Emerging evidence indicates a central role for the microbiome in immunity. However, causal evidence in humans is sparse. Here, we administered broad-spectrum antibiotics to healthy adults prior and subsequent to seasonal influenza vaccination. Despite a 10,000-fold reduction in gut bacterial load and long-lasting diminution in bacterial diversity, antibody responses were not significantly affected. However, in a second trial of subjects with low pre-existing antibody titers, there was significant impairment in H1N1-specific neutralization and binding IgG1 and IgA responses. In addition, in both studies antibiotics treatment resulted in (1) enhanced inflammatory signatures (including AP-1/NR4A expression), observed previously in the elderly, and increased dendritic cell activation;(2) divergent metabolic trajectories, with a 1,000-fold reduction in serum secondary bile acids, which was highly correlated with AP-1/NR4A signaling and inflammasome activation. Multiomics integration revealed significant associations between bacterial species and metabolic phenotypes, highlighting a key role for the microbiome in modulating human immunity.

Interpreting variants, especially noncoding ones, in the increasing number of personal genomes is challenging. We used patterns of polymorphisms in functionally annotated regions in 1092 humans to identify deleterious variants; then we experimentally validated candidates. We analyzed both coding and noncoding regions, with the former corroborating the latter. We found regions particularly sensitive to mutations (“ultrasensitive”) and variants that are disruptive because of mechanistic effects on transcription-factor binding (that is, “motif-breakers”). We also found variants in regions with higher network centrality tend to be deleterious. Insertions and deletions followed a similar pattern to single-nucleotide variants, with some notable exceptions (e.g., certain deletions and enhancers). On the basis of these patterns, we developed a computational tool (FunSeq), whose application to ~90 cancer genomes reveals nearly a hundred candidate noncoding drivers.

In an effort to understand molecular mechanisms of human disease and to determine genes responsible, we systematically examine relationships between 3,949 genes, 62,663 mutations and 3,453 associated disorders within the framework of a three-dimensional structurally resolved human interactome, consisting of 4,222 high-quality binary protein-protein interactions with their atomic-resolution interfaces. We find that in-frame mutations (missense point mutations and in-frame insertions and deletions) are enriched on the interaction interfaces of proteins associated with the corresponding disorders, indicating that alteration of specific interactions by in-frame disease mutations is critical in understanding the pathogenesis of many genes. Furthermore, locations of mutations on proteins with regard to interaction interfaces are significantly associated with underlying pathogenic processes and the disease specificity for different mutations of the same gene. Based on these findings, we generate 292 new gene candidates for 694 unknown disease-to-gene associations with proposed molecular mechanism hypotheses, readily expanding our understanding of human genetic diseases and corresponding therapeutic possibilities.

BackgroundA global map of protein-protein interactions in cellular systems provides key insights into the workings of an organism. A repository of well-validated high-quality protein-protein interactions can be used in both large- and small-scale studies to generate and validate a wide range of functional hypotheses.ResultsWe develop HINT (http://hint.yulab.org) - a database of high-quality protein-protein interactomes for human, Saccharomyces cerevisiae, Schizosaccharomyces pombe, and Oryza sativa. These were collected from several databases and filtered both systematically and manually to remove low-quality/erroneous interactions. The resulting datasets are classified by type (binary physical interactions vs. co-complex associations) and data source (high-throughput systematic setups vs. literature-curated small-scale experiments). We find strong sociological sampling biases in literature-curated datasets of small-scale interactions. An interactome without such sampling biases was used to understand network properties of human disease-genes - hubs are unlikely to cause disease, but if they do, they usually cause multiple disorders.ConclusionsHINT is of significant interest to researchers in all fields of biology as it addresses the ubiquitous need of having a repository of high-quality protein-protein interactions. These datasets can be utilized to generate specific hypotheses about specific proteins and/or pathways, as well as analyzing global properties of cellular networks. HINT will be regularly updated and all versions will be tracked.

Graphical Abstract Highlights d NK cell-activating antibodies are selectively transferred across the placenta d Digalactosylated Fc glycans are preferentially transferred across the placenta d Digalactosylated antibodies bind more effectively to FcRn and FCGR3A d Although immature, neonatal NK cells are highly responsive to immune complexes SUMMARY Despite the worldwide success of vaccination, newborns remain vulnerable to infections. While neonatal vaccination has been hampered by maternal antibody-mediated dampening of immune responses, enhanced regulatory and tolerogenic mechanisms, and immune system immaturity, maternal pre-natal immunization aims to boost neonatal immunity via antibody transfer to the fetus. However, emerging data suggest that antibodies are not transferred equally across the placenta. To understand this, we used systems serology to define Fc features associated with antibody transfer. The Fc-profile of neonatal and maternal antibodies differed, skewed toward natural killer (NK) cell-activating antibodies.This selective transfer was linked to digalactosylated Fc-glycans that selectively bind FcRn and FCGR3A, resulting in transfer of antibodies able to efficiently leverage innate immune cells present at birth. Given emerging data that vaccination may direct antibody glycosylation, our study provides insights for the development of next-generation maternal vaccines designed to elicit antibodies that will most effectively aid neonates. Antibodies against pertussis derived filamentous hemagglutinin (FHA), pertactin (PTN), fimbriae (FIM), and pertussis toxin (PTX) antigens were compared in 14 mother:cord pairs. (A) The flow cytometric plots depict the gating strategy for antibody dependent cellular phagocytosis (ADCP). (B) The connected dot-plot shows the phagocytic activity across mother:cord pairs. (C) The box-and-whisker plot shows the transfer ratio of ADCP. The dotted line indicates a 100% transfer efficiency (equivalent levels across both compartments). (D) The flow plots highlight the gating strategy for antibody dependent neutrophil phagocytosis (ADNP). (E) The dot-plot shows the relationship between ADNP activity across mother:cord pairs for each antigen-specificity. (F) The whisker plots show the transfer ratio for ADNP. (G) The flow plots highlighting the gating strategy for the NK cell activation assay. (H-J) The dot-line plots show NK-dependent degranulation plotted as the percentage of NK cells positive for CD107a (H), IFNg (I), and MIP-1b (J). (K-M) The whisker plots depict the transfer ratio across the three NK cell activation markers, CD107a (K), IFNg (L), and MIP-1b (M).