Ilana Lauren Brito

Mobile genes in the human microbiome are structured from global to individual scales

Recent work has underscored the importance of the microbiome in human health, and has largely attributed differences in phenotype to differences in the species present among individuals. However, 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 those 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 found in Fijian individuals. Notably, we also observed differences between the mobile gene pools of neighbouring 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 behaviours provide selective pressures that shape mobile gene pools, and that acquisition of mobile genes is important for colonizing specific human populations.

Condensins Promote Coorientation of Sister Chromatids During Meiosis I in Budding Yeast

The condensin complex is a key determinant of higher-ordered chromosome structure. We show here that the complex is also important for the correct alignment of chromosomes on the meiosis I spindle. Unlike during mitosis and meiosis II, when sister chromatids attach to microtubules emanating from opposite spindle poles (biorientation), accurate meiosis I chromosome segregation requires that sister chromatids attach to microtubules emanating from the same spindle pole (coorientation). The monopolin complex, consisting of Lrs4, Csm1, and the meiosis-specific component Mam1, brings about meiosis I coorientation. We find that in the absence of functional condensin complexes, a fraction of sister kinetochores biorient on the meiosis I spindle and association of the monopolin complex subunit Mam1 with kinetochores is decreased. Our studies uncover a new locus-specific effect of the condensin complex.

Virtual microfluidics for digital quantification and single-cell sequencing

We have developed hydrogel-based virtual microfluidics as a simple and robust alternative to complex engineered microfluidic systems for the compartmentalization of nucleic acid amplification reactions. We applied in-gel digital multiple displacement amplification (dMDA) to purified DNA templates, cultured bacterial cells and human microbiome samples in the virtual microfluidics system, and demonstrated whole-genome sequencing of single-cell MDA products with excellent coverage uniformity and markedly reduced chimerism compared with products of liquid MDA reactions.

The Lrs4-Csm1 monopolin complex associates with kinetochores during anaphase and is required for accurate chromosome segregation

Lrs4 and Csm1, components of the monopolin complex, localize to the rDNA where they regulate rDNA maintenance and segregation. During meiosis, the complex also associates with kinetochores to bring about sister kinetochore co-orientation, an essential aspect of meiosis I chromosome segregation. We show here that the Lrs4-Csm1 complex associates with kinetochores during mitosis. This kinetochore localization is observed during anaphase and depends on the on the Mitotic Exit Network, a signaling cascade essential for the completion of mitosis. Furthermore, we find that Lrs4 and Csm1 are important for chromosome segregation fidelity. Our results reveal a previously unanticipated function for Lrs4-Csm1 in mitotic chromosome segregation.

Computational Methods for High-Throughput Comparative Analyses of Natural Microbial Communities

One of the most widely employed methods in metagenomics is the amplification and sequencing of the highly conserved ribosomal RNA (rRNA) genes from organisms in complex microbial communities. rRNA surveys, typically using the 16S rRNA gene for prokaryotic identification, provide information about the total diversity and taxonomic affiliation of organisms present in a sample. Greatly enhanced by high-throughput sequencing, these surveys have uncovered the remarkable diversity of uncultured organisms and revealed unappreciated ecological roles ranging from nutrient cycling to human health. This chapter outlines the best practices for comparative analyses of microbial community surveys. We explain how to transform raw data into meaningful units for further analysis and discuss how to calculate sample diversity and community distance metrics. Finally, we outline how to find associations of species with specific metadata and true correlations between species from compositional data. We focus on data generated by next-generation sequencing platforms, using the Illumina platform as a test case, because of its widespread use especially among researchers just entering the field.

Tracking Strains in the Microbiome: Insights from Metagenomics and Models

Transmission usually refers to the movement of pathogenic organisms. Yet, commensal microbes that inhabit the human body also move between individuals and environments. Surprisingly little is known about the transmission of these endogenous microbes, despite increasing realizations of their importance for human health. The health impacts arising from the transmission of commensal bacteria range widely, from the prevention of autoimmune disorders to the spread of antibiotic resistance genes. Despite this importance, there are outstanding basic questions: what is the fraction of the microbiome that is transmissible? What are the primary mechanisms of transmission? Which organisms are the most highly transmissible? Higher resolution genomic data is required to accurately link microbial sources (such as environmental reservoirs or other individuals) with sinks (such as a single persons microbiome). New computational advances enable strain-level resolution of organisms from shotgun metagenomic data, allowing the transmission of strains to be followed over time and after discrete exposure events. Here, we highlight the latest techniques that reveal strain-level resolution from raw metagenomic reads and new studies that are tracking strains across people and environments. We also propose how models of pathogenic transmission may be applied to study the movement of commensals between microbial communities.