Effects of plant diversity on productivity strengthen over time due to trait-dependent shifts in species overyielding.

Plant diversity effects on community productivity often increase over time. Whether the strengthening of diversity effects is caused by temporal shifts in species-level overyielding (i.e., higher species-level productivity in diverse communities compared with monocultures) remains unclear. Here, using data from 65 grassland and forest biodiversity experiments, we show that the temporal strength of diversity effects at the community scale is underpinned by temporal changes in the species that yield. These temporal trends of species-level overyielding are shaped by plant ecological strategies, which can be quantitatively delimited by functional traits. In grasslands, the temporal strengthening of biodiversity effects on community productivity was associated with increasing biomass overyielding of resource-conservative species increasing over time, and with overyielding of species characterized by fast resource acquisition either decreasing or increasing. In forests, temporal trends in species overyielding differ when considering above- versus belowground resource acquisition strategies. Overyielding in stem growth decreased for species with high light capture capacity but increased for those with high soil resource acquisition capacity. Our results imply that a diversity of species with different, and potentially complementary, ecological strategies is beneficial for maintaining community productivity over time in both grassland and forest ecosystems.

Transformation scenarios towards multifunctional landscapes: A multi-criteria land-use allocation model applied to Jambi Province, Indonesia.

In tropical regions, shifting from forests and traditional agroforestry to intensive plantations generates conflicts between human welfare (farmers' demands and societal needs) and environmental protection. Achieving sustainability in this transformation will inevitably involve trade-offs between multiple ecological and socioeconomic functions. To address these trade-offs, our study used a new methodological approach allowing the identification of transformation scenarios, including theoretical landscape compositions that satisfy multiple ecological functions (i.e., structural complexity, microclimatic conditions, organic carbon in plant biomass, soil organic carbon and nutrient leaching losses), and farmers needs (i.e., labor and input requirements, total income to land, and return to land and labor) while accounting for the uncertain provision of these functions and having an actual potential for adoption by farmers. We combined a robust, multi-objective optimization approach with an iterative search algorithm allowing the identification of ecological and socioeconomic functions that best explain current land-use decisions. The model then optimized the theoretical land-use composition that satisfied multiple ecological and socioeconomic functions. Between these ends, we simulated transformation scenarios reflecting the transition from current land-use composition towards a normative multifunctional optimum. These transformation scenarios involve increasing the number of optimized socioeconomic or ecological functions, leading to higher functional richness (i.e., number of functions). We applied this method to smallholder farms in the Jambi Province, Indonesia, where traditional rubber agroforestry, rubber plantations, and oil palm plantations are the main land-use systems. Given the currently practiced land-use systems, our study revealed short-term returns to land as the principal factor in explaining current land-use decisions. Fostering an alternative composition that satisfies additional socioeconomic functions would require minor changes ("low-hanging fruits"). However, satisfying even a single ecological indicator (e.g., reduction of nutrient leaching losses) would demand substantial changes in the current land-use composition ("moonshot"). This would inevitably lead to a profit decline, underscoring the need for incentives if the societal goal is to establish multifunctional agricultural landscapes. With many oil palm plantations nearing the end of their production cycles in the Jambi province, there is a unique window of opportunity to transform agricultural landscapes.

Microfluidic Diffusional Sizing (MDS) Measurements of Secretory Neutralizing Antibody Affinity Against SARS-CoV-2.

SARS-CoV-2 has rampantly spread around the globe and continues to cause unprecedented loss through ongoing waves of (re)infection. Increasing our understanding of the protection against infection with SARS-CoV-2 is critical to ending the pandemic. Serological assays have been widely used to assess immune responses, but secretory antibodies, the essential first line of defense, have been studied to only a limited extent. Of particular interest and importance are neutralizing antibodies, which block the binding of the spike protein of SARS-CoV-2 to the human receptor angiotensin-converting enzyme-2 (ACE2) and thus are essential for immune defense. Here, we employed Microfluidic Diffusional Sizing (MDS), an immobilization-free technology, to characterize neutralizing antibody affinity to SARS-CoV-2 spike receptor-binding domain (RBD) and spike trimer in saliva. Affinity measurement was obtained through a contrived sample and buffer using recombinant SARS-CoV-2 RBD and monoclonal antibody. Limited saliva samples demonstrated that MDS applies to saliva neutralizing antibody measurement. The ability to disrupt a complex of ACE2-Fc and spike trimer is shown. Using a quantitative assay on the patient sample, we determined the affinity and binding site concentration of the neutralizing antibodies.

Protocol to determine antibody affinity and concentration in complex solutions using microfluidic antibody affinity profiling.

Conventional methods of measuring affinity are limited by artificial immobilization, large sample volumes, and homogeneous solutions. This protocol describes microfluidic antibody affinity profiling on complex human samples in solution to obtain a fingerprint reflecting both affinity and active concentration of the target protein. To illustrate the protocol, we analyze the antibody response in SARS-CoV-2 omicron-naïve samples against different SARS-CoV-2 variants of concern. However, the protocol and the technology are amenable to a broad spectrum of biomedical questions. For complete details on the use and execution of this protocol, please refer to Emmenegger et al. (2022),1 Schneider et al. (2022),2 and Fiedler et al. (2022).3.

FULL-MDS: Fluorescent Universal Lipid Labeling for Microfluidic Diffusional Sizing.

Microfluidic diffusional sizing (MDS) is a recent and powerful method for determining the hydrodynamic sizes and interactions of biomolecules and nanoparticles. A major benefit of MDS is that it can report the size of a fluorescently labeled target even in mixtures with complex, unpurified samples. However, a limitation of MDS is that the target itself has to be purified and covalently labeled with a fluorescent dye. Such covalent labeling is not suitable for crude extracts such as native nanodiscs directly obtained from cellular membranes. In this study, we introduce fluorescent universal lipid labeling for MDS (FULL-MDS) as a sparse, noncovalent labeling method for determining particle size. We first demonstrate that the inexpensive and well-characterized fluorophore, Nile blue, spontaneously partitions into lipid nanoparticles without disrupting their structure. We then highlight the key advantage of FULL-MDS by showing that it yields robust size information on lipid nanoparticles in crude cell extracts that are not amenable to other sizing methods. Furthermore, even for synthetic nanodiscs, FULL-MDS is faster, cheaper, and simpler than existing labeling schemes.

Serological fingerprints link antiviral activity of therapeutic antibodies to affinity and concentration.

The effectiveness of therapeutic monoclonal antibodies (mAbs) against variants of the SARS-CoV-2 virus is highly variable. As target recognition of mAbs relies on tight binding affinity, we assessed the affinities of five therapeutic mAbs to the receptor binding domain (RBD) of wild type (A), Delta (B.1.617.2), and Omicron BA.1 SARS-CoV-2 (B.1.1.529.1) spike using microfluidic diffusional sizing (MDS). Four therapeutic mAbs showed strongly reduced affinity to Omicron BA.1 RBD, whereas one (sotrovimab) was less impacted. These affinity reductions correlate with reduced antiviral activities suggesting that affinity could serve as a rapid indicator for activity before time-consuming virus neutralization assays are performed. We also compared the same mAbs to serological fingerprints (affinity and concentration) obtained by MDS of antibodies in sera of 65 convalescent individuals. The affinities of the therapeutic mAbs to wild type and Delta RBD were similar to the serum antibody response, indicating high antiviral activities. For Omicron BA.1 RBD, only sotrovimab retained affinities within the range of the serum antibody response, in agreement with high antiviral activity. These results suggest that serological fingerprints provide a route to evaluating affinity and antiviral activity of mAb drugs and could guide the development of new therapeutics.

Both COVID-19 infection and vaccination induce high-affinity cross-clade responses to SARS-CoV-2 variants.

The B.1.1.529 (omicron) variant has rapidly supplanted most other SARS-CoV-2 variants. Using microfluidics-based antibody affinity profiling (MAAP), we have characterized affinity and IgG concentration in the plasma of 39 individuals with multiple trajectories of SARS-CoV-2 infection and/or vaccination. Antibody affinity was similar against the wild-type, delta, and omicron variants (K A ranges: 122 ± 155, 159 ± 148, 211 ± 307 µM-1, respectively), indicating a surprisingly broad and mature cross-clade immune response. Postinfectious and vaccinated subjects showed different IgG profiles, with IgG3 (p-value = 0.002) against spike being more prominent in the former group. Lastly, we found that the ELISA titers correlated linearly with measured concentrations (R = 0.72) but not with affinity (R = 0.29). These findings suggest that the wild-type and delta spike induce a polyclonal immune response capable of binding the omicron spike with similar affinity. Changes in titers were primarily driven by antibody concentration, suggesting that B-cell expansion, rather than affinity maturation, dominated the response after infection or vaccination.

Microfluidic Antibody Affinity Profiling Reveals the Role of Memory Reactivation and Cross-Reactivity in the Defense Against SARS-CoV-2.

Recent efforts in understanding the course and severity of SARS-CoV-2 infections have highlighted both potentially beneficial and detrimental effects of cross-reactive antibodies derived from memory immunity. Specifically, due to a significant degree of sequence similarity between SARS-CoV-2 and other members of the coronavirus family, memory B-cells that emerged from previous infections with endemic human coronaviruses (HCoVs) could be reactivated upon encountering the newly emerged SARS-CoV-2, thus prompting the production of cross-reactive antibodies. Determining the affinity and concentration of these potentially cross-reactive antibodies to the new SARS-CoV-2 antigens is therefore particularly important when assessing both existing immunity against common HCoVs and adverse effects like antibody-dependent enhancement (ADE) in COVID-19. However, these two fundamental parameters cannot easily be disentangled by surface-based assays like enzyme-linked immunosorbent assays (ELISAs), which are routinely used to assess cross-reactivity. Here, we have used microfluidic antibody affinity profiling (MAAP) to quantitatively evaluate the humoral immune response in COVID-19 convalescent patients by determining both antibody affinity and concentration against spike antigens of SARS-CoV-2 directly in nine convalescent COVID-19 patient and three pre-pandemic sera that were seropositive for common HCoVs. All 12 sera contained low concentrations of high-affinity antibodies against spike antigens of HCoV-NL63 and HCoV-HKU1, indicative of past exposure to these pathogens, while the affinity against the SARS-CoV-2 spike protein was lower. These results suggest that cross-reactivity as a consequence of memory reactivation upon an acute SARS-CoV-2 infection may not be a significant factor in generating immunity against SARS-CoV-2.

Microfluidic characterisation reveals broad range of SARS-CoV-2 antibody affinity in human plasma.

The clinical outcome of SARS-CoV-2 infections, which can range from asymptomatic to lethal, is crucially shaped by the concentration of antiviral antibodies and by their affinity to their targets. However, the affinity of polyclonal antibody responses in plasma is difficult to measure. Here we used microfluidic antibody affinity profiling (MAAP) to determine the aggregate affinities and concentrations of anti-SARS-CoV-2 antibodies in plasma samples of 42 seropositive individuals, 19 of which were healthy donors, 20 displayed mild symptoms, and 3 were critically ill. We found that dissociation constants, K d, of anti-receptor-binding domain antibodies spanned 2.5 orders of magnitude from sub-nanomolar to 43 nM. Using MAAP we found that antibodies of seropositive individuals induced the dissociation of pre-formed spike-ACE2 receptor complexes, which indicates that MAAP can be adapted as a complementary receptor competition assay. By comparison with cytopathic effect-based neutralisation assays, we show that MAAP can reliably predict the cellular neutralisation ability of sera, which may be an important consideration when selecting the most effective samples for therapeutic plasmapheresis and tracking the success of vaccinations.

Antibody Affinity Governs the Inhibition of SARS-CoV-2 Spike/ACE2 Binding in Patient Serum.

The humoral immune response plays a key role in suppressing the pathogenesis of SARS-CoV-2. The molecular determinants underlying the neutralization of the virus remain, however, incompletely understood. Here, we show that the ability of antibodies to disrupt the binding of the viral spike protein to the angiotensin-converting enzyme 2 (ACE2) receptor on the cell, the key molecular event initiating SARS-CoV-2 entry into host cells, is controlled by the affinity of these antibodies to the viral antigen. By using microfluidic antibody-affinity profiling, we were able to quantify the serum-antibody mediated inhibition of ACE2-spike binding in two SARS-CoV-2 seropositive individuals. Measurements to determine the affinity, concentration, and neutralization potential of antibodies were performed directly in human serum. Using this approach, we demonstrate that the level of inhibition in both samples can be quantitatively described using the dissociation constants (KD) of the binary interactions between the ACE2 receptor and the spike protein as well as the spike protein and the neutralizing antibody. These experiments represent a new type of in-solution receptor binding competition assay, which has further potential applications, ranging from decisions on donor selection for convalescent plasma therapy, to identification of lead candidates in therapeutic antibody development, and vaccine development.

Disentangling climatic and anthropogenic contributions to nonlinear dynamics of alpine grassland productivity on the Qinghai-Tibetan Plateau.

Alpine grasslands on the Qinghai-Tibetan Plateau are sensitive and vulnerable to climate change and human activities. Climate warming and overgrazing have already caused degradation in a large fraction of alpine grasslands on this plateau. However, it remains unclear how human activities (mainly livestock grazing) regulates vegetation dynamics under climate change. Here, alpine grassland productivity (substituted with the normalized difference vegetation index, NDVI) is hypothesized to vary in a nonlinear trajectory to follow climate fluctuations and human disturbances. With generalized additive mixed modelling (GAMM) and residual-trend (RESTREND) analysis together, both magnitude and direction of climatic (in terms of temperature, precipitation, and radiation) and anthropogenic impacts on NDVI variation were examined across alpine meadows, steppes, and desert-steppes on the Qinghai-Tibetan Plateau. The results revealed that accelerating warming and greening, respectively, took place in 76.2% and 78.8% of alpine grasslands on the Qinghai-Tibetan Plateau. The relative importance of temperature, precipitation, and radiation impacts was comparable, between 20.4% and 24.8%, and combined to explain 66.2% of NDVI variance at the pixel scale. The human influence was strengthening and weakening, respectively, in 15.5% and 14.3% of grassland pixels, being slightly larger than any sole climatic variable across the entire plateau. Anthropogenic and climatic factors can be in opposite ways to affect alpine grasslands, even within the same grassland type, likely regulated by plant community assembly and species functional traits. Therefore, the underlying mechanisms of how plant functional diversity regulates nonlinear ecosystem response to climatic and anthropogenic stresses should be carefully explored in the future.

Structural and functional characterization of C0021158, a high-affinity monoclonal antibody that inhibits Arginase 2 function via a novel non-competitive mechanism of action.

Arginase 2 (ARG2) is a binuclear manganese metalloenzyme that catalyzes the hydrolysis of L-arginine. The dysregulated expression of ARG2 within specific tumor microenvironments generates an immunosuppressive niche that effectively renders the tumor 'invisible' to the host's immune system. Increased ARG2 expression leads to a concomitant depletion of local L-arginine levels, which in turn leads to suppression of anti-tumor T-cell-mediated immune responses. Here we describe the isolation and characterization of a high affinity antibody (C0021158) that inhibits ARG2 enzymatic function completely, effectively restoring T-cell proliferation in vitro. Enzyme kinetic studies confirmed that C0021158 exhibits a noncompetitive mechanism of action, inhibiting ARG2 independently of L-arginine concentrations. To elucidate C0021158's inhibitory mechanism at a structural level, the co-crystal structure of the Fab in complex with trimeric ARG2 was solved. C0021158's epitope was consequently mapped to an area some distance from the enzyme's substrate binding cleft, indicating an allosteric mechanism was being employed. Following C0021158 binding, distinct regions of ARG2 undergo major conformational changes. Notably, the backbone structure of a surface-exposed loop is completely rearranged, leading to the formation of a new short helix structure at the Fab-ARG2 interface. Moreover, this large-scale structural remodeling at ARG2's epitope translates into more subtle changes within the enzyme's active site. An arginine residue at position 39 is reoriented inwards, sterically impeding the binding of L-arginine. Arg39 is also predicted to alter the pKA of a key catalytic histidine residue at position 160, further attenuating ARG2's enzymatic function. In silico molecular docking simulations predict that L-arginine is unable to bind effectively when antibody is bound, a prediction supported by isothermal calorimetry experiments using an L-arginine mimetic. Specifically, targeting ARG2 in the tumor microenvironment through the application of C0021158, potentially in combination with standard chemotherapy regimens or alternate immunotherapies, represents a potential new strategy to target immune cold tumors.

Extensive sequence and structural evolution of Arginase 2 inhibitory antibodies enabled by an unbiased approach to affinity maturation.

Affinity maturation is a powerful technique in antibody engineering for the in vitro evolution of antigen binding interactions. Key to the success of this process is the expansion of sequence and combinatorial diversity to increase the structural repertoire from which superior binding variants may be selected. However, conventional strategies are often restrictive and only focus on small regions of the antibody at a time. In this study, we used a method that combined antibody chain shuffling and a staggered-extension process to produce unbiased libraries, which recombined beneficial mutations from all six complementarity-determining regions (CDRs) in the affinity maturation of an inhibitory antibody to Arginase 2 (ARG2). We made use of the vast display capacity of ribosome display to accommodate the sequence space required for the diverse library builds. Further diversity was introduced through pool maturation to optimize seven leads of interest simultaneously. This resulted in antibodies with substantial improvements in binding properties and inhibition potency. The extensive sequence changes resulting from this approach were translated into striking structural changes for parent and affinity-matured antibodies bound to ARG2, with a large reorientation of the binding paratope facilitating increases in contact surface and shape complementarity to the antigen. The considerable gains in therapeutic properties seen from extensive sequence and structural evolution of the parent ARG2 inhibitory antibody clearly illustrate the advantages of the unbiased approach developed, which was key to the identification of high-affinity antibodies with the desired inhibitory potency and specificity.

Microfluidic diffusional sizing probes lipid nanodiscs formation.

The biophysical characterisation of membrane proteins and their interactions with lipids in native membrane habitat remains a major challenge. Indeed, traditional solubilisation procedures with detergents often causes the loss of native lipids surrounding membrane proteins, which ultimately impacts structural and functional properties. Recently, copolymer-based nanodiscs have emerged as a highly promising tool, thanks to their unique ability of solubilising membrane proteins directly from native membranes, in the shape of discoidal patches of lipid bilayers. While this methodology finally set us free from the use of detergents, some limitations are however associated with the use of such copolymers. Among them, one can cite the tedious control of the nanodiscs size, their instability in basic pH and in the presence of divalent cations. In this respect, many variants of the widely used Styrene Maleic Acid (SMA) copolymer have been developed to specifically address those limitations. With the multiplication of new SMA copolymer variants and the growing interest in copolymer-based nanodiscs for the characterisation of membrane proteins, there is a need to better understand and control their formation. Among the techniques used to characterise the solubilisation of lipid bilayer by amphipathic molecules, cryo-TEM, 31P NMR, DLS, ITC and fluorescence spectroscopy are the most widely used, with a consensus made in the sense that a combination of these techniques is required. In this work, we propose to evaluate the capacity of Microfluidic Diffusional Sizing (MDS) as a new method to follow copolymer nanodiscs formation. Originally designed to determine protein size through laminar flow diffusion, we present a novel application along with a protocol development to observe nanodiscs formation by MDS. We show that MDS allows to precisely measure the size of nanodiscs, and to determine the copolymer/lipid ratio at the onset of solubilisation. Finally, we use MDS to characterise peptide/nanodisc interaction. The technique shows a promising ability to highlight the pivotal role of lipids in promoting interactions through a case study with an aggregating peptide. This confirmed the relevance of using the MDS and nanodiscs as biomimetic models for such investigations.

Impacts of grazing exclusion on productivity partitioning along regional plant diversity and climatic gradients in Tibetan alpine grasslands.

The biodiversity-productivity relationship is critical for better predicting ecosystem responses to climate change and human disturbance. However, it remains unclear about the effects of climate change, land use shifts, plant diversity, and their interactions on productivity partitioning above- and below-ground components in alpine grasslands on the Tibetan Plateau. To answer this question, we conducted field surveys at 33 grazed vs. fenced paired sites that are distributed across the alpine meadow, steppe, and desert-steppe zones on the northern Tibetan Plateau in early August of 2010-2013. Generalized additive models (GAMs) showed that aboveground net primary productivity (ANPP) linearly increased with growing season precipitation (GSP) while belowground net primary productivity (BNPP) decreased with growing season temperature (GST). Compared to grazed sites, short-term fencing did not alter the patterns of ANPP along climatic gradients but tended to decrease BNPP at moderate precipitation levels of 200 mm < GSP <450 mm. We also found that ANPP and BNPP linearly increased with species richness, ANPP decreased with Shannon diversity index, and BNPP did not correlate with the Shannon diversity index. Fencing did not alter the relationships between productivity components and plant diversity indices. Generalized additive mixed models furtherly confirmed that the interaction of localized plant diversity and climatic condition nonlinearly regulated productivity partitioning of alpine grasslands in this area. Finally, structural equation models (SEMs) revealed the direction and strength of causal links between biotic and abiotic variables within alpine grassland ecosystems. ANPP was controlled directly by GSP (0.53) and indirectly via species richness (0.41) and Shannon index (-0.12). In contrast, BNPP was influenced directly by GST (-0.43) and indirectly by GSP via species richness (0.05) and Shannon index (-0.02). Therefore, we recommend using a joint approach of GAMs and SEMs for better understanding mechanisms behind the relationship between biodiversity and ecosystem function under climate change and human disturbance.

Preparation of Asymmetric Liposomes Using a Phosphatidylserine Decarboxylase.

Lipid asymmetries between the outer and inner leaflet of the lipid bilayer exist in nearly all biological membranes. Although living cells spend great effort to adjust and maintain these asymmetries, little is known about the biophysical phenomena within asymmetric membranes and their role in cellular function. One reason for this lack of insight into such a fundamental membrane property is the fact that the majority of model-membrane studies have been performed on symmetric membranes. Our aim is to overcome this problem by employing a targeted, enzymatic reaction to prepare asymmetric liposomes with phosphatidylserine (PS) primarily in the inner leaflet. To achieve this goal, we use a recombinant version of a water soluble PS decarboxylase from Plasmodium knowlesi, which selectively decarboxylates PS in the outer leaflet, converting it to phosphatidylethanolamine. The extent of decarboxylation is quantified using high-performance thin-layer chromatography, and the local concentration of anionic PS in the outer leaflet is monitored in terms of the ζ potential. Starting, for example, with 21 mol % 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-L-serine sodium salt, the assay leads to liposomes with 21 mol % in the inner and 6 mol % PS in the outer leaflet. This asymmetry persists virtually unchanged for at least 4 days at 20°C and at least 2 days at 40°C. The use of a highly specific enzyme carries the advantage that a minor component such as PS can be adjusted without affecting or being affected by the other lipid species present in the model membrane. The phenomena governing the residual outside PS content are addressed but warrant further study.

Integrating trait-based empirical and modeling research to improve ecological restoration.

A global ecological restoration agenda has led to ambitious programs in environmental policy to mitigate declines in biodiversity and ecosystem services. Current restoration programs can incompletely return desired ecosystem service levels, while resilience of restored ecosystems to future threats is unknown. It is therefore essential to advance understanding and better utilize knowledge from ecological literature in restoration approaches. We identified an incomplete linkage between global change ecology, ecosystem function research, and restoration ecology. This gap impedes a full understanding of the interactive effects of changing environmental factors on the long-term provision of ecosystem functions and a quantification of trade-offs and synergies among multiple services. Approaches that account for the effects of multiple changing factors on the composition of plant traits and their direct and indirect impact on the provision of ecosystem functions and services can close this gap. However, studies on this multilayered relationship are currently missing. We therefore propose an integrated restoration agenda complementing trait-based empirical studies with simulation modeling. We introduce an ongoing case study to demonstrate how this framework could allow systematic assessment of the impacts of interacting environmental factors on long-term service provisioning. Our proposed agenda will benefit restoration programs by suggesting plant species compositions with specific traits that maximize the supply of multiple ecosystem services in the long term. Once the suggested compositions have been implemented in actual restoration projects, these assemblages should be monitored to assess whether they are resilient as well as to improve model parameterization. Additionally, the integration of empirical and simulation modeling research can improve global outcomes by raising the awareness of which restoration goals can be achieved, due to the quantification of trade-offs and synergies among ecosystem services under a wide range of environmental conditions.

Engineering Asymmetric Lipid Vesicles: Accurate and Convenient Control of the Outer Leaflet Lipid Composition.

The asymmetric distribution of lipids between the two bilayer leaflets represents a typical feature of biological membranes. The loss of this asymmetry, for example the exposure of negatively charged lipids on the extracellular membrane leaflet of mammalian cells, is involved in apoptosis and occurs in tumor cells. Thus, the controlled production of asymmetric liposomes helps to better understand such crucial cellular processes. Here, we present an approach that allows us to design asymmetric model-membrane experiments on a rational basis and predict the fraction of exchanged lipid. In addition, we developed a label-free and nondestructive assay to quantify the asymmetric uptake of negatively charged lipids in terms of the zeta potential. This significantly enhances the applicability, impact, and predictive power of model membranes.

Construction and Selection of Affilin® Phage Display Libraries.

Affilin® molecules represent a new class of so-called scaffold proteins. The concept of scaffold proteins is to use stable and versatile protein structures which can be endowed with de novo binding properties and specificities by introducing mutations in surface exposed amino acid residues. Complex variations and combinations are generated by genetic methods of randomization resulting in large cDNA libraries. The selection for candidates binding to a desired target can be executed by display methods, especially the very robust and flexible phage display. Here, we describe the construction of ubiquitin based Affilin® phage display libraries and their use in biopanning experiments for the identification of novel protein ligands.

Vesicle Leakage Reflects the Target Selectivity of Antimicrobial Lipopeptides from Bacillus subtilis.

Cyclic lipopeptides act against a variety of plant pathogens and are thus highly efficient crop-protection agents. Some pesticides contain Bacillus subtilis strains that produce lipopeptide families, such as surfactins (SF), iturins (IT), and fengycins (FE). The antimicrobial activity of these peptides is mainly mediated by permeabilizing cellular membranes. We used a fluorescence-lifetime based leakage assay to examine the effect of individual lipid components in model membranes on lipopeptide activity. Leakage induction by FE was strongly inhibited by cholesterol (CHOL) as well as by phosphatidylethanolamine (PE) and -glycerol (PG) lipids. Already moderate amounts of CHOL increased the tolerable FE content in membranes by an order of magnitude to 0.5 FE per PC + CHOL. This indicates reduced FE-lipid demixing and aggregation, which is known to be required for membrane permeabilization and explains the strong inhibition by CHOL. Ergosterol (ERG) had a weak antagonistic effect. This confirms results of microbiological tests and agrees with the fungicidal activity and selectivity of FE. SF is known to be much less selective in its antimicrobial action. In line with this, liposome leakage by SF was little affected by sterols and PE. Interestingly, PG increased SF activity and changed its leakage mechanism toward all-or-none, suggesting more specific, larger, and/or longer-lived defect structures. This may be because of the reduced energetic cost of locally accumulating anionic SF in an anionic lipid matrix. IT was found largely inactive in our assays. B. subtilis QST713 produces the lipopeptides in a ratio of 6 mol SF: 37 mol FE: 57 mol IT. Leakage induced by this native mixture was inhibited by CHOL and PE, but unaffected by ERG and by PG in the absence of PE. Note that fungi contain anionic lipids, but little PE. Hence, our data explain the strong, fungicidal activity and selectivity of B. subtilis QST713 lipopeptides.