Daniel E. Russ

Characterization of the human Ig heavy chain antigen binding complementarity determining region 3 using a newly developed software algorithm, JOINSOLVER.

We analyzed 77 nonproductive and 574 productive human VHDJH rearrangements with a newly developed program, JOINSOLVER. In the productive repertoire, the H chain complementarity determining region 3 (CDR3H) was significantly shorter (46.7 ± 0.5 nucleotides) than in the nonproductive repertoire (53.8 ± 1.9 nucleotides) because of the tendency to select rearrangements with less TdT activity and shorter D segments. Using criteria established by Monte Carlo simulations, D segments could be identified in 71.4% of nonproductive and 64.4% of productive rearrangements, with a mean of 17.6 ± 0.7 and 14.6 ± 0.2 retained germline nucleotides, respectively. Eight of 27 D segments were used more frequently than expected in the nonproductive repertoire, whereas 3 D segments were positively selected and 3 were negatively selected, indicating that both molecular mechanisms and selection biased the D segment usage. There was no bias for D segment reading frame (RF) use in the nonproductive repertoire, whereas negative selection of the RFs encoding stop codons and positive selection of RF2 that frequently encodes hydrophilic amino acids were noted in the productive repertoire. Except for serine, there was no consistent selection or expression of hydrophilic amino acids. A bias toward the pairing of 5′ D segments with 3′ JH segments was observed in the nonproductive but not the productive repertoire, whereas VH usage was random. Rearrangements using inverted D segments, DIR family segments, chromosome 15 D segments and multiple D segments were found infrequently. Analysis of the human CDR3H with JOINSOLVER has provided comprehensive information on the influences that shape this important Ag binding region of VH chains.

Gene Clustering Based on Clusterwide Mutual Information

Cluster analysis of gene-wide expression data from DNA microarray hybridization studies has proved to be a useful tool for identifying biologically relevant groupings of genes and constructing gene regulatory networks. The motivation for considering mutual information is its capacity to measure a general dependence among gene random variables. We propose a novel clustering strategy based on minimizing mutual information among gene clusters. Simulated annealing is employed to solve the optimization problem. Bootstrap techniques are employed to get more accurate estimates of mutual information when the data sample size is small. Moreover, we propose to combine the mutual information criterion and traditional distance criteria such as the Euclidean distance and the fuzzy membership metric in designing the clustering algorithm. The performances of the new clustering methods are compared with those of some existing methods, using both synthesized data and experimental data. It is seen that the clustering algorithm based on a combined metric of mutual information and fuzzy membership achieves the best performance. The supplemental material is available at www.gspsnap.tamu.edu/gspweb/zxb/glioma_zxb.

Analysis of somatic hypermutation in X-linked hyper-IgM syndrome shows specific deficiencies in mutational targeting

Subjects with X-linked hyper-IgM syndrome (X-HIgM) have a markedly reduced frequency of CD27(+) memory B cells, and their Ig genes have a low level of somatic hypermutation (SHM). To analyze the nature of SHM in X-HIgM, we sequenced 209 nonproductive and 926 productive Ig heavy chain genes. In nonproductive rearrangements that were not subjected to selection, as well as productive rearrangements, most of the mutations were within targeted RGYW, WRCY, WA, or TW motifs (R = purine, Y = pyrimidine, and W = A or T). However, there was significantly decreased targeting of the hypermutable G in RGYW motifs. Moreover, the ratio of transitions to transversions was markedly increased compared with normal. Microarray analysis documented that specific genes involved in SHM, including activation-induced cytidine deaminase (AICDA) and uracil-DNA glycosylase (UNG2), were up-regulated in normal germinal center (GC) B cells, but not induced by CD40 ligation. Similar results were obtained from light chain rearrangements. These results indicate that in the absence of CD40-CD154 interactions, there is a marked reduction in SHM and, specifically, mutations of AICDA-targeted G residues in RGYW motifs along with a decrease in transversions normally related to UNG2 activity.

Characterization of germline antibody libraries from human umbilical cord blood and selection of monoclonal antibodies to viral envelope glycoproteins: Implications for mechanisms of immune evasion and design of vaccine immunogens

Abstract We have previously observed that all known HIV-1 broadly neutralizing antibodies (bnAbs) are highly divergent from germline antibodies in contrast to bnAbs against Hendra virus, Nipah virus and SARS coronavirus (SARS CoV). We have hypothesized that because the germline antibodies are so different from the mature HIV-1-specific bnAbs they may not bind the epitopes of the mature antibodies and provided the first evidence to support this hypothesis by using individual putative germline-like predecessor antibodies. To further validate the hypothesis and understand initial immune responses to different viruses, two phage-displayed human cord blood-derived IgM libraries were constructed which contained mostly germline antibodies or antibodies with very low level of somatic hypermutations. They were panned against different HIV-1 envelope glycoproteins (Envs), SARS CoV protein receptor-binding domain (RBD), and soluble Hendra virus G protein (sG). Despite a high sequence and combinatorial diversity observed in the cord blood-derived IgM antibody repertoire, no enrichment for binders of Envs was observed in contrast to considerable specific enrichments produced with panning against RBD and sG; one of the selected monoclonal antibodies (against the RBD) was of high (nM) affinity with only few somatic mutations. These results further support and expand our initial hypothesis for fundamental differences in immune responses leading to elicitation of bnAbs against HIV-1 compared to SARS CoV and Hendra virus. HIV-1 uses a strategy to minimize or eliminate strong binding of germline antibodies to its Env; in contrast, SARS CoV and Hendra virus, and perhaps other viruses causing acute infections, can bind germline antibody or minimally somatically mutated antibodies with relatively high affinity which could be one of the reasons for the success of sG and RBD as vaccine immunogens.

Computer-based coding of free-text job descriptions to efficiently identify occupations in epidemiological studies

Background Mapping job titles to standardised occupation classification (SOC) codes is an important step in identifying occupational risk factors in epidemiological studies. Because manual coding is time-consuming and has moderate reliability, we developed an algorithm called SOCcer (Standardized Occupation Coding for Computer-assisted Epidemiologic Research) to assign SOC-2010 codes based on free-text job description components. Methods Job title and task-based classifiers were developed by comparing job descriptions to multiple sources linking job and task descriptions to SOC codes. An industry-based classifier was developed based on the SOC prevalence within an industry. These classifiers were used in a logistic model trained using 14 983 jobs with expert-assigned SOC codes to obtain empirical weights for an algorithm that scored each SOC/job description. We assigned the highest scoring SOC code to each job. SOCcer was validated in 2 occupational data sources by comparing SOC codes obtained from SOCcer to expert assigned SOC codes and lead exposure estimates obtained by linking SOC codes to a job-exposure matrix. Results For 11 991 case–control study jobs, SOCcer-assigned codes agreed with 44.5% and 76.3% of manually assigned codes at the 6-digit and 2-digit level, respectively. Agreement increased with the score, providing a mechanism to identify assignments needing review. Good agreement was observed between lead estimates based on SOCcer and manual SOC assignments (κ 0.6–0.8). Poorer performance was observed for inspection job descriptions, which included abbreviations and worksite-specific terminology. Conclusions Although some manual coding will remain necessary, using SOCcer may improve the efficiency of incorporating occupation into large-scale epidemiological studies.

Parallel Computing Methods for Analyzing Gene Expression Relationships

This paper presents a parallel program for assessing the codetermination of gene transcriptional states from large- scale simultaneous gene expression measurements with cDNA microarrays. The parallel program is based on a nonlinear statistical framework recently proposed for the analysis of gene interaction via multivariate expression arrays. Parallel computing is key in the application of the statistical framework to a large set of genes because a prohibitive amount of computer time is required on a classical single-CPU machine. Our parallel program, named the Parallel Analysis of Gene Expression (PAGE) program, exploits inherent parallelism exhibited in the proposed codetermination prediction models. By running PAGE on 64 processors in Beowulf, a clustered parallel system, an analysis of melanoma cDNA microarray expression data has been completed within 12 days of computer time, an analysis that would have required about one and half years on a single-CPU computing system. A data visualization program, named the Visualization of Gene Expression (VOGE) program, has been developed to help interpret the massive amount of quantitative information produced by PAGE. VOGE provides graphical data visualization and analysis tools with filters, histograms, and accesses to other genetic databanks for further analyses of the quantitative information.

Computer-Based Coding of Occupation Codes for Epidemiological Analyses

Mapping job titles to standardized occupation classification (SOC) codes is an important step in evaluating changes in health risks over time as measured in inspection databases. However, manual SOC coding is cost prohibitive for very large studies. Computer based SOC coding systems can improve the efficiency of incorporating occupational risk factors into large-scale epidemiological studies. We present a novel method of mapping verbatim job titles to SOC codes using a large table of prior knowledge available in the public domain that included detailed description of the tasks and activities and their synonyms relevant to each SOC code. Job titles are compared to our knowledge base to find the closest matching SOC code. A soft Jaccard index is used to measure the similarity between a previously unseen job title and the knowledge base. Additional information such as standardized industrial codes can be incorporated to improve the SOC code determination by providing additional context to break ties in matches.

HTJoinSolver: Human immunoglobulin VDJ partitioning using approximate dynamic programming constrained by conserved motifs

BackgroundPartitioning the human immunoglobulin variable region into variable (V), diversity (D), and joining (J) segments is a common sequence analysis step. We introduce a novel approximate dynamic programming method that uses conserved immunoglobulin gene motifs to improve performance of aligning V-segments of rearranged immunoglobulin (Ig) genes. Our new algorithm enhances the former JOINSOLVER algorithm by processing sequences with insertions and/or deletions (indels) and improves the efficiency for large datasets provided by high throughput sequencing.ResultsIn our simulations, which include rearrangements with indels, the V-matching success rate improved from 61% for partial alignments of sequences with indels in the original algorithm to over 99% in the approximate algorithm. An improvement in the alignment of human VDJ rearrangements over the initial JOINSOLVER algorithm was also seen when compared to the Stanford.S22 human Ig dataset with an online VDJ partitioning software evaluation tool.ConclusionsHTJoinSolver can rapidly identify V- and J-segments with indels to high accuracy for mutated sequences when the mutation probability is around 30% and 20% respectively. The D-segment is much harder to fit even at 20% mutation probability. For all segments, the probability of correctly matching V, D, and J increases with our alignment score.

Parallel Computation and Visualization Tools for Codetermination Analysis of Multivariate Gene Expression Relations

This chapter presents PAGE, a parallel program for analyzing the codetermination of gene transcriptional states from large-scale simultaneous gene expression measurements with cDNA microarrays, and its application to a large set of genes. Using PAGE, it was possible to compute coefficients of determination for all possible three-predictor sets from 587 genes for 58 targets in a reasonable amount of time. Given the limited samplesizes currently being used for microarray analysis, it is not necessary to go beyond three predictors at this time since the data are insufficient for four-predictor CoD estimation. As shown in Tables 13.1, 13.2, and 13.3, significant speedups are achieved by the parallelization when compared to the sequential version of the program modules.