Biology subjects

Ed Reznik

Publications and source records attributed to Ed Reznik.

4 recordsLinked to original sources

bioRxiv2016

Design principles of autocatalytic cycles constrain enzyme kinetics and force over-expression at flux branch points

A set of chemical reactions that require a metabolite to synthesize more of that metabolite is an autocatalytic cycle. Here we show that most of the reactions in the core of central carbon metabolism are part of compact autocatalytic cycles. Such metabolic designs must meet specific conditions to support stable fluxes, hence avoiding depletion of intermediate metabolites. As such, they are subjected to constraints that may seem counter-intuitive: the enzymes of branch reactions out of the cycle must be overexpressed and the affinity of these enzymes to their substrates must be relatively weak. We use recent quantitative proteomics and fluxomics measurements to show that the above conditions hold for functioning cycles in central carbon metabolism of E.coli. This work demonstrates that the topology of a metabolic network can shape kinetic parameters of enzymes and lead to seemingly wasteful enzyme usage.

Systems Biology↗

bioRxiv2015

Mitochondrial DNA Copy Number Variation Across Human Cancers

In cancer, mitochondrial dysfunction, through mutations, deletions, and changes in copy number of mitochondrial DNA (mtDNA), contributes to the malignant transformation and progress of tumors. Here, we report the first large-scale survey of mtDNA copy number variation across 21 distinct solid tumor types, examining over 13,000 tissue samples profiled with next-generation sequencing methods. We find a tendency for cancers, especially of the bladder and kidney, to be significantly depleted of mtDNA, relative to matched normal tissue. We show that mtDNA copy number is correlated to the expression of mitochondrially-localized metabolic pathways, suggesting that mtDNA copy number variation reflect gross changes in mitochondrial metabolic activity. Finally, we identify a subset of tumor-type-specific somatic alterations, including IDH1 and NF1 mutations in gliomas, whose incidence is strongly correlated to mtDNA copy number. Our findings suggest that modulation of mtDNA copy number may play a role in the pathology of cancer.

Genomics↗

bioRxiv2015

Protein Domain Hotspots Reveal Functional Mutations across Genes in Cancer

In cancer genomics, frequent recurrence of mutations in independent tumor samples is a strong indication of functional impact. However, rare functional mutations can escape detection by recurrence analysis for lack of statistical power. We address this problem by extending the notion of recurrence of mutations from single genes to gene families that share homologous protein domains. In addition to lowering the threshold of detection, this sharpens the functional interpretation of the impact of mutations, as protein domains more succinctly embody function than entire genes. Mapping mutations in 22 different tumor types to equivalent positions in multiple sequence alignments of protein domains, we confirm well-known functional mutation hotspots and make two types of discoveries: 1) identification and functional interpretation of uncharacterized rare variants in one gene that are equivalent to well-characterized mutations in canonical cancer genes, such as uncharacterized ERBB4 (S303F) mutations that are analogous to canonical ERRB2 (S310F) mutations in the furin-like domain, and 2) detection of previously unknown mutation hotspots with novel functional implications. With the rapid expansion of cancer genomics projects, protein domain hotspot analysis is likely to provide many more leads linking mutations in proteins to the cancer phenotype.

Genomics↗

bioRxiv2014

Extensive Decoupling of Metabolic Genes in Cancer

Tumorigenesis involves, among other factors, the alteration of metabolic gene expression to support malignant, unrestrained proliferation. Here, we examine how the altered metabolism of cancer cells is reflected in changes in co-expression patterns of metabolic genes between normal and tumor tissues. Our emphasis on changes in the interactions of pairs of genes, rather than on the expression levels of individual genes, exposes changes in the activity of metabolic pathways which do not necessarily show clear patterns of over- or under-expression. We report the existence of key metabolic genes which act as hubs of differential co-expression, showing significantly different co-regulation patterns between normal and tumor states. Notably, we find that the extent of differential co-expression of a gene is only weakly correlated with its differential expression, suggesting that the two measures probe different features of metabolism. By leveraging our findings against existing pathway knowledge, we extract networks of functionally connected differentially co-expressed genes and the transcription factors which regulate them. Doing so, we identify a previously unreported network of dysregulated metabolic genes in clear cell renal cell carcinoma transcriptionally controlled by the transcription factor HNF4A. While HNF4A shows no significant differential expression, the co-expression HNF4A and several of its regulated target genes in normal tissue is completely abrogated in tumor tissue. Finally, we aggregate the results of differential co-expression analysis across seven distinct cancer types to identify pairs of metabolic genes which may be recurrently dysregulated. Among our results is a cluster of four genes, all located in the mitochondrial electron transport chain, which show significant loss of co-expression in tumor tissue, pointing to potential mitochondrial dysfunction in these tumor types.

Systems Biology↗