Purification and Immunogenicity of a Recombinant Bordetella pertussis S1S3FHA Fusion Protein Expressed by Streptococcus gordonii

Acellular pertussis vaccines typically consist of antigens isolated from Bordetella pertussis, and pertussis toxin (PT) and filamentous hemagglutinin (FHA) are two prominent components. One of the disadvantages of a multiple-component vaccine is the cost associated with the production of the individual components. In this study, we constructed an in-frame fusion protein consisting of PT fragments (179 amino acids of PT subunit S1 and 180 amino acids of PT subunit S3) and a 456-amino-acid type I domain of FHA. The fusion protein was expressed by the commensal oral bacterium Streptococcus gordonii. The fusion protein was secreted into the culture medium as an expected 155-kDa protein, which was recognized by a polyclonal anti-PT antibody, a monoclonal anti-S1 antibody, and a monoclonal anti-FHA antibody. The fusion protein was purified from the culture supernatant by affinity and gel permeation chromatography. The immunogenicity of the purified fusion protein was assessed in BALB/c mice by performing parenteral and mucosal immunization experiments. When given parenterally, the fusion protein elicited a very strong antibody titer against the FHA type I domain, a moderate titer against native FHA, and a weak titer against PT. When given mucosally, it elicited a systemic response and a mucosal response to FHA and PT. In Western blots, the immune sera recognized the S1, S3, and S2 subunits of PT. These data collectively indicate that fragments of the pertussis vaccine components can be expressed in a single fusion protein by S. gordonii and that the fusion protein is immunogenic. This multivalent fusion protein approach may be used in designing a new generation of acellular pertussis vaccines.     

Weight History in Clinical Practice: The State of the Science and Future Directions

Eliciting a weight history can provide clinically important information to aid in treatment decision‐making. This view is consistent with the life course perspective of obesity and the aim of patient‐centered care, one of six domains of health care quality. However, thus far, the value and practicality of including a weight history in the clinical assessment and treatment of patients with obesity have not been systematically explored. For these reasons, the Clinical Committee of The Obesity Society established a task force to review and assess the available evidence to address five key questions. It is concluded that weight history is an essential component of the medical history for patients presenting with overweight or obesity, and there are strong and emerging data that demonstrate the importance of life stage, duration of exposure to obesity, maximum BMI, and group‐based trajectory modeling in predicting risk for increased morbidity and mortality. Consideration of these and other patient‐specific factors may improve risk stratification and clinical decision‐making for screening, counseling, and management. Recommendations are provided for the key elements that should be included in a weight history, and several needs for future clinical research are outlined.     

The genetic history of Cochin Jews from India

Cochin Jews form a small and unique community on the Malabar coast in southwest India. While the arrival time of any putative Jewish ancestors of the community has been speculated to have taken place as far back as biblical times (King Solomon’s era), a Jewish community in the Malabar coast has been documented only since the 9th century CE. Here, we explore the genetic history of Cochin Jews by collecting and genotyping 21 community members and combining the data with that of 707 individuals from 72 other Indian, Jewish, and Pakistani populations, together with additional individuals from worldwide populations. We applied comprehensive genome-wide analyses based on principal component analysis, F _ST, ADMIXTURE, identity-by-descent sharing, admixture linkage disequilibrium decay, haplotype sharing, allele sharing autocorrelation decay and contrasting the X chromosome with the autosomes. We find that, as reported by several previous studies, the genetics of Cochin Jews resembles that of local Indian populations. However, we also identify considerable Jewish genetic ancestry that is not present in any other Indian or Pakistani populations (with the exception of the Jewish Bene Israel, which we characterized previously). Combined, Cochin Jews have both Jewish and Indian ancestry. Specifically, we detect a significant recent Jewish gene flow into this community 13–22 generations (~470–730 years) ago, with contributions from Yemenite, Sephardi, and Middle-Eastern Jews, in accordance with historical records. Genetic analyses also point to high endogamy and a recent population bottleneck in this population, which might explain the increased prevalence of some recessive diseases in Cochin Jews.     

Ontology-Based Meta-Analysis of Global Collections of High-Throughput Public Data

Background

The investigation of the interconnections between the molecular and genetic events that govern biological systems is essential if we are to understand the development of disease and design effective novel treatments. Microarray and next-generation sequencing technologies have the potential to provide this information. However, taking full advantage of these approaches requires that biological connections be made across large quantities of highly heterogeneous genomic datasets. Leveraging the increasingly huge quantities of genomic data in the public domain is fast becoming one of the key challenges in the research community today.

Methodology/Results

We have developed a novel data mining framework that enables researchers to use this growing collection of public high-throughput data to investigate any set of genes or proteins. The connectivity between molecular states across thousands of heterogeneous datasets from microarrays and other genomic platforms is determined through a combination of rank-based enrichment statistics, meta-analyses, and biomedical ontologies. We address data quality concerns through dataset replication and meta-analysis and ensure that the majority of the findings are derived using multiple lines of evidence. As an example of our strategy and the utility of this framework, we apply our data mining approach to explore the biology of brown fat within the context of the thousands of publicly available gene expression datasets.

Conclusions

Our work presents a practical strategy for organizing, mining, and correlating global collections of large-scale genomic data to explore normal and disease biology. Using a hypothesis-free approach, we demonstrate how a data-driven analysis across very large collections of genomic data can reveal novel discoveries and evidence to support existing hypothesis.     

Pedigree reconstruction using identity by descent

Can we find the family trees, or pedigrees, that relate the haplotypes of a group of individuals? Collecting the genealogical information for how individuals are related is a very time-consuming and expensive process. Methods for automating the construction of pedigrees could stream-line this process. While constructing single-generation families is relatively easy given whole genome data, reconstructing multi-generational, possibly inbred, pedigrees is much more challenging. This article addresses the important question of reconstructing monogamous, regular pedigrees, where pedigrees are regular when individuals mate only with other individuals at the same generation. This article introduces two multi-generational pedigree reconstruction methods: one for inbreeding relationships and one for outbreeding relationships. In contrast to previous methods that focused on the independent estimation of relationship distances between every pair of typed individuals, here we present methods that aim at the reconstruction of the entire pedigree. We show that both our methods out-perform the state-of-the-art and that the outbreeding method is capable of reconstructing pedigrees at least six generations back in time with high accuracy. The two programs are available at http://cop.icsi.berkeley.edu/cop/.     

Correlated mutations: advances and limitations. A study on fusion proteins and on the Cohesin-Dockerin families

Correlated mutations have been repeatedly exploited for intramolecular contact map prediction. Over the last decade these efforts yielded several methods for measuring correlated mutations. Nevertheless, the application of correlated mutations for the prediction of intermolecular interactions has not yet been explored. This gap is due to several obstacles, such as 3D complexes availability, paralog discrimination, and the availability of sequence pairs that are required for inter- but not intramolecular analyses. Here we selected for analysis fusion protein families that bypass some of these obstacles. We find that several correlated mutation measurements yield reasonable accuracy for intramolecular contact map prediction on the fusion dataset. However, the accuracy level drops sharply in intermolecular contacts prediction. This drop in accuracy does not occur always. In the Cohesin-Dockerin family, reasonable accuracy is achieved in the prediction of both intra- and intermolecular contacts. The Cohesin-Dockerin family is well suited for correlated mutation analysis. Because, however, this family constitutes a special case (it has radical mutations, has domain repeats, within each species each Dockerin domain interacts with each Cohesin domain, see below), the successful prediction in this family does not point to a general potential in using correlated mutations for predicting intermolecular contacts. Overall, the results of our study indicate that current methodologies of correlated mutations analysis are not suitable for large-scale intermolecular contact prediction, and thus cannot assist in docking. With current measurements, sequence availability, sequence annotations, and underdeveloped sequence pairing methods, correlated mutations can yield reasonable accuracy only for a handful of families.     

Using DNA pools for genotyping trios

The genotyping of mother–father–child trios is a very useful tool in disease association studies, as trios eliminate population stratification effects and increase the accuracy of haplotype inference. Unfortunately, the use of trios for association studies may reduce power, since it requires the genotyping of three individuals where only four independent haplotypes are involved. We describe here a method for genotyping a trio using two DNA pools, thus reducing the cost of genotyping trios to that of genotyping two individuals. Furthermore, we present extensions to the method that exploit the linkage disequilibrium structure to compensate for missing data and genotyping errors. We evaluated our method on trios from CEPH pedigree 66 of the Coriell Institute. We demonstrate that the error rates in the genotype calls of the proposed protocol are comparable to those of standard genotyping techniques, although the cost is reduced considerably. The approach described is generic and it can be applied to any genotyping platform that achieves a reasonable precision of allele frequency estimates from pools of two individuals. Using this approach, future trio-based association studies may be able to increase the sample size by 50% for the same cost and thereby increase the power to detect associations.