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Biomedical subjects

Jochen Kumm

Publications and source records attributed to Jochen Kumm.

10 recordsLinked to original sources

Rapid and highly informative diagnostic assay for H5N1 influenza viruses.

A highly discriminative and information-rich diagnostic assay for H5N1 avian influenza would meet immediate patient care needs and provide valuable information for public health interventions, e.g., tracking of new and more dangerous variants by geographic area as well as avian-to-human or human-to-human transmission. In the present study, we have designed a rapid assay based on multilocus nucleic acid sequencing that focuses on the biologically significant regions of the H5N1 hemagglutinin gene. This allows the prediction of viral strain, clade, receptor binding properties, low- or high-pathogenicity cleavage site and glycosylation status. H5 HA genes were selected from nine known high-pathogenicity avian influenza subtype H5N1 viruses, based on their diversity in biologically significant regions of hemagglutinin and/or their ability to cause infection in humans. We devised a consensus pre-programmed pyrosequencing strategy, which may be used as a faster, more accurate alternative to de novo sequencing. The available data suggest that the assay described here is a reliable, rapid, information-rich and cost-effective approach for definitive diagnosis of H5N1 avian influenza. Knowledge of the predicted functional sequences of the HA will enhance H5N1 avian influenza surveillance efforts.

Animals↗

Molecular inversion probe analysis of gene copy alterations reveals distinct categories of colorectal carcinoma.

Genomic instability is a major feature of neoplastic development in colorectal carcinoma and other cancers. Specific genomic instability events, such as deletions in chromosomes and other alterations in gene copy number, have potential utility as biologically relevant prognostic biomarkers. For example, genomic deletions on chromosome arm 18q are an indicator of colorectal carcinoma behavior and potentially useful as a prognostic indicator. Adapting a novel genomic technology called molecular inversion probes which can determine gene copy alterations, such as genomic deletions, we designed a set of probes to interrogate several hundred individual exons of >200 cancer genes with an overall distribution covering all chromosome arms. In addition, >100 probes were designed in close proximity of microsatellite markers on chromosome arm 18q. We analyzed a set of colorectal carcinoma cell lines and primary colorectal tumor samples for gene copy alterations and deletion mutations in exons. Based on clustering analysis, we distinguished the different categories of genomic instability among the colorectal cancer cell lines. Our analysis of primary tumors uncovered several distinct categories of colorectal carcinoma, each with specific patterns of 18q deletions and deletion mutations in specific genes. This finding has potential clinical ramifications given the application of 18q loss of heterozygosity events as a potential indicator for adjuvant treatment in stage II colorectal carcinoma.

Biomarkers, Tumor↗

A latent variable model for chemogenomic profiling.

MOTIVATION: In haploinsufficiency profiling data, pleiotropic genes are often misclassified by clustering algorithms that impose the constraint that a gene or experiment belong to only one cluster. We have developed a general probabilistic model that clusters genes and experiments without requiring that a given gene or drug only appear in one cluster. The model also incorporates the functional annotation of known genes to guide the clustering procedure. RESULTS: We applied our model to the clustering of 79 chemogenomic experiments in yeast. Known pleiotropic genes PDR5 and MAL11 are more accurately represented by the model than by a clustering procedure that requires genes to belong to a single cluster. Drugs such as miconazole and fenpropimorph that have different targets but similar off-target genes are clustered more accurately by the model-based framework. We show that this model is useful for summarizing the relationship among treatments and genes affected by those treatments in a compendium of microarray profiles. AVAILABILITY: Supplementary information and computer code at http://genomics.lbl.gov/llda.

Computer Simulation↗

Microbes on the human vaginal epithelium.

Using solely a gene-based procedure, PCR amplification of the 16S ribosomal RNA gene coupled with very deep sequencing of the amplified products, the microbes on 20 human vaginal epithelia of healthy women have been identified and quantitated. The Lactobacillus content on these 20 healthy vaginal epithelia was highly variable, ranging from 0% to 100%. For four subjects, Lactobacillus was (virtually) the only bacterium detected. However, that Lactobacillus was far from clonal and was a mixture of species and strains. Eight subjects presented complex mixtures of Lactobacillus and other microbes. The remaining eight subjects had no Lactobacillus. Instead, Bifidobacterium, Gardnerella, Prevotella, Pseudomonas, or Streptococcus predominated.

Adult↗

Functional genomic analysis of the rates of protein evolution.

The evolutionary rates of proteins vary over several orders of magnitude. Recent work suggests that analysis of large data sets of evolutionary rates in conjunction with the results from high-throughput functional genomic experiments can identify the factors that cause proteins to evolve at such dramatically different rates. To this end, we estimated the evolutionary rates of >3,000 proteins in four species of the yeast genus Saccharomyces and investigated their relationship with levels of expression and protein dispensability. Each protein's dispensability was estimated by the growth rate of mutants deficient for the protein. Our analyses of these improved evolutionary and functional genomic data sets yield three main results. First, dispensability and expression have independent, significant effects on the rate of protein evolution. Second, measurements of expression levels in the laboratory can be used to filter data sets of dispensability estimates, removing variates that are unlikely to reflect real biological effects. Third, structural equation models show that although we may reasonably infer that dispensability and expression have significant effects on protein evolutionary rate, we cannot yet accurately estimate the relative strengths of these effects.

Evolution, Molecular↗

Mechanisms of haploinsufficiency revealed by genome-wide profiling in yeast.

Haploinsufficiency is defined as a dominant phenotype in diploid organisms that are heterozygous for a loss-of-function allele. Despite its relevance to human disease, neither the extent of haploinsufficiency nor its precise molecular mechanisms are well understood. We used the complete set of Saccharomyces cerevisiae heterozygous deletion strains to survey the genome for haploinsufficiency via fitness profiling in rich (YPD) and minimal media to identify all genes that confer a haploinsufficient growth defect. This assay revealed that approximately 3% of all approximately 5900 genes tested are haploinsufficient for growth in YPD. This class of genes is functionally enriched for metabolic processes carried out by molecular complexes such as the ribosome. Much of the haploinsufficiency in YPD is alleviated by slowing the growth rate of each strain in minimal media, suggesting that certain gene products are rate limiting for growth only in YPD. Overall, our results suggest that the primary mechanism of haploinsufficiency in yeast is due to insufficient protein production. We discuss the relevance of our findings in yeast to human haploinsufficiency disorders.

Alleles↗

Noise minimization in eukaryotic gene expression.

All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or "noise." Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection.

Gene Expression Regulation, Fungal↗

Global genetic analysis.

The introduction of molecular markers in genetic analysis has revolutionized medicine. These molecular markers are genetic variations associated with a predisposition to common diseases and individual variations in drug responses. Identification and genotyping a vast number of genetic polymorphisms in large populations are increasingly important for disease gene identification, pharmacogenetics and population-based studies. Among variations being analyzed, single nucleotide polymorphisms seem to be most useful in large-scale genetic analysis. This review discusses approaches for genetic analysis, use of different markers, and emerging technologies for large-scale genetic analysis where millions of genotyping need to be performed.

Animals↗

Chemogenomic profiling: identifying the functional interactions of small molecules in yeast.

We demonstrate the efficacy of a genome-wide protocol in yeast that allows the identification of those gene products that functionally interact with small molecules and result in the inhibition of cellular proliferation. Here we present results from screening 10 diverse compounds in 80 genome-wide experiments against the complete collection of heterozygous yeast deletion strains. These compounds include anticancer and antifungal agents, statins, alverine citrate, and dyclonine. In several cases, we identified previously known interactions; furthermore, in each case, our analysis revealed novel cellular interactions, even when the relationship between a compound and its cellular target had been well established. In addition, we identified a chemical core structure shared among three therapeutically distinct compounds that inhibit the ERG24 heterozygous deletion strain, demonstrating that cells may respond similarly to compounds of related structure. The ability to identify on-and-off target effects in vivo is fundamental to understanding the cellular response to small-molecule perturbants.

Antifungal Agents↗

Coevolution of pathogens and cultural practices: a new look at behavioral heterogeneity in epidemics.

The effect of heterogeneity within populations on the spread of infectious diseases has been a recent focus of research. Such heterogeneity may be, for example, spatial, temporal or behavioral in form. Generally, models that include population subdivision have assumed that individuals are permanently assigned to given behavioral states represented by the subpopulations. We consider a simple epidemic model in which a behavioral trait affects disease transmission, and this trait may be transferred among hosts as a consequence of social interaction. This creates a situation where the frequencies of different behavioral traits and disease states as well as their associations may change over time. We consider the impact of the culturally transmitted trait on the criterion for initial spread of the disease. We also explore the evolution of cultural traits in response to pathogen dynamics and show some conditions under which behavioral traits that reduce transmission evolve. We find that behaviors increasing the risk of infection can also evolve when they are inherently favored or when there is sufficient clustering of contacts between like behaviors.

Communicable Diseases↗