Metabolic collaboration between cells in the tumor microenvironment has a negligible effect on tumor growth

The tumor microenvironment is composed of a complex mixture of different cell types interacting under conditions of nutrient deprivation, but the metabolism therein is not fully understood due to difficulties in measuring metabolic fluxes and exchange of metabolites between different cell types in vivo. Genome-scale metabolic modeling enables estimation of such exchange fluxes as well as an opportunity to gain insight into the metabolic behavior of individual cell types. Here, we estimated the availability of nutrients and oxygen within the tumor microenvironment using concentration measurements from blood together with a metabolite diffusion model. In addition, we developed an approach to efficiently apply enzyme usage constraints in a comprehensive metabolic model of human cells. The combined modeling reproduced severe hypoxic conditions and the Warburg effect, and we found that limitations in enzymatic capacity contribute to cancer cells' preferential use of glutamine as a substrate to the citric acid cycle. Furthermore, we investigated the common hypothesis that some stromal cells are exploited by cancer cells to produce metabolites useful for the cancer cells. We identified over 200 potential metabolites that could support collaboration between cancer cells and cancer-associated fibroblasts, but when limiting to metabolites previously identified to participate in such collaboration, no growth advantage was observed. Our work highlights the importance of enzymatic capacity limitations for cell behaviors and exemplifies the utility of enzyme-constrained models for accurate prediction of metabolism in cells and tumor microenvironments.

Brain energy metabolism is optimized to minimize the cost of enzyme synthesis and transport

The energy metabolism of the brain is poorly understood partly due to the complex morphology of neurons and fluctuations in ATP demand over time. To investigate this, we used metabolic models that estimate enzyme usage per pathway, enzyme utilization over time, and enzyme transportation to evaluate how these parameters and processes affect ATP costs for enzyme synthesis and transportation. Our models show that the total enzyme maintenance energy expenditure of the human body depends on how glycolysis and mitochondrial respiration are distributed both across and within cell types in the brain. We suggest that brain metabolism is optimized to minimize the ATP maintenance cost by distributing the different ATP generation pathways in an advantageous way across cell types and potentially also across synapses within the same cell. Our models support this hypothesis by predicting export of lactate from both neurons and astrocytes during peak ATP demand, reproducing results from experimental measurements reported in the literature. Furthermore, our models provide potential explanation for parts of the astrocyte-neuron lactate shuttle theory, which is recapitulated under some conditions in the brain, while contradicting other aspects of the theory. We conclude that enzyme usage per pathway, enzyme utilization over time, and enzyme transportation are important factors for defining the optimal distribution of ATP production pathways, opening a broad avenue to explore in brain metabolism.

Do improvements in clinical practice guidelines alter pregnancy outcomes in asthmatic women? A single-center retrospective cohort study

OBJECTIVE

Asthma occurs in ∼17% of Australian pregnancies and is associated with adverse perinatal outcomes, which worsen with poor asthma control . Consequently, the South Australian 'Asthma in Pregnancy' perinatal guidelines were revised in 2012 to address management according to severity. This study investigated if these revised guidelines reduced the impact of maternal asthma on risks of adverse perinatal outcomes before (Epoch 1, 2006-2011) and after the revision (Epoch 2, 2013-2018).

METHODS

Routinely collected perinatal and neonatal datasets from the Women's and Children's Hospital (Adelaide, Australia) were linked. Maternal asthma (prevalence:7.5%) was defined as asthma medication use or symptoms described to midwives. In imputation (n = 59131) and complete case datasets (n = 49594), analyses were conducted by inverse proportional weighting and multivariate logistic regression, accounting for confounders.

RESULTS

Overall, maternal asthma was associated with increased risks of any antenatal corticosteroid treatment for threatened preterm birth (aOR 1.319, 95% CI 1.078-1.614), any Caesarean section (aOR 1.196, 95% CI 1.059-1.351), Caesarean section without labor (aOR 1.241, 95% CI 1.067-1.444), intrauterine growth restriction (IUGR, aOR 1.285, 95% CI 1.026-1.61), and small for gestational age (aOR 1.324, 95% CI 1.136-1.542). After guideline revision, asthma-associated risks of any Caesarean section (p < 0.001), any antenatal corticosteroids (p = 0.041), and small for gestational age (p = 0.050), but not IUGR and Caesarean section without labour, were reduced.

CONCLUSIONS

Clinical practice guidelines based on the latest evidence do not guarantee clinical efficacy. Since adverse perinatal outcomes did not all improve, this work highlights the need to evaluate the ongoing impact of guidelines on clinical outcomes.

Enhanced metabolism and negative regulation of ER stress support higher erythropoietin production in HEK293 cells

Recombinant protein production can cause severe stress on cellular metabolism, resulting in limited titer and product quality. To investigate cellular and metabolic characteristics associated with these limitations, we compare HEK293 clones producing either erythropoietin (EPO) (secretory) or GFP (non-secretory) protein at different rates. Transcriptomic and functional analyses indicate significantly higher metabolism and oxidative phosphorylation in EPO producers compared with parental and GFP cells. In addition, ribosomal genes exhibit specific expression patterns depending on the recombinant protein and the production rate. In a clone displaying a dramatically increased EPO secretion, we detect higher gene expression related to negative regulation of endoplasmic reticulum (ER) stress, including upregulation of ATF6B, which aids EPO production in a subset of clones by overexpression or small interfering RNA (siRNA) knockdown. Our results offer potential target pathways and genes for further development of the secretory power in mammalian cell factories.

Salivary antibodies are detected with a commercial anti-SARS-CoV-2 assay only after two doses of vaccine using serum thresholds

Salivary matrix is an appealing specimen type for SARS-CoV-2 serology because of ease of collection and potential for concurrent nucleic acid testing. We address the feasibility of salivary matrix to detect anti-SARS-CoV-2 antibodies using two commercially available anti-SARS-CoV-2 Total antibody assays including analytical validations.

Matched serum and saliva samples were collected from 10 convalescent COVID-19 patients and tested using a quantitative anti-Spike Total antibody assay and a qualitative anti-Nucleocapsid Total antibody assay from Roche Diagnostics. Both assays were 100% sensitive for COVID-19 history in serum. However, saliva samples were below serum positivity thresholds. We then collected longitudinal salivary samples from a volunteer cohort receiving the Pfizer-BioNTech COVID-19 BNT162b2 vaccine. Saliva was negative for anti-SARS-CoV-2 antibodies at 5 time points after a single dose of vaccine including day 56 when mean (min-max) serum levels of anti-Spike Total antibody were 79.0 U/mL (46.6–110.1) (N = 8). After a second vaccine dose serum-matched samples were beyond the analytical measuring range of the assay (>2500 U/mL), and detection of salivary anti-Spike Total antibody was achieved in all volunteers (12.2 U/mL [2.0–32.7]) (N = 11) 30 days after the second dose. Mean anti-Spike Total antibody levels in serum (1558 U/mL (434–>2500)) and saliva (2.6 U/mL (<0.4–11.4)) declined 216–233 days after the first dose of vaccine (P < 0.05); and saliva was 75% sensitive for two doses of vaccination at this latter time point (N = 25). These data suggest commercial assays are capable of detecting vaccine status after two doses of BNT162b2 vaccine up to 6 months and could inform COVID-19 surveillance.

Genome-scale metabolic network reconstruction of model animals as a platform for translational research

Genome-scale metabolic models (GEMs) are used extensively for analysis of mechanisms underlying human diseases and metabolic malfunctions. However, the lack of comprehensive and high-quality GEMs for model organisms restricts translational utilization of omics data accumulating from the use of various disease models. Here we present a unified platform of GEMs that covers five major model animals, including Mouse1 (Mus musculus), Rat1 (Rattus norvegicus), Zebrafish1 (Danio rerio), Fruitfly1 (Drosophila melanogaster), and Worm1 (Caenorhabditis elegans). These GEMs represent the most comprehensive coverage of the metabolic network by considering both orthology-based pathways and species-specific reactions. All GEMs can be interactively queried via the accompanying web portal Metabolic Atlas. Specifically, through integrative analysis of Mouse1 with RNA-sequencing data from brain tissues of transgenic mice we identified a coordinated up-regulation of lysosomal GM2 ganglioside and peptide degradation pathways which appears to be a signature metabolic alteration in Alzheimer's disease (AD) mouse models with a phenotype of amyloid precursor protein overexpression. This metabolic shift was further validated with proteomics data from transgenic mice and cerebrospinal fluid samples from human patients. The elevated lysosomal enzymes thus hold potential to be used as a biomarker for early diagnosis of AD. Taken together, we foresee that this evolving open-source platform will serve as an important resource to facilitate the development of systems medicines and translational biomedical applications.

Single-cell BCR and transcriptome analysis after influenza infection reveals spatiotemporal dynamics of antigen-specific B cells

B cell responses are critical for antiviral immunity. However, a comprehensive picture of antigen-specific B cell differentiation, clonal proliferation, and dynamics in different organs after infection is lacking. Here, by combining single-cell RNA and B cell receptor (BCR) sequencing of antigen-specific cells in lymph nodes, spleen, and lungs after influenza infection in mice, we identify several germinal center (GC) B cell subpopulations and organ-specific differences that persist over the course of the response. We discover transcriptional differences between memory cells in lungs and lymphoid organs and organ-restricted clonal expansion. Remarkably, we find significant clonal overlap between GC-derived memory and plasma cells. By combining BCR-mutational analyses with monoclonal antibody (mAb) expression and affinity measurements, we find that memory B cells are highly diverse and can be selected from both low- and high-affinity precursors. By linking antigen recognition with transcriptional programming, clonal proliferation, and differentiation, these finding provide important advances in our understanding of antiviral immunity.

Machine learning-based investigation of the cancer protein secretory pathway

Deregulation of the protein secretory pathway (PSP) is linked to many hallmarks of cancer, such as promoting tissue invasion and modulating cell-cell signaling. The collection of secreted proteins processed by the PSP, known as the secretome, is often studied due to its potential as a reservoir of tumor biomarkers. However, there has been less focus on the protein components of the secretory machinery itself. We therefore investigated the expression changes in secretory pathway components across many different cancer types. Specifically, we implemented a dual approach involving differential expression analysis and machine learning to identify PSP genes whose expression was associated with key tumor characteristics: mutation of p53, cancer status, and tumor stage. Eight different machine learning algorithms were included in the analysis to enable comparison between methods and to focus on signals that were robust to algorithm type. The machine learning approach was validated by identifying PSP genes known to be regulated by p53, and even outperformed the differential expression analysis approach. Among the different analysis methods and cancer types, the kinesin family members KIF20A and KIF23 were consistently among the top genes associated with malignant transformation or tumor stage. However, unlike most cancer types which exhibited elevated KIF20A expression that remained relatively constant across tumor stages, renal carcinomas displayed a more gradual increase that continued with increasing disease severity. Collectively, our study demonstrates the complementary nature of a combined differential expression and machine learning approach for analyzing gene expression data, and highlights key PSP components relevant to features of tumor pathophysiology that may constitute potential therapeutic targets.

The secretory pathway is a series of intracellular compartments and enzymes that process and export proteins from the cell to its surrounding environment. Dysfunction of the secretory pathway is associated with many diseases, including cancer, and therefore constitutes a potential target for novel therapeutic strategies. The large number of interacting components that comprise the secretory pathway pose a challenge when attempting to identify where the dysfunction originates or how to restore healthy function. To improve our understanding of how the secretory pathway is changed within tumors, we used gene expression data from normal tissue and tumor samples from thousands of individuals which included many different types of cancers. The data was analyzed using different machine learning algorithms which we trained to predict sample characteristics, such as disease severity. This training quantified the relative degree to which each gene was associated with the tumor characteristic, allowing us to predict which secretory pathway components were important for processes such as tumor progression—both within specific cancer types and across many different cancer types. The machine learning-based approach demonstrated excellent performance compared to traditional gene expression analysis methods and identified several secretory pathway components with strong evidence of involvement in tumor development.

UPLC-ESI-MRM/MS for Absolute Quantification and MS/MS Structural Elucidation of Six Specialized Pyranonaphthoquinone Metabolites From Ventilago harmandiana

Pyranonaphthoquinones (PNQs) are important structural scaffolds found in numerous natural products. Research interest in these specialized metabolites lies in their natural occurrence and therapeutic activities. Nonetheless, research progress has thus far been hindered by the lack of analytical standards and analytical methods for both qualitative and quantitative analysis. We report here that various parts of Ventilago harmandiana are rich sources of PNQs. We developed an ultraperformance liquid chromatography-electrospray ionization multiple reaction monitoring/mass spectrometry method to quantitatively determine six PNQs from leaves, root, bark, wood, and heartwood. The addition of standards in combination with a stable isotope of salicylic acid-D₆ was used to overcome the matrix effect with average recovery of 82% ± 1% (n = 15). The highest concentration of the total PNQs was found in the root (11,902 μg/g dry weight), whereas the lowest concentration was found in the leaves (28 μg/g dry weight). Except for the root, PNQ-332 was found to be the major compound in all parts of V. harmandiana, accounting for ∼48% of the total PNQs quantified in this study. However, PNQ-318A was the most abundant PNQ in the root sample, accounting for 27% of the total PNQs. Finally, we provide novel MS/MS spectra of the PNQs at different collision induction energies: 10, 20, and 40 eV (POS and NEG). For structural elucidation purposes, we propose complete MS/MS fragmentation pathways of PNQs using MS/MS spectra at collision energies of 20 and 40 eV. The MS/MS spectra along with our discussion on structural elucidation of these PNQs should be very useful to the natural products community to further exploring PNQs in V. harmandiana and various other sources.

Sources of variation in cell-type RNA-Seq profiles

Cell-type specific gene expression profiles are needed for many computational methods operating on bulk RNA-Seq samples, such as deconvolution of cell-type fractions and digital cytometry. However, the gene expression profile of a cell type can vary substantially due to both technical factors and biological differences in cell state and surroundings, reducing the efficacy of such methods. Here, we investigated which factors contribute most to this variation. We evaluated different normalization methods, quantified the variance explained by different factors, evaluated the effect on deconvolution of cell type fractions, and examined the differences between UMI-based single-cell RNA-Seq and bulk RNA-Seq. We investigated a collection of publicly available bulk and single-cell RNA-Seq datasets containing B and T cells, and found that the technical variation across laboratories is substantial, even for genes specifically selected for deconvolution, and this variation has a confounding effect on deconvolution. Tissue of origin is also a substantial factor, highlighting the challenge of using cell type profiles derived from blood with mixtures from other tissues. We also show that much of the differences between UMI-based single-cell and bulk RNA-Seq methods can be explained by the number of read duplicates per mRNA molecule in the single-cell sample. Our work shows the importance of either matching or correcting for technical factors when creating cell-type specific gene expression profiles that are to be used together with bulk samples.

An atlas of human metabolism

Genome-scale metabolic models (GEMs) are valuable tools to study metabolism and provide a scaffold for the integrative analysis of omics data. Researchers have developed increasingly comprehensive human GEMs, but the disconnect among different model sources and versions impedes further progress. We therefore integrated and extensively curated the most recent human metabolic models to construct a consensus GEM, Human1. We demonstrated the versatility of Human1 through the generation and analysis of cell- and tissue-specific models using transcriptomic, proteomic, and kinetic data. We also present an accompanying web portal, Metabolic Atlas (https://www.metabolicatlas.org/), which facilitates further exploration and visualization of Human1 content. Human1 was created using a version-controlled, open-source model development framework to enable community-driven curation and refinement. This framework allows Human1 to be an evolving shared resource for future studies of human health and disease.

A Systematic Investigation of the Malignant Functions and Diagnostic Potential of the Cancer Secretome

The collection of proteins secreted from a cell-the secretome-is of particular interest in cancer pathophysiology due to its diagnostic potential and role in tumorigenesis. However, cancer secretome studies are often limited to one tissue or cancer type or focus on biomarker prediction without exploring the associated functions. We therefore conducted a pan-cancer analysis of secretome gene expression changes to identify candidate diagnostic biomarkers and to investigate the underlying biological function of these changes. Using transcriptomic data spanning 32 cancer types and 30 healthy tissues, we quantified the relative diagnostic potential of secretome proteins for each cancer. Furthermore, we offer a potential mechanism by which cancer cells relieve secretory pathway stress by decreasing the expression of tissue-specific genes, thereby facilitating the secretion of proteins promoting invasion and proliferation. These results provide a more systematic understanding of the cancer secretome, facilitating its use in diagnostics and its targeting for therapeutic development.

Estrogen receptor alpha mediates mandibular condylar cartilage growth in male mice

OBJECTIVES

In the appendicular skeleton, estrogen via ERα signalling has been shown to mediate endochondral growth plate fusion in both males and females. However, the role of ERα in mediating growth of the mandibular condylar cartilage is unknown. Thus, this study focuses on the characterization of the mandibular condylar cartilage phenotype in young and adult male ERαKO mice.

SETTING

Columbia University Medical Center.

MATERIAL AND METHODS

WT and ERαKO C57BL/6 male mice were sacrificed at 49 days or 9 months for phenotypic analysis. Changes to MCC thickness, cell number and cell density were measured using histomorphometric methods. Cartilage-specific gene expression and OARSI scores were investigated for 49-day and 9-month-old male ERαKO and WT mice.

RESULTS

In young mice, a significant increase in the number of mandibular condylar cartilage cells and a significant decrease in the expression of Col10, Runx2 and DMP1 were observed in the male ERαKO mice compared to WT. In 9-month-old mice, we found a similar increase in the number of cells but no change in osteoarthritic histological scoring in ERαKO mice compared to WT mice.

CONCLUSION

In summary, estrogen plays a role in mediating mandibular condylar maturation in young male mice. However, according to this study, it does not play a role in mediating long-term growth or age-related mandibular condylar cartilage degeneration in males.

Comparison of In Vivo and Ex Vivo MRI of the Human Hippocampal Formation in the Same Subjects

Multiple techniques for quantification of hippocampal subfields from in vivo MRI have been proposed. Linking in vivo MRI to the underlying histology can help validate and improve these techniques. High-resolution ex vivo MRI can provide an intermediate modality to map information between these very different imaging modalities. This article evaluates the ability to match information between in vivo and ex vivo MRI in the same subjects. We perform rigid and deformable registration on 10 pairs of in vivo (3 T, 0.4 × 0.4 × 2.6 mm3) and ex vivo (9.4 T, 0.2 × 0.2 × 0.2 mm3) scans, and describe differences in MRI appearance between these modalities qualitatively and quantitatively. The feasibility of using this dataset to validate in vivo segmentation is evaluated by applying an automatic hippocampal subfield segmentation technique (ASHS) to in vivo scans and comparing SRLM (stratum/radiatum/lacunosum/moleculare) surface to manual tracing on corresponding ex vivo scans (and in 2 cases, histology). Regional increases in thickness are detected in ex vivo scans adjacent to the ventricles and were not related to scanner, resolution differences, or susceptibility artefacts. Satisfactory in vivo/ex vivo registration and subvoxel accuracy of ASHS segmentation of hippocampal SRLM demonstrate the feasibility of using this dataset for validation, and potentially, improvement of in vivo segmentation methods.

Targeting CDK2 overcomes melanoma resistance against BRAF and Hsp90 inhibitors

Novel therapies are undergoing clinical trials, for example, the Hsp90 inhibitor, XL888, in combination with BRAF inhibitors for the treatment of therapy-resistant melanomas. Unfortunately, our data show that this combination elicits a heterogeneous response in a panel of melanoma cell lines including PDX-derived models. We sought to understand the mechanisms underlying the differential responses and suggest a patient stratification strategy. Thermal proteome profiling (TPP) identified the protein targets of XL888 in a pair of sensitive and unresponsive cell lines. Unbiased proteomics and phosphoproteomics analyses identified CDK2 as a driver of resistance to both BRAF and Hsp90 inhibitors and its expression is regulated by the transcription factor MITF upon XL888 treatment. The CDK2 inhibitor, dinaciclib, attenuated resistance to both classes of inhibitors and combinations thereof. Notably, we found that MITF expression correlates with CDK2 upregulation in patients; thus, dinaciclib would warrant consideration for treatment of patients unresponsive to BRAF-MEK and/or Hsp90 inhibitors and/or harboring MITF amplification/overexpression.

Novel conformation-selective alpha-synuclein antibodies raised against different in vitro fibril forms show distinct patterns of Lewy pathology in Parkinson's disease

AIMS

The aim of this study was to test the hypothesis that different conformations of misfolded α-synuclein (α-syn) are present in Parkinson's disease (PD) brain.

METHODS

Using two previously characterized conformations of α-syn fibrils, we generated new conformation-selective α-syn monoclonal antibodies (mAbs). We then interrogated multiple brain regions in a well-characterized autopsy cohort of PD patients (n = 49) with these mAbs, Syn7015 and Syn9029.

RESULTS

Syn7015 detects Lewy bodies (LBs) and Lewy neurites (LNs) formed by pathological α-syn in all brain regions tested, and is particularly sensitive to LNs and small Lewy dots, inclusions believed to form early in the disease. Further, we observed colocalization between Syn7015 and an early marker of α-syn pathology formation, phospho-Ser129-α-syn, and a lack of extensive colocalization with markers of more mature pathology. In comparison, Syn9029 detects Lewy pathology in all regions examined, but indicates significantly fewer LNs than Syn7015. In addition, colocalization of Syn9029 with later markers of α-syn pathology maturation (ubiquitin and P62) suggests that the pathology detected by Syn9029 is older. Semiquantitative scoring of both LN and LB pathology in nine brain regions further established this trend, with Syn7015 LN scores consistently higher than Syn9029 LN scores.

CONCLUSIONS

Our data indicate that different conformations of α-syn pathology are present in PD brain and correspond to different stages of maturity for Lewy pathology. Regional analysis of Syn7015 and Syn9029 immunostaining also provides support for the Braak hypothesis that α-syn pathology advances through the brain.

An integrated network analysis reveals that nitric oxide reductase prevents metabolic cycling of nitric oxide by Pseudomonas aeruginosa

Nitric oxide (NO) is a chemical weapon within the arsenal of immune cells, but is also generated endogenously by different bacteria. Pseudomonas aeruginosa are pathogens that contain an NO-generating nitrite (NO₂^-) reductase (NirS), and NO has been shown to influence their virulence. Interestingly, P. aeruginosa also contain NO dioxygenase (Fhp) and nitrate (NO₃^-) reductases, which together with NirS provide the potential for NO to be metabolically cycled (NO→NO₃^-→NO₂^-→NO). Deeper understanding of NO metabolism in P. aeruginosa will increase knowledge of its pathogenesis, and computational models have proven to be useful tools for the quantitative dissection of NO biochemical networks. Here we developed such a model for P. aeruginosa and confirmed its predictive accuracy with measurements of NO, O₂, NO₂^-, and NO₃^- in mutant cultures devoid of Fhp or NorCB (NO reductase) activity. Using the model, we assessed whether NO was metabolically cycled in aerobic P. aeruginosa cultures. Calculated fluxes indicated a bottleneck at NO₃^-, which was relieved upon O₂ depletion. As cell growth depleted dissolved O₂ levels, NO₃^- was converted to NO₂^- at near-stoichiometric levels, whereas NO₂^- consumption did not coincide with NO or NO₃^- accumulation. Assimilatory NO₂^- reductase (NirBD) or NorCB activity could have prevented NO cycling, and experiments with ΔnirB, ΔnirS, and ΔnorC showed that NorCB was responsible for loss of flux from the cycle. Collectively, this work provides a computational tool to analyze NO metabolism in P. aeruginosa, and establishes that P. aeruginosa use NorCB to prevent metabolic cycling of NO.

Progression of alpha-synuclein pathology in multiple system atrophy of the cerebellar type

AIMS

The aim of this study was to identify early foci of α-synuclein (α-syn pathology) accumulation, subsequent progression and neurodegeneration in multiple system atrophy of the cerebellar type (MSA-C).

METHODS

We analysed 70-μm-thick sections of 10 cases with MSA-C and 24 normal controls.

RESULTS

MSA-C cases with the lowest burden of pathology showed α-syn glial cytoplasmic inclusions (GCIs) in the cerebellum as well as in medullary and pontine cerebellar projections. Cerebellar pathology was highly selective and severely involved subcortical white matter, whereas deep white matter and granular layer were only mildly affected and the molecular layer was spared. Loss of Purkinje cells increased with disease duration and was associated with neuronal and axonal abnormalities. Neocortex, basal ganglia and spinal cord became consecutively involved with the increasing burden of α-syn pathology, followed by hippocampus, amygdala, and, finally, the visual cortex. GCIs were associated with myelinated axons, and the severity of GCIs correlated with demyelination.

CONCLUSIONS

Our findings indicate that cerebellar subcortical white matter and cerebellar brainstem projections are likely the earliest foci of α-syn pathology in MSA-C, followed by involvement of more widespread regions of the central nervous system and neurodegeneration with disease progression.

Integrative analysis of human omics data using biomolecular networks

High-throughput '-omics' technologies have given rise to an increasing abundance of genome-scale data detailing human biology at the molecular level. Although these datasets have already made substantial contributions to a more comprehensive understanding of human physiology and diseases, their interpretation becomes increasingly cryptic and nontrivial as they continue to expand in size and complexity. Systems biology networks offer a scaffold upon which omics data can be integrated, facilitating the extraction of new and physiologically relevant information from the data. Two of the most prevalent networks that have been used for such integrative analyses of omics data are genome-scale metabolic models (GEMs) and protein-protein interaction (PPI) networks, both of which have demonstrated success among many different omics and sample types. This integrative approach seeks to unite 'top-down' omics data with 'bottom-up' biological networks in a synergistic fashion that draws on the strengths of both strategies. As the volume and resolution of high-throughput omics data continue to grow, integrative network-based analyses are expected to play an increasingly important role in their interpretation.

Starved Escherichia coli preserve reducing power under nitric oxide stress

Nitric oxide (NO) detoxification enzymes, such as NO dioxygenase (NOD) and NO reductase (NOR), are important to the virulence of numerous bacteria. Pathogens use these defense systems to ward off immune-generated NO, and they do so in environments that contain additional stressors, such as reactive oxygen species, nutrient deprivation, and acid stress. NOD and NOR both use reducing equivalents to metabolically deactivate NO, which suggests that nutrient deprivation could negatively impact their functionality. To explore the relationship between NO detoxification and nutrient deprivation, we examined the ability of Escherichia coli to detoxify NO under different levels of carbon source availability in aerobic cultures. We observed failure of NO detoxification under both carbon source limitation and starvation, and those failures could have arisen from inabilities to synthesize Hmp (NOD of E. coli) and/or supply it with sufficient NADH (preferred electron donor). We found that when limited quantities of carbon source were provided, NO detoxification failed due to insufficient NADH, whereas starvation prevented Hmp synthesis, which enabled cells to maintain their NADH levels. This maintenance of NADH levels under starvation was confirmed to be dependent on the absence of Hmp. Intriguingly, these data show that under NO stress, carbon-starved E. coli are better positioned with regard to reducing power to cope with other stresses than cells that had consumed an exhaustible amount of carbon.

Discovery and dissection of metabolic oscillations in the microaerobic nitric oxide response network of Escherichia coli

The virulence of many pathogens depends upon their ability to cope with immune-generated nitric oxide (NO·). In Escherichia coli, the major NO· detoxification systems are Hmp, an NO· dioxygenase (NOD), and NorV, an NO· reductase (NOR). It is well established that Hmp is the dominant system under aerobic conditions, whereas NorV dominates anaerobic conditions; however, the quantitative contributions of these systems under the physiologically relevant microaerobic regime remain ill defined. Here, we investigated NO· detoxification in environments ranging from 0 to 50 μM O2, and discovered a regime in which E. coli NO· defenses were severely compromised, as well as conditions that exhibited oscillations in the concentration of NO·. Using an integrated computational and experimental approach, E. coli NO· detoxification was found to be extremely impaired at low O2 due to a combination of its inhibitory effects on NorV, Hmp, and translational activities, whereas oscillations were found to result from a kinetic competition for O2 between Hmp and respiratory cytochromes. Because at least 777 different bacterial species contain the genetic requirements of this stress response oscillator, we hypothesize that such oscillatory behavior could be a widespread phenomenon. In support of this hypothesis,Pseudomonas aeruginosa, whose respiratory and NO· response networks differ considerably from those of E. coli, was found to exhibit analogous oscillations in low O2 environments. This work provides insight into how bacterial NO· defenses function under the low O2 conditions that are likely to be encountered within host environments.

Construction and Experimental Validation of a Quantitative Kinetic Model of Nitric Oxide Stress in Enterohemorrhagic Escherichia coli O157:H7

Enterohemorrhagic Escherichia coli (EHEC) are responsible for large outbreaks of hemorrhagic colitis, which can progress to life-threatening hemolytic uremic syndrome (HUS) due to the release of Shiga-like toxins (Stx). The presence of a functional nitric oxide (NO·) reductase (NorV), which protects EHEC from NO· produced by immune cells, was previously found to correlate with high HUS incidence, and it was shown that NorV activity enabled prolonged EHEC survival and increased Stx production within macrophages. To enable quantitative study of EHEC NO· defenses and facilitate the development of NO·-potentiating therapeutics, we translated an existing kinetic model of the E. coli K-12 NO· response to an EHEC O157:H7 strain. To do this, we trained uncertain model parameters on measurements of [NO·] and [O₂] in EHEC cultures, assessed parametric and prediction uncertainty with the use of a Markov chain Monte Carlo approach, and confirmed the predictive accuracy of the model with experimental data from genetic mutants lacking NorV or Hmp (NO· dioxygenase). Collectively, these results establish a methodology for the translation of quantitative models of NO· stress in model organisms to pathogenic sub-species, which is a critical step toward the application of these models for the study of infectious disease.

Correction: In situ crosslinking of electrospun gelatin for improved fiber morphology retention and tunable degradation

Correction for 'In situ crosslinking of electrospun gelatin for improved fiber morphology retention and tunable degradation' by A. P. Kishan et al., J. Mater. Chem. B, 2015, DOI: .

Model-driven identification of dosing regimens that maximize the antimicrobial activity of nitric oxide

The antimicrobial properties of nitric oxide (NO^●) have motivated the design of NO^●-releasing materials for the treatment and prevention of infection. The biological activity of NO^● is dependent on its delivery rate, suggesting that variable antimicrobial effects can result from identical NO^● payloads dosed at different rates. Using a kinetic model of the Escherichia coli NO^● biochemical network, we investigated the relationship between NO^● delivery rate, payload, and cytotoxicity, as indicated by the duration of respiratory inhibition. At low NO^● payloads, the model predicted greater toxicity with rapid delivery, while slower delivery was more effective at higher payloads. These predictions were confirmed experimentally, and exhibited quantitative agreement with measured O₂ and NO^● concentrations, and durations of respiratory inhibition. These results provide important information on key design parameters in the formulation of NO^●-based therapeutics, and highlight the utility of a model-based approach for the analysis of dosing regimens.

•

Antimicrobial activity of NO^● was predicted to depend strongly on delivery rate.

•

Fast NO^● delivery rates were more effective for low NO^● payloads.

•

Slow NO^● delivery rates were more effective for high NO^● payloads.

•

Kinetic modeling of NO^● metabolism correctly predicted the observed dependencies.

Deciphering nitric oxide stress in bacteria with quantitative modeling

Many pathogens depend on nitric oxide (NO•) detoxification and repair to establish an infection, and inhibitors of these systems are under investigation as next-generation antibiotics. Because of the broad reactivity of NO• and its derivatives with biomolecules, a deep understanding of how pathogens sense and respond to NO•, as an integrated system, has been elusive. Quantitative kinetic modeling has been proposed as a method to enhance analysis and understanding of NO• stress at the systems-level. Here we review the motivation for, current state of, and future prospects of quantitative modeling of NO• stress in bacteria, and suggest that such mathematical approaches would prove equally useful in the study of other broadly reactive antimicrobials, such as hydrogen peroxide (H2O2).

A kinetic platform to determine the fate of nitric oxide in Escherichia coli

Nitric oxide (NO•) is generated by the innate immune response to neutralize pathogens. NO• and its autoxidation products have an extensive biochemical reaction network that includes reactions with iron-sulfur clusters, DNA, and thiols. The fate of NO• inside a pathogen depends on a kinetic competition among its many targets, and is of critical importance to infection outcomes. Due to the complexity of the NO• biochemical network, where many intermediates are short-lived and at extremely low concentrations, several species can be measured, but stable products are non-unique, and damaged biomolecules are continually repaired or regenerated, kinetic models are required to understand and predict the outcome of NO• treatment. Here, we have constructed a comprehensive kinetic model that encompasses the broad reactivity of NO• in Escherichia coli. The incorporation of spontaneous and enzymatic reactions, as well as damage and repair of biomolecules, allowed for a detailed analysis of how NO• distributes in E. coli cultures. The model was informed with experimental measurements of NO• dynamics, and used to identify control parameters of the NO• distribution. Simulations predicted that NO• dioxygenase (Hmp) functions as a dominant NO• consumption pathway at O2 concentrations as low as 35 µM (microaerobic), and interestingly, loses utility as the NO• delivery rate increases. We confirmed these predictions experimentally by measuring NO• dynamics in wild-type and mutant cultures at different NO• delivery rates and O2 concentrations. These data suggest that the kinetics of NO• metabolism must be considered when assessing the importance of cellular components to NO• tolerance, and that models such as the one described here are necessary to rigorously investigate NO• stress in microbes. This model provides a platform to identify novel strategies to potentiate the effects of NO•, and will serve as a template from which analogous models can be generated for other organisms.

The long-QT syndrome Genetic considerations

The familial long-QT syndrome (LQTS) is an infrequently occurring disorder in which affected family members have QT prolongation on the ECG, often associated with recurrent syncope and fatal ventricular arrhythmias. Autosomal recessive and autosomal dominant modes of inheritance were suggested by the pattern of occurrence of this disorder in the first reported LQTS families. Statistical genetic analysis (segregation analysis) has substantiated a major gene effect on QTc length in two large pedigrees. Gene linkage studies have uncovered tight linkage between a DNA marker at the Harvey ras-1 locus on chromosome 11 and LQTS in one large pedigree, substantiating a genetic basis of this disorder.

Variants in several genomic regions associated with asperger disorder

Asperger disorder (ASP) is one of the autism spectrum disorders (ASD) and is differentiated from autism largely on the absence of clinically significant cognitive and language delays. Analysis of a homogenous subset of families with ASP may help to address the corresponding effect of genetic heterogeneity on identifying ASD genetic risk factors. To examine the hypothesis that common variation is important in ASD, we performed a genome-wide association study (GWAS) in 124 ASP families in a discovery data set and 110 ASP families in a validation data set. We prioritized the top 100 association results from both cohorts by employing a ranking strategy. Novel regions on 5q21.1 (P = 9.7 × 10(-7) ) and 15q22.1-q22.2 (P = 7.3 × 10(-6) ) were our most significant findings in the combined data set. Three chromosomal regions showing association, 3p14.2 (P = 3.6 × 10(-6) ), 3q25-26 (P = 6.0 × 10(-5) ) and 3p23 (P = 3.3 × 10(-4) ) overlapped linkage regions reported in Finnish ASP families, and eight association regions overlapped ASD linkage areas. Our findings suggest that ASP shares both ASD-related genetic risk factors, as well as has genetic risk factors unique to the ASP phenotype.

Predicting activation enthalpies of cytochrome-P450-mediated hydrogen abstractions. 2. Comparison of semiempirical PM3, SAM1, and AM1 with a density functional theory method

Predicting the biotransformation of xenobiotics is important in the chemical and pharmaceutical industries, as well as in toxicology. Here, we extend and evaluate the rapid methodology of Korzekwa, Jones, and Gillette (J. Am. Chem. Soc. 1990, 112, 7042-7046 ) to estimate the activation enthalpy (DeltaH) of hydrogen-abstraction by cytochrome P450 (CYP) enzymes, using the p-nitrosophenoxy radical (PNPO) as a simple surrogate for the CYP active oxygen species. The DeltaH is estimated with a linear regression model using the reaction enthalpy and ionization energy (of the substrate radical) as predictor variables, calculated by semiempirical (SE) methods. While Korzekwa et al. used the SE method AM1, we applied PM3 and SAM1 and compared the results of the three methods. For 24 substrates, the AM1-, PM3-, and SAM1-derived regression models showed R(2) values of 0.89, 0.90, and 0.93, respectively, for the correlation between calculated and predicted DeltaH. Furthermore, we compared the DeltaH() calculated semiempirically using PNPO radical with density functional theory (DFT) B3LYP activation energies calculated by Olsen et al. (J. Med. Chem. 2006, 49, 6489-6499 ) using a more realistic iron-oxo-porphine model, and the results revealed limitations of the PNPO radical model. Thus, predictive models developed using SE predictors provide rapid and generally internally consistent results, but they should be interpreted and used cautiously.

Respiratory failure associated with human metapneumovirus infection in an infant posthepatic transplant

This is the first reported case of respiratory failure associated with human metapneumovirus (hMPV) infection in a liver transplant recipient or in a pediatric solid transplant recipient. A 9-month-old female developed respiratory distress 8 days following a liver transplant. hMPV was detected and she required intubation followed by extracorporeal membrane oxygenation for 26 days. Immunosuppressive medications were stopped during the acute infection except for methylprednisolone as treatment for acute respiratory distress. Serial Doppler ultrasounds were used to monitor for hepatic vessel thromboses and serum liver function tests to assess for hepatic dysfunction and there was no evidence of allograft rejection. The patient recovered from the nosocomial hMPV infection with satisfactory pulmonary function and possible mild developmental delay.

Ontogeny and chain-length specificity of gastrointestinal lipases affect medium-chain triacylglycerol utilization by newborn pigs1

Ontogeny and fatty acid chain-length specificity of gastrointestinal lipases in neonatal piglets were examined to explore the basis for variations in postnatal use of medium-chain triacylglycerols (MCT). Twenty-four newborn pigs were studied at 4 ages: 0, 6, 18, and 48 h postpartum (n = 6 pigs/age). Piglets were gastrically intubated and given 3.0 mmol/kg of BW(0.75) each of emulsified tri-C6:0 and tri-C8:0. One hour after intubation, the plasma concentration of C6:0 was 7.5-fold greater than that of C8:0 (P < 0.001), with total plasma medium-chain fatty acid concentrations 3.7-fold greater at 48 h than at 6 h of age (P < 0.05). Pancreatic, gastric, and lingual tissues were analyzed for lipase activity using an equimolar mixture of tri-C6:0 and tri-C8:0 as substrate. Pancreatic lipase activity averaged 7.0 +/- 0.8 micromol of fatty acid released/min per mg of protein for the medium-chain fatty acid substrates. Hexanoate (C6:0) release was greater at 0 h than at 6, 18, or 48 h (P < 0.05); however, age did not affect C8:0 release (P > 0.05). The lowest lipase activity was observed at 18 h for both tri-C6:0 and tri-C8:0. Chain-length specificity of pancreatic lipase was measured with tri-C4:0, tri-C6:0, tri-C8:0, and tri-C10:0 as combined or separate substrates. As separate substrates, the lipase activity decreased progressively as chain length increased from tri-C4:0 to tri-C10:0. As combined substrates, tri-C6:0 was hydrolyzed fastest (P < 0.05), followed by C4:0, C8:0, and C10:0. Gastric and lingual lipase activities averaged 2.7 nmol/min per mg of protein for the medium-chain fatty acid substrates, with hydrolysis of C6:0 being 7-fold greater than that of C8:0. In conclusion, pancreatic lipase dominates the preduodenal lipases in the neonatal pig, and greater activity of the gastrointestinal lipases toward tri-C6:0 underlies its increased rate of use.

Identification of a mutation associated with factor XI deficiency in Holstein cattle

An autosomal recessive deficiency of blood coagulation factor XI (FXI) has been described in Holstein cattle. Current testing methods are unsuitable for accurately identifying carriers (heterozygotes) of the disease. To identify the molecular basis of this deficiency, a polymerase chain reaction (PCR)-based strategy was implemented to clone and sequence the bovine FXI gene (F11) from animals of different genotypes. Approximately 14 kb of genomic DNA sequence and 1.8 kb of cDNA sequence, corresponding to exon 3 through the 3'-UTR, of the bovine gene were obtained. Comparison of sequences derived from homozygous normal and deficient individuals revealed that FXI deficiency in Holsteins is associated with the insertion of a 76 bp segment [AT(A)(28)TAAAG(A)(26)GGAAATAATAATTCA] within exon 12. This insertion introduces a stop codon that results in a mature FXI protein lacking the functional protease domain encoded by exons 13, 14 and 15. Based on these data, a DNA-based diagnostic test has been developed for accurate genotyping. Using this method, the frequency of the mutated allele has been determined to be 1.2% in a contemporary population of the USA Holstein sires.

Case Report and Literature Review of Late-Onset Group B Streptococcal Disease Manifesting as Necrotizing Fasciitis in Preterm Infants: Is This a New Syndrome?

We describe a 5-month-old preterm female infant who presented with necrotizing fasciitis involving the face and neck caused by group B streptococcus (GBS). Because of the extent and anatomic location of the necrosis, surgical debridement was delayed for 16 days, but the infant survived. Review of the literature demonstrated that 3 of the 10 previously reported cases of necrotizing fasciitis caused by GBS involved preterm infants and that 2 of these cases also involved the head and neck.

Net cost of palivizumab for respiratory syncytial virus prophylaxis during the 1998/99 season in northern Alberta

OBJECTIVE

Palivizumab has been shown to decrease respiratory syncytial virus (RSV) hospitalization rates in preterm infants and infants with chronic lung disease. The objective of the present study was to determine whether the use of palivizumab during the 1998/99 RSV season would have resulted in a cost-saving in infants discharged from Edmonton hospitals.

DESIGN

A retrospective study of RSV hospitalizations was performed by contacting parents and reviewing hospital lists. The net cost of using palivizumab was determined by comparing the cost of giving the drug from November 1, 1998 to April 1, 1999 with the cost of potentially averted medical transports and hospitalizations.

POPULATION

One hundred fifty-nine infants discharged from Edmonton hospitals who met the Canadian Paediatric Society's criteria for receiving palivizumab during the 1998/99 RSV season were studied.

RESULTS

The cost of using palivizumab in these 159 study infants would have been $753,300. The infants had 21 RSV hospitalizations and required four medical transports. The estimated cost of RSV hospital-based care for these infants was $168,888. Assuming a drug efficacy of 39% in infants with chronic lung disease and 78% in infants born before 33 weeks' gestation with no chronic lung disease, $121,147 of these costs could have been averted if palivizumab had been used.

CONCLUSIONS

The net cost to the health care system of using palivizumab, as recommended in the Canadian Paediatric Society guidelines, in study infants in northern Alberta during the 1998/99 RSV season would have been $632,153.

Certificate of need and the quality of cardiac surgery

Historically, states have used Certificate of Need (CON) programs to review proposals for new construction and expanded services in an effort to control costs and to improve the quality of and promote access to health care services. Congressional funding for CON ended in 1987. However, today, 26 states use CON to regulate cardiac surgery. There has been little evidence of the impact of CON on the quality of services. Pennsylvania is in a unique position to study the impact of CON on the quality and outcomes of care because the state terminated CON in 1996 and has publicly reported quality and outcomes data on coronary bypass graft (CABG) surgeries since 1992. Using a statewide inpatient data-reporting system, the volumes and outcomes of CABG surgeries at all Pennsylvania hospitals were examined in the 3 years prior to and the 3 years after the termination of CON. In the 3 years following the elimination of CON, the number of open-heart surgery programs increased 25%, yet there was no significant increase in the number of CABG surgeries performed. Quality, as measured by mortality rate, was not impacted by the real-location of the relatively stable CABG volume in the short term; this may be due, in part, to itinerant surgeons and statewide public performance monitoring. The long-term implications of deregulation are unclear and deserve future study.

Clinical implications for affected parents and siblings of probands with long-QT syndrome

BACKGROUND

Whenever a proband is identified with long-QT syndrome (LQTS), his or her parents and siblings should be evaluated regarding the possibility of carrying the disorder. In the majority of cases, one of the proband's parents and one or more siblings are affected. The aim of this study was (1) to determine whether the clinical severity of LQTS in the proband is useful in identifying first-degree family members at high risk for cardiac events, and (2) to evaluate the clinical course of affected parents and siblings of LQTS probands.

METHODS AND RESULTS

The clinical and ECG characteristics of 211 LQTS probands and 791 first-degree relatives (422 parents and 369 siblings) were studied to determine if the clinical profile of the proband is useful in determining the clinical severity of LQTS in affected parents and siblings. Affected female parents of an LQTS proband had a greater cumulative risk for a first cardiac event than affected male parents. The probability of a parent or sibling having a first cardiac event was not significantly influenced by the severity of the proband's clinical symptoms. Female sex and QT(c) duration were risk factors for cardiac events among affected parents, and QT(c) was the only risk factor for cardiac events in affected siblings.

CONCLUSIONS

The severity profile of LQTS in a proband was not found to be useful in identifying the clinical severity of LQTS in affected first-degree relatives of the proband.

Infant reactivity and reliance on mother during emotion challenges: prediction of cognition and language skills in a low-income sample

This investigation considers the association between patterns of emotional reactivity and reliance on mother in infancy and cognitive and language developments at age 2. Low-income women (N = 518) and their firstborn infants participated in (1) a lab-based assessment where emotion challenges were presented when the infants were 6 to 9 months old, and (2) an assessment of language and cognitive skills at age 2. After controlling for birthweight, early sensorimotor delay, and age at testing, infants who displayed a pattern of combined high reactivity and high reliance on mother in response to positive, anger, and fear emotion challenges had higher cognitive and language skills at age 2 compared with infants who displayed patterns of low reactivity and low reliance on mother. Children who showed high fearful distress and low reliance on mother and whose mothers had low psychological resources had especially poor developmental outcomes. The role of maternal availability in the socialization of emotion and early communication is discussed.

Genotype-phenotype correlation in the long-QT syndrome: gene-specific triggers for life-threatening arrhythmias

BACKGROUND

The congenital long-QT syndrome (LQTS) is caused by mutations on several genes, all of which encode cardiac ion channels. The progressive understanding of the electrophysiological consequences of these mutations opens unforeseen possibilities for genotype-phenotype correlation studies. Preliminary observations suggested that the conditions ("triggers") associated with cardiac events may in large part be gene specific.

METHODS AND RESULTS

We identified 670 LQTS patients of known genotype (LQT1, n=371; LQT2, n=234; LQT3, n=65) who had symptoms (syncope, cardiac arrest, sudden death) and examined whether 3 specific triggers (exercise, emotion, and sleep/rest without arousal) differed according to genotype. LQT1 patients experienced the majority of their events (62%) during exercise, and only 3% occurred during rest/sleep. These percentages were almost reversed among LQT2 and LQT3 patients, who were less likely to have events during exercise (13%) and more likely to have events during rest/sleep (29% and 39%). Lethal and nonlethal events followed the same pattern. Corrected QT interval did not differ among LQT1, LQT2, and LQT3 patients (498, 497, and 506 ms, respectively). The percent of patients who were free of recurrence with ss-blocker therapy was higher and the death rate was lower among LQT1 patients (81% and 4%, respectively) than among LQT2 (59% and 4%, respectively) and LQT3 (50% and 17%, respectively) patients.

CONCLUSIONS

Life-threatening arrhythmias in LQTS patients tend to occur under specific circumstances in a gene-specific manner. These data allow new insights into the mechanisms that relate the electrophysiological consequences of mutations on specific genes to clinical manifestations and offer the possibility of complementing traditional therapy with gene-specific approaches.

Spectrum of ST-T-wave patterns and repolarization parameters in congenital long-QT syndrome: ECG findings identify genotypes

BACKGROUND

Congenital long-QT syndrome (LQTS) is caused by mutations of genes encoding the slow component of the delayed rectifier current (LQT1, LQT5), the rapid component of the delayed rectifier current (LQT2, LQT6), or the Na(+) current (LQT3), resulting in ST-T-wave abnormalities on the ECG. This study evaluated the spectrum of ST-T-wave patterns and repolarization parameters by genotype and determined whether genotype could be identified by ECG.

METHODS AND RESULTS

ECGs of 284 gene carriers were studied to determine ST-T-wave patterns, and repolarization parameters were quantified. Genotypes were identified by individual ECG versus family-grouped ECG analysis in separate studies using ECGs of 146 gene carriers from 29 families and 233 members of 127 families undergoing molecular genotyping, respectively. Ten typical ST-T patterns (4 LQT1, 4 LQT2, and 2 LQT3) were present in 88% of LQT1 and LQT2 carriers and in 65% of LQT3 carriers. Repolarization parameters also differed by genotype. A combination of quantified repolarization parameters identified genotype with sensitivity/specificity of 85%/70% for LQT1, 83%/94% for LQT2, and 47%/63% for LQT3. Typical patterns in family-grouped ECGs best identified the genotype, being correct in 56 of 56 (21 LQT1, 33 LQT2, and 2 LQT3) families with mutation results.

CONCLUSIONS

Typical ST-T-wave patterns are present in the majority of genotyped LQTS patients and can be used to identify LQT1, LQT2, and possibly LQT3 genotypes. Family-grouped ECG analysis improves genotype identification accuracy. This approach can simplify genetic screening by targeting the gene for initial study. The multiple ST-T patterns in each genotype raise questions regarding the pathophysiology and regulation of repolarization in LQTS.