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Resilience trinity
(2020)
Ensuring ecosystem resilience is an intuitive approach to safeguard the functioning of ecosystems and hence the future provisioning of ecosystem services (ES). However, resilience is a multi-faceted concept that is difficult to operationalize. Focusing on resilience mechanisms, such as diversity, network architectures or adaptive capacity, has recently been suggested as means to operationalize resilience. Still, the focus on mechanisms is not specific enough. We suggest a conceptual framework, resilience trinity, to facilitate management based on resilience mechanisms in three distinctive decision contexts and time-horizons: 1) reactive, when there is an imminent threat to ES resilience and a high pressure to act, 2) adjustive, when the threat is known in general but there is still time to adapt management and 3) provident, when time horizons are very long and the nature of the threats is uncertain, leading to a low willingness to act. Resilience has different interpretations and implications at these different time horizons, which also prevail in different disciplines. Social ecology, ecology and engineering are often implicitly focussing on provident, adjustive or reactive resilience, respectively, but these different notions of resilience and their corresponding social, ecological and economic tradeoffs need to be reconciled. Otherwise, we keep risking unintended consequences of reactive actions, or shying away from provident action because of uncertainties that cannot be reduced. The suggested trinity of time horizons and their decision contexts could help ensuring that longer-term management actions are not missed while urgent threats to ES are given priority.
Resilience trinity
(2020)
Ensuring ecosystem resilience is an intuitive approach to safeguard the functioning of ecosystems and hence the future provisioning of ecosystem services (ES). However, resilience is a multi-faceted concept that is difficult to operationalize. Focusing on resilience mechanisms, such as diversity, network architectures or adaptive capacity, has recently been suggested as means to operationalize resilience. Still, the focus on mechanisms is not specific enough. We suggest a conceptual framework, resilience trinity, to facilitate management based on resilience mechanisms in three distinctive decision contexts and time-horizons: 1) reactive, when there is an imminent threat to ES resilience and a high pressure to act, 2) adjustive, when the threat is known in general but there is still time to adapt management and 3) provident, when time horizons are very long and the nature of the threats is uncertain, leading to a low willingness to act. Resilience has different interpretations and implications at these different time horizons, which also prevail in different disciplines. Social ecology, ecology and engineering are often implicitly focussing on provident, adjustive or reactive resilience, respectively, but these different notions of resilience and their corresponding social, ecological and economic tradeoffs need to be reconciled. Otherwise, we keep risking unintended consequences of reactive actions, or shying away from provident action because of uncertainties that cannot be reduced. The suggested trinity of time horizons and their decision contexts could help ensuring that longer-term management actions are not missed while urgent threats to ES are given priority.
Physically interacting proteins form macromolecule complexes that drive diverse cellular processes. Advances in experimental techniques that capture interactions between proteins provide us with protein-protein interaction (PPI) networks from several model organisms. These datasets have enabled the prediction and other computational analyses of protein complexes. Here we provide a systematic review of the state-of-the-art algorithms for protein complex prediction from PPI networks proposed in the past two decades. The existing approaches that solve this problem are categorized into three groups, including: cluster-quality-based, node affinity-based, and network embedding-based approaches, and we compare and contrast the advantages and disadvantages. We further include a comparative analysis by computing the performance of eighteen methods based on twelve well-established performance measures on four widely used benchmark protein-protein interaction networks. Finally, the limitations and drawbacks of both, current data and approaches, along with the potential solutions in this field are discussed, with emphasis on the points that pave the way for future research efforts in this field. (c) 2022 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/).
A Cell-free Expression Pipeline for the Generation and Functional Characterization of Nanobodies
(2022)
Cell-free systems are well-established platforms for the rapid synthesis, screening, engineering and modification of all kinds of recombinant proteins ranging from membrane proteins to soluble proteins, enzymes and even toxins. Also within the antibody field the cell-free technology has gained considerable attention with respect to the clinical research pipeline including antibody discovery and production. Besides the classical full-length monoclonal antibodies (mAbs), so-called "nanobodies" (Nbs) have come into focus. A Nb is the smallest naturally-derived functional antibody fragment known and represents the variable domain (VHH, similar to 15 kDa) of a camelid heavy-chain-only antibody (HCAb). Based on their nanoscale and their special structure, Nbs display striking advantages concerning their production, but also their characteristics as binders, such as high stability, diversity, improved tissue penetration and reaching of cavity-like epitopes. The classical way to produce Nbs depends on the use of living cells as production host. Though cell-based production is well-established, it is still time-consuming, laborious and hardly amenable for high-throughput applications. Here, we present for the first time to our knowledge the synthesis of functional Nbs in a standardized mammalian cell-free system based on Chinese hamster ovary (CHO) cell lysates. Cell-free reactions were shown to be time-efficient and easy-to-handle allowing for the "on demand" synthesis of Nbs. Taken together, we complement available methods and demonstrate a promising new system for Nb selection and validation.
Metabolites influence flowering time, and thus are among the major determinants of yield. Despite the reported role of trehalose 6-phosphate and nitrate signaling on the transition from the vegetative to the reproductive phase, little is known about other metabolites contributing and responding to developmental phase changes. To increase our understanding which metabolic traits change throughout development in Arabidopsis thaliana and to identify metabolic markers for the vegetative and reproductive phases, especially among individual amino acids (AA), we profiled metabolites of plants grown in optimal (ON) and limited nitrogen (N) (LN) conditions, the latter providing a mild but consistent limitation of N. We found that although LN plants adapt their growth to a decreased level of N, their metabolite profiles are strongly distinct from ON plant profiles, with N as the driving factor for the observed differences. We demonstrate that the vegetative and the reproductive phase are not only marked by growth parameters such as biomass and rosette area, but also by specific metabolite signatures including specific single AA. In summary, we identified N-dependent and -independent indicators manifesting developmental stages, indicating that the plant's metabolic status also reports on the developmental phases.
Broad and unspecific use of antibiotics accelerates spread of resistances. Sensitive and robust pathogen detection is thus important for a more targeted application. Bacteriophages contain a large repertoire of pathogen-binding proteins. These tailspike proteins (TSP) often bind surface glycans and represent a promising design platform for specific pathogen sensors. We analysed bacteriophage Sf6 TSP that recognizes the O-polysaccharide of dysentery-causing Shigella flexneri to develop variants with increased sensitivity for sensor applications. Ligand polyrhamnose backbone conformations were obtained from 2D H-1,H-1-trNOESY NMR utilizing methine-methine and methine-methyl correlations. They agreed well with conformations obtained from molecular dynamics (MD), validating the method for further predictions. In a set of mutants, MD predicted ligand flexibilities that were in good correlation with binding strength as confirmed on immobilized S. flexneri O-polysaccharide (PS) with surface plasmon resonance. In silico approaches combined with rapid screening on PS surfaces hence provide valuable strategies for TSP-based pathogen sensor design.
Simple Summary:& nbsp;High alpine meadows are home to numerous endemic butterfly species. A combination of climate change and changes in agricultural practices has led to a severe decline in many species. A seemingly unaffected representative of this habitat is Erebia pronoe. We studied the behaviour, resource use and population structure of this species to explain its resilience and estimate its future survival potential. This species shows pronounced protandry in combination with serial eclosion. Males were significantly more active and mobile and were also caught significantly more often than females, resulting in a pronounced shift in sex ratio in the predicted population structure. The adults use a wide range of nectar plants and establish homeranges in areas of high habitat quality. Thus, Erebia pronoe adults use a wide array of resources combined with a slight specialisation to avoid niche overlap with closely related species. The resulting ecological flexibility seems to be an adaptation to unpredictable environmental conditions, which should be the result of a long-lasting adaptation process. Moreover, the combination of opportunism and modest specialisation should also be a good basis for coping with future changes caused by climate and land-use change.</p> <br /> <br></p> <br /> A mark-recapture study of the nominotypical Erebia pronoe in the Alps was conducted to survey its ecological demands and characteristics. Population structure analysis revealed a combination of protandry (one-week earlier eclosion of males) and serial eclosion. Significant differences between both sexes were found in population density (males: 580/ha & PLUSMN; 37 SE; females: 241/ha & PLUSMN; 66 SE), sex-ratio (2.4) and behaviour (57.7 vs. 11.9% flying). Both sexes used a wide range of nectar plants (Asteraceae, 77.3%; Dipsacaceae, 12.3%; Gentianaceae, 9.7%). The use of nectar plants shows a non-specific spectrum, which, however, completely avoids overlap with the locally co-occurring species Erebia nivalis. Movement patterns show the establishment of homeranges, which significantly limits the migration potential. Due to its broad ecological niche, E. pronoe will probably be able to react plastically to the consequences of climate change. The formation of high population densities, the unconcerned endangerment status, the unspecific resource spectrum and the sedentary character of the species make E. pronoe a potential indicator of the quality and general resource occurrence of alpine rupicolous grasslands.
Coherent network partitions
(2021)
We continue to study coherent partitions of graphs whereby the vertex set is partitioned into subsets that induce biclique spanned subgraphs. The problem of identifying the minimum number of edges to obtain biclique spanned connected components (CNP), called the coherence number, is NP-hard even on bipartite graphs. Here, we propose a graph transformation geared towards obtaining an O (log n)-approximation algorithm for the CNP on a bipartite graph with n vertices. The transformation is inspired by a new characterization of biclique spanned subgraphs. In addition, we study coherent partitions on prime graphs, and show that finding coherent partitions reduces to the problem of finding coherent partitions in a prime graph. Therefore, these results provide future directions for approximation algorithms for the coherence number of a given graph.
Resource polymorphism is common across taxa and can result in alternate ecotypes with specific morphologies, feeding modes, and behaviors that increase performance in a specific habitat. This can result in high intraspecific variation in the expression of specific traits and the extent to which these traits are correlated within a single population. Although metabolic rate influences resource acquisition and the overall pace of life of individuals it is not clear how metabolic rate interacts with the larger suite of traits to ultimately determine individual fitness. We examined the relationship between metabolic rates and the major differences (habitat use, morphology, and resource use) between littoral and pelagic ecotypes of European perch (Perca fluviatilis) from a single lake in Central Sweden. Standard metabolic rate (SMR) was significantly higher in pelagic perch but did not correlate with resource use or morphology. Maximum metabolic rate (MMR) was not correlated with any of our explanatory variables or with SMR. Aerobic scope (AS) showed the same pattern as SMR, differing across habitats, but contrary to expectations, was lower in pelagic perch. This study helps to establish a framework for future experiments further exploring the drivers of intraspecific differences in metabolism. In addition, since metabolic rates scale with temperature and determine predator energy requirements, our observed differences in SMR across habitats will help determine ecotype-specific vulnerabilities to climate change and differences in top-down predation pressure across habitats.
Human sulfite oxidase (hSO) is a homodimeric two-domain enzyme central in the biological sulfur cycle. A pyranopterin molybdenum cofactor (Moco) is the catalytic site and a heme b(5) group located in the N-terminal domain. The two domains are connected by a flexible linker region. Electrons produced at the Moco in sulfite oxidation, are relayed via heme b(5) to electron acceptors or an electrode surface. Inter-domain conformational changes between an open and a closed enzyme conformation, allowing "gated" electron transfer has been suggested. We first recorded cyclic voltammetry (CV) of hSO on single-crystal Au(111)-electrode surfaces modified by self-assembled monolayers (SAMs) both of a short rigid thiol, cysteamine and of a longer structurally flexible thiol, omega-amino-octanethiol (AOT). hSO on cysteamine SAMs displays a well-defined pair of voltammetric peaks around -0.207 V vs. SCE in the absence of sulfite substrate, but no electrocatalysis. hSO on AOT SAMs displays well-defined electrocatalysis, but only "fair" quality voltammetry in the absence of sulfite. We recorded next in situ scanning tunnelling spectroscopy (STS) of hSO on AOT modified Au(111)-electrodes, disclosing, a 2-5 % surface coverage of strong molecular scale contrasts, assigned to single hSO molecules, notably with no contrast difference in the absence and presence of sulfite. In situ STS corroborated this observation with a sigmoidal tunnelling current/overpotential correlation.
An amperometric trimethylamine N-oxide (TMAO) biosensor is reported, where TMAO reductase (TorA) and glucose oxidase (GOD) and catalase (Cat) were immobilized on the electrode surface, enabling measurements of mediated enzymatic TMAO reduction at low potential under ambient air conditions. The oxygen anti-interference membrane composed of GOD, Cat and polyvinyl alcohol (PVA) hydrogel, together with glucose concentration, was optimized until the O-2 reduction current of a Clark-type electrode was completely suppressed for at least 3 h. For the preparation of the TMAO biosensor, Escherichia coli TorA was purified under anaerobic conditions and immobilized on the surface of a carbon electrode and covered by the optimized O-2 scavenging membrane. The TMAO sensor operates at a potential of -0.8 V vs. Ag/AgCl (1 M KCl), where the reduction of methylviologen (MV) is recorded. The sensor signal depends linearly on TMAO concentrations between 2 mu M and 15 mM, with a sensitivity of 2.75 +/- 1.7 mu A/mM. The developed biosensor is characterized by a response time of about 33 s and an operational stability over 3 weeks. Furthermore, measurements of TMAO concentration were performed in 10% human serum, where the lowest detectable concentration is of 10 mu M TMAO.
With the advent of increasingly powerful computational architectures, scientists use these possibilities to create simulations of ever-increasing size and complexity. Large-scale simulations of environmental systems require huge amounts of resources. Managing these in an operational way becomes increasingly complex and difficult to handle for individual scientists. State-of-the-art simulation infrastructures usually provide the necessary re-sources in a centralised setup, which often results in an all-or-nothing choice for the user. Here, we outline an alternative approach to handling this complexity, while rendering the use of high-performance hardware and large datasets still possible. It retains a number of desirable properties: (i) a decentralised structure, (ii) easy sharing of resources to promote collaboration and (iii) secure access to everything, including natural delegation of authority across levels and system boundaries. We show that the object capability paradigm will cover these issues, and present the first steps towards developing a simulation infrastructure based on these principles.
Next-generation sequencing methods provide comprehensive data for the analysis of structural and functional analysis of the genome. The draft genomes with low contig number and high N50 value can give insight into the structure of the genome as well as provide information on the annotation of the genome. In this study, we designed a pipeline that can be used to assemble prokaryotic draft genomes with low number of contigs and high N50 value. We aimed to use combination of two de novo assembly tools (SPAdes and IDBA-Hybrid) and evaluate the impact of this approach on the quality metrics of the assemblies. The followed pipeline was tested with the raw sequence data with short reads (< 300) for a total of 10 species from four different genera. To obtain the final draft genomes, we firstly assembled the sequences using SPAdes to find closely related organism using the extracted 16 s rRNA from it. IDBA-Hybrid assembler was used to obtain the second assembly data using the closely related organism genome. SPAdes assembler tool was implemented using the second assembly, produced by IDBA-hybrid as a hint. The results were evaluated using QUAST and BUSCO. The pipeline was successful for the reduction of the contig numbers and increasing the N50 statistical values in the draft genome assemblies while preserving the coverage of the draft genomes.
Light is the essential energy source for plants to drive photosynthesis. In nature, light availability is highly variable and often fluctuates on very short time scales. As a result, plants developed mechanisms to cope with these fluctuations. Understanding how to improve light use efficiency in natural fluctuating light (FL) conditions is a major target for agronomy.
In the first project, we identified an Arabidopsis thaliana plant that showed reduced levels of rapidly inducible non-photochemical quenching (NPQ). This plant was devoid of any T-DNA insertion. Using a mapping-by-sequencing approach, we successfully located the causal genomic region near the end of chromosome 4. Through variant investigations in that region, we identified a deletion of about 20 kb encompassing 9 genes. By complementation analysis, we confirmed that one of the deleted genes, VTC2, is the causal gene responsible for the low NPQ. Loss of VTC2 decreased NPQ particularly in old leaves, with young leaves being only slightly affected. Additionally, ascorbate levels were almost abolished in old leaves, likely causing the NPQ decrease by reducing the activity of the xanthophyll cycle. Although ascorbate levels in younger leaves were reduced compared to wild-type plants, they remained at a comparably higher level. This difference may be due to the VTC2 paralog VTC5, which is expressed at a higher level in young leaves than in old ones.
Plants require the PROTON GRADIENT REGULATION 5 (PGR5) protein for survival in FL. pgr5 mutants die because they fail to increase the luminal proton concentration in response to high light (HL) phases. A rapid elevation in ∆pH is needed to slow down electron transport through the Cytochrome b6 f complex (photosynthetic control). In FL, such lack of control in the pgr5 mutants results in photosystem I (PSI) overreduction, reactive oxygen species (ROS) production, and cell death. Decreases in photosystem II (PSII) activity introduced by crossing pgr5 with PSII deficient mutants
rescued the lethality of pgr5 in FL. PGR5 was suggested to act as part of the ferredoxin-plastoquinone reductase (FQR), involved in cyclic electron transfer around PSI. However, the proposed molecular role of PGR5 remains highly debated. To learn more about PGR5 function, we performed a forward genetic screen in Arabidopsis thaliana to identify EMS-induced suppressor mutants surviving longer when grown in FL compared to pgr5 mutants (referred to as ”suppressor of pgr5 lethality in fluctuating light”, splf ). 11 different candidate genes were identified in a total of 22 splf plants.
Mutants of seven of these genes in the pgr5 background showed low Fv/Fm values when grown in non-fluctuating low light (LL). Five of these 4genes were previously reported to have a role in PSII biogenesis or function. Two others, RPH1 and a DEAD/DEAH box helicase (AT3G02060), have not been linked to PSII function before. Three of splf candidate genes link to primary metabolism, fructose-2,6-bisphosphatase (F2KP ), udp-glucose pyrophosphorylase 1 (UGP1 ) and ferredoxin-dependent glutamate synthase (Fd-GOGAT ). They are characterized by the fact that they survive longer in FL than pgr5 mutants but do not procede beyond the early vegetative
phase and then die.
Background: Microbiome assembly was identified as an important factor for plant growth and health, but this process is largely unknown, especially for the fruit microbiome. Therefore, we analyzed strawberry plants of two cultivars by focusing on microbiome tracking during the different growth stages and storage using amplicon sequencing, qPCR, and microscopic approaches. <br /> Results: Strawberry plants carried a highly diverse microbiome, therein the bacterial families Sphingomonadaceae (25%), Pseudomonadaceae (17%), and Burkholderiaceae (11%); and the fungal family Mycosphaerella (45%) were most abundant. All compartments were colonized by high number of bacteria and fungi (10(7)-10(10) marker gene copies per g fresh weight), and were characterized by high microbial diversity (6049 and 1501 ASVs); both were higher for the belowground samples than in the phyllosphere. Compartment type was the main driver of microbial diversity, structure, and abundance (bacterial: 45%; fungal: 61%) when compared to the cultivar (1.6%; 2.2%). Microbiome assembly was strongly divided for belowground habitats and the phyllosphere; only a low proportion of the microbiome was transferred from soil via the rhizosphere to the phyllosphere. During fruit development, we observed the highest rates of microbial transfer from leaves and flowers to ripe fruits, where most of the bacteria occured inside the pulp. In postharvest fruits, microbial diversity decreased while the overall abundance increased. Developing postharvest decay caused by Botrytis cinerea decreased the diversity as well, and induced a reduction of potentially beneficial taxa. <br /> Conclusion: Our findings provide insights into microbiome assembly in strawberry plants and highlight the importance of microbe transfer during fruit development and storage with potential implications for food health and safety.