The incidence of preterm birth exceeds 10% worldwide. There are significant disparities in the frequency of preterm birth among populations within countries, and women of African ancestry disproportionately bear the burden of risk in the United States. In the present study, we report a community resource that includes ‘omics’ data from approximately 12,000 samples as part of the integrative Human Microbiome Project. Longitudinal analyses of 16S ribosomal RNA, metagenomic, metatranscriptomic and cytokine profiles from 45 preterm and 90 term birth controls identified harbingers of preterm birth in this cohort of women predominantly of African ancestry. Women who delivered preterm exhibited significantly lower vaginal levels of Lactobacillus crispatus and higher levels of BVAB1, Sneathia amnii, TM7-H1, a group of Prevotella species and nine additional taxa. The first representative genomes of BVAB1 and TM7-H1 are described. Preterm-birth-associated taxa were correlated with proinflammatory cytokines in vaginal fluid. These findings highlight new opportunities for assessment of the risk of preterm birth.

Engineering cell metabolism for bioproduction not only consumes building blocks and energy molecules (e.g., ATP) but also triggers energetic inefficiency inside the cell. The metabolic burdens on microbial workhorses lead to undesirable physiological changes, placing hidden constraints on host productivity. We discuss cell physiological responses to metabolic burdens, as well as strategies to identify and resolve the carbon and energy burden problems, including metabolic balancing, enhancing respiration, dynamic regulatory systems, chromosomal engineering, decoupling cell growth with production phases, and co-utilization of nutrient resources. To design robust strains with high chances of success in industrial settings, novel genome-scale models (GSMs), (13)C-metabolic flux analysis (MFA), and machine-learning approaches are needed for weighting, standardizing, and predicting metabolic costs.

Immune cell-specific expression is one indication of the importance of a gene's role in the immune response. We have compiled a compendium of microarray expression data for virtually all human genes from six key immune cell types and their activated and differentiated states. Immune Response In Silico (IRIS) is a collection of genes that have been selected for specific expression in immune cells. The expression pattern of IRIS genes recapitulates the phylogeny of immune cells in terms of the lineages of their differentiation. Gene Ontology assignments for IRIS genes reveal significant involvement in inflammation and immunity. Genes encoding CD antigens, cytokines, integrins and many other gene families playing key roles in the immune response are highly represented. IRIS also includes proteins of unknown function and expressed sequence tags that may not represent genes. The predicted cellular localization of IRIS proteins is evenly distributed between cell surface and intracellular compartments, indicating that immune specificity is important at many points in the signaling pathways of the immune response. IRIS provides a resource for further investigation into the function of the immune system and immune diseases.

Laboratory evolution can be used to address fundamental questions about adaptation to selection pressures and, ultimately, the process of evolution. In this study, we investigated the reproducibility of growth phenotypes and global gene expression states during adaptive evolution. The results from parallel, replicate adaptive evolution experiments of Escherichia coli K-12 MG1655 grown on either lactate or glycerol minimal media showed that (1) growth phenotypes at the endpoint of evolution are convergent and reproducible; (2) endpoints of evolution have different underlying gene expression states; and (3) the evolutionary gene expression response involves a large number of compensatory expression changes and a smaller number of adaptively beneficial expression changes common across evolution strains. Gene expression changes initially showed a large number of differentially expressed genes in response to an environmental change followed by a return of most genes to a baseline expression level, leaving a relatively small set of differentially expressed genes at the endpoint that varied between evolved populations.

The microbiome of the female reproductive tract has implications for women’s reproductive health. We examined the vaginal microbiome in two cohorts of women who experienced normal term births: a cross-sectionally sampled cohort of 613 pregnant and 1,969 non-pregnant women, focusing on 300 pregnant and 300 non-pregnant women of African, Hispanic or European ancestry case-matched for race, gestational age and household income; and a longitudinally sampled cohort of 90 pregnant women of African or non-African ancestry. In these women, the vaginal microbiome shifted during pregnancy toward Lactobacillus-dominated profiles at the expense of taxa often associated with vaginal dysbiosis. The shifts occurred early in pregnancy, followed predictable patterns, were associated with simplification of the metabolic capacity of the microbiome and were significant only in women of African or Hispanic ancestry. Both genomic and environmental factors are likely contributors to these trends, with socioeconomic status as a likely environmental influence.