Bottom-up Analysis Research Articles

Techno-Economic Evaluation of Biological and Fluidised-Bed Based Methanation Process Chains for Grid-Ready Biomethane Production

Three different power-to-methane process chains with grid injection in two scales (1 MWel and 6 MWel) were analysed regarding their investment and operation cost. The process chains were based on biological or catalytic bubbling fluidised bed methanation in combination with proton exchange membrane or solid oxide electrolyser cells. A bottom-up techno-economic analysis showed a cost benefit of around 17–19% lower biomethane production cost for the bubbling fluidised bed technology as less than a third of the reactor volumes is required for catalytic methanation. This cost benefit is only given in combination with PEM electrolysis, as the high-temperature electrolyser stacks currently result in high investment cost. Based on electricity cost of 5 €-ct/kWhel and a plant size of 6 MWel, biomethane production cost of 13.95 €-ct./kWh for catalytic and 17.30 €-ct/kWh for biological methanation could be obtained, both including PEM electrolysis. A significant efficiency increase by integrating the heat of catalytic methanation reaction with the high-temperature electrolysis can be achieved; however investment cost have to decrease below 1000 €/kWel to obtain economically feasible production cost of biomethane. Under current economic and technological circumstances, CO2 methanation using the bubbling fluidised bed technology is the most cost effective.

Analysis on the evolution law and influencing factors of Beijing’s power generation carbon emissions

Emission reduction is a necessary choice for achieving carbon neutrality, and one of the important preconditions for its successful implementation is to determine the evolution law and identify the factors affecting carbon emissions from power generation. For providing guidance on the formulation of carbon emissions reduction scheme, this paper established a scientific direct carbon emission accounting model for power generation with the bottom-up analysis method, and a decomposition model of the factors influencing carbon emissions from power generation was constructed utilizing the Kaya Identity and LMDI decomposition approach. Then, research was conducted based on the power generation and consumption in Beijing from 2005 to 2019, and the main conclusions are as follows: (1) Beijing’s thermal power CO2 emissions have not changed much and are generally shows a downward trend. The structural changes in thermal power carbon emissions show that the main source of carbon emissions in Beijing has gradually changed from raw coal to natural gas. (2) From the decomposition of influencing factors of direct carbon emissions, energy structure, conversion efficiency and power intensity are three drivers to reduce power-related carbon emissions. (3) Economic development is the main driver of increase in carbon emissions. (4) Beijing’s thermal power carbon intensity is declining, and the electricity consumption of various sectors shows a certain positive correlation with direct carbon emissions. These results show that scientifically quantifying the contribution of the decomposed factors to the change of carbon emissions from thermal power generation can provide a directional guidance for the formulation of carbon emissions reduction scheme, so as to achieve the “double carbon” goals more reasonably and effectively.

Well-Plate μFASP for Proteomic Analysis of Single Pancreatic Islets.

Filter-aided sample preparation (FASP) is widely used in bottom-up proteomics for tryptic digestion. However, the sample recovery yield of this method is limited by the amount of the starting material. While ∼100 ng of digested protein is sufficient for thorough protein identification, proteomic information gets lost with a protein content <10 μg due to incomplete peptide recovery from the filter. We developed and optimized a flexible well-plate μFASP device and protocol that is suitable for an ∼1 μg protein sample. In 1 μg of HeLa digest, we identified 1295 ± 10 proteins with μFASP followed by analysis with liquid chromatography–mass spectrometry. In contrast, only 524 ± 5 proteins were identified with the standard FASP protocol, while 1395 ± 4 proteins were identified in 20 μg after standard FASP as a benchmark. Furthermore, we conducted a combined peptidomic and proteomic study of single pancreatic islets with well-plate μFASP. Here, we separated neuropeptides and digested the remaining on-filter proteins for bottom-up proteomic analysis. Our results indicate inter-islet heterogeneity for the expression of proteins involved in glucose catabolism, pancreatic hormone processing, and secreted peptide hormones. We consider our method to provide a useful tool for proteomic characterization of samples where the biological material is scarce. All proteomic data are available under DOI: 10.6019/PXD029039.

Exploring trade-offs between landscape impact, land use and resource quality for onshore variable renewable energy: an application to Great Britain

The ambitious Net Zero aspirations of Great Britain (GB) require massive and rapid developments of Variable Renewable Energy (VRE) technologies. GB possesses substantial resources for these technologies, but questions remain about which VRE should be exploited where. This study develops a transferable methodology to explore the trade-offs between landscape impact, land use competition and resource quality for onshore wind as well as ground- and roof-mounted photovoltaic (PV) systems for the first time across GB. These trade-offs constrain the technical and economic potentials for these technologies at the Local Authority level. Our approach combines techno-economic and geospatial analyses with crowd-sourced ‘scenicness’ data to quantify landscape aesthetics. Despite strong correlations between scenicness and planning application outcomes for onshore wind, no such relationship exists for ground-mounted PV. The innovative method for rooftop-PV assessment combines bottom-up analysis of four cities with a top-down approach at the national level. The results show large technical potentials that are strongly constrained by both landscape and land use aspects. This equates to about 1324 TWh of onshore wind, 153 TWh of rooftop PV and 1200–7093 TWh ground-mounted PV, depending on scenario. We conclude with five recommendations that focus around aligning energy and planning policies for VRE technologies across multiple scales and governance arenas.

Modular automated bottom-up proteomic sample preparation for high-throughput applications.

Manual proteomic sample preparation methods limit sample throughput and often lead to poor data quality when thousands of samples must be analyzed. Automated liquid handler systems are increasingly used to overcome these issues for many of the sample preparation steps. Here, we detail a step-by-step protocol to prepare samples for bottom-up proteomic analysis for Gram-negative bacterial and fungal cells. The full modular protocol consists of three optimized protocols to: (A) lyse Gram-negative bacteria and fungal cells; (B) quantify the amount of protein extracted; and (C) normalize the amount of protein and set up tryptic digestion. These protocols have been developed to facilitate rapid, low variance sample preparation of hundreds of samples, be easily implemented on widely-available Beckman-Coulter Biomek automated liquid handlers, and allow flexibility for future protocol development. By using this workflow 50 micrograms of protein from 96 samples can be prepared for tryptic digestion in under an hour. We validate these protocols by analyzing 47 Pseudomonas putida and Rhodosporidium toruloides samples and show that this modular workflow provides robust, reproducible proteomic samples for high-throughput applications. The expected results from these protocols are 94 peptide samples from Gram-negative bacterial and fungal cells prepared for bottom-up quantitative proteomic analysis without the need for desalting column cleanup and with protein relative quantity variance (CV%) below 15%.

Shotgun proteomics approaches for authentication, biological analyses, and allergen detection in feed and food-grade insect species

Untargeted proteomics can contribute to composition and authenticity analyses of highly processed mixed food and feed products. Here, we present the setup of an analytical flow tandem mass spectrometry method (AF-HPLC HR-MS) for analysis of insect meal from five different species. Data acquired were compared with previously published data employing spectra matching and standard bottom-up proteomics bioinformatics analyses. In addition, data were screened for insect species marker peptides and common allergens, respectively. The results obtained indicate that the performance of the newly established AF-HPLC HR-MS workflow is in line with previously published methods for insect species differentiation. Data obtained in the present study, also lead to the discovery of novel markers for the development of targeted MS analyses of insect species in food- and feed-mixes and highlighted that known allergen such as arginine kinase or tropomyosin were consistently detected across all five species tested.

Greenhouse Gas Abatement in EUROPE—A Scenario-Based, Bottom-Up Analysis Showing the Effect of Deep Emission Mitigation on the European Energy System

Greenhouse gas emissions need to be drastically reduced to mitigate the environmental impacts caused by climate change, and to lead to a transformation of the European energy system. A model landscape consisting of four final energy consumption sector models with high spatial (NUTS-3) and temporal (hourly) resolution and the multi-energy system model ISAaR is extended and applied to investigate the transformation pathway of the European energy sector in the deep emission mitigation scenario solidEU. The solidEU scenario describes not only the techno-economic but also the socio-political contexts, and it includes the EU27 + UK, Norway, and Switzerland. The scenario analysis shows that volatile renewable energy sources (vRES) dominate the energy system in 2050. In addition, the share of flexible sector coupling technologies increases to balance electricity generation from vRES. Seasonal differences are balanced by hydrogen storage with a seasonal storage profile. The deployment rates of vRES in solidEU show that a fast, profound energy transition is necessary to achieve European climate protection goals.

A Novel Fibrinolytic Protein From Pheretima vulgaris: Purification, Identification, Antithrombotic Evaluation, and Mechanisms Investigation.

Thrombotic diseases have been considered major causes of death around the world. Treatments with thrombolytic drugs, such as recombinant tissue-plasminogen activator, urokinase, and streptokinase, are reported to have a life-threatening bleeding tendency. On the contrary, lumbrokinase, identified from Lumbricus rubellus, is specific to fibrin and does not cause excessive bleeding. It possesses fibrinolytic activity and activation of plasminogen to dissolve fibrin. Hence, the purification of fibrinolytic protein monomer from earthworm and antithrombotic evaluation and investigation of mechanisms are needed. In this study, a novel fibrinolytic protein EPF3, with strong fibrinolytic activity, was purified from Pheretima vulgaris by ion exchange and size exclusion chromatography. SDS PAGE, bottom-up proteomics analysis, de novo sequencing, and circular dichroism (CD) analysis were carried out for identification and characterization of it. EPF3, with a molecular weight of 25136.24 Da, consisted of 241 amino acids and contained various forms of secondary structures, including α-helix (3.9%), β-sheet (42.8%), β-turn (21.2%), and random coil (32.1%). It was a trypsin-like serine protease and stable at pH 7.0 to 11.0 and below 40°C. EPF3 was confirmed to possess an antithrombotic effect by ex vivo clot lysis test and fibrinogen-thrombin time (Fib-TT) assay. The three-dimensional structure of EPF3 was predicted by SWISS-MODEL. Molecular docking analysis predicted that EPF3 could directly interact with antithrombotic target proteins (fibrin, fibrinogen, and plasminogen), which was further confirmed by further studies. The antithrombotic mechanism of EPF3 was clarified to be outstanding direct fibrinolysis, fibrinogenolytic activity, and certain activation of plasminogen. EPF3 possesses the potential to be developed into a promising antithrombotic agent.

Spatiotemporal upscaling errors of building stock clustering for energy demand simulation

Energy demand of buildings forms a key component of energy system analyses. To integrate building energy demand into energy system models, detailed simulation of every single building is impractical and often computationally infeasible. Simulations are therefore typically performed on a sample of buildings for bottom-up analysis. For a simplified representation of the building stock, grouping and clustering are widely applied. However, a spatiotemporal quantification of the resulting upscaling errors is however lacking. Here, a grouping and clustering approach is performed for all Swiss buildings for bottom-up energy demand analysis. The spatiotemporal simulation error is quantified at the national, regional and neighbourhood (300×300 m) scales. Whereas national energy demands are well represented, the error induced by the grouping and clustering is significant at the neighbourhood scale: simulated demand is easily over or underestimated by double-digit percentages. Obtained regional full load hours and daily load factor values by a grouping and clustering approach are comparable to a full simulation of all buildings. However, careful consideration must be given to the used climate data if relying on clustering approaches. Our analysis reveals the challenge of representing peak demands well by aggregation of building demand profiles, which is exacerbated by grouping and clustering. Bottom-up studies thus need to consider errors arising from the grouping and clustering approach and distinguish between errors resulting from the upscaling process and other sources of uncertainty such as data inputs or modelling concepts. Finally, calculated energy signatures are shown to perform well as a fast and viable alternative to grouping and clustering.

Capillary Electrophoresis Coupled to Electrospray Ionization Tandem Mass Spectrometry for Ultra-Sensitive Proteomic Analysis of Limited Samples.

In this work, we developed an ultra-sensitive CE-MS/MS method for bottom-up proteomics analysis of limited samples, down to sub-nanogram levels of total protein. Analysis of 880 and 88 pg of the HeLa protein digest standard by CE-MS/MS yielded ∼1100 ± 46 and ∼160 ± 59 proteins, respectively, demonstrating higher protein and peptide identifications than the current state-of-the-art CE-MS/MS-based proteomic analyses with similar amounts of sample. To demonstrate potential applications of our ultra-sensitive CE-MS/MS method for the analysis of limited biological samples, we digested 500 and 1000 HeLa cells using a miniaturized in-solution digestion workflow. From 1-, 5-, and 10-cell equivalents injected from the resulted digests, we identified 744 ± 127, 1139 ± 24, and 1271 ± 6 proteins and 3353 ± 719, 5709 ± 513, and 8527 ± 114 peptide groups, respectively. Furthermore, we performed a comparative assessment of CE-MS/MS and two reversed-phased nano-liquid chromatography (RP-nLC-MS/MS) methods (monolithic and packed columns) for the analysis of a ∼10 ng HeLa protein digest standard. Our results demonstrate complementarity in the protein- and especially peptide-level identifications of the evaluated CE-MS- and RP-nLC-MS-based methods. The techniques were further assessed to detect post-translational modifications and highlight the strengths of the CE-MS/MS approach in identifying potentially important and biologically relevant modified peptides. With a migration window of ∼60 min, CE-MS/MS identified ∼2000 ± 53 proteins on average from a single injection of ∼8.8 ng of the HeLa protein digest standard. Additionally, an average of 232 ± 10 phosphopeptides and 377 ± 14 N-terminal acetylated peptides were identified in CE-MS/MS analyses at this sample amount, corresponding to 2- and 1.5-fold more identifications for each respective modification found by nLC-MS/MS methods.

Openings and closings in tourist offices in Belgium, France and the Netherlands.

This paper deals with openings and closings in 400 service encounters in tourist offices situated in Belgium’s two main language communities, Flanders and Wallonia, in the north of France and the south of the Netherlands. On the basis of a detailed, bottom-up quantitative analysis of the structural properties of the openings and closings, we draw part of the interactional profiles of the tourist office encounters. Differences between the four regions are shown to be related to the degree of volubility and involvement of the interactants and to the degree of ritualisation and efficiency of the opening and the closing section.

Enhanced Coverage of Low-Abundance Proteins in Bottom-Up Proteomics Analysis of Yeast Using Fluoroalcohol-Mediated Supramolecular Biphasic Systems of Chaps and Mixed Amphiphiles

Enhanced Coverage of Low-Abundance Proteins in Bottom-Up Proteomics Analysis of Yeast Using Fluoroalcohol-Mediated Supramolecular Biphasic Systems of Chaps and Mixed Amphiphiles

Bottom-Up Analysis of Proteins by Peptide Mass Fingerprinting with tCITP-CZE-ESI-TOF MS After Tryptic Digest.

The identification of proteins in samples of moderate to complex composition is primarily done by bottom-up approaches. Therefore, proteins are enzymatically digested, mostly by trypsin, and the resulting peptides are then separated prior to their transfer to a mass spectrometer. The following protocol portrays a bottom-up method, which was optimized for the application of CZE-ESI-TOF MS. Protein denaturation is achieved by addition of 2,2,2-trifluoroethanol (TFE) and heat treatment. Afterwards, disulfide bonds are reduced with tris-(2-carboxyethyl)phosphine (TCEP) and subsequently alkylated with iodoacetamide (IAA). The tryptic digest is performed in an ammonium bicarbonate buffer at pH8.0. The digested protein sample is then concentrated in-capillary by transient capillary isotachophoresis (tCITP) with subsequent CZE separation of tryptic peptides in an acidic background electrolyte. Hyphenation to a time-of-flight (TOF) mass spectrometer is carried out by a triple-tube coaxial sheath flow interface, which uses electrospray ionization (ESI). Peptide identification is done by peptide mass fingerprinting (PMF). The protocol is outlined exemplarily for a model protein, i.e., bovine β-lactoglobulin A.

Possibilistic response surfaces: incorporating fuzzy thresholds into bottom-up flood vulnerability analysis

Abstract. Several alternatives have been proposed to shift the paradigms of water management under uncertainty from predictive to decision-centric. An often-mentioned tool is the response surface mapping system performance with a large sample of future hydroclimatic conditions through a stress test. Dividing this exposure space between acceptable and unacceptable states requires a criterion of acceptable performance defined by a threshold. In practice, however, stakeholders and decision-makers may be confronted with ambiguous objectives for which the acceptability threshold is not clearly defined (crisp). To accommodate such situations, this paper integrates fuzzy thresholds to the response surface tool. Such integration is not straightforward when response surfaces also have their own irreducible uncertainty from the limited number of descriptors and the stochasticity of hydroclimatic conditions. Incorporating fuzzy thresholds, therefore, requires articulating categories of imperfect knowledge that are different in nature, i.e., the irreducible uncertainty of the response itself relative to the variables that describe change and the ambiguity of the acceptability threshold. We, thus, propose possibilistic surfaces to assess flood vulnerability with fuzzy acceptability thresholds. An adaptation of the logistic regression for fuzzy set theory combines the probability of an acceptable outcome and the ambiguity of the acceptability criterion within a single possibility measure. We use the flood-prone reservoir system of the Upper Saint François River basin in Canada as a case study to illustrate the proposed approach. Results show how a fuzzy threshold can be quantitatively integrated when generating a response surface and how ignoring it might lead to different decisions. This study suggests that further conceptual developments could link the reliance on acceptability thresholds in bottom-up assessment frameworks with the current uses of fuzzy set theory.

An integrated flood risk assessment approach based on coupled hydrological-hydraulic modeling and bottom-up hazard vulnerability analysis

Accurately quantifying and assessing the flood risks is critical for flood hazard mitigation and prevention. This study proposed a new integrated flood risk assessment framework to map flood risk, hazard and vulnerability by coupling the HEC-HMS hydrological model, the HEC-RAS 1D and 2D hydraulic models, and a bottom-up hazard vulnerability analysis. The Old Brahmaputra River floodplain of Bangladesh, a flood-prone region, was chosen as a case study. The coupled hydrological-hydraulic model shows a comparable robust performance in both calibration and validation periods with Nash-Sutcliffe efficiency coefficient = 0.93 (0.81), coefficient of determination = 0.95 (0.89), and percent bias = −1.17% (2.40%) for the calibration (validation) period. Our results indicate that the assessed risk levels are roughly consistent with the overall property distribution and flood-hazard potential in the study area. The proposed framework and associated findings are valuable for developing adaptation strategies and early-warning systems to reduce flood impacts in the future.

Quantitative proteome profiling provides evidence of an activation of the complement cascade in ATTR amyloidosis

Amyloidosis is a disease group caused by pathological aggregation and deposition of peptides in diverse tissue sites. Apart from the fibril protein, amyloid deposits frequently enclose non-fibrillar constituents. In this study, carpal tunnel tissue sections with ATTR amyloid were analysed by quantitative mass spectrometry-based proteomics. Following manual dissection, tissue samples of equal size and with heterogeneous amyloid load were dissected and forwarded to bottom-up proteome analysis and label-free protein profiling. The amyloid-associated proteins showed significant correlations of label-free intensity profiles. A comprehensive list of 83 proteins specifically enriched in amyloid deposits was discovered. In addition to well-known signature proteins (e.g. apolipoprotein E, apolipoprotein A-IV, and vitronectin), 22 members of the complement system, including all seven components of the membrane attack complex could be associated to the disease. These data lend support to the hypothesis that the complement system is activated in ATTR amyloidosis.

Cost and cost-effectiveness of dolutegravir-based antiretroviral regimens: an economic evaluation of a clinical trial.

HIV programmes world-wide currently make decisions regarding new antiretroviral therapy (ART) regimens with less side-effects and higher resistance barriers, which may improve adherence and viral suppression. Economic evaluation helps inform these decisions. We conducted an economic evaluation of three ART regimens included in the ADVANCE trial from the provider's perspective: tenofovir alafenamide (TAF)/emtricitabine (FTC)+dolutegravir (DTG) and tenofovir disoproxil fumarate (TDF)/FTC+DTG, compared with TDF/FTC/efavirenz (EFV). We used top-down and bottom-up cost analysis with resource utilization based on trial data and adjusted to emulate routine care. We estimated the cost-effectiveness of each regimen as cost per person virally suppressed or retained and per life-year saved, at 48 and 96 weeks. Though the DTG-based trial arms were 2% more costly than TDF/FTC/EFV, both had slightly lower cost-per-outcome ($9783 and $9929/patient virally suppressed for TDF/FTC+DTG and TAF/FTC+DTG, respectively) than TDF/FTC/EFV ($10 365). The trial cost per additional virally suppressed patient, compared with TDF/FTC/EFV, was lower in the TDF/FTC+DTG arm ($2967) compared with TAF/FTC+DTG ($3430). In routine care, cost per virally suppressed patient was estimated as similar between TDF/FTC+DTG ($426) and TDF/FTC/EFV ($424) but more costly under TAF/FTC+DTG. Similar results were seen in the cost per additional person retained across scenarios. When modelled over 20 years, TDF/FTC+DTG was more cost-effective than TAF/FTC+DTG ($10 341 vs $41 958/life-year saved). TDF/FTC+DTG had similar costs per outcome as TDF/FTC/EFV in the routine care scenario but TDF/FTC+DTG was more cost-effective when modelled over 20 years.

Building back better: How big are green spending multipliers?

Is there a trade-off between spending on the green economy and an economy's strength? This paper addresses this question by estimating output multipliers for spending in clean energy and biodiversity conservation, and by comparing these to multipliers of spending on non-ecofriendly energy and land use activities. Using a new international dataset, we arrive at two key results. First, we find that every dollar spent on key carbon-neutral or carbon-sink activities can generate more than a dollar's worth of economic activity, whereas non-green spending returns less than a dollar. Second, for categories of spending where formal comparisons are possible, like renewable versus fossil fuel energy, we find that multipliers on green spending are about twice as large as their non-green counterparts. The point estimates of the multipliers are 1.1–1.7 for renewable energy investment and 0.4–0.7 for fossil fuel energy investment, depending on horizon and specification. These findings survive several robustness checks and lend support to bottom-up analyses that find that stabilizing climate and reversing biodiversity loss go hand in hand with economic prosperity.

Mass Spectrometric Identification of Antimicrobial Peptides from Medicinal Seeds.

Traditional medicinal plants contain a variety of bioactive natural products including cysteine-rich (Cys-rich) antimicrobial peptides (AMPs). Cys-rich AMPs are often crosslinked by multiple disulfide bonds which increase their resistance to chemical and enzymatic degradation. However, this class of molecules is relatively underexplored. Herein, in silico analysis predicted 80–100 Cys-rich AMPs per species from three edible traditional medicinal plants: Linum usitatissimum (flax), Trifolium pratense (red clover), and Sesamum indicum (sesame). Bottom-up proteomic analysis of seed peptide extracts revealed direct evidence for the translation of 3–10 Cys-rich AMPs per species, including lipid transfer proteins, defensins, α-hairpinins, and snakins. Negative activity revealed by antibacterial screening highlights the importance of employing a multi-pronged approach for AMP discovery. Further, this study demonstrates that flax, red clover, and sesame are promising sources for further AMP discovery and characterization.

Evaluation of an integrative Bayesian peptide detection approach on a combinatorial peptide library.

Detection of peptides lies at the core of bottom-up proteomics analyses. We examined a Bayesian approach to peptide detection, integrating match-based models (fragments, retention time, isotopic distribution, and precursor mass) and peptide prior probability models under a unified probabilistic framework. To assess the relevance of these models and their various combinations, we employed a complete- and a tail-complete search of a low-precursor-mass synthetic peptide library based on oncogenic KRAS peptides. The fragment match was by far the most informative match-based model, while the retention time match was the only remaining such model with an appreciable impact--increasing correct detections by around 8 %. A peptide prior probability model built from a reference proteome greatly improved the detection over a uniform prior, essentially transforming de novo sequencing into a reference-guided search. The knowledge of a correct sequence tag in advance to peptide-spectrum matching had only a moderate impact on peptide detection unless the tag was long and of high certainty. The approach also derived more precise error rates on the analyzed combinatorial peptide library than those estimated using PeptideProphet and Percolator, showing its potential applicability for the detection of homologous peptides. Although the approach requires further computational developments for routine data analysis, it illustrates the value of peptide prior probabilities and presents a Bayesian approach for their incorporation into peptide detection.