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.     

Gut microbiota,inflammation, and molecular signatures of host response to infection

Gut microbial dysbiosis has been linked to many noncommunicable diseases. However, little is known about specific gut microbiota composition and its correlated metabolites associated with molecular signatures underlying host response to infection. Here, we describe the construction of a proteomic risk score based on 20 blood proteomic biomarkers, which have recently been identified as molecular signatures predicting the progression of the COVID-19. We demonstrate that in our cohort of 990 healthy individuals without infection, this proteomic risk score is positively associated with proinflammatory cytokines mainly among older, but not younger, individuals. We further discover that a core set of gut microbiota can accurately predict the above proteomic biomarkers among 301 individuals using a machine learning model and that these gut microbiota features are highly correlated with proinflammatory cytokines in another independent set of 366 individuals. Fecal metabolomics analysis suggests potential amino acid-related pathways linking gut microbiota to host metabolism and inflammation. Overall, our multi-omics analyses suggest that gut microbiota composition and function are closely related to inflammation and molecular signatures of host response to infection among healthy individuals. These results may provide novel insights into the cross-talk between gut microbiota and host immune system.     

Genetic basis of stony coral biomineralization: History,trends and future prospects

Despite their simple body plan, stony corals (order Scleractinia, phylum Cnidaria) can produce massive and complex exoskeletal structures in shallow, tropical and subtropical regions of Earth’s oceans. The species-specific macromorphologies of their aragonite skeletons suggest a highly coordinated biomineralization process that is rooted in their genomes, and which has persisted across major climatic shifts over the past 400 + million years. The mechanisms by which stony corals produce their skeletons has been the subject of interest for at least the last 160 years, and the pace of understanding the process has increased dramatically in the past decade since the sequencing of the first coral genome in 2011. In this review, we detail what is known to date about the genetic basis of the stony coral biomineralization process, with a focus on advances in the last several years as well as ways that physical and chemical tools can be combined with genetics, and then propose next steps forward for the coming decade.     

Translation of proteomic biomarkers into FDA approved cancer diagnostics: issues and challenges

Tremendous efforts have been made over the past few decades to discover novel cancer biomarkers for use in clinical practice. However, a striking discrepancy exists between the effort directed toward biomarker discovery and the number of markers that make it into clinical practice. One of the confounding issues in translating a novel discovery into clinical practice is that quite often the scientists working on biomarker discovery have limited knowledge of the analytical, diagnostic, and regulatory requirements for a clinical assay. This review provides an introduction to such considerations with the aim of generating more extensive discussion for study design, assay performance, and regulatory approval in the process of translating new proteomic biomarkers from discovery into cancer diagnostics. We first describe the analytical requirements for a robust clinical biomarker assay, including concepts of precision, trueness, specificity and analytical interference, and carryover. We next introduce the clinical considerations of diagnostic accuracy, receiver operating characteristic analysis, positive and negative predictive values, and clinical utility. We finish the review by describing components of the FDA approval process for protein-based biomarkers, including classification of biomarker assays as medical devices, analytical and clinical performance requirements, and the approval process workflow. While we recognize that the road from biomarker discovery, validation, and regulatory approval to the translation into the clinical setting could be long and difficult, the reward for patients, clinicians and scientists could be rather significant.     

Photoaffinity electrophoretic mobility shift assay using photoreactive DNA bearing 3-trifluoromethyl-3-phenyldiazirine in its phosphate backbone

Photoaffinity cross-linking enables the analysis of interactions between DNA and proteins even under denaturing conditions. We present a photoaffinity electrophoretic mobility shift assay (EMSA) in which two heterogeneous techniques―photoaffinity cross-linking using DNA bearing 3-trifluoromethyl-3-phenyldiazirine and sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS–PAGE) analysis—are combined. To prepare the photoreactive DNA, which is an essential tool for photoaffinity EMSA, we first determined the optimal conditions for the integration of 4-(3-trifluoromethyl-3H-diazirin-3-yl)benzyl bromide to the specific site of oligonucleotide where phosphodiester linkage was replaced with phosphorothioate linkage. The photoaffinity EMSA was developed using the POU (initial letters of three genes: Pit-l, Oct-1,2, and unc-86) domain region of Oct-1 protein, which specifically bound to octamer DNA motif (ATGCAAAT). The affinity-purified recombinant POU domain proteins conjugated with glutathione-S-transferase (GST) contained three distinct proteins with molecular weights of 34, 36, and 45 kDa. The photoaffinity EMSA could clearly distinguish the individual binding abilities of three proteins on a single lane and showed that the whole POU domain protein specifically bound to octamer DNA motif by competition experiments. Using the nuclear extract of HeLa cells, the photoaffinity EMSA revealed that at least five specific proteins could bind to the octamer DNA motif. These results show that photoaffinity EMSA using 3-trifluoromethyl-3-phenyldiazirine can provide high-performance analysis of DNA-binding proteins.     

DYRK1A regulates the recruitment of 53BP1 to the sites of DNA damage in part through interaction with RNF169

Human Dual-specificity tyrosine (Y) Regulated Kinase 1A (DYRK1A) is encoded by a dosage dependent gene whereby either trisomy or haploinsufficiency result in developmental abnormalities. However, the function and regulation of this important protein kinase are not fully understood. Here, we report proteomic analysis of DYRK1A in human cells that revealed a novel role of DYRK1A in DNA double-strand breaks (DSBs) repair, mediated in part by its interaction with the ubiquitin-binding protein RNF169 that accumulates at the DSB sites and promotes homologous recombination repair (HRR) by displacing 53BP1, a key mediator of non-homologous end joining (NHEJ). We found that overexpression of active, but not the kinase inactive DYRK1A in U-2 OS cells inhibits accumulation of 53BP1 at the DSB sites in the RNF169-dependent manner. DYRK1A phosphorylates RNF169 at two sites that influence its ability to displace 53BP1 from the DSBs. Although DYRK1A is not required for the recruitment of RNF169 to the DSB sites and 53BP1 displacement, inhibition of DYRK1A or mutation of the DYRK1A phosphorylation sites in RNF169 decreases its ability to block accumulation of 53BP1 at the DSB sites. Interestingly, CRISPR-Cas9 knockout of DYRK1A in human and mouse cells also diminished the 53BP1 DSB recruitment in a manner that did not require RNF169, suggesting that dosage of DYRK1A can influence the DNA repair processes through both RNF169-dependent and independent mechanisms. Human U-2 OS cells devoid of DYRK1A display an increased HRR efficiency and resistance to DNA damage, therefore our findings implicate DYRK1A in the DNA repair processes.     

Proteomic patterns for classification of ovarian cancer and CTCL serum samples utilizing peak pairs indicative of post-translational modifications

Proteomic patterns as a potential diagnostic technology has been well established for several cancer conditions and other diseases. The use of machine learning techniques such as decision trees, neural networks, genetic algorithms, and other methods has been the basis for pattern determination. Cancer is known to involve signaling pathways that are regulated through PTM of proteins. These modifications are also detectable with high confidence using high-resolution MS. We generated data using a prOTOF mass spectrometer on two sets of patient samples: ovarian cancer and cutaneous t-cell lymphoma (CTCL) with matched normal samples for each disease. Using the knowledge of mass shifts caused by common modifications, we built models using peak pairs and compared this to a conventional technique using individual peaks. The results for each disease showed that a small number of peak pairs gave classification equal to or better than the conventional technique that used multiple individual peaks. This simple peak picking technique could be used to guide identification of important peak pairs involved in the disease process.     

Identification of HMG-5 as a double-stranded telomeric DNA-binding protein in the nematode Caenorhabditis elegans

Many protein components of telomeres, the multifunctional DNA-protein complexes at the ends of eukaryotic chromosomes, have been identified in diverse species ranging from yeast to humans. In Caenorhabditis elegans, CEH-37 has been identified by a yeast one hybrid screen to be a double-stranded telomere-binding protein. However, the role of CEH-37 in telomere function is unclear because a deletion mutation in this gene does not cause severe telomere defects. This observation raises the possibility of the presence of genetic redundancy. To identify additional double-stranded telomere-binding proteins in C. elegans, we used a different approach, namely, a proteomic approach. Affinity chromatography followed by Finnigan LCQ ion trap mass spectrometer analysis allowed us to identify several candidate proteins. We further characterized one of these, HMG-5, which is encoded by F45E4.9. HMG-5 bound to double-stranded telomere in vitro as shown by competition assays. At least two telomeric DNA repeats were needed for this binding. HMG-5 was expressed in the nuclei of the oocytes and all embryonic cells, but not in the hatched larvae or adults. HMG-5 mainly localized to the chromosomal ends, indicating that HMG-5 also binds to telomeres in vivo. These observations suggest that HMG-5 may participate, together with CEH-37, in early embryogenesis by acting at the telomeres.     

<Emphasis Type="Italic">Pseudomonas stutzeri</Emphasis> as a novel biocatalyst for pyruvate production from<Emphasis Type="SmallCaps"> DL</Emphasis>-lactate

Pseudomonas stutzeri SDM oxidized dl-lactic acid (25.5 g l^-1) into pyruvic acid (22.6 g l^-1) over 24 h. Both NAD⁺-independent d-lactate dehydrogenase and NAD⁺-independent l-lactate dehydrogenase were found for the first time in the bioconversion of lactate to pyruvate based on the enzyme activity assay and proteomic analysis. Jianrong Hao and Cuiqing Ma contributed equally to this work     

A proteomic analysis of murine bone marrow and its response to ionizing radiation

To characterize the mouse bone marrow tissue proteome and investigate the response to radiation damage we took bone marrow before and after 4-Gy gamma-irradiation from mouse strains (C57BL/6 and CBA/Ca) that differ in their short-term and long-term radiation responses and analyzed extracellular proteins by high-resolution 2-DE. Twenty proteins were identified from 71 protein spots in both C57BL/6 and CBA/Ca. We detected significant differences between control and irradiated bone marrow and between genotypes and identified many of the changed proteins by MS. In C57BL/6, 27 spots were significantly different between control and irradiated samples. In CBA/Ca, 18 spots showed significant changes following irradiation. Proteins such as serum albumin, apolipoprotein A-I, ferritin, haptoglobin (Hp) and alpha-1-antitrypsin were changed in irradiated bone marrow of both mouse strains, reflecting an ongoing acute-phase reaction. Several other proteins including serotransferrin, neutrophil collagenase, peroxiredoxin 2 and creatine kinase M chain were changed specifically in an individual mouse strain. The proteomic approach makes an important contribution to characterizing bone marrow proteome and investigating the tissue response of bone marrow to radiation, assists in identifying genotype-dependent responses and provides support for the importance of microenvironmental factors contributing to the overall response.