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.     

A comparative Proteomics Analysis Identified Differentially Expressed Proteins in Pancreatic Cancer–Associated Stellate Cell Small Extracellular Vesicles

Human pancreatic stellate cells (HPSCs) are an essential stromal component and mediators of pancreatic ductal adenocarcinoma (PDAC) progression. Small extracellular vesicles (sEVs) are membrane-enclosed nanoparticles involved in cell-to-cell communications and are released from stromal cells within PDAC. A detailed comparison of sEVs from normal pancreatic stellate cells (HPaStec) and from PDAC-associated stellate cells (HPSCs) remains a gap in our current knowledge regarding stellate cells and PDAC. We hypothesized there would be differences in sEVs secretion and protein expression that might contribute to PDAC biology. To test this hypothesis, we isolated sEVs using ultracentrifugation followed by characterization by electron microscopy and Nanoparticle Tracking Analysis. We report here our initial observations. First, HPSC cells derived from PDAC tumors secrete a higher volume of sEVs when compared to normal pancreatic stellate cells (HPaStec). Although our data revealed that both normal and tumor-derived sEVs demonstrated no significant biological effect on cancer cells, we observed efficient uptake of sEVs by both normal and cancer epithelial cells. Additionally, intact membrane-associated proteins on sEVs were essential for efficient uptake. We then compared sEV proteins isolated from HPSCs and HPaStecs cells using liquid chromatography–tandem mass spectrometry. Most of the 1481 protein groups identified were shared with the exosome database, ExoCarta. Eighty-seven protein groups were differentially expressed (selected by 2-fold difference and adjusted p value ≤0.05) between HPSC and HPaStec sEVs. Of note, HPSC sEVs contained dramatically more CSE1L (chromosome segregation 1–like protein), a described marker of poor prognosis in patients with pancreatic cancer. Based on our results, we have demonstrated unique populations of sEVs originating from stromal cells with PDAC and suggest that these are significant to cancer biology. Further studies should be undertaken to gain a deeper understanding that could drive novel therapy.     

Impact of High Deductible Health Plans on Diabetes Care Quality and Outcomes: Systematic Review

ObjectiveTo provide a review of the impact of high deductible health plans (HDHPs) on the utilizations of services required for optimal management of diabetes and subsequent health outcomes.MethodsSystematic literature review of studies published between January 1, 2000, and May 7, 2021, was conducted that examined the impact of HDHP on diabetes monitoring (eg, recommended laboratory and surveillance testing), routine care (eg, ambulatory appointments), medication management (eg, medication initiation, adherence), and acute health care utilization (eg, emergency department visits, hospitalizations, incident complications).ResultsOf the 303 reviewed articles, 8 were relevant. These studies demonstrated that HDHPs lower spending at the expense of reduced high-value diabetes monitoring, routine care, and medication adherence, potentially contributing to the observed increases in acute health care utilization. Additionally, patient out-of-pocket costs for recommended screenings doubled, and total health care expenditures increased by 49.4% for HDHP enrollees compared with enrollees in traditional health plans. Reductions in disease monitoring and routine care and increases in acute health care utilization were greatest in lower-income patients. None of the studies examined the impact of HDHPs on access to diabetes self-management education, technology use, or glycemic control.ConclusionAlthough HDHPs reduce some health care utilization and costs, they appear to do so at the expense of limiting high-value care and medication adherence. Policymakers, providers, and payers should be more cognizant of the potential for negative consequences of HDHPs on patients’ health.     

Chromatographic separation of extruded iron-sulfur cores from the apoproteins of Clostridium pasteurianum and spinach ferredoxins in aqueous Triton X-100/urea

Iron-sulfur core extrusions from spinach [( 2Fe-2S]) and Clostridium pasteurianum (2[4Fe-4S]) ferredoxins in aqueous Triton X-100/urea containing excess benzenethiol yield quantitatively [FenSn(SPh)4]2- with n = 2 and n = 4, respectively. The iron-sulfur cluster can be separated from the corresponding apoprotein by rapid passage of the extrusion mixture over a small anaerobic column of Whatman DE-52 anion-exchange cellulose. Essentially quantitative recovery of [FenSn (SPh)4]2- is achieved in the eluate. The apoprotein remaining on the column can be eluted with 0.5 M NaCl. Most of the residual Triton X-100 and benzenethiol can be removed by passage of the apoprotein eluate over a small column of Bio-Beads SM-2, a hydrophobic polystyrene adsorbent. Apoprotein recovery is comparable to that obtained by other chromatographic methods. At least with spinach ferredoxin, the apoprotein prepared in this fashion can be reconstituted. The procedures developed in this work are potentially most applicable to selective removal of [2Fe-2S] and [4Fe-4S] centers from a multicenter enzyme without irreversible denaturation.     

Structural Decomposition Analysis of Raw Material Consumption

The aim of this article is to quantify the drivers for the changes in raw material consumption (domestic material consumption expressed in the form of all materials extracted and used in the production phase) in terms of technology, which refers to the concept of sustainable production; the product structure of final demand, which refers to the concept of sustainable consumption; and the volume of final demand, which is related to economic growth. We also aim to determine to what extent the technological development and a shift in product structure of the final demand compensate for the growth in final consumption volume. Therefore, we apply structural decomposition analysis (SDA) to the change in raw material consumption (RMC) of the Czech Republic between 2000 and 2007. To present the study in a broader context, we also show other material flow indicators for the Czech Republic for 2000 and 2007. Our findings of SDA show that final demand structure has a very limited effect on the change in material flows. The rapid change in final demand volume was not compensated for crude oil, metal ores, construction materials, food crops, and timber. For the material category of non‐iron metal ores, even the change in technology contributes to an increase in material flows. The largest relative increases are reported for non‐iron metal ores (38%) and construction materials (30%). The main changes in material flows related to the Czech Republic are driven by exports and enabled by imports, the main source of these increased material flows. This emphasizes the increasing role of international trade.     

An Extreme Value Analysis of Pollutant Concentrations in Surface Soils Due to Atmospheric Deposition

Risk assessments often rely on deterministic models using long-term averages or “steady-state” values of input variables. Such models do not provide the information needed to estimate acute exposures. This study uses extreme value theory to examine the frequency and magnitude of daily pollutant concentrations in surface soils predicted at six U.S. locations. Concentrations are predicted using a deposition-leaching model and 50 years of historical precipitation data. A stochastic model also is used to generate 1000 years of precipitation data as modeling inputs for each location. The annual maximum concentrations at each site are fitted to a Gumbel type I distribution to estimate occurrence probability. For soluble pollutants, the predicted concentration varied substantially with precipitation, and the maximum daily concentrations exceeded annual averages by 4 to 8 times. Observed and synthetic precipitation data produced similar results at most study locations, though the synthetic data provided a slightly better fit to the Gumbel type I distribution. The precipitation model allows the generation of representative precipitation data that extend limited historical records. The extreme value analysis facilitates the evaluation of maximum pollutant concentrations, return periods, and other statistics that are important in evaluating acute exposures.     

Amino acid analysis of bone from a possible case of prehistoric iron deficiency anemia from the American southwest

It is possible that dietary conditions can result in the production of abnormal bone protein. For example, a heavily maize-dependent diet could be deficient in one or more essential amino acids necessary to normal human biochemistry and consequently necessary for normal bone protein synthesis. Amino acid analysis of bone tissues, thus, could provide a useful diagnostic tool in paleopathology. To test this potential we have compared the amino acid analyses of bone samples from a prehistoric Southwest Indian child exhibiting porotic hyperostosis with samples taken from (1) two children's skeletons lacking bone lesions but from the same area and time, (2) a modern child who died from accidental causes, and (3) adult human compact bone. Analytical results of the nonpathological prehistoric specimens were virtually identical to that of the modern infant, indicating remarkable preservation of bone protein. The pathological bone sample differed from the three control specimens by having as much as 25% less of those amino acids containing hydroxyl group and acidic side chains. We interpret the amino acid profile for the diseased child as indicating the presence of a greater proportion of helical protein (or less noncollagenous protein) as well as a lowered degree of hydroxylation of proline and lysine. One explanation for our data is that protein biosynthesis is altered in the child exhibiting porotic hyperostosis, and either some proteins important in the early phases of mineralization are not produced in sufficient quantity, or some necessary enzyme cofactors (e.g., dietary ferrous ions) are missing. We conclude that our data are compatible with, but do not prove, the hypothesis that the porotic hyperostosis exhibited by the Southwest Indian child is the result of iron deficiency anemia.     

Mass spectrometry techniques for imaging and detection of metallodrugs

Undoubtedly, metallomic approaches based on mass spectrometry have evolved into essential tools supporting the drug development of novel metal-based anticancer drugs. This article will comment on the state-of-the-art instrumentation and highlight some of the recent analytical advances beyond routine, especially focusing on the latest developments in inductively coupled plasma-mass spectrometry (ICP-MS). Mass spectrometry-based bioimaging and single-cell methods will be presented, paving the way to exciting investigations of metal-based anticancer drugs in heterogeneous and structurally, as well as functionally complex solid tumor tissues.     

An order-specific monoclonal antibody to Diptera reveals the impact of alternative prey on spider feeding behavior in a complex food web

Generalist predators have the capacity to restrict pest population growth, especially early in the season before densities increase. However, their polyphagous feeding habits sometimes translate into reduced pest consumption when they target alternative prey. An order-specific monoclonal antibody was developed to examine the strength of trophic connections between Diptera, a major category of non-pest prey, and linyphiid spiders in alfalfa. We report the development and characterization of a monoclonal antibody with order-level specificity to Diptera. This antibody elicited strong absorbance to 22 Diptera from 13 families, no false-positive reactivity to non-dipteran invertebrates, and antigen detection periods following prey consumption that were comparable between spiders. Over 900 field-collected females of the linyphiid spiders Erigone autumnalis and Bathyphantes pallidus were screened for Diptera antigen. Significantly more B. pallidus screened positive for Diptera (40%) compared to E. autumnalis (16%), indicating differential reliance on these prey. In parallel with the collection of spiders for gut-content analysis, prey availability was estimated at web sites. The two spiders exhibited different feeding responses to prey availability. Consumption of Diptera by B. pallidus was strongly correlated with Diptera abundance whilst the availability of other potential prey did not influence predation rates. Conversely, E. autumnalis did not prey upon Diptera in proportion to availability, but increased Collembola activity-density reduced dipteran consumption. Integration of molecular gut-content analysis with precise sampling of prey demonstrated how two closely related linyphiid spiders exhibit different feeding responses to the availability of prey under natural field conditions. Elucidating the feeding preferences of natural enemies is critical to effective incorporation of biological control by generalist predators in the management of agricultural pests.