Background: Recent studies of various human microbiome habitats have revealed thousands of bacterial species and the existence of large variation in communities of microorganisms in the same habitats across individual human subjects. Previous efforts to summarize this diversity, notably in the human gut and vagina, have categorized microbiome profiles by clustering them into community state types (CSTs). The functional relevance of specific CSTs has not been established. Objective: We investigate whether CSTs can be used to assess dynamics in the microbiome. Design: We conduct a re-analysis of five sequencing-based microbiome surveys derived from vaginal samples with repeated measures. Results: We observe that detection of a CST transition is largely insensitive to choices in methods for normalization or clustering. We find that healthy subjects persist in a CST for two to three weeks or more on average, while those with evidence of dysbiosis tend to change more often. Changes in CST can be gradual or occur over less than one day. Upcoming CST changes and switches to high-risk CSTs can be predicted with high accuracy in certain scenarios. Finally, we observe that presence of Gardnerella vaginalis is a strong predictor of an upcoming CST change. Conclusion: Overall, our results show that the CST concept is useful for studying microbiome dynamics.

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Neutralizing antibodies (inhibitors) to replacement Factor-VIII impair the effective management of hemophilia-A1. Individuals with hemophilia-A due to major F8 gene disruptions lack antigenically cross-reactive material in their plasma (CRM-negative) and prevalence of inhibitors is >60%. Conversely, subjects with missense mutations are CRM-positive and the prevalence of inhibitors is <10%2. Individuals with the intron-22-inversion (~50% of individuals with severe hemophilia-A) should be in the former group based on the genetic defect. Although these individuals are CRM-negative, only 20% of them develop inhibitors3. Here we demonstrate the presence of comparable levels of F8 mRNA and intracellular Factor-VIII protein in B-lymphoblastoid cells and liver biopsies from healthy controls and subjects with the intron-22-inversion. These results support the hypothesis that most individuals with the intron-22-inversion are tolerized to Factor-VIII and thus do not develop inhibitors. Furthermore we developed a pharmacogenetic algorithm that permits the stratification of inhibitor risk for sub-populations by predicting immunogenicity using, as input, the number of putative T-cell epitopes in the infused FVIII and the competence of MHC-Class-II molecules to present such epitopes. The algorithm exhibited significant accuracy in predicting inhibitors in 25 unrelated individuals with the intron-22-inversion (AUC = 0.890; P = 0.001).

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The development of epitope-based vaccines crucially relies on the ability to classify Human Leukocyte Antigen (HLA) molecules into sets that have similar peptide binding specificities, termed supertypes. In their seminal work, Sette and Sidney [21] defined 9 HLA class I supertypes, and claimed that these provide an almost perfect coverage of the entire repertoire of HLA class I molecules.HLA alleles are highly polymorphic and polygenic and therefore experimentally classifying each of these molecules to supertypes is at present an impossible task. Recently, a number of computational methods have been proposed for this task. These methods are based on defining protein similarity measures, derived from analysis of binding peptides or from analysis of the proteins themselves [13,7]. In this paper we define both peptide derived and protein derived similarity measures, which are based on learning distance functions. The peptide driven measure is defined using a peptide-peptide distance function, which is learnt using information about known binding and non-binding peptides [28]. The protein similarity measure is defined using a protein-protein distance function, which is learnt using information about alleles previously classified into supertypes by [21]. We compare the classification obtained by these two complimentary methods to previously suggested classification methods. In general, our results are in excellent agreement with the classifications suggested by Sette and Sidney [21] and with those reported in [13].There are two important advantages of our proposed distancebased approach. First, it makes use of two different and important immunological sources of information -HLA alleles and peptides that are known to bind or not bind to these alleles. Second, since each of our distance measures is trained using a different source of information, their combination can provide a more confident classification of alleles into supertypes.