mobile genes in the human microbiome, and in particular whether the gene pool is globally homogenous or constrained by human population structure. Here, we investigate this question by comparing the mobile genes found in the microbiomes of 81 metropolitan North Americans with that of 172 agrarian Fiji islanders using a combination of single-cell genomics and metagenomics. We find large differences in mobile gene content between the Fijian and North American microbiomes, with functional variation that mirrors known dietary differences such as the excess of plant-based starch degradation genes. Remarkably, differences are also observed between the mobile gene pools of proximal Fijian villages, even though microbiome composition across villages is similar. Finally, we observe high rates of recombination leading to individual-specific mobile elements, suggesting that the abundance of some genes may reflect environmental selection rather than dispersal limitation. Together, these data support the hypothesis that human activities and behaviors provide selective pressures that shape mobile gene pools, and that acquisition of mobile genes is important to colonizing specific human populations.

The predominance of rRNAs in the transcriptome is a major technical challenge in sequence-based analysis of cDNAs from microbial isolates and communities. Several approaches have been applied to deplete rRNAs from (meta)transcriptomes, but no systematic investigation of potential biases introduced by any of these approaches has been reported. Here we validated the effectiveness and fidelity of the two most commonly used approaches, subtractive hybridization and exonuclease digestion as well as combinations of these treatments, on two synthetic five-microorganism metatranscriptomes using massively parallel sequencing. We found that the effectiveness of rRNA removal was a function of community composition and RNA integrity for these treatments. Subtractive hybridization alone introduced the least bias in relative transcript abundance, whereas exonuclease and in particular combined treatments greatly compromised mRNA abundance fidelity. Illumina sequencing itself also can compromise quantitative data analysis by introducing a G+C bias between runs.Rapid technological advances in ultra-high-throughput sequencing are making de novo sequencing of transcriptomes (RNA-seq) a viable alternative to microarray analysis of microbial isolates and communities 1 . A major technical challenge for de novo transcriptome sequencing is the low relative abundance of mRNAs in total cellular RNA (1-5%; ref.2), the bulk of which is rRNAs and tRNAs 3 . Unlike eukaryotic mRNAs, which can be selectively synthesized into cDNA by virtue of their poly(A) tails 4 , bacterial and archaeal cDNAs are predominantly rRNA -2-sequences 5,6 . Therefore, prokaryotic rRNAs are often removed before sequencing to improve mRNA detection sensitivity. Different methods have been used to eliminate prokaryotic rRNA, including subtractive hybridization with rRNA-specific probes 7,8 , digestion with exonuclease that preferentially acts on rRNA, poly(A) tail addition to discriminate against rRNA 9,10 , reverse transcription with rRNA-specific primers followed by RNase H digestion to degrade rRNA:DNA hybrids 11 , and gel electrophoresis size separation and extraction of non-rRNA bands 12 .Among these methods, subtractive hybridization and exonuclease digestion have become the most popular owing to the availability of commercial kits from Ambion (MICROBExpress Bacterial mRNA Enrichment kit) and Epicentre (mRNA-ONLY Prokaryotic mRNA Isolation kit). The former kit uses a subtractive hybridization with capture oligonucleotides specific to 16S and 23S rRNAs. It has been applied to both bacterial isolates and environmental samples, in one or two rounds 6,[13][14][15][16][17][18] . The Epicentre kit uses exonuclease to preferentially degrade processed RNAs with 5′ monophosphate (the majority of which are believed to be rRNAs) 19,20 . In some instances, these methods have been used in combination to improve rRNA removal [21][22][23] . There is no consensus, however, on the best approach, and existing data are anecdotal. Here we validated the performance of these kits wit...

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Ocean viruses are ubiquitous and abundant and play important roles in global biogeochemical cycles by means of their mortality, horizontal gene transfer, and manipulation of host metabolism. However, the obstacles involved in linking viruses to their hosts in a high-throughput manner bottlenecks our ability to understand virus-host interactions in complex communities. We have developed a method called viral tagging (VT), which combines mixtures of host cells and fluorescent viruses with flow cytometry. We investigated multiple viruses which infect each of two model marine bacteria that represent the slow-growing, photoautotrophic genus Synechococcus (Cyanobacteria) and the fast-growing, heterotrophic genus Pseudoalteromonas (Gammaproteobacteria). Overall, viral tagging results for viral infection were consistent with plaque and liquid infection assays for cyanobacterial myo-, podo- and siphoviruses and some (myo- and podoviruses) but not all (four siphoviruses) heterotrophic bacterial viruses. Virus-tagged Pseudoalteromonas organisms were proportional to the added viruses under varied infection conditions (virus-bacterium ratios), while no more than 50% of the Synechococcus organisms were virus tagged even at viral abundances that exceeded (5 to 10×) that of their hosts. Further, we found that host growth phase minimally impacts the fraction of virus-tagged Synechococcus organisms while greatly affecting phage adsorption to Pseudoalteromonas. Together these findings suggest that at least two contrasting viral life strategies exist in the oceans and that they likely reflect adaptation to their host microbes. Looking forward to the point at which the virus-tagging signature is well understood (e.g., for Synechococcus), application to natural communities should begin to provide population genomic data at the proper scale for predictively modeling two of the most abundant biological entities on Earth.

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Chemical analysis Orthophosphate-phosphorus (PO 4 3-P) was measured by ascorbic acid method after the solution being filtered by the membrane with 0.45 µm pore size. Total phosphorus (TP)

Whole genome amplification and next-generation sequencing of single cells has become a powerful approach for studying uncultivated microorganisms that represent 90–99 % of all environmental microbes. Single cell sequencing enables not only the identification of microbes but also linking of functions to species, a feat not achievable by metagenomic techniques. Moreover, it allows the analysis of low abundance species that may be missed in community-based analyses. It has also proved very useful in complementing metagenomics in the assembly and binning of single genomes. With the advent of drastically cheaper and higher throughput sequencing technologies, it is expected that single cell sequencing will become a standard tool in studying the genome and transcriptome of microbial communities.