Genetic analysis of sterile mutants in the dpy-5 unc-13 (I) genomic region of Caenorhabditis elegans

Essential genes were identified in the 1.5-map unit dpy-5 unc-13 region of chromosome I in the Caenorhabditis elegans genome by rescuing lethal mutations using the duplication sDp2. In this paper, we report the mapping and complementation testing of lethal mutations, 45 of which identify 18 new, essential genes. This analysis brings the number of essential genes defined by the sDp2 rescue of lethal mutants to 97; 64 of these map between dpy-5 and unc-13. 61% of these essential genes are identified by more than one allele. Positioning of the mutations was done using the breakpoints of six duplications. The mutant phenotypes of 14 loci essential for fertility were characterized by Nomarski microscopy and DAPI staining. None of the mutants were rescued by wild-type male sperm. The cytological data showed that four genes produced mutants with defects in gonadogenesis, let-395, let-603, let-605 and let-610. Mutations in seven genes, let-355, let-367, let-384, let-513, let-544, let-545 and let-606, affected germ cell proliferation or gametogenesis. Mutants for the remaining three genes, let-370, let-599 and let-604, produced eggs that failed to develop or hatch, thereby acting as maternal effect lethals. We observed a nonrandom distribution of arrest phenotypes with regard to map position. Received: 8 May 1996 / Accepted : 27 January 1997     

Structural Insights into the Mechanism of Base Excision by MBD4

DNA glycosylases remove damaged or modified nucleobases by cleaving the N-glycosyl bond and the correct nucleotide is restored through subsequent base excision repair. In addition to excising threatening lesions, DNA glycosylases contribute to epigenetic regulation by mediating DNA demethylation and perform other important functions. However, the catalytic mechanism remains poorly defined for many glycosylases, including MBD4 (methyl-CpG binding domain IV), a member of the helix-hairpin-helix (HhH) superfamily. MBD4 excises thymine from G·T mispairs, suppressing mutations caused by deamination of 5-methylcytosine, and it removes uracil and modified uracils (e.g., 5-hydroxymethyluracil) mispaired with guanine. To investigate the mechanism of MBD4 we solved high-resolution structures of enzyme-DNA complexes at three stages of catalysis. Using a non-cleavable substrate analog, 2′-deoxy-pseudouridine, we determined the first structure of an enzyme-substrate complex for wild-type MBD4, which confirms interactions that mediate lesion recognition and suggests that a catalytic Asp, highly conserved in HhH enzymes, binds the putative nucleophilic water molecule and stabilizes the transition state. Observation that mutating the Asp (to Gly) reduces activity by 2700-fold indicates an important role in catalysis, but probably not one as the nucleophile in a double-displacement reaction, as previously suggested. Consistent with direct-displacement hydrolysis, a structure of the enzyme-product complex indicates a reaction leading to inversion of configuration. A structure with DNA containing 1-azadeoxyribose models a potential oxacarbenium-ion intermediate and suggests the Asp could facilitate migration of the electrophile towards the nucleophilic water. Finally, the structures provide detailed snapshots of the HhH motif, informing how these ubiquitous metal-binding elements mediate DNA binding.     

An in-depth Comparison of the Pediatric and Adult Urinary N-glycomes

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Highlights

• •N-glycan patterns are distinct in pediatric and adult urine.
• •Sex differences of N-glycans are much larger in adults.
• •Pediatric urine has almost no sex differences in N-glycan levels.
• •In adults, the majority of N-glycans were more abundant in males.

     

Validating Landsat-based landscape metrics with fine-grained land cover data

ContextModerate-grained data may not always represent landscape structure in adequate detail which could cause misleading results. Certain metrics have been shown to be predictable with changes in scale; however, no studies have verified such predictions using independent fine-grained data.ObjectivesOur objective was to use independently derived land cover datasets to assess relationships between metrics based on fine- and moderate-grained data for a range of analysis extents. We focus on metrics that previous literature has shown to have predictable relationships across scales.MethodsThe study area was located in eastern Connecticut. We compared a 1 m land cover dataset to a 30 m resampled dataset, derived from the 1 m data, as well as two Landsat-based datasets. We examined 11 metrics which included cover areas and patch metrics. Metrics were analyzed using analysis extents ranging from 100 to 1400 m in radius.ResultsThe resampled data had very strong linear relationships to the 1 m data, from which it was derived, for all metrics regardless of the analysis extent size. Landsat-based data had strong correlations for most cover area metrics but had little or no correlation for patch metrics. Increasing analysis areas improved correlations.ConclusionsRelationships between coarse- and fine-grained data tend to be much weaker when comparing independent land cover datasets. Thus, trends across scales that are found by resampling land cover are likely to be unsuitable for predicting the effects of finer-scale elements in the landscape. Nevertheless, coarser data shows promise in predicting fine-grained for cover area metrics provided the analysis area used is sufficiently large.     

Rethinking trophic niches: Speed and body mass colimit prey space of mammalian predators

1. Realized trophic niches of predators are often characterized along a one‐dimensional range in predator–prey body mass ratios. This prey range is constrained by an “energy limit” and a “subdue limit” toward small and large prey, respectively. Besides these body mass ratios, maximum speed is an additional key component in most predator–prey interactions.
2. Here, we extend the concept of a one‐dimensional prey range to a two‐dimensional prey space by incorporating a hump‐shaped speed‐body mass relation. This new “speed limit” additionally constrains trophic niches of predators toward fast prey.
3. To test this concept of two‐dimensional prey spaces for different hunting strategies (pursuit, group, and ambush predation), we synthesized data on 63 terrestrial mammalian predator–prey interactions, their body masses, and maximum speeds.
4. We found that pursuit predators hunt smaller and slower prey, whereas group hunters focus on larger but mostly slower prey and ambushers are more flexible. Group hunters and ambushers have evolved different strategies to occupy a similar trophic niche that avoids competition with pursuit predators. Moreover, our concept suggests energetic optima of these hunting strategies along a body mass axis and thereby provides mechanistic explanations for why there are no small group hunters (referred to as “micro‐lions”) or mega‐carnivores (referred to as “mega‐cheetahs”).
5. Our results demonstrate that advancing the concept of prey ranges to prey spaces by adding the new dimension of speed will foster a new and mechanistic understanding of predator trophic niches and improve our predictions of predator–prey interactions, food web structure, and ecosystem functions.

     

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.