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Multidirectional communicative interactions in social networks can have a profound effect on mate choice behavior. Male Atlantic molly Poecilia mexicana exhibit weaker mating preferences when an audience male is presented. This could be a male strategy to reduce sperm competition risk: interacting more equally with different females may be advantageous because rivals might copy mate choice decisions. In line with this hypothesis, a previous study found males to show a strong audience effect when being observed while exercising mate choice, but not when the rival was presented only before the choice tests. Audience effects on mate choice decisions have been quantified in poeciliid fishes using association preference designs, but it remains unknown if patterns found from measuring association times translate into actual mating behavior. Thus, we created five audience treatments simulating different forms of perceived sperm competition risk and determined focal males' mating preferences by scoring pre-mating (nipping) and mating behavior (gonopodial thrusting). Nipping did not reflect the pattern that was found when association preferences were measured, while a very similar pattern was uncovered in thrusting behavior. The strongest response was observed when the audience could eavesdrop on the focal male's behavior. A reduction in the strength of focal males' preferences was also seen after the rival male had an opportunity to mate with the focal male's preferred mate. In comparison, the reduction of mating preferences in response to an audience was greater when measuring association times than actual mating behavior. While measuring direct sexual interactions between the focal male and both stimulus females not only the male's motivational state is reflected but also females' behavior such as avoidance of male sexual harassment.
In order to predict which ecosystem functions are most at risk from biodiversity loss, meta-analyses have generalised results from biodiversity experiments over different sites and ecosystem types. In contrast, comparing the strength of biodiversity effects across a large number of ecosystem processes measured in a single experiment permits more direct comparisons. Here, we present an analysis of 418 separate measures of 38 ecosystem processes. Overall, 45 % of processes were significantly affected by plant species richness, suggesting that, while diversity affects a large number of processes not all respond to biodiversity. We therefore compared the strength of plant diversity effects between different categories of ecosystem processes, grouping processes according to the year of measurement, their biogeochemical cycle, trophic level and compartment (above- or belowground) and according to whether they were measures of biodiversity or other ecosystem processes, biotic or abiotic and static or dynamic. Overall, and for several individual processes, we found that biodiversity effects became stronger over time. Measures of the carbon cycle were also affected more strongly by plant species richness than were the measures associated with the nitrogen cycle. Further, we found greater plant species richness effects on measures of biodiversity than on other processes. The differential effects of plant diversity on the various types of ecosystem processes indicate that future research and political effort should shift from a general debate about whether biodiversity loss impairs ecosystem functions to focussing on the specific functions of interest and ways to preserve them individually or in combination.
Reliable information on past and present vegetation is important to project future changes, especially for rapidly transitioning areas such as the boreal treeline. To study past vegetation, pollen analysis is common, while current vegetation is usually assessed by field surveys. Application of detailed sedimentary DNA (sedDNA) records has the potential to enhance our understanding of vegetation changes, but studies systematically investigating the power of this proxy are rare to date. This study compares sedDNA metabarcoding and pollen records from surface sediments of 31 lakes along a north-south gradient of increasing forest cover in northern Siberia (Taymyr peninsula) with data from field surveys in the surroundings of the lakes. sedDNA metabarcoding recorded 114 plant taxa, about half of them to species level, while pollen analyses identified 43 taxa, both exceeding the 31 taxa found by vegetation field surveys. Increasing Larix percentages from north to south were consistently recorded by all three methods and principal component analyses based on percentage data of vegetation surveys and DNA sequences separated tundra from forested sites. Comparisons of the ordinations using procrustes and protest analyses show a significant fit among all compared pairs of records. Despite similarities of sedDNA and pollen records, certain idiosyncrasies, such as high percentages of Alnus and Betula in all pollen and high percentages of Salix in all sedDNA spectra, are observable. Our results from the tundra to single-tree tundra transition zone show that sedDNA analyses perform better than pollen in recording site-specific richness (i.e., presence/absence of taxa in the vicinity of the lake) and perform as well as pollen in tracing vegetation composition.
A comparative whole-genome approach identifies bacterial traits for marine microbial interactions
(2022)
Luca Zoccarato, Daniel Sher et al. leverage publicly available bacterial genomes from marine and other environments to examine traits underlying microbial interactions.
Their results provide a valuable resource to investigate clusters of functional and linked traits to better understand marine bacteria community assembly and dynamics.
Microbial interactions shape the structure and function of microbial communities with profound consequences for biogeochemical cycles and ecosystem health. Yet, most interaction mechanisms are studied only in model systems and their prevalence is unknown. To systematically explore the functional and interaction potential of sequenced marine bacteria, we developed a trait-based approach, and applied it to 473 complete genomes (248 genera), representing a substantial fraction of marine microbial communities.
We identified genome functional clusters (GFCs) which group bacterial taxa with common ecology and life history. Most GFCs revealed unique combinations of interaction traits, including the production of siderophores (10% of genomes), phytohormones (3-8%) and different B vitamins (57-70%). Specific GFCs, comprising Alpha- and Gammaproteobacteria, displayed more interaction traits than expected by chance, and are thus predicted to preferentially interact synergistically and/or antagonistically with bacteria and phytoplankton. Linked trait clusters (LTCs) identify traits that may have evolved to act together (e.g., secretion systems, nitrogen metabolism regulation and B vitamin transporters), providing testable hypotheses for complex mechanisms of microbial interactions.
Our approach translates multidimensional genomic information into an atlas of marine bacteria and their putative functions, relevant for understanding the fundamental rules that govern community assembly and dynamics.
Genomic prediction has revolutionized crop breeding despite remaining issues of transferability of models to unseen environmental conditions and environments. Usage of endophenotypes rather than genomic markers leads to the possibility of building phenomic prediction models that can account, in part, for this challenge. Here, we compare and contrast genomic prediction and phenomic prediction models for 3 growth-related traits, namely, leaf count, tree height, and trunk diameter, from 2 coffee 3-way hybrid populations exposed to a series of treatment-inducing environmental conditions. The models are based on 7 different statistical methods built with genomic markers and ChlF data used as predictors. This comparative analysis demonstrates that the best-performing phenomic prediction models show higher predictability than the best genomic prediction models for the considered traits and environments in the vast majority of comparisons within 3-way hybrid populations. In addition, we show that phenomic prediction models are transferrable between conditions but to a lower extent between populations and we conclude that chlorophyll a fluorescence data can serve as alternative predictors in statistical models of coffee hybrid performance. Future directions will explore their combination with other endophenotypes to further improve the prediction of growth-related traits for crops.
Downscaling of microfluidic cell culture and detection devices for electrochemical monitoring has mostly focused on miniaturization of the microfluidic chips which are often designed for specific applications and therefore lack functional flexibility. We present a compact microfluidic cell culture and electrochemical analysis platform with in-built fluid handling and detection, enabling complete cell based assays comprising on-line electrode cleaning, sterilization, surface functionalization, cell seeding, cultivation and electrochemical real-time monitoring of cellular dynamics. To demonstrate the versatility and multifunctionality of the platform, we explored amperometric monitoring of intracellular redox activity in yeast (Saccharomyces cerevisiae) and detection of exocytotically released dopamine from rat pheochromocytoma cells (PC12). Electrochemical impedance spectroscopy was used in both applications for monitoring cell sedimentation and adhesion as well as proliferation in the case of PC12 cells. The influence of flow rate on the signal amplitude in the detection of redox metabolism as well as the effect of mechanical stimulation on dopamine release were demonstrated using the programmable fluid handling capability. The here presented platform is aimed at applications utilizing cell based assays, ranging from e.g. monitoring of drug effects in pharmacological studies, characterization of neural stem cell differentiation, and screening of genetically modified microorganisms to environmental monitoring.
Diatom diversity in lakes of northwest Yakutia (Siberia) was investigated by microscopic and genetic analysis of surface and cored lake sediments, to evaluate the use of sedimentary DNA for paleolimnological diatom studies and to identify obscure genetic diversity that cannot be detected by microscopic methods. Two short (76 and 73 bp) and one longer (577 bp) fragments of the ribulose 1,5-bisphosphate carboxylase/oxygenase (rbcL) gene, encoding the large subunit of the rbcL, were used as genetic markers. Diverse morphological assemblages of diatoms, dominated by small benthic fragilarioid taxa, were retrieved from the sediments of each lake. These minute fragilarioid taxa were examined by scanning electron microscopy, revealing diverse morphotypes in Staurosira and Staurosirella from the different lakes. Genetic analyses indicated a dominance of haplotypes that were assigned to fragilarioid taxa and less genetic diversity in other diatom taxa. The long rbcL_577 amplicon identified considerable diversification among haplotypes clustering within the Staurosira/Staurosirella genera, revealing 19 different haplotypes whose spatial distribution appears to be primarily related to the latitude of the lakes, which corresponds to a vegetation and climate gradient. Our rbcL markers are valuable tools for tracking differences between diatom lineages that are not visible in their morphologies. These markers revealed putatively high genetic diversity within the Staurosira/Staurosirella species complex, at a finer scale than is possible to resolve by microscopic determination. The rbcL markers may provide additional reliable information on the diversity of barely distinguishable minute benthic fragilarioids. Environmental sequencing may thus allow the tracking of spatial and temporal diversification in Siberian lakes, especially in the context of diatom responses to recent environmental changes, which remains a matter of controversy.
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.
Incorporation of noncanonical amino acids (ncAAs) with bioorthogonal reactive groups by amber suppression allows the generation of synthetic proteins with desired novel properties. Such modified molecules are in high demand for basic research and therapeutic applications such as cancer treatment and in vivo imaging. The positioning of the ncAA-responsive codon within the protein's coding sequence is critical in order to maintain protein function, achieve high yields of ncAA-containing protein, and allow effective conjugation. Cell-free ncAA incorporation is of particular interest due to the open nature of cell-free systems and their concurrent ease of manipulation. In this study, we report a straightforward workflow to inquire ncAA positions in regard to incorporation efficiency and protein functionality in a Chinese hamster ovary (CHO) cell-free system. As a model, the well-established orthogonal translation components Escherichia coli tyrosyl-tRNA synthetase (TyrRS) and tRNATyr(CUA) were used to site-specifically incorporate the ncAA p-azido-l-phenylalanine (AzF) in response to UAG codons. A total of seven ncAA sites within an anti-epidermal growth factor receptor (EGFR) single-chain variable fragment (scFv) N-terminally fused to the red fluorescent protein mRFP1 and C-terminally fused to the green fluorescent protein sfGFP were investigated for ncAA incorporation efficiency and impact on antigen binding. The characterized cell-free dual fluorescence reporter system allows screening for ncAA incorporation sites with high incorporation efficiency that maintain protein activity. It is parallelizable, scalable, and easy to operate. We propose that the established CHO-based cell-free dual fluorescence reporter system can be of particular interest for the development of antibody-drug conjugates (ADCs).
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.
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.
A Biosensor for aromatic aldehydes comprising the mediator dependent PaoABC-Aldehyde oxidoreductase
(2013)
A novel aldehyde oxidoreductase (PaoABC) from Escherichia coli was utilized for the development of an oxygen insensitive biosensor for benzaldehyde. The enzyme was immobilized in polyvinyl alcohol and currents were measured for aldehyde oxidation with different one and two electron mediators with the highest sensitivity for benzaldehyde in the presence of hexacyanoferrate(III). The benzaldehyde biosensor was optimized with respect to mediator concentration, enzyme loading and pH using potassium hexacyanoferrate(III). The linear measuring range is between 0.5200 mu M benzaldehyde. In correspondence with the substrate selectivity of the enzyme in solution the biosensor revealed a preference for aromatic aldehydes and less effective conversion of aliphatic aldehydes. The biosensor is oxygen independent, which is a particularly attractive feature for application. The biosensor can be applied to detect contaminations with benzaldehyde in solvents such as benzyl alcohol, where traces of benzaldehyde in benzyl alcohol down to 0.0042?% can be detected.
We report the influence of different nutritional modes-autotrophy, mixotrophy, and heterotrophy-on the fatty acid and sterol composition of the freshwater flagellate Ochromonas sp. and discuss the ecological significance of our results with respect to the resource competition theory (rct). Polyunsaturated fatty acids (PUFAs) are the most efficient biochemical variable distinguishing between nutritional modes of Ochromonas sp. Decreasing concentrations of PUFAs were observed in the order autotrophs, mixotrophs, heterotrophs. In mixotrophs and heterotrophs, concentrations of saturated fatty acids were higher than those of monounsaturated fatty acids and PUFAs as a result of bacterivory. Stigmasterol was the main sterol in Ochromonas sp., regardless of nutritional mode. Mixotrophs showed higher growth rates than heterotrophs, which could not be explained by rct. Heterotrophs, in turn, exhibited higher growth rates than autotrophs, which were cultured under the same light conditions as mixotrophs. Mixotrophs can synthesize PUFAs, which are important for many physiological functions such as membrane permeability and growth. Thus, mixotrophy facilitated efficient growth as well as the ability to synthesize complex and essential biomolecules. These strong synergetic effects are due to the combination of biochemical benefits of heterotrophic and autotrophic metabolic pathways and cannot be predicted by rct.
Aldol reactions play an important role in organic synthesis, as they belong to the class of highly beneficial C-C-linking reactions. Aldol-type reactions can be efficiently and stereoselectively catalyzed by the enzyme 2-deoxy-D-ribose-5-phosphate aldolase (DERA) to gain key intermediates for pharmaceuticals such as atorvastatin. The immobilization of DERA would open the opportunity for a continuous operation mode which gives access to an efficient, large-scale production of respective organic intermediates. In this contribution, we synthesize and utilize DERA/polymer conjugates for the generation and fixation of a DERA bearing thin film on a polymeric membrane support. The conjugation strongly increases the tolerance of the enzyme toward the industrial relevant substrate acetaldehyde while UV-cross-linkable groups along the conjugated polymer chains provide the opportunity for covalent binding to the support. First, we provide a thorough characterization of the conjugates followed by immobilization tests on representative, nonporous cycloolefinic copolymer supports. Finally, immobilization on the target supports constituted of polyacrylonitrile (PAN) membranes is performed, and the resulting enzymatically active membranes are implemented in a simple membrane module setup for the first assessment of biocatalytic performance in the continuous operation mode using the combination hexanal/acetaldehyde as the substrate.
Binding or catalysis? Both can be distinguished with a molecularly imprinted polymer (MIP) by the different patterns of heat generation. The catalytically active sites, like in the corresponding enzyme, generate a steady-state temperature increase. Thus, enzyme-like catalysis and antibody-analogue binding are analyzed simultaneously in a bifunctional MIP for the first time (see scheme).
Ecological communities are complex adaptive systems that exhibit remarkable feedbacks between their biomass and trait dynamics. Trait-based aggregate models cope with this complexity by focusing on the temporal development of the community’s aggregate properties such as its total biomass, mean trait and trait variance. They are based on particular assumptions about the shape of the underlying trait distribution, which is commonly assumed to be normal. However, ecologically important traits are usually restricted to a finite range, and empirical trait distributions are often skewed or multimodal. As a result, normal distribution-based aggregate models may fail to adequately represent the biomass and trait dynamics of natural communities. We resolve this mismatch by developing a new moment closure approach assuming the trait values to be beta-distributed. We show that the beta distribution captures important shape properties of both observed and simulated trait distributions, which cannot be captured by a Gaussian. We further demonstrate that a beta distribution-based moment closure can strongly enhance the reliability of trait-based aggregate models. We compare the biomass, mean trait and variance dynamics of a full trait distribution (FD) model to the ones of beta (BA) and normal (NA) distribution-based aggregate models, under different selection regimes. This way, we demonstrate under which general conditions (stabilizing, fluctuating or disruptive selection) different aggregate models are reliable tools. All three models predicted very similar biomass and trait dynamics under stabilizing selection yielding unimodal trait distributions with small standing trait variation. We also obtained an almost perfect match between the results of the FD and BA models under fluctuating selection, promoting skewed trait distributions and ongoing oscillations in the biomass and trait dynamics. In contrast, the NA model showed unrealistic trait dynamics and exhibited different alternative stable states, and thus a high sensitivity to initial conditions under fluctuating selection. Under disruptive selection, both aggregate models failed to reproduce the results of the FD model with the mean trait values remaining within their ecologically feasible ranges in the BA model but not in the NA model. Overall, a beta distribution-based moment closure strongly improved the realism of trait-based aggregate models.