Boosted Enzyme Activity via Encapsulation within Metal-Organic Frameworks with Pores Matching Enzyme Size and Shape.

A novel and versatile approach called "physical imprinting" is introduced to modulate enzyme conformation using mesoporous materials, addressing challenges in achieving improved enzyme activity and stability. Metal-organic frameworks with tailored mesopores, precisely matching enzyme size and shape, are synthesized. Remarkably, enzymes encapsulated within these customized mesopores exhibit over 1670% relative activity compared to free enzymes, maintaining outstanding efficiency even under harsh conditions such as heat, exposure to organic solvents, wide-ranging pH extremes from acidic to alkaline, and exposure to a digestion cocktail. After 18 consecutive cycles of use, the immobilized enzymes retain 80% of their initial activity. Additionally, the encapsulated enzymes exhibit a substantial increase in catalytic efficiency, with a 14.1-fold enhancement in kcat/KM compared to native enzymes. This enhancement is among the highest reported for immobilized enzymes. The improved enzyme activity and stability are corroborated by solid-state UV-vis, electron paramagnetic resonance, Fourier-transform infrared spectroscopy, and solid-state NMR spectroscopy. The findings not only offer valuable insights into the crucial role of size and shape complementarity within confined microenvironments but also establish a new pathway for developing solid carriers capable of enhancing enzyme activity and stability.

High-throughput quantitative assessments of the chemical complementarity of celiac disease related IGH CDR3s and a gliadin epitope.

The long-term value of efficient antigen discovery includes gaining insights into the variety of potential cancer neoantigens, effective vaccines lacking adverse effects, and adaptive immune receptor (IR) targets for blocking adaptive IR-antigen interactions in autoimmunity. While the preceding goals have been partially addressed via big data approaches to HLA-epitope binding, there has been little such progress in the big data setting for adaptive IR-epitope binding. This delay in progress for the latter is likely due to, among other things, the much more complicated adaptive IR repertoire in an individual compared to individual HLA alleles. Thus, results described here represent the application of an algorithm for efficient assessment of IGH CDR3-gliadin epitope interactions, with a focus on epitopes known to be associated with an immune response in celiac disease. The hydrophobic, chemical complementarity between celiac case IGH CDR3s and known celiac epitopes was found to be greater in comparison to the hydrophobic, chemical complementarity between the same celiac case IGH CDR3s and a series of control epitopes. Thus, the approaches indicated here likely offer guidance for the development of conveniently applied algorithms for antigen verification and discovery.

A Concept of Complementarity Between Complexity and Redundancy can Account for Kant's Biological Teleology and Unify Mechanistic and Finalistic Biology.

Over 160 years after Darwin and 70 years after the discovery of DNA, two fundamental questions of biology remain unanswered: What differentiates the living from the nonliving? How can mechanistic and finalistic or holistic biology be unified? Niels Bohr introduced a concept of complementarity in quantum physics and based on the paradox of light as a simultaneous wave and particle, conjectured that a similar concept might exist in biology that would solve the paradox of life originating from the nonliving. Bohr proposed that two mutually exclusive-independent observations may be necessary to explain a phenomenon and provided support to Immanuel Kant's idea that the "purposive" behaviour of organisms could only be explained in teleological terms and that mechanical and teleological approaches were necessary and complementary to explain biology. We present a concept of complementarity whereby biochemical pathways or cellular channels for the flow of information are simultaneously complex and redundant and complexity and redundancy complement each other. The postulates of biological complementarity are that (1) it was an essential condition in the origin of life; (2) it provided physiological flexibility that allowed organisms to mount self-protection response and complexity to evolve in the face of deleterious mutations before the evolution of bi-parental sex; (3) it laid the foundation for the evolution of a choice of response when confronted with threat; and (4) it applies to all levels of biological organizations and, thus, can serve as a basis for the unification of mechanistic and holistic biology. It is proposed that teleology is simultaneously constitutive and heuristic: constitutive because organisms' "purposive" behaviours are adaptive and are grounded in mechanism (complexity and redundancy), and heuristic because with our finite cognition and our goal-oriented (humans alone are aware of "tomorrow") and anthropomorphic pre-disposition, teleology will remain useful as a guide to our making sense of the world, even how to ask a meaningful question.

Environmental corporate social responsibility practices and firm innovation: Complementarities and empirical evidence from Spanish firms.

This study examines the complementarity effect of combining different types of environmental corporate social responsibility (ECSR) practices on firm innovation. We apply the complementarity approach to test whether the adoption of different ECSR practices (i.e. practices for fewer materials per unit produced [materials], less energy per unit produced [energy], or decreasing environmental impact [impact]) generates super-additive effects on firms' innovation, measured by innovations type: adoption, new-to-the-market, and new-to-the-firm innovation. We use data from the Spanish Community Innovation Survey for the period 2009-2014. The results show that the best combination of ECSR practices depends on the innovation type. For innovation adoption, all possible combinations of the three practices produce super-additive effects; however, the complementarity patterns differ for new-to-the-market and new-to-the-firm innovations. For new-to-the-market innovation, energy practices appear to be a key factor in fostering innovation when combined with materials or impact practices. For new-to-the-firm innovation, the combination of these three ECSR practices shows complementarity effects. These findings provide useful insights for the design of corporate social responsibility strategies.

Intraspecific chemical variation of Tanacetum vulgare affects plant growth and reproductive traits in field plant communities.

The study investigated the impact of intraspecific plant chemodiversity on plant growth and reproductive traits at both the plant and plot levels. It also aimed to understand how chemodiversity at stand level affects ecosystem functioning and plant-plant interactions. We describe a biodiversity experiment in which we manipulated intraspecific plant chemodiversity at the plot level using six different chemotypes of common tansy (Tanacetum vulgare L., Asteraceae). We tested the effects of chemotype identity and plot-level chemotype richness on plant growth and reproductive traits and plot-level headspace emissions. The study found that plant chemotypes differed in growth and reproductive traits and that traits were affected by the chemotype richness of the plots. Although morphological differences among chemotypes became less pronounced over time, reproductive phenology patterns persisted. Plot-level trait means were also affected by the presence or absence of certain chemotypes in a plot, and the direction of the effect depended on the specific chemotype. However, chemotype richness did not lead to overyielding effects. Lastly, chemotype blends released from plant communities were neither richer nor more diverse with increasing plot-level chemotype richness, but became more dissimilar as they became more dissimilar in their leaf terpenoid profiles. We found that intraspecific plant chemodiversity is crucial in plant-plant interactions. We also found that the effects of chemodiversity on plant growth and reproductive traits were complex and varied depending on the chemotype richness of the plots. This long-term field experiment will allow further investigation into plant-insect interactions and insect community assembly in response to intraspecific chemodiversity.

Loss of TET2 increases B-1 cell number and IgM production while limiting CDR3 diversity.

Recent studies have demonstrated a role for Ten-Eleven Translocation-2 (TET2), an epigenetic modulator, in regulating germinal center formation and plasma cell differentiation in B-2 cells, yet the role of TET2 in regulating B-1 cells is largely unknown. Here, B-1 cell subset numbers, IgM production, and gene expression were analyzed in mice with global knockout of TET2 compared to wildtype (WT) controls. Results revealed that TET2-KO mice had elevated numbers of B-1a and B-1b cells in their primary niche, the peritoneal cavity, as well as in the bone marrow (B-1a) and spleen (B-1b). Consistent with this finding, circulating IgM, but not IgG, was elevated in TET2-KO mice compared to WT. Analysis of bulk RNASeq of sort purified peritoneal B-1a and B-1b cells revealed reduced expression of heavy and light chain immunoglobulin genes, predominantly in B-1a cells from TET2-KO mice compared to WT controls. As expected, the expression of IgM transcripts was the most abundant isotype in B-1 cells. Yet, only in B-1a cells there was a significant increase in the proportion of IgM transcripts in TET2-KO mice compared to WT. Analysis of the CDR3 of the BCR revealed an increased abundance of replicated CDR3 sequences in B-1 cells from TET2-KO mice, which was more clearly pronounced in B-1a compared to B-1b cells. V-D-J usage and circos plot analysis of V-J combinations showed enhanced usage of VH11 and VH12 pairings. Taken together, our study is the first to demonstrate that global loss of TET2 increases B-1 cell number and IgM production and reduces CDR3 diversity, which could impact many biological processes and disease states that are regulated by IgM.

Multi-Time-Scale Optimal Scheduling Strategy for Marine Renewable Energy Based on Deep Reinforcement Learning Algorithm.

Surrounded by the Shandong Peninsula, the Bohai Sea and Yellow Sea possess vast marine energy resources. An analysis of actual meteorological data from these regions indicates significant seasonality and intra-day uncertainty in wind and photovoltaic power generation. The challenge of scheduling to leverage the complementary characteristics of various renewable energy sources for maintaining grid stability is substantial. In response, we have integrated wave energy with offshore photovoltaic and wind power generation and propose a day-ahead and intra-day multi-time-scale rolling optimization scheduling strategy for the complementary dispatch of these three energy sources. Using real meteorological data from this maritime area, we employed a CNN-LSTM neural network to predict the power generation and load demand of the area on both day-ahead 24 h and intra-day 1 h time scales, with the DDPG algorithm applied for refined electricity management through rolling optimization scheduling of the forecast data. Simulation results demonstrate that the proposed strategy effectively meets load demands through complementary scheduling of wave power, wind power, and photovoltaic power generation based on the climatic characteristics of the Bohai and Yellow Sea regions, reducing the negative impacts of the seasonality and intra-day uncertainty of these three energy sources on the grid. Additionally, compared to the day-ahead scheduling strategy alone, the day-ahead and intra-day rolling optimization scheduling strategy achieved a reduction in system costs by 16.1% and 22% for a typical winter day and a typical summer day, respectively.

Do antibody CDR loops change conformation upon binding?

Antibodies have increasingly been developed as drugs with over 100 now licensed in the US or EU. During development, it is often necessary to increase or reduce the affinity of an antibody and rational attempts to do so rely on having a structure of the antibody-antigen complex often obtained by modeling. The antigen-binding site consists primarily of six loops known as complementarity-determining regions (CDRs), and an open question has been whether these loops change their conformation when they bind to an antigen. Existing surveys of antibody-antigen complex structures have only examined CDR conformational change in case studies or small-scale surveys. With an increasing number of antibodies where both free and complexed structures have been deposited in the Protein Data Bank, a large-scale survey of CDR conformational change during binding is now possible. To this end, we built a dataset, AbAgDb, that currently includes 177 antibodies with high-quality CDRs, each of which has at least one bound and one unbound structure. We analyzed the conformational change of the Cα backbone of each CDR upon binding and found that, in most cases, the CDRs (other than CDR-H3) show minimal movement, while 70.6% and 87% of CDR-H3s showed global Cα RMSD ≤ 1.0Å and ≤ 2.0Å, respectively. We also compared bound CDR conformations with the conformational space of unbound CDRs and found most of the bound conformations are included in the unbound conformational space. In future, our results will contribute to developing insights into antibodies and new methods for modeling and docking.

Trophic interactions in soil micro-food webs drive ecosystem multifunctionality along tree species richness.

Rapid biodiversity losses under global climate change threaten forest ecosystem functions. However, our understanding of the patterns and drivers of multiple ecosystem functions across biodiversity gradients remains equivocal. To address this important knowledge gap, we measured simultaneous responses of multiple ecosystem functions (nutrient cycling, soil carbon stocks, organic matter decomposition, plant productivity) to a tree species richness gradient of 1, 4, 8, 16, and 32 species in a young subtropical forest. We found that tree species richness had negligible effects on nutrient cycling, organic matter decomposition, and plant productivity, but soil carbon stocks and ecosystem multifunctionality significantly increased with tree species richness. Linear mixed-effect models showed that soil organisms, particularly arbuscular mycorrhizal fungi (AMF) and soil nematodes, elicited the greatest relative effects on ecosystem multifunctionality. Structural equation models revealed indirect effects of tree species richness on ecosystem multifunctionality mediated by trophic interactions in soil micro-food webs. Specifically, we found a significant negative effect of gram-positive bacteria on soil nematode abundance (a top-down effect), and a significant positive effect of AMF biomass on soil nematode abundance (a bottom-up effect). Overall, our study emphasizes the significance of a multitrophic perspective in elucidating biodiversity-multifunctionality relationships and highlights the conservation of functioning soil micro-food webs to maintain multiple ecosystem functions.

Investigating the ability of deep learning-based structure prediction to extrapolate and/or enrich the set of antibody CDR canonical forms.

Deep learning models have been shown to accurately predict protein structure from sequence, allowing researchers to explore protein space from the structural viewpoint. In this paper we explore whether "novel" features, such as distinct loop conformations can arise from these predictions despite not being present in the training data. Here we have used ABodyBuilder2, a deep learning antibody structure predictor, to predict the structures of ~1.5M paired antibody sequences. We examined the predicted structures of the canonical CDR loops and found that most of these predictions fall into the already described CDR canonical form structural space. We also found a small number of "new" canonical clusters composed of heterogeneous sequences united by a common sequence motif and loop conformation. Analysis of these novel clusters showed their origins to be either shapes seen in the training data at very low frequency or shapes seen at high frequency but at a shorter sequence length. To evaluate explicitly the ability of ABodyBuilder2 to extrapolate, we retrained several models whilst withholding all antibody structures of a specific CDR loop length or canonical form. These "starved" models showed evidence of generalisation across CDRs of different lengths, but they did not extrapolate to loop conformations which were highly distinct from those present in the training data. However, the models were able to accurately predict a canonical form even if only a very small number of examples of that shape were in the training data. Our results suggest that deep learning protein structure prediction methods are unable to make completely out-of-domain predictions for CDR loops. However, in our analysis we also found that even minimal amounts of data of a structural shape allow the method to recover its original predictive abilities. We have made the ~1.5 M predicted structures used in this study available to download at https://doi.org/10.5281/zenodo.10280181.

From symbiosis to independence: Investigating changes in the relationship between general practitioners' presence and pharmacies' market size in Slovakia.

Using the Slovak pharmacy retail market case, this study examines the evolving interdependency between general practitioners (GPs) and pharmacies. Traditionally, they have operated symbiotically, with pharmacy revenues heavily reliant on prescriptions. However, the development of the market structures of these providers after the liberalization of the pharmacy retail market in 2005 raises a question about the stability of this relationship. By analyzing entry thresholds as a measure of the market size required for pharmacies to cover their entry costs, the study reveals that the dependency of pharmacies on the presence of GPs has diminished over time. In the initial year following the liberalization, the presence of a GP decreased the market size sufficient to cover entry costs for the first pharmacy by about 83% compared to a market without a GP. However, in 2019, this effect decreased to approximately 65%. This could imply worsened coverage of pharmaceutical services in small and rural areas with GPs as the entry decision of pharmacies is less elastic towards their presence.

Positive effects of tree species diversity on productivity switch to negative after severe drought mortality in a temperate forest experiment.

The synthesis of a large body of evidence from field experiments suggests more diverse plant communities are more productive as well as more resistant to the effects of climatic extremes like drought. However, this view is strongly based on data from grasslands due to the limited empirical evidence from tree diversity experiments. Here we report on the relationship between tree diversity and productivity over 10 years in a field experiment established in 2005 that was then affected by the 2018 mega-drought in central Europe. Across a number of years, tree species diversity and productivity were significantly positively related; however, the slope switched to negative in the year of the drought. Net diversity effects increased through time, with complementarity effects making greater contributions to the net diversity effect than selection effects. Complementarity effects were clearly positive in three- and five-species mixtures before the drought (2012-2016) but were found to decrease in the year of the drought. Selection effects were clearly positive in 2016 and remained positive in the drought year 2018 in two-, three-, and five-species mixtures. The survival of Norway spruce (Picea abies) plummeted in response to the drought, and a negative relationship between species diversity and spruce survival was found. Taken together, our findings suggest that tree diversity per se may not buffer communities against the impacts of extreme drought and that tree species composition and the drought tolerance of tree species (i.e., species identity) will be important determinants of community productivity as the prevalence of drought increases.

Symphony of sustainability: how technology similarity impacts international trade patterns in environmental goods.

The global consensus on sustainable development and environmental cooperation has prompted the promotion of trade in environmental goods (EGs) for green growth. This study delves into the diversity of EGs trade patterns, using decomposed environmental technology similarity indicators to reveal the technological drivers. Linking innovation indicators to trade performance in EGs provides new insights into the determinants of inequality in environmental governance cooperation. Based on an extended gravity model, we empirically analyze their impact on bilateral EGs trade flows among 176 countries over the period 2002-2019. The study finds that (1) the global EGs trade network presents a "core-periphery" structure, with increased network density and participation of developing countries. (2) Technology similarity contributes significantly to EGs trade. Compared to competition, technology complementarity has a greater impact on EGs trade flows. (3) The influence of technology similarity varies across trade patterns and product complexity explains the mechanisms, with technology complementarity promoting more trade in high-complexity products, mainly concentrated in the trade from Northern countries, while technology competition greatly promotes the export of low-complexity products from the South. (4) Technology similarity helps to overcome information barriers in EGs trade, and its trade-enhancing effects exhibit geographical regionalization. The findings offer empirical evidence on the technological drivers of EGs trade and provide policy implications for fostering inclusive global environmental governance and enhancing the competitive advantages of Southern countries, fostering more opportunities for green growth.

T-Cell Receptor Sequences Identify Combined Coxsackievirus-Streptococci Infections as Triggers for Autoimmune Myocarditis and Coxsackievirus-Clostridia Infections for Type 1 Diabetes.

Recent research suggests that T-cell receptor (TCR) sequences expanded during human immunodeficiency virus and SARS-CoV-2 infections unexpectedly mimic these viruses. The hypothesis tested here is that TCR sequences expanded in patients with type 1 diabetes mellitus (T1DM) and autoimmune myocarditis (AM) mimic the infectious triggers of these diseases. Indeed, TCR sequences mimicking coxsackieviruses, which are implicated as triggers of both diseases, are statistically significantly increased in both T1DM and AM patients. However, TCRs mimicking Clostridia antigens are significantly expanded in T1DM, whereas TCRs mimicking Streptococcal antigens are expanded in AM. Notably, Clostridia antigens mimic T1DM autoantigens, such as insulin and glutamic acid decarboxylase, whereas Streptococcal antigens mimic cardiac autoantigens, such as myosin and laminins. Thus, T1DM may be triggered by combined infections of coxsackieviruses with Clostridia bacteria, while AM may be triggered by coxsackieviruses with Streptococci. These TCR results are consistent with both epidemiological and clinical data and recent experimental studies of cross-reactivities of coxsackievirus, Clostridial, and Streptococcal antibodies with T1DM and AM antigens. These data provide the basis for developing novel animal models of AM and T1DM and may provide a generalizable method for revealing the etiologies of other autoimmune diseases. Theories to explain these results are explored.

Tyrosine Sulfation at Antibody Light Chain CDR-1 Increases Binding Affinity and Neutralization Potency to Interleukine-4.

Structure and function of therapeutic antibodies can be modulated by a variety of post-translational modifications (PTM). Tyrosine (Tyr) sulfation is a type of negatively charged PTM that occurs during protein trafficking through the Golgi. In this study, we discovered that an anti-interleukin (IL)-4 human IgG1, produced by transiently transfected HEK293 cells, contained a fraction of unusual negatively charged species. Interestingly, the isolated acidic species exhibited a two-fold higher affinity to IL-4 and a nearly four-fold higher potency compared to the main species. Mass spectrometry (MS) showed the isolated acidic species possessed an +80-Dalton from the expected mass, suggesting an occurrence of Tyr sulfation. Consistent with this hypothesis, we show the ability to control the acidic species during transient expression with the addition of Tyr sulfation inhibitor sodium chlorate or, conversely, enriched the acidic species from 30% to 92% of the total antibody protein when the IL-4 IgG was co-transfected with tyrosylprotein sulfotransferase genes. Further MS and mutagenesis analysis identified a Tyr residue at the light chain complementarity-determining region-1 (CDRL-1), which was sulfated specifically. These results together have demonstrated for the first time that Tyr sulfation at CDRL-1 could modulate antibody binding affinity and potency to a human immune cytokine.

Menu choice stated preference tasks to capture demand complementarity in health.

Health programs/services are often bundled, allowing for both substitution and complementarity. We adapt Discrete Choice Experiments to capture bundling, with application to a case study of exercise and nutrition; complementarity arises due to the goal of improving health. Our contributions are (1) to present a menu-based choice experiment to explore bundling; (2) to analyse the menu-based data using an extension of the choice set generation model (GenL) to account for correlations between bundles and component singles. A nationally representative sample of 333 Australians chose between a nutrition program only; exercise program only; both nutrition and exercise programs; or their status quo. Overall, we show that by incorporating the menu choice task and introducing the combined alternative, we capture a significant portion of the population seeking both exercise and nutrition components. We estimate a latent class GenL model, and identify two latent classes: Class 1 preferred to choose programs on offer, and Class 2 was more price sensitive and had a stronger preference for staying with their status quo. We show in the post-estimation analysis that heterogeneity in preferences translates into heterogeneity in the way alternatives are bundled, indicating that the combined offering is appealing to specific classes of individuals who prefer bundling. By implementing the menu choice task, researchers and policymakers can effectively identify, cater to and influence the demand for combined exercise and nutrition options, leading to more targeted and impactful interventions in promoting healthier lifestyle choices.

Plant community diversity alters the response of ecosystem multifunctionality to multiple global change factors.

Biodiversity is considered important to the mitigation of global change impacts on ecosystem multifunctionality in terrestrial ecosystems. However, potential mechanisms through which biodiversity maintains ecosystem multifunctionality under global change remain unclear. We grew 132 plant communities with two levels of plant diversity, crossed with treatments based on 10 global change factors (nitrogen deposition, soil salinity, drought, plant invasion, simulated grazing, oil pollution, plastics pollution, antibiotics pollution, heavy metal pollution, and pesticide pollution). All global change factors negatively impacted ecosystem multifunctionality, but negative impacts were stronger in high compared with low diversity plant communities. We explored potential mechanisms for this unexpected result, finding that the inhibition of selection effects (i.e., selection for plant species associated with high ecosystem functioning) contributed to sensitivity of ecosystem multifunctionality to global change. Specifically, global change factors decreased the abundance of novel functional plants (i.e., legumes) in high but not low diversity plant communities. The negative impacts of global change on ecosystem multifunctionality were also mediated by increased relative abundance of fungal plant pathogens (identified from metabarcoding of soil samples) and their negative relationship with the abundance of novel functional plants. Taken together, our experiment highlights the importance of protecting high diversity plant communities and legumes, and managing fungal pathogens, to the maintenance of ecosystem multifunctionality in the face of complex global change.

Structure- and machine learning-guided engineering demonstrate that a non-canonical disulfide in an anti-PD-1 rabbit antibody does not impede antibody developability.

Rabbits produce robust antibody responses and have unique features in their antibody repertoire that make them an attractive alternative to rodents for in vivo discovery. However, the frequent occurrence of a non-canonical disulfide bond between complementarity-determining region (CDR) H1 (C35a) and CDRH2 (C50) is often seen as a liability for therapeutic antibody development, despite limited reports of its effect on antibody binding, function, and stability. Here, we describe the discovery and humanization of a human-mouse cross-reactive anti-programmed cell death 1 (PD-1) monoclonal rabbit antibody, termed h1340.CC, which possesses this non-canonical disulfide bond. Initial removal of the non-canonical disulfide resulted in a loss of PD-1 affinity and cross-reactivity, which led us to explore protein engineering approaches to recover these. First, guided by the sequence of a related clone and the crystal structure of h1340.CC in complex with PD-1, we generated variant h1340.SA.LV with a potency and cross-reactivity similar to h1340.CC, but only partially recovered affinity. Side-by-side developability assessment of both h1340.CC and h1340.SA.LV indicate that they possess similar, favorable properties. Next, and prompted by recent developments in machine learning (ML)-guided protein engineering, we used an unbiased ML- and structure-guided approach to rapidly and efficiently generate a different variant with recovered affinity. Our case study thus indicates that, while the non-canonical inter-CDR disulfide bond found in rabbit antibodies does not necessarily constitute an obstacle to therapeutic antibody development, combining structure- and ML-guided approaches can provide a fast and efficient way to improve antibody properties and remove potential liabilities.

Interference Requirements of Type III CRISPR-Cas Systems from Thermus thermophilus.

Among the diverse prokaryotic adaptive immunity mechanisms, the Type III CRISPR-Cas systems are the most complex. The multisubunit Type III effectors recognize RNA targets complementary to CRISPR RNAs (crRNAs). Target recognition causes synthesis of cyclic oligoadenylates that activate downstream auxiliary effectors, which affect cell physiology in complex and poorly understood ways. Here, we studied the ability of III-A and III-B CRISPR-Cas subtypes from Thermus thermophilus to interfere with plasmid transformation. We find that for both systems, requirements for crRNA-target complementarity sufficient for interference depend on the target transcript abundance, with more abundant targets requiring shorter complementarity segments. This result and thermodynamic calculations indicate that Type III effectors bind their targets in a simple bimolecular reaction with more extensive crRNA-target base pairing compensating for lower target abundance. Since the targeted RNA used in our work is non-essential for either the host or the plasmid, the results also establish that a certain number of target-bound effector complexes must be present in the cell to interfere with plasmid establishment. For the more active III-A system, we determine the minimal length of RNA-duplex sufficient for interference and show that the position of this minimal duplex can vary within the effector. Finally, we show that the III-A immunity is dependent on the HD nuclease domain of the Cas10 subunit. Since this domain is absent from the III-B system the result implies that the T. thermophilus III-B system must elicit a more efficient cyclic oligoadenylate-dependent response to provide the immunity.

Preparation and characterization of monoclonal antibodies against porcine gasdermin D protein.

Pyroptosis is a newly discovered type of pro-inflammatory programmed cell death that plays a vital role in various processes such as inflammations, immune responses, and pathogen infections. As one of the main executioners of pyroptosis, gasdermin D (GSDMD) is a membrane pore-forming protein that typically exists in a self-inhibitory state. Once activated, GSDMD will be cleaved into an N-terminal fragment with pore-forming activity, becoming the key indicator of pyroptosis activation, and a C-terminal fragment. Although commercial antibodies against human and murine GSDMD proteins are currently available, their reactivity with porcine GSDMD (pGSDMD) is poor, which limits research on the biological functions of pGSDMD and pyroptosis in pigs in vivo and in vitro. Here, five monoclonal antibodies (mAbs) were prepared by immunizing BALB/c mice with procaryotically expressed full-length pGSDMD, all of which did not cross react with human and murine GSDMD proteins. Epitope mapping demonstrated that 15H6 recognizes amino acids (aa) at positions 28-34 of pGSDMD (LQTSDRF), 19H3 recognizes 257-260aa (PPQF), 23H10 and 27A10 recognize 78-82aa (GPFYF), and 25E2 recognizes 429-435aa (PPTLLGS). The affinity constant and isotype of 15H6, 19H3, 23H10, 27A10, and 25E2 mAbs were determined to be 1.32 × 10-9, 3.66 × 10-9, 9.04 × 10-9, 1.83 × 10-9, and 8.00 × 10-8 mol/L and IgG1/κ, IgG2a/κ, IgG2a/κ, IgG1/κ, and IgG1/κ, respectively. Heavy- and light-chain variable regions sequencing showed that the heavy-chain complementarity-determining region (CDR) sequences of all five mAbs are completely different, while the light-chain CDR sequences of the four mAbs that recognize the N-terminus of pGSDMD are identical. Our prepared mAbs provide valuable materials for studying pGSDMD function and pyroptosis. KEY POINTS: • A total of five mouse anti-pGSDMD mAbs were prepared, of which four recognize the N-terminus of pGSDMD and one recognize its C-terminus. • The main performance parameters of the five mAbs, including epitope, antibody titer, affinity constant, isotype, and heavy- and light-chain CDR, were characterized. • All five mAbs specifically recognize pGSDMD protein and do not cross react with human and murine GSDMD proteins.