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Anaerobic digestion : making biogas - making energy : the Earthscan expert guide
\"Hundreds of million tonnes of agricultural and food waste are produced each year around the world, most of which is just that, waste. Anaerobic digestion, biogas and the heat and electricity that can be produced from it is still a nascent industry in many countries, yet the benefits of AD spread throughout the community: - Gives good financial returns to farmers and eco-entrepreneurs. - Helps community leaders meet various policies and legislative targets. - Offers an environmentally sensitive waste disposal option. - Provides a local heat and power supply, & creates employment opportunities - Reduces greenhouse gas emissions, as well as providing an organic fertilizer. Although the process of AD itself is relatively simple there are several system options available to meet the demands of different feedstocks. This book describes, in simple, easy to read language the five common systems of AD; how they work, the impact of scale, the basic requirements, the costs and financial implications, and how to get involved in this rapidly growing green industry\"--Provided by publisher.
Book
The future-focused Proactive Conservation Index highlights unrecognized global priorities for vertebrate conservation
Human-induced environmental pressures are expected to intensify worldwide during the 21st century. Consequently, future-focused tools and approaches to anticipate pressures on biodiversity are key to effectively prioritize conservation actions and supplement existing approaches. Here, we develop a continuous conservation prioritization index, the Proactive Conservation Index (PCI), that integrates projected future extrinsic threats and traits that can predispose species’ vulnerability. We used the PCI to assess the conservation priority of 33,560 species of land vertebrates worldwide, compared our results to the extinction risk categories of these species in the International Union for Conservation of Nature (IUCN) Red List of Threatened Species, and examined spatial and phylogenetic patterns in these species future conservation needs. We found that median PCI scores broadly followed the order expected under the IUCN Red List classification, but varied substantially within each IUCN Red List category. According to the PCI, reptiles will be the group of land vertebrates with highest conservation priority in the future, despite amphibians currently having the highest proportion of threatened species according to the IUCN Red List. The PCI revealed that species in the Near Threatened category will have future conservation needs more similar to species in threatened categories than to species in the Least Concern category. Arid ecoregions, tropical montane forests, and islands showed the highest differences between conservation priorities set using the PCI and the IUCN Red List, indicating possible unrecognized future conservation needs. The proportion of threatened species according to the IUCN Red List was uncorrelated with the protected area coverage of each ecoregion, while the PCI, by design, highlighted currently unprotected ecoregions with sensitive fauna that will have high exposure to threats in the future. We produced a user-friendly web application to display our results and an R package to enable users to calculate PCI scores for any taxon and region, customizing the index according to the severity of predicted threats and importance of species attributes in other systems. Our novel index can help practitioners prioritize fine-scale species conservation actions in light of future threats and different global change scenarios.
Journal Article
iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria
The extraordinary diversity of viruses infecting bacteria and archaea is now primarily studied through metagenomics. While metagenomes enable high-throughput exploration of the viral sequence space, metagenome-derived sequences lack key information compared to isolated viruses, in particular host association. Different computational approaches are available to predict the host(s) of uncultivated viruses based on their genome sequences, but thus far individual approaches are limited either in precision or in recall, i.e., for a number of viruses they yield erroneous predictions or no prediction at all. Here, we describe iPHoP, a two-step framework that integrates multiple methods to reliably predict host taxonomy at the genus rank for a broad range of viruses infecting bacteria and archaea, while retaining a low false discovery rate. Based on a large dataset of metagenome-derived virus genomes from the IMG/VR database, we illustrate how iPHoP can provide extensive host prediction and guide further characterization of uncultivated viruses.
Journal Article
ClipKIT: A multiple sequence alignment trimming software for accurate phylogenomic inference
Highly divergent sites in multiple sequence alignments (MSAs), which can stem from erroneous inference of homology and saturation of substitutions, are thought to negatively impact phylogenetic inference. Thus, several different trimming strategies have been developed for identifying and removing these sites prior to phylogenetic inference. However, a recent study reported that doing so can worsen inference, underscoring the need for alternative alignment trimming strategies. Here, we introduce ClipKIT, an alignment trimming software that, rather than identifying and removing putatively phylogenetically uninformative sites, instead aims to identify and retain parsimony-informative sites, which are known to be phylogenetically informative. To test the efficacy of ClipKIT, we examined the accuracy and support of phylogenies inferred from 14 different alignment trimming strategies, including those implemented in ClipKIT, across nearly 140,000 alignments from a broad sampling of evolutionary histories. Phylogenies inferred from ClipKIT-trimmed alignments are accurate, robust, and time saving. Furthermore, ClipKIT consistently outperformed other trimming methods across diverse datasets, suggesting that strategies based on identifying and retaining parsimony-informative sites provide a robust framework for alignment trimming.
Journal Article
CellProfiler 3.0: Next-generation image processing for biology
CellProfiler has enabled the scientific research community to create flexible, modular image analysis pipelines since its release in 2005. Here, we describe CellProfiler 3.0, a new version of the software supporting both whole-volume and plane-wise analysis of three-dimensional (3D) image stacks, increasingly common in biomedical research. CellProfiler's infrastructure is greatly improved, and we provide a protocol for cloud-based, large-scale image processing. New plugins enable running pretrained deep learning models on images. Designed by and for biologists, CellProfiler equips researchers with powerful computational tools via a well-documented user interface, empowering biologists in all fields to create quantitative, reproducible image analysis workflows.
Journal Article
Inferring the mammal tree: Species-level sets of phylogenies for questions in ecology, evolution, and conservation
Big, time-scaled phylogenies are fundamental to connecting evolutionary processes to modern biodiversity patterns. Yet inferring reliable phylogenetic trees for thousands of species involves numerous trade-offs that have limited their utility to comparative biologists. To establish a robust evolutionary timescale for all approximately 6,000 living species of mammals, we developed credible sets of trees that capture root-to-tip uncertainty in topology and divergence times. Our \"backbone-and-patch\" approach to tree building applies a newly assembled 31-gene supermatrix to two levels of Bayesian inference: (1) backbone relationships and ages among major lineages, using fossil node or tip dating, and (2) species-level \"patch\" phylogenies with nonoverlapping in-groups that each correspond to one representative lineage in the backbone. Species unsampled for DNA are either excluded (\"DNA-only\" trees) or imputed within taxonomic constraints using branch lengths drawn from local birth-death models (\"completed\" trees). Joining time-scaled patches to backbones results in species-level trees of extant Mammalia with all branches estimated under the same modeling framework, thereby facilitating rate comparisons among lineages as disparate as marsupials and placentals. We compare our phylogenetic trees to previous estimates of mammal-wide phylogeny and divergence times, finding that (1) node ages are broadly concordant among studies, and (2) recent (tip-level) rates of speciation are estimated more accurately in our study than in previous \"supertree\" approaches, in which unresolved nodes led to branch-length artifacts. Credible sets of mammalian phylogenetic history are now available for download at http://vertlife.org/phylosubsets, enabling investigations of long-standing questions in comparative biology.
Journal Article
Characterising metabolomic signatures of lipid-modifying therapies through drug target mendelian randomisation
Large-scale molecular profiling and genotyping provide a unique opportunity to systematically compare the genetically predicted effects of therapeutic targets on the human metabolome. We firstly constructed genetic risk scores for 8 drug targets on the basis that they primarily modify low-density lipoprotein (LDL) cholesterol (HMGCR, PCKS9, and NPC1L1 ) , high-density lipoprotein (HDL) cholesterol (CETP), or triglycerides (APOC3, ANGPTL3, ANGPTL4, and LPL). Conducting mendelian randomisation (MR) provided strong evidence of an effect of drug-based genetic scores on coronary artery disease (CAD) risk with the exception of ANGPTL3. We then systematically estimated the effects of each score on 249 metabolic traits derived using blood samples from an unprecedented sample size of up to 115,082 UK Biobank participants. Genetically predicted effects were generally consistent among drug targets, which were intended to modify the same lipoprotein lipid trait. For example, the linear fit for the MR estimates on all 249 metabolic traits for genetically predicted inhibition of LDL cholesterol lowering targets HMGCR and PCSK9 was r 2 = 0.91. In contrast, comparisons between drug classes that were designed to modify discrete lipoprotein traits typically had very different effects on metabolic signatures (for instance, HMGCR versus each of the 4 triglyceride targets all had r 2 < 0.02). Furthermore, we highlight this discrepancy for specific metabolic traits, for example, finding that LDL cholesterol lowering therapies typically had a weak effect on glycoprotein acetyls, a marker of inflammation, whereas triglyceride modifying therapies assessed provided evidence of a strong effect on lowering levels of this inflammatory biomarker. Our findings indicate that genetically predicted perturbations of these drug targets on the blood metabolome can drastically differ, despite largely consistent effects on risk of CAD, with potential implications for biomarkers in clinical development and measuring treatment response.
Journal Article
Multiplex qPCR discriminates variants of concern to enhance global surveillance of SARS-CoV-2
With the emergence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants that may increase transmissibility and/or cause escape from immune responses, there is an urgent need for the targeted surveillance of circulating lineages. It was found that the B.1.1.7 (also 501Y.V1) variant, first detected in the United Kingdom, could be serendipitously detected by the Thermo Fisher TaqPath COVID-19 PCR assay because a key deletion in these viruses, spike Δ69–70, would cause a “spike gene target failure” (SGTF) result. However, a SGTF result is not definitive for B.1.1.7, and this assay cannot detect other variants of concern (VOC) that lack spike Δ69–70, such as B.1.351 (also 501Y.V2), detected in South Africa, and P.1 (also 501Y.V3), recently detected in Brazil. We identified a deletion in the ORF1a gene (ORF1a Δ3675–3677) in all 3 variants, which has not yet been widely detected in other SARS-CoV-2 lineages. Using ORF1a Δ3675–3677 as the primary target and spike Δ69–70 to differentiate, we designed and validated an open-source PCR assay to detect SARS-CoV-2 VOC. Our assay can be rapidly deployed in laboratories around the world to enhance surveillance for the local emergence and spread of B.1.1.7, B.1.351, and P.1.
Journal Article
The structural context of posttranslational modifications at a proteome-wide scale
The recent revolution in computational protein structure prediction provides folding models for entire proteomes, which can now be integrated with large-scale experimental data. Mass spectrometry (MS)-based proteomics has identified and quantified tens of thousands of posttranslational modifications (PTMs), most of them of uncertain functional relevance. In this study, we determine the structural context of these PTMs and investigate how this information can be leveraged to pinpoint potential regulatory sites. Our analysis uncovers global patterns of PTM occurrence across folded and intrinsically disordered regions. We found that this information can help to distinguish regulatory PTMs from those marking improperly folded proteins. Interestingly, the human proteome contains thousands of proteins that have large folded domains linked by short, disordered regions that are strongly enriched in regulatory phosphosites. These include well-known kinase activation loops that induce protein conformational changes upon phosphorylation. This regulatory mechanism appears to be widespread in kinases but also occurs in other protein families such as solute carriers. It is not limited to phosphorylation but includes ubiquitination and acetylation sites as well. Furthermore, we performed three-dimensional proximity analysis, which revealed examples of spatial coregulation of different PTM types and potential PTM crosstalk. To enable the community to build upon these first analyses, we provide tools for 3D visualization of proteomics data and PTMs as well as python libraries for data accession and processing.
Journal Article
Proteome-wide analysis of chaperone-mediated autophagy targeting motifs
Chaperone-mediated autophagy (CMA) contributes to the lysosomal degradation of a selective subset of proteins. Selectivity lies in the chaperone heat shock cognate 71 kDa protein (HSC70) recognizing a pentapeptide motif (KFERQ-like motif) in the protein sequence essential for subsequent targeting and degradation of CMA substrates in lysosomes. Interest in CMA is growing due to its recently identified regulatory roles in metabolism, differentiation, cell cycle, and its malfunctioning in aging and conditions such as cancer, neurodegeneration, or diabetes. Identification of the subset of the proteome amenable to CMA degradation could further expand our understanding of the pathophysiological relevance of this form of autophagy. To that effect, we have performed an in silico screen for KFERQ-like motifs across proteomes of several species. We have found that KFERQ-like motifs are more frequently located in solvent-exposed regions of proteins, and that the position of acidic and hydrophobic residues in the motif plays the most important role in motif construction. Cross-species comparison of proteomes revealed higher motif conservation in CMA-proficient species. The tools developed in this work have also allowed us to analyze the enrichment of motif-containing proteins in biological processes on an unprecedented scale and discover a previously unknown association between the type and combination of KFERQ-like motifs in proteins and their participation in specific biological processes. To facilitate further analysis by the scientific community, we have developed a free web-based resource (KFERQ finder) for direct identification of KFERQ-like motifs in any protein sequence. This resource will contribute to accelerating understanding of the physiological relevance of CMA.
Journal Article