Evolutionary transitions in symbioses: dramatic reductions in bathymetric and geographic ranges of Zoanthidea coincide with loss of symbioses with invertebrates

Two fundamental symbiosis‐based trophic types are recognized among Zoanthidea (Cnidaria, Anthozoa): fixed carbon is either obtained directly from zooxanthellae photosymbionts or from environmental sources through feeding with the assistance of host‐invertebrate behaviour and structure. Each trophic type is characteristic of the suborders of Zoanthidea and is associated with substantial distributional asymmetries: suborder Macrocnemina are symbionts of invertebrates and have global geographic and bathymetric distributions and suborder Brachycnemina are hosts of endosymbiotic zooxanthellae and are restricted to tropical photic zones. While exposure to solar radiation could explain the bathymetric asymmetry it does not explain the geographic asymmetry, nor is it clear why evolutionary transitions to the zooxanthellae‐free state have apparently occurred within Macrocnemina but not within Brachycnemina. To better understand the transitions between symbiosis‐based trophic types of Zoanthidea, a concatenated data set of nuclear and mitochondrial nucleotide sequences were used to test hypotheses of monophyly for groups defined by morphology and symbiosis, and to reconstruct the evolutionary transitions of morphological and symbiotic characters. The results indicate that the morphological characters that define Macrocnemina are plesiomorphic and the characters that define its subordinate taxa are homoplasious. Symbioses with invertebrates have ancient and recent transitions with a general pattern of stability in host associations through evolutionary time. The reduction in distribution of Zoanthidea is independent of the evolution of zooxanthellae symbiosis and consistent with hypotheses of the benefits of invertebrate symbioses, indicating that the ability to persist in most habitats may have been lost with the termination of symbioses with invertebrates.     

Enhancing Data Reliability in TOMAHAQ for Large‐Scale Protein Quantification

The analytical scale of most mass‐spectrometry‐based targeted proteomics assays is usually limited by assay performance and instrument utilization. A recently introduced method, called triggered by offset, multiplexed, accurate mass, high resolution, and absolute quantitation (TOMAHAQ), combines both peptide and sample multiplexing to simultaneously improve analytical scale and quantitative performance. In the present work, critical technical requirements and data analysis considerations for successful implementation of the TOMAHAQ technique based on the study of a total of 185 target peptides across over 200 clinical plasma samples are discussed. Importantly, it is observed that significant interference originate from the TMTzero reporter ion used for the synthetic trigger peptides. This interference is not expected because only TMT10plex reporter ions from the target peptides should be observed under typical TOMAHAQ conditions. In order to unlock the great promise of the technique for high throughput quantification, here a post‐acquisition data correction strategy to deconvolute the reporter ion superposition and recover reliable data is proposed.     

MicroPhenoDB Associates Metagenomic Datawith Pathogenic Microbes,Microbial Core Genes,and Human Disease Phenotypes

Microbes play important roles in human health and disease. The interaction between microbes and hosts is a reciprocal relationship, which remains largely under-explored. Current computational resources lack manually and consistently curated data to connect metagenomic data to pathogenic microbes, microbial core genes, and disease phenotypes. We developed the MicroPhenoDB database by manually curating and consistently integrating microbe-disease association data. MicroPhenoDB provides 5677 non-redundant associations between 1781 microbes and 542 human disease phenotypes across more than 22 human body sites. MicroPhenoDB also provides 696,934 relationships between 27,277 unique clade-specific core genes and 685 microbes. Disease phenotypes are classified and described using the Experimental Factor Ontology (EFO). A refined score model was developed to prioritize the associations based on evidential metrics. The sequence search option in MicroPhenoDB enables rapid identification of existing pathogenic microbes in samples without running the usual metagenomic data processing and assembly. MicroPhenoDB offers data browsing, searching, and visualization through user-friendly web interfaces and web service application programming interfaces. MicroPhenoDB is the first database platform to detail the relationships between pathogenic microbes, core genes, and disease phenotypes. It will accelerate metagenomic data analysis and assist studies in decoding microbes related to human diseases. MicroPhenoDB is available through http://www.liwzlab.cn/microphenodb and http://lilab2.sysu.edu.cn/microphenodb.     

A cost–benefit analysis of the environmental taxation policy in China: A frontier analysis‐based environmentally extended input–output optimization method

China's high‐speed economic development and reliance on overconsumption of natural resources have led to serious environmental pollution. Environmental taxation is seen as an effective economic tool to help mitigate air pollution. In order to assess the effects of different scenarios of environmental taxation policies, we propose a frontier‐based environmentally extended input–output optimization model with explicit emission abatement sectors to reflect the inputs and benefits of abatement. Frontier analysis ensures policy scenarios are assessed under the same technical efficiency benchmark, while input–output analysis depicts the wide range of economic transactions among sectors of an economy. Four scenarios are considered in this study, which are increasing specific tax rates of SO₂, NO_x, and soot and dust separately and increasing all three tax rates simultaneously. Our estimation results show that: raising tax rates of SO₂, NO_x, and soot and dust simultaneously would have the highest emission reduction effects, with the SO₂ tax rate making the greatest contribution to emission reduction. Raising the soot and dust tax rate is the most environmentally friendly strategy due to its highest abatement to welfare through avoided health costs. The combination of frontier analysis and input–output analysis provides policy makers a comprehensive and sectoral approach to assess costs and benefits of environmental taxation.     

Life cycle assessment of emerging technologies at the lab scale: The case of nanowire‐based solar cells

Nanomaterials are expected to play an important role in the development of sustainable products. The use of nanomaterials in solar cells has the potential to increase their conversion efficiency. In this study, we performed a life cycle assessment (LCA) for an emerging nanowire‐based solar technology. Two lab‐scale manufacturing routes for the production of nanowire‐based solar cells have been compared—the direct growth of GaInP nanowires on silicon substrate and the growth of InP nanowires on native substrate, peel off, and transfer to silicon substrate. The analysis revealed critical raw materials and processes of the current lab‐scale manufacturing routes such as the use of trifluoromethane (CHF₃), gold, and an InP wafer and a stamp, which are used and discarded. The environmental performance of the two production routes under different scenarios has been assessed. The scenarios include the use of an alternative process to reduce the gold requirements—electroplating instead of metallization, recovery of gold, and reuse of the InP wafer and the stamp. A number of suggestions, based on the LCA results—including minimization of the use of gold and further exploration for upscaling of the electroplating process, the increase in the lifetimes of the wafer and the stamp, and the use of fluorine‐free etching materials—have been communicated to the researchers in order to improve the environmental performance of the technology. Finally, the usefulness and limitations of lab‐scale LCA as a tool to guide the sustainable development of emerging technologies are discussed.     

Lifting the veil on the correction of double counting incidents in hybrid life cycle assessment

Life cycle assessment (LCA) and environmentally extended input–output analyses (EEIOA) are two techniques commonly used to assess environmental impacts of an activity/product. Their strengths and weaknesses are complementary, and they are thus regularly combined to obtain hybrid LCAs. A number of approaches in hybrid LCA exist, which leads to different results. One of the differences is the method used to ensure that mixed LCA and EEIOA data do not overlap, which is referred to as correction for double counting. This aspect of hybrid LCA is often ignored in reports of hybrid assessments and no comprehensive study has been carried out on it. This article strives to list, compare, and analyze the different existing methods for the correction of double counting. We first harmonize the definitions of the existing correction methods and express them in a common notation, before introducing a streamlined variant. We then compare their respective assumptions and limitations. We discuss the loss of specific information regarding the studied activity/product and the loss of coherent financial representation caused by some of the correction methods. This analysis clarifies which techniques are most applicable to different tasks, from hybridizing individual LCA processes to integrating complete databases. We finally conclude by giving recommendations for future hybrid analyses.