A Cross-linking Mass Spectrometry Approach Defines Protein Interactions in Yeast Mitochondria

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Highlights

• •XL-MS reveals new PPIs in yeast mitochondria under glycerol and glucose condition.
• •Significant but limited results from quantitative XL-MS experiments.
• •Ndi1 participates in a CIII₂CIV₂ respiratory supercomplex.
• •Min8 promotes assembly of Cox12 into an intermediate complex IV.

     

Photosynthesis,Transpiration, and Water Use Efficiency of Vegetative and Reproductive Shoots of Grassland Species from North-Eastern China

The differences in net photosynthetic rate (P _N), transpiration rate (E), and water use efficiency (WUE) between the vegetative and reproductive shoots of three native grass species from the grassland of northeastern China [grey-green and yellow green populations of Leymus chinensis (Trin.) Tzvel., Puccinellia tenuiflora (Griseb) Scrib & Merr, Puccinellia chinampoensis Ohwi] were compared. The two type shoots experienced similar habitats, but differed in leaf life-span and leaf area. The leaf P _N and WUE for the vegetative shoots were significantly higher than those for the reproductive shoots in the grasses, while their E were remarked lower in the dry season. Relative lower leaf P _N and WUE for the reproductive shoots of grassland grasses may explain the facts of lower seed production and the subordinate role of seed in the grassland renewal in north-eastern China.     

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 predictive model for freshwater bioassessment (Mondego River,Portugal)

We sampled macroinvertebrates at 75 locations in the Mondego river catchment, Central Portugal, and developed a predictive model for water quality assessment of this basin, based on the Reference Condition Approach. Sampling was done from June to September 2001. Fifty-five sites were identified as “Reference sites” and 20 sites were used as “Test sites” to test the model. At each site we also measured 40 habitat variables to characterize water physics and chemistry, habitat type, land use, stream hydrology and geographic location. Macroinvertebrates were generally identified to species or genus level; a total of 207 taxa were found. By Unweighted Pair Group Method with Arithmetic mean (UPGMA) clustering and analysis of species contribution to similarities percentage (SIMPER), two groups of reference sites were established. Using Discriminant Analysis (stepwise forward), four variables correctly predicted 78% of the reference sites to the appropriate group: stream order, pool quality, substrate quality and current velocity. Test sites’ environmental quality was established from their relative distance to reference sites, in MDS ordination space, using a series of bands (BEAST methodology). The model performed well at upstream sites, but at downstream sites it was compromised by the lack of reference sites. As with the English RIVPACS predictive model, the Mondego model should be continually improved with the addition of new reference sites. The adaptation of the Mondego model methodology to the Water Framework Directive is possible and would consist mainly of the integration of the WFD typology and increasing the number of ellipses that define quality bands. Handling editor: K. Martens     

Biochemistry and genetics of taste- and odor-producing cyanobacteria

Cyanobacteria are one of the principal sources of volatile organic compounds (VOCs) which cause offensive taste and odor (T&O) in drinking and recreational water, fish, shellfish and other seafood. Although non-toxic to humans, these T&O compounds severely undermine public trust in these commodities, resulting in substantial costs in treatment, and lost revenue to drinking water, aquaculture, food and beverage and tourist/hospitality industries. Mitigation and control have been hindered by the complexity of the communities and processes which produce and modify T&O events, making it difficult to source-track the major producer(s) and the factors governing VOC production and fate. Over the past decade, however, advances in bioinformatics, enzymology, and applied detection technologies have greatly enhanced our understanding of the pathways, the enzymes and the genetic coding for some of the most problematic VOCs produced by cyanobacteria. This has led to the development of tools for rapid and sensitive detection and monitoring for the VOC production at source, and provided the basis for further diagnostics of endogenous and exogenous controls. This review provides an overview of current knowledge of the major cyanobacterial VOCs, the producers, the biochemistry and the genetics and highlight the current applications and further research needs in this area.     

Biosensors based on peptide exposure show single molecule conformations in live cells

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Effects of detergents on catalytic activity of human endometase/matrilysin 2, a putative cancer biomarker

Matrix metalloproteinases (MMPs) are a family of hydrolytic enzymes that play significant roles in development, morphogenesis, inflammation, and cancer invasion. Endometase (matrilysin 2 or MMP-26) is a putative early biomarker for human carcinomas. The effects of the ionic and nonionic detergents on catalytic activity of endometase were investigated. The hydrolytic activity of endometase was detergent concentration dependent, exhibiting a bell-shaped curve with its maximum activity near the critical micelle concentration (CMC) of nonionic detergents tested. The effect of Brij-35 on human gelatinase B (MMP-9), matrilysin (MMP-7), and membrane-type 1 MMP (MT1-MMP) was further explored. Their maximum catalysis was observed near the CMC of Brij-35 (∼ 90 μM). Their IC₅₀ values were above the CMC. The inhibition mechanism of MMP-7, MMP-9, and MT1-MMP by Brij-35 was a mixed type as determined by Dixon’s plot; however, the inhibition mechanism of endometase was noncompetitive with a K_i value of 240 μM. The catalytic activities of MMPs are influenced by detergents. Monomer of detergents may activate and stabilize MMPs to enhance catalysis, but micelle of detergents may sequester enzyme and block the substrate binding site to impede catalysis. Under physiological conditions, a lipid or membrane microenvironment may regulate enzymatic activity.     

Effects of grazing intensity and grazing exclusion on litter decomposition in the temperate steppe of Nei Mongol,China

Aims Grazing intensity and grazing exclusion affect ecosystem carbon cycling by changing the plant community and soil micro-environment in grassland ecosystems. The aims of this study were: 1) to determine the effects of grazing intensity and grazing exclusion on litter decomposition in the temperate grasslands of Nei Mongol; 2) to compare the difference between above-ground and below-ground litter decomposition; 3) to identify the effects of precipitation on litter production and decomposition. Methods We measured litter production, quality, decomposition rates and soil nutrient contents during the growing season in 2011 and 2012 in four plots, i.e. light grazing, heavy grazing, light grazing exclusion and heavy grazing exclusion. Quadrate surveys and litter bags were used to measure litter production and decomposition rates. All data were analyzed with ANOVA and Pearson’s correlation procedures in SPSS. Important findings Litter production and decomposition rates differed greatly among four plots. During the two years of our study, above-ground litter production and decomposition in heavy-grazing plots were faster than those in light-grazing plots. In the dry year, below-ground litter production and decomposition in light-grazing plots were faster than those in heavy-grazing plots, which is opposite to the findings in the wet year. Short-term grazing exclusion could promote litter production, and the exclusion of light-grazing could increase litter decomposition and nutrient cycling. In contrast, heavy-grazing exclusion decreased litter decomposition. Thus, grazing exclusion is beneficial to the restoration of the light-grazing grasslands, and more human management measures are needed during the restoration of heavy-grazing grasslands. Precipitation increased litter production and decomposition, and below-ground litter was more vulnerable to the inter-annual change of precipitation than above-ground litter. Compared to the light-grazing grasslands, heavy-grazing grasslands had higher sensitivity to precipitation. The above-ground litter decomposition was strongly positively correlated with the litter N content (R² = 0.489, p < 0.01) and strongly negatively correlated with the soil total N content (R² = 0.450, p < 0.01), but it was not significantly correlated with C:N and lignin:N. Below-ground litter decomposition was negatively correlated with the litter C (R² = 0.263, p < 0.01), C:N (R² = 0.349, p < 0.01) and cellulose content (R² = 0.460, p < 0.01). Our results will provide a theoretical basis for ecosystem restoration and the research of carbon cycling.     

Assessing water scarcity by simultaneously considering environmental flow requirements,water quantity,and water quality

Water scarcity is a widespread problem in many parts of the world. Most previous methods of water scarcity assessment only considered water quantity, and ignored water quality. In addition, the environmental flow requirement (EFR) was commonly not explicitly considered in the assessment. In this study, we developed an approach to assess water scarcity by considering both water quantity and quality, while at the same time explicitly considering EFR. We applied this quantity–quality-EFR (QQE) approach for the Huangqihai River Basin in Inner Mongolia, China. We found that to keep the river ecosystem health at a “good” level (i.e., suitable for swimming, fishing, and aquaculture), 26% of the total blue water resources should be allocated to meet the EFR. When such a “good” level is maintained, the quantity- and quality-based water scarcity indicators were 1.3 and 14.2, respectively; both were above the threshold of 1.0. The QQE water scarcity indicator thus can be expressed as 1.3(26%)|14.2, indicating that the basin was suffering from scarcity problems related to both water quantity and water quality for a given rate of EFR. The current water consumption has resulted in degradation of the basin's river ecosystems, and the EFR cannot be met in 3 months of a year. To reverse this situation, future policies should aim to reduce water use and pollution discharge, meet the EFR for maintaining healthy river ecosystems, and substantially improve pollution treatment.