Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

Direct Comparisons of 2D and 3D Dental Microwear Proxies in Extant Herbivorous and Carnivorous Mammals

The analysis of dental microwear is commonly used by paleontologists and anthropologists to clarify the diets of extinct species, including herbivorous and carnivorous mammals. Currently, there are numerous methods employed to quantify dental microwear, varying in the types of microscopes used, magnifications, and the characterization of wear in both two dimensions and three dimensions. Results from dental microwear studies utilizing different methods are not directly comparable and human quantification of wear features (e.g., pits and scratches) introduces interobserver error, with higher error being produced by less experienced individuals. Dental microwear texture analysis (DMTA), which analyzes microwear features in three dimensions, alleviates some of the problems surrounding two-dimensional microwear methods by reducing observer bias. Here, we assess the accuracy and comparability within and between 2D and 3D dental microwear analyses in herbivorous and carnivorous mammals at the same magnification. Specifically, we compare observer-generated 2D microwear data from photosimulations of the identical scanned areas of DMTA in extant African bovids and carnivorans using a scanning white light confocal microscope at 100x magnification. Using this magnification, dental microwear features quantified in 2D were able to separate grazing and frugivorous bovids using scratch frequency; however, DMTA variables were better able to discriminate between disparate dietary niches in both carnivorous and herbivorous mammals. Further, results demonstrate significant interobserver differences in 2D microwear data, with the microwear index remaining the least variable between experienced observers, consistent with prior research. Overall, our results highlight the importance of reducing observer error and analyzing dental microwear in three dimensions in order to consistently interpret diets accurately.     

Calculation of effective diffusivities for biofilms and tissues.

In this study we describe a scheme for numerically calculating the effective diffusivity of cellular systems such as biofilms and tissues. This work extends previous studies in which we developed the macroscale representations of the transport equations for cellular systems based on the subcellular-scale transport and reaction processes. A finite-difference model is used to predict the effective diffusivity of a cellular system on the basis of the subcellular-scale geometry and transport parameters. The effective diffusivity is predicted for a complex three-dimensional structure that is based on laboratory observations of a biofilm, and these numerical predictions are compared with predictions from a simple analytical solution and with experimental data. Our results indicate that, under many practical circumstances, the simple analytical solution can be used to provide reasonable estimates of the effective diffusivity.     

Calcium binding mode of gamma-carboxyglutamic acids in conantokins.

Conantokin-T (con-T) and conantokin-G (con-G) are two highly homologous peptide toxins found in Conus venom. The former is a 21-residue peptide with four gamma-carboxyglutamic acid (Gla) residues (at positions 3, 4, 10 and 14), while the latter is a 17-residue peptide with five gamma-carboxyglutamic acid residues (at positions 3, 4, 7, 10 and 14). Despite the apparent similarity in number and relative positions of the gamma-carboxyglutamic acid residues, (113)Cd-NMR studies indicated a distinct metal binding behavior for con-G and con-T. There appears to be four binding sites in con-G in contrast to one metal binding site in con-T. To elucidate the mode of calcium binding by the gamma-carboxyglutamic acid residues in these conantokins, we designed various analogous peptides with their gamma-carboxyglutamic acid replaced by other amino acid residues. (113)Cd-NMR experiments on conantokin analogues reveal that the major difference in the number of metal binding sites between con-G and con-T is due to the residue at position 7. We also performed molecular simulations to calculate the relative binding free energies of several potential binding sites. Based on our theoretical and experimental results, we propose a 'four-site' binding model for conantokin-G and a 'single-site' binding model for conantokin-T.     

Dual Cyclin-Binding Domains Are Required for p107 To Function as a Kinase Inhibitor

The retinoblastoma (pRB) family of proteins includes three proteins known to suppress growth of mammalian cells. Previously we had found that growth suppression by two of these proteins, p107 and p130, could result from the inhibition of associated cyclin-dependent kinases (cdks). One important unresolved issue, however, is the mechanism through which inhibition occurs. Here we present in vivo and in vitro evidence to suggest that p107 is a bona fide inhibitor of both cyclin A-cdk2 and cyclin E-cdk2 that exhibits an inhibitory constant (K_i) comparable to that of the cdk inhibitor p21/WAF1. In contrast, pRB is unable to inhibit cdks. Further reminiscent of p21, a second cyclin-binding site was mapped to the amino-terminal portions of p107 and p130. This amino-terminal domain is capable of inhibiting cyclin-cdk2 complexes, although it is not a potent substrate for these kinases. In contrast, a carboxy-terminal fragment of p107 that contains the previously identified cyclin-binding domain serves as an excellent kinase substrate although it is unable to inhibit either kinase. Clustered point mutations suggest that the amino-terminal domain is functionally important for cyclin binding and growth suppression. Moreover, peptides spanning the cyclin-binding region are capable of interfering with p107 binding to cyclin-cdk2 complexes and kinase inhibition. Our ability to distinguish between p107 and p130 as inhibitors rather than simple substrates suggests that these proteins may represent true inhibitors of cdks.