Single-domain antibodies efficiently neutralize SARS-CoV-2 variants of concern, including Omicron variant Virus-neutralizing antibodies are one of the few treatment options for COVID-19. The evolution of SARS-CoV-2 virus has led to the emergence of virus variants with reduced sensitivity to some antibody-based therapies. The development of potent antibodies with a broad spectrum of neutralizing activity is urgently needed. Here we isolated a panel of single-domain antibodies that specifically bind to the receptor-binding domain of SARS-CoV-2 S glycoprotein. Three of the selected antibodies exhibiting most robust neutralization potency were used to generate dimeric molecules. We observed that these modifications resulted in up to a 200-fold increase in neutralizing activity. The most potent heterodimeric molecule efficiently neutralized each of SARS-CoV-2 variant of concern, including Alpha, Beta, Gamma, Delta and Omicron variants. This heterodimeric molecule could be a promising drug candidate for a treatment for COVID-19 caused by virus variants of concern.
Spatial transcriptomic characterization of COVID-19 pneumonitis identifies immune circuits related to tissue injury Severe lung damage in COVID-19 involves complex interactions between diverse populations of immune and stromal cells. In this study, we used a spatial transcriptomics approach to delineate the cells, pathways and genes present across the spectrum of histopathological damage in COVID-19 lung tissue. We applied correlation network-based approaches to deconvolve gene expression data from areas of interest within well preserved post-mortem lung samples from three patients. Despite substantial inter-patient heterogeneity we discovered evidence for a common immune cell signaling circuit in areas of severe tissue that involves crosstalk between cytotoxic lymphocytes and pro-inflammatory macrophages. Expression of IFNG by cytotoxic lymphocytes was associated with induction of chemokines including CXCL9, CXCL10 and CXCL11 which are known to promote the recruitment of CXCR3+ immune cells. The tumour necrosis factor (TNF) superfamily members BAFF (TNFSF13B) and TRAIL (TNFSF10) were found to be consistently upregulated in the areas with severe tissue damage. We used published spatial and single cell SARS-CoV-2 datasets to confirm our findings in the lung tissue from additional cohorts of COVID-19 patients. The resulting model of severe COVID-19 immune-mediated tissue pathology may inform future therapeutic strategies.

One Sentence SummarySpatial analysis identifies IFN{gamma} response signatures as focal to severe alveolar damage in COVID-19 pneumonitis.
GCN5L1 promotes diastolic dysfunction by inhibiting cardiac pyruvate oxidation Left ventricular diastolic dysfunction is a structural and functional condition that precedes the development of heart failure with preserved ejection fraction (HFpEF). The etiology of diastolic dysfunction includes alterations in fuel substrate metabolism that negatively impact cardiac bioenergetics, and may precipitate the eventual transition to heart failure. To date, the molecular mechanisms that regulate early changes in fuel metabolism leading to diastolic dysfunction remain unclear. In this report, we use a diet-induced obesity model and quantitative acetylproteomics in aged mice to show that inhibitory lysine acetylation of the pyruvate dehydrogenase (PDH) complex promotes energetic deficits and diastolic dysfunction in mouse hearts. Cardiomyocyte-specific deletion of the mitochondrial lysine acetylation regulatory protein GCN5L1 prevented hyperacetylation of the PDH complex subunit PDHA1, allowing aged obese mice to continue using pyruvate as a bioenergetic substrate in the heart. Our findings suggest that changes in mitochondrial protein lysine acetylation represent a key metabolic component of diastolic dysfunction that precedes the development of heart failure. A Hierarchy of Biomolecular Proportional-Integral-Derivative Feedback Controllers for Robust Perfect Adaptation and Dynamic Performance Proportional-Integral-Derivative (PID) feedback controllers have been the most widely used controllers in industry for almost a century due to their good performance, simplicity, and ease of tuning. Motivated by their success in various engineering disciplines, PID controllers recently found their way into synthetic biology, where the design of feedback molecular control systems has been identified as an important goal. In this paper, we consider the mathematical realization of PID controllers via biomolecular interactions. We propose an array of topologies that offer a compromise between simplicity and high performance. We first demonstrate that different Proportional-Integral (PI) controllers exhibit different capabilities for enhancing the dynamics and reducing variance (cell-to-cell variability). Next, we introduce several derivative controllers that are realized based on incoherent feedforward loops acting in a feedback configuration. Alternatively, we show that differentiators can be realized by placing molecular integrators in a negative feedback loop--an arrangement that can then be augmented by PI components to yield PID feedback controllers. We demonstrate that the derivative component can be exploited for enhancing system stability, dramatically increasing the molecular control systems dynamic performance, and for reducing the noise effect on the output of interest. The PID controller features are established through various deterministic and stochastic analyses as well as numerical simulations. Finally, we provide an experimental demonstration using a recently developed hybrid setup, the cyberloop, where the controller is implemented in silico to control a biological genetic circuit in vivo. The large array of novel biomolecular PID controllers introduced here forms a basis for the design and construction of advanced high-performance biomolecular control systems that robustly regulate the dynamics of living systems. BatchDTA: Implicit batch alignment enhances deep learning-based drug-target affinity estimation Candidate compounds with high binding affinities toward a target protein are likely to be developed as drugs. Deep neural networks (DNNs) have attracted increasing attention for drug-target affinity (DTA) estimation owning to their efficiency. However, the negative impact of batch effects caused by measure metrics, system technologies, and other assay information is seldom discussed when training a DNN model for DTA. Suffering from the data deviation caused by batch effects, the DNN models can only be trained on a small amount of "clean" data. Thus, it is challenging for them to provide precise and consistent estimations. We design a batch-sensitive training framework, namely BatchDTA, to train the DNN models. BatchDTA implicitly aligns multiple batches toward the same protein, alleviating the impact of the batch effects on the DNN models. Extensive experiments demonstrate that BatchDTA facilitates four mainstream DNN models to enhance the ability and robustness on multiple DTA datasets. The average concordance index (CI) of the DNN models achieves a relative improvement of 4.0%. BatchDTA can also be applied to the fused data collected from multiple sources to achieve further improvement. An hidden Markov model to estimate homozygous-by-descent probabilities associated with nested layers of ancestors Inbreeding results from the mating of related individuals and has negative consequences because it brings together deleterious variants in one individual. Genomic estimates of the inbreeding coefficients are preferred to pedigree-based estimators as they measure the realized inbreeding levels and they are more robust to pedigree errors. Several methods identifying homozygous-by-descent (HBD) segments with hidden Markov models (HMM) have been recently developed and are particularly valuable when the information is degraded or heterogeneous (e.g., low-fold sequencing, low marker density, heterogeneous genotype quality or variable marker spacing). We previously developed a multiple HBD class HMM where HBD segments are classified in different groups based on their length (e.g., recent versus old HBD segments) but we recently observed that for high inbreeding levels with many HBD segments, the estimated contributions might be biased towards more recent classes (i.e., associated with large HBD segments) although the overall estimated level of inbreeding remained unbiased. We herein propose a new model in which the HBD classification is modeled in successive nested levels with decreasing expected HBD segment lengths, the underlying exponential rates being directly related to the number of generations to the common ancestor. The non-HBD classes are now modeled as a mixture of HBD segments from later generations and shorter non-HBD segments (i.e., both with higher rates). The new model has improved statistical properties and performs better on simulated data compared to our previous version. We also show that the parameters of the model are easier to interpret and that the model is more robust to the choice of the number of classes. Overall, the new model results in an improved partitioning of inbreeding in different HBD classes and should be preferred. Sensing their plasma membrane curvature allows migrating cells to circumvent obstacles Cell migration is a hallmark out-of-equilibrium process in biology. In addition to persistent self-propelled motion, many cells display remarkable adaptive behaviors when they navigate complex environments within the body. Combining theory and experiments, we identify a curvature-sensing mechanism underlying obstacle avoidance in immune-like cells. The genetic perturbation of this machinery leads to a reduced capacity to evade obstructions combined with faster and more persistent cell migration in obstacle-free environments. We propose that the active polymerization of the actin cytoskeleton at the advancing edge of migrating cells is locally inhibited by the curvature-sensitive BAR protein Snx33 in regions with inward plasma membrane curvature. This coupling between actin and membrane dynamics leads to a mechanochemical instability that generates complex protrusive patterns at the cellular front. Adaptive motility thus arises from two simultaneous curvature-dependent effects, i) the specific reduction of propulsion in regions where external objects deform the plasma membrane and ii) the intrinsic patterning capacity due to the membrane-actin coupling that promotes spontaneous changes in the cells protrusions. Our results show how cells utilize actin- and plasma membrane biophysics to sense their environment, allowing them to adaptively decide if they should move ahead or turn away. On the basis of our findings, we propose that the natural diversity of BAR proteins may allow cells to tune their curvature sensing machinery to match the shape characteristics in their environment. A MALDI-TOF assay identifies nilotinib as an inhibitor of inflammation in acute myeloid leukaemia Inflammatory responses are important in cancer, particularly in the context of monocyte-rich aggressive myeloid neoplasm. We developed a label-free cellular phenotypic drug discovery assay to identify anti-inflammatory drugs in human monocytes derived from acute myeloid leukaemia (AML), by tracking several biological features ionizing from only 2,500 cells using matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry. A proof-of-concept screen showed that the BCR-ABL inhibitor nilotinib, but not the structurally similar imatinib, blocks inflammatory responses. In order to identify the cellular (off-)targets of nilotinib, we performed thermal proteome profiling (TPP). Unlike imatinib, nilotinib and other later generation BCR-ABL inhibitors inhibit the p38-MK2/3 signalling axis which suppressed the expression of inflammatory cytokines, cell adhesion and innate immunity markers in activated human monocytes derived from AML. Thus, our study provides a tool for the discovery of new anti-inflammatory drugs, which could contribute to the treatment of inflammation in myeloid neoplasms and other diseases.

Key PointsLabel-free cell-based assay identifies new anti-inflammatory drugs using MALDI-TOF MS. Nilotinib reduces inflammation by inhibition of MAPK14-MK2/3 signalling axis in AML. An NLR Integrated Domain toolkit to identify plant pathogen effector targets Plant resistance genes (or NLR "Nod-like Receptors") are known to contain atypical domains procuring them with a decoy capacity. Some of these integrated domains (or ID) allow the plant to lure the virulence determinants ("effectors") of pathogens and triggering a specific NLR immune reaction.

In this work, our goal was to generate a library of known IDs that could be screened with plant pathogen effectors in order to identify putative new effector virulence targets and NLR-effector pairs.

We curated the IDs contained in NLRs from seven model and crop plant species. We cloned 52 IDs representing 31 distinct Pfam domains. This library was screened for interaction by yeast-two-hybrid with a set of 31 conserved Ralstonia solanacearum type III effectors. This screening and the further in planta interaction assay allowed us to identify three interactions, involving different IDs (kinase, DUF3542, WRKY) and two type III effectors (RipAE and PopP2).

PopP2 was found to physically interact with ID#85, an atypical WRKY domain integrated in the GmNLR-ID85 NLR protein from Soybean. Using a imaging method in living plant cells, we showed that PopP2 associates with ID#85 in the nucleus. But unlike the known WRKY-containing Arabidopsis RRS1-R NLR receptor, this newly identified soybean WRKY domain could not be acetylated by PopP2 and its atypical sequence (WRKYGKR) also probably renders it inefficient in plant immunity triggering.

This ID toolkit is available for screening with other plant pathogen effectors and should prove useful to discover new effectors targets and potentially engineer new plant resistance genes. Mapping the planet's critical natural assets Sustaining the organisms, ecosystems, and processes that underpin human well-being is necessary to achieve sustainable development. Here we identify critical natural assets, natural and semi-natural ecosystems that provide 90% of the total current magnitude of 14 types of natures contributions to people (NCP). Critical natural assets for maintaining local-scale NCP (12 of the 14 NCP mapped) comprise 30% of total global land area and 24% of national territorial waters, while 44% of land area is required for maintaining all NCP (including those that accrue at the global scale, carbon storage and moisture recycling). At least 87% of the worlds population lives in the areas benefiting from critical natural assets for local-scale NCP, while only 16% lives on the lands containing these assets. Critical natural assets also overlap substantially with areas important for biodiversity (covering area requirements for 73% of birds and 66% of mammals) and cultural diversity (representing 96% of global Indigenous and non-migrant languages). Many of the NCP mapped here are left out of international agreements focused on conserving species or mitigating climate change, yet this analysis shows that explicitly prioritizing critical natural assets for NCP could simultaneously advance development, climate, and conservation goals. Crafting policy and investment strategies that protect critical natural assets is essential for sustaining human well-being and securing Earths life support systems. Reuse of a wing venation gene-regulatory network in patterning the eyespot rings of butterflies Novel organismal traits might reuse ancestral gene-regulatory networks (GRNs) in their development, but data supporting this mechanism are still sparse. Here we propose that a conserved venation gene network, used in patterning insect wings, has been recruited to pattern the sharp and distinct rings of color in butterfly eyespot development. This network involves Decapentaplegic (Dpp), acting as a central morphogen, activating optix and spalt at different concentration thresholds. It also involves Spalt cross-regulating optix resulting in the formation of a sharp boundary between the two genes. First, using in situ hybridizations, we show that dpp is expressed in the eyespot centers during the early pupal stage and that CRISPR-Cas9 embryonic knockouts of dpp, optix, and spalt result in the loss of eyespots, loss of the orange ring, and loss of the black scales, respectively. Furthermore, using RNAi during the pupal stage, we show that dpp down-regulation results in the complete or partial loss of eyespots. Using CRISPR disruptions of optix or spalt, followed by immunostainings, we show that Spalt represses optix in the central region of the eyespot, limiting optix expression to a more peripheral ring. We further illustrate that optix disruptions alter scale pigmentation and scale ultrastructure as they transform orange to brown scales. Altogether, the regulatory interactions between dpp, spalt and optix mimic those found in earlier larval developmental stages, in the anterior compartment of an insects wing, where these genes play a role in venation patterning. The network similarities suggest that the venation GRN was co-opted to aid in the differentiation of the eyespot rings. ALLOPURINOL BLOCKS THE AORTIC ANEURYSM IN A MOUSE MODEL OF MARFAN SYNDROME VIA REDUCING AORTIC OXIDATIVE STRESS BackgroundThe pathogenesis and progression of aortic aneurysm in Marfan syndrome (MFS) involves dysregulated TGF-{beta} and nitric oxide signaling, altered hemodynamics, and biomechanical forces. Increasing evidence indicates that redox stress participates in MFS aortopathy, though its contribution is not well established. We reported elevated reactive oxygen species (ROS) formation and NADPH oxidase NOX4 upregulation in MFS patients and mice aortic samples. Here we address the contribution of xanthine oxidoreductase (XOR), which is transcribed as dehydrogenase (XDH) and then post-translationally modified to oxidase (XO), catabolizing mainly purines into uric acid and ROS.

Methods and ResultsWe report that in MFS patients, XOR protein levels increased in aortic samples. In MFS mice (Fbn1C1041G/+), XOR mRNA transcripts augmented in the aorta of young but not older MFS mice. Moreover, the enzymatic activity of XO form increased with respect to XDH. The administration of the XOR inhibitor allopurinol (ALO) blocked the progression of aortic root aneurysm in MFS mice. ALO was also protective when administrated before the appearance of aneurysm. MFS-induced elastic fiber fragmentation, fibrotic remodeling, nuclear translocation of pNRF2, and increased 3-nitrotyrosine levels in the aortic tunica media as well as endothelial dysfunction were all prevented by allopurinol. The large overproduction of H2O2 in MFS aorta did not occur in allopurinol-treated mice whose uric acid plasma levels remained unaltered.

ConclusionsThis study strengthens the concept that redox stress is an important determinant of aortic aneurysm formation and progression in MFS and supports a clinical trial for ALO in the pharmacological treatment of MFS aortopathy.

GRAPHICAL ABSTRACT

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=146 SRC="FIGDIR/small/464182v3_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@eab02aorg.highwire.dtl.DTLVardef@1d3b39eorg.highwire.dtl.DTLVardef@1b54d0forg.highwire.dtl.DTLVardef@1d61ad0_HPS_FORMAT_FIGEXP  M_FIG C_FIG Exploring functional protein covariation across single cells using nPOP Many biological processes, such as the cell division cycle, are reflected in protein covariation across single cells. This covariation can be quantified and interpreted by single-cell proteomics with sufficiently high throughput and accuracy. Toward this goal, we developed the nano-ProteOmic sample Preparation (nPOP) method for single-cell proteomics. nPOP uses piezo acoustic dispensing to isolate individual cells in 300 picoliter volumes and performs all subsequent preparation steps in small droplets on a fluorocarbon-coated slide. This design enables simultaneous sample preparation of thousands of single cells, including lysing, digesting, and labeling individual cells in volumes below 20 nl. We used nPOP to prepare 1,888 single cells and 128 negative controls in a single batch. Their analysis enabled quantifying the covariation between thousands of proteins and cell-cycle protein markers. Many protein sets covaried with the cell cycle similarly across all cell types and states, reflecting cell-type independent cell cycle functions. However, the cell cycle covariation of other protein sets differed markedly between cell types, even within subpopulation of melanoma cells expressing markers for drug-resistance priming. The cells expressing these markers accumulated in the G1 phase of the cell cycle and exhibited different covariation of enzymes catabolizing glucose. These results demonstrate that protein covariation across single cells may reveal functionally concerted biological differences between closely related cell states.

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=59 SRC="FIGDIR/small/441211v3_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@1e23b1org.highwire.dtl.DTLVardef@b93faeorg.highwire.dtl.DTLVardef@3c00forg.highwire.dtl.DTLVardef@362b41_HPS_FORMAT_FIGEXP  M_FIG C_FIG Electrocommunication signals indicate motivation to compete during dyadic interactions of an electric fish Animals across species compete for limited resources. While in some species competition behavior is solely based on own abilities, others assess their opponents to facilitate these interactions. Using cues and communication signals, contestants gather information about their opponent, adjust their behavior accordingly, and can thereby avoid high costs of escalating fights. We tracked electrocommunication signals, in particular "rises", and agonistic behaviors of the gymnotiform electric fish Apteronotus leptorhynchus in staged competition experiments. A larger body size relative to the opponent was the sole significant predictor for winners. Sex and the frequency of the continuously emitted electric field were only mildly influencing competition outcome. In males, correlations of body-size and winning were stronger than in females and, especially when losing against females, communication and agonistic interactions were enhanced, hinting towards males being more motivated to compete. Fish that lost competitions emitted the majority of rises in dependence on the competitors relative size and sex. The emission of rises was costly since it provoked ritualized biting or chasing behaviors by the other fish. Despite winners being accurately predictable based on rise numbers already after the initial 25 minutes, losers continued to emit rises. The number of rises emitted by losers and the duration of chasing behaviors depended in similar ways on physical attributes of contestants. The detailed evaluation of these correlations hint towards A. leptorhynchus adjusting their competition behavior according to mutual assessment, where rises could signal a losers motivation to continue assessment through ritualized fighting. First evidence of in vitro cytotoxic effects of marine microlitter on Merluccius merluccius and Mullus barbatus, two Mediterranean commercial fish species Marine litter is composed mainly of plastics and is recognized as a serious threats to marine ecosystems. Ecotoxicological approaches have started elucidating the potential severity of microplastics (MPs) in controlled laboratory studies with pristine materials but no information exist on marine environmental microlitter as a whole. Here, we characterized the litter in the coastal Northern Tyrrhenian sea and in the stomach of two fish species of socio-economic importance, and exposed primary cell cultures of mucosal and lymphoid organs to marine microlitter for evaluating possible cytotoxic effects. An average of 0.30 {+/-} 0.02 microlitter items m-3 was found in water samples. FT-IR analysis revealed that plastic particles, namely HDPE, polyamide and polypropylene were present in 100% and 83.3% of Merluccius merluccius and Mullus barbatus analyzed, which overall ingested 14.67 {+/-} 4.10 and 5.50 {+/-} 1.97 items/individual, respectively. Moreover, microlitter was confirmed as a vector of microorganisms. Lastly, the apical end-point of viability was found to be significantly reduced in splenic cells exposed in vitro to two microlitter conditions. Considering the role of the spleen in the mounting of adaptive immune responses, our results warrant more in-depth investigations for clarifying the actual susceptibility of these two species to anthropogenic microlitter.

HighlightsO_LI0.30 {+/-} 0.02 microlitter items m-3 were found at the surface of coastal Northern Tyrrhenian sea
C_LIO_LI14.67 {+/-} 4.10 and 5.50 {+/-} 1.97 items/individual were retrieved from the stomach of hakes and mullets
C_LIO_LIThe ingested microlitter contained plastic items
C_LIO_LIMicrolitter was validated as a carrier of bacteria, fungi and flagellates
C_LIO_LISplenic cells exposed to two microlitter conditions for 72 hours suffered cytotoxicity
C_LI A Novel Paradigm for Deep Reinforcement Learning of Biomimetic Systems Mechanisms behind neural control of movement have been an active area of research. Goal-directed movement is a common experimental setup used to understand these mechanisms and relevant neural pathways. On the one hand, optimal feedback control theory is used to model and make quantitative predictions of the coordinated activations of the effectors, such as muscles, joints or limbs. While on the other hand, evidence shows that higher centres such as Basal Ganglia and Cerebellum are involved in activities such as reinforcement learning and error correction. In this paper, we provide a framework to build a digital twin of relevant sections of the human spinal cord using our NEUROiD platform. The digital twin is anatomically and physiologically realistic model of the spinal cord at cellular, spinal networks and system level. We then build a framework to learn the supraspinal activations necessary to perform a simple goal directed movement of the upper limb. The NEUROiD model is interfaced to an Opensim model for all the musculoskeletal simulations. We use Deep Reinforcement Learning to obtain the supraspinal activations necessary to perform the goal directed movement. As per our knowledge, this is the first time an attempt is made to learn the stimulation pattern at the spinal cord level, especially by limiting the observation space to only the afferent feedback received on the Ia, II and Ib fibers. Such a setup results in a biologically realistic constrained environment for learning. Our results show that (1) Reinforcement Learning algorithm converges naturally to the triphasic response observed during goal directed movement (2) Increasing the complexity of the goal gradually helped to accelerate learning (3) Modulation of the afferent inputs were sufficient to execute tasks which were not explicitly learned, but were closely related to the learnt task. Molecular diversity maintained by long-term balancing selection in mating loci defines multiple mating types in fungi Balancing selection, an evolutionary force that retains genetic diversity, has been detected in multiple genes and organisms, such as the sexual mating loci in fungi. However, to quantify the strength of balancing selection and define the mating-related genes require a large number of specimens. In tetrapolar basidiomycete fungi, sexual type is determined by two unlinked loci, MATA and MATB. Genes in both loci defines mating type identity, control successful mating and completion of the life cycle. These loci are usually highly diverse. Previous studies have speculated, based on culture crosses, that species of the non-model genus Trichaptum (Hymenochaetales, Basidiomycota) possess a tetrapolar mating system, with multiple alleles. Here, we sequenced a hundred and eighty specimens of three Trichaptum species. We characterized the chromosomal location of MATA and MATB, the molecular structure of MAT regions and their allelic richness. Our sequencing effort was sufficient to molecularly characterize multiple MAT alleles segregating before the speciation event of Trichaptum species. Our analyses suggested that long-term balancing selection has generated trans-species polymorphisms. Mating sequences were classified in different allelic classes based on an amino acid identity (AAI) threshold supported by phylogenetics. The inferred allelic information mirrored the outcome of in vitro crosses, thus allowing us to support the degree of allelic divergence needed for successful mating. Even with the high amount of divergence, key amino acids in functional domains are conserved. The observed allelic classes could potentially generate 14,560 different mating types. We conclude that the genetic diversity of mating in Trichaptum loci is due to long-term balancing selection, with limited recombination and duplication activity. Our large number of sequenced specimens highlighted the importance of sequencing multiple individuals from different species to detect the mating-related genes, the mechanisms generating diversity and the evolutionary forces maintaining them.

Author summaryFungi have complex mating systems, and basidiomycete fungi can encode thousands of mating types. Individuals with the same mating type cannot mate. This sexual system has evolved to facilitate sexual mating, increasing the chances to recombine into advantageous allelic combination and prune deleterious alleles. We explored the genomes of hundred and eighty specimens, combined with experimental mating studies of selected specimens, from a non-model organism (Trichaptum). We characterized the genomic regions controlling sex. The mating ability of the specimens confirmed the role of the mating alleles observed in the genomic data. The detailed analyses of many specimens allowed us to observe gene duplication and rearrangements within the mating loci, increasing the diversity within these loci. We supported previous suggestions of balancing selection in this region, an evolutionary force that maintains genomic diversity. These results supports that our fungal specimens are prone to outcross, which might facilitate the adaptation to new conditions. Agonist efficiency from concentration-response curves: structural implications and applications Agonists are evaluated by a concentration-response curve (CRC), with a midpoint (EC50) that indicates potency, a high-concentration asymptote that indicates efficacy and a low-concentration asymptote that indicates constitutive activity. A third agonist attribute, efficiency ({eta}), is the fraction of binding energy that is applied to the conformational change that activates the receptor. We show that {eta} can be calculated from EC50 and the asymptotes of a CRC derived from either single-channel or whole-cell responses. For 20 agonists of skeletal muscle nicotinic receptors, the distribution of {eta} values is bimodal with population means at 51% (including ACh, nornicotine and DMPP) and 40% (including epibatidine, varenicline and cytisine). The value of {eta} is related inversely to the size of the agonists head-group, with high-versus low-efficiency ligands having an average volume of 70 [A]3 versus 102 [A]3. Most binding site mutations have only a small effect on ACh efficiency except for Y190A (35%), W149A (60%) and those at G153 (42%). If {eta} is known, the midpoint and high-concentration asymptote can be calculated from each other. Hence, an entire CRC can be estimated from the response to a single agonist concentration, and efficacy can be estimated from EC50 of a CRC that has been normalized to 1. Given {eta}, the level of constitutive activity can be estimated from a single CRC.

Statement of significanceReceptors are molecular machines that convert chemical energy from agonist binding into mechanical energy of a global conformational change that generates a cell response. Agonists are distinguished by their potency (proportional to affinity) and efficacy, but also by the efficiency at which their binding energy is applied to receptor activation. Here we show that agonist efficiency can be estimated from a single concentrationresponse curve, and estimate efficiencies of 20 nicotinic receptor agonists. These have a bimodal distribution with larger agonists belonging to the lower-efficiency population. We further show that mutations of some binding site residues alter efficiency, and that knowledge of agonist efficiency simplifies and extends dose-response curve analysis. Comparison of hybrid learning and remote education in the implementation of the 'Adopt a Microorganism' methodology The Internet has changed the way teachers and students access information and build knowledge. The recent COVID-19 pandemic has created challenges for both teachers and students and a demand for new methodologies of remote learning. In the life sciences, mixing online content with practical activities represents an even greater challenge. In microbiology, the implementation of an active teaching methodology, the #Adopt project, based on the social network Facebook(R), represents an excellent option for connecting remote education with classroom activities. In 2020, the version applied in high school, "Adopt a Microorganism", was adapted to meet the demands of emergency remote education owing to the suppression of face-to-face activities caused by the pandemic. In the present study, we assessed how the change in methodology impacted the discourse richness of students from high school integrated with technical education in the Business Administration program of the Federal Institute of Sao Paulo, Sorocaba Campus. Three questionnaires related to the groups of microorganisms (Archaea, Bacteria, Virus, Fungi, and Protozoan) were applied. The students responses in the 2019 and 2020 classes were compared concerning content richness and multiplicity of concepts through the application of the Shannon diversity index, an approach that is generally used to assess biodiversity in different environments. The observed results suggest that remote learning provided students with a conceptual basis and richness of content equivalent to that achieved by students subjected to the hybrid teaching model. In conclusion, this study suggests that the #Adopt project methodology increases students discourse richness in microbiology even without face-to-face traditional classes. Augmenting Recombinant Antibody Production in HEK293E Cells: Optimising Transfection and Culture Parameters BackgroundOptimising recombinant antibody production is important for cost-effective therapeutics and diagnostics. With impact on commercialisation, higher productivity beyond laboratory scales is highly sought, where efficient production can also accelerate antibody characterisations and investigations.

MethodsInvestigating HEK293E cells for mammalian antibody production, various transfection and culture parameters were systematically analysed for antibody light chain production before evaluating them for whole antibody production. Transfection parameters investigated include seeding cell density, the concentration of the transfection reagent and DNA, complexation time, temperature, and volume, as well as culture parameters such as medium replacement, serum deprivation, use of cell maintenance antibiotic, incubation temperature, medium volume, post-transfection harvest day and common nutrient supplements.

ResultsUsing 2 mL adherent HEK293E cell culture transfections with 25 kDa linear Polyethylenimine in the most optimised parameters, we demonstrated a ~2-fold production increase for light chain alone and for whole antibody production reaching 536 and 49 g respectively in a cost-effective manner. With the addition of peptone, {kappa} light chain increased by ~4-fold to 1032 g while whole antibody increased to a lesser extent by ~2.5-fold to 51 g, with benefits potentially for antibodies limited by their light chains in production.

ConclusionsOur optimised findings show promise for a more efficient and convenient antibody production method through transfection and culture optimisations that can be incorporated to scale up processes and with potential transferability to other mammalian-based recombinant protein production using HEK293E cells.

Statement of SignificanceRecombinant antibody production is crucial for antibody research and development. Systematically investigating transfection and culture parameters such as PEI/DNA concentrations, complexation time, volume, and temperature, supplements, etc., we demonstrated a ~4-fold light chain alone production increase to 1032 g and a 2.5-fold whole antibody production increase to 51 g from 2 mL transfections. Establishing farm dust as a useful viral metagenomic surveillance matrix Farm animals may harbor many viral pathogens, some with zoonotic potential which can possibly cause severe clinical outcomes in animals and humans. Documenting viral content of dust may provide information of potential sources and movement of viruses. Here, we describe a dust sequencing strategy that provides detailed viral sequence characterization from farm dust samples and use this method to document the virus communities from chicken farm dust samples and paired feces collected at multiple time points during the production cycle in broiler farms in the Netherlands. From the sequencing data, Parvoviridae and Picornaviridae were the most prevalent families, detected in 85-100% of all feces and dust samples. Surprisingly large genomic diversity was identified in Picornaviridae and viruses from the Caliciviridae and Astroviridae were also obtained. This study provides a unique characterization of virus communities in farmed chickens and paired farm dust samples and our sequencing methodology enabled the recovery of viral genome sequences from farm dust, providing important tracking details for virus movement between livestock animals and their farm environment. This study serves as a proof of concept supporting that dust sampling could potentially be incorporated as part of viral metagenomic surveillance. Conversion of mammalian cell culture media waste to microbial fermentation feed efficiently supports production of recombinant protein by Escherichia coli Deriving new value from waste streams through secondary processes is a central aim of the circular bioeconomy. In this study we investigate whether chemically defined spent media (CDSM) waste from cell culture bioprocess can be recycled and used as a feed in secondary microbial fermentation to produce new recombinant protein products. Our results show that CDSM supplemented with 2% glycerol supported a specific growth rate of E. coli cultures equivalent to that achieved using a nutritionally rich microbiological media (LB). The titre of recombinant protein produced following induction in a 4-hour expression screen was approximately equivalent in the CDSM fed cultures to that of baseline, and this was maintained in a 16-hr preparative fermentation. To understand the protein production achieved in CDSM fed culture we performed a quantitative analysis of proteome changes in the E. coli using mass spectrometry. This analysis revealed significant upregulation of protein synthesis machinery enzymes and significant downregulation of carbohydrate metabolism enzymes. We conclude that spent cell culture media, which represents 100s of millions of litres of waste generated by the bioprocessing industry annually, may be valorized as a feed resource for the production of recombinant proteins in secondary microbial fermentations. Inhibitors of ERp44, PDIA1, and AGR2 induce disulfide-mediated oligomerization of Death Receptors 4 and 5 and cancer cell death Breast cancer mortality remains unacceptably high, indicating a need for safer and more effective therapeutic agents. Disulfide bond Disrupting Agents (DDAs) were previously identified as a novel class of anticancer compounds that selectively kill cancers that overexpress the Epidermal Growth Factor Receptor (EGFR) or its family member HER2. DDAs kill EGFR+ and HER2+ cancer cells via the parallel downregulation of EGFR, HER2, and HER3 and activation/oligomerization of Death Receptors 4 and 5 (DR4/5). However, the mechanisms by which DDAs mediate these effects are unknown. Affinity purification analyses employing biotinylated-DDAs reveal that the Protein Disulfide Isomerase (PDI) family members AGR2, PDIA1, and ERp44 are DDA target proteins. Further analyses demonstrate that shRNA-mediated knockdown of AGR2 and ERp44, or expression of ERp44 mutants, enhance basal and DDA-induced DR5 oligomerization. DDA treatment of breast cancer cells disrupts PDIA1 and ERp44 mixed disulfide bonds with their client proteins. Together, the results herein reveal DDAs as the first small molecule, active site inhibitors of AGR2 and ERp44, and demonstrate roles for AGR2 and ERp44 in regulating the activity, stability, and localization of DR4 and DR5, and activation of Caspase 8. Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. Continuous Theta Burst Stimulation to the Secondary Visual Cortex at 80% Active Motor Threshold Does Not Impair Central Vision in Humans During a Simple Detection Task Continuous theta burst stimulation (cTBS) is a powerful form of repetitive transcranial magnetic stimulation capable of suppressing cortical excitability for up to 50 min. A growing number of studies have applied cTBS to the visual cortex in human subjects to investigate the neural dynamics of visual processing, but few have specifically examined its effects on central vision, which has crucial implications for safety and inference on downstream cognitive effects. The present study assessed the safety of offline, neuronavigated cTBS to V2 by examining its effects on central vision performance. In this single-blind, randomized sham-controlled, crossover study, 17 healthy adults received cTBS (at 80% active motor threshold) and sham to V2 1-2 weeks apart. Their central vision ([&le;]8{degrees}) was tested at 1-min (T1) and again at 50-min (T50) post-stimulation. Effects of condition (cTBS vs. sham) and time (T1 vs. T50) on accuracy and reaction time were examined using Bayes factor. Bayes factor results suggested that cTBS did not impair stimulus detection over the entire central visual field nor subfields at T1 or T50. Our results offer the first explicit evidence supporting that cTBS applied to V2 does not create blind spots in the central visual field in humans during a simple detection task. Any subtler changes to vision and downstream visual perception should be investigated in future studies. Raman Signal Denoising using Fully Convolutional Encoder Decoder Network Raman spectroscopy is a vibrational method that gives molecular information rapidly and non-invasively. Despite its advantages, the weak intensity of Raman spectroscopy leads to low-quality signals, particularly with tissue samples. The requirement of high exposure times makes Raman a time-consuming process and diminishes its non-invasive property while studying living tissues. Novel denoising techniques using convolutional neural networks (CNN) have achieved remarkable results in image processing. Here, we propose a similar approach for noise reduction for the Raman spectra acquired with 10x lower exposure times. In this work, we developed fully convolutional encoder-decoder architecture (FCED) and trained them with noisy Raman signals. The results demonstrate that our model is superior (p-value < 0.0001) to the conventional denoising techniques such as the Savitzky-Golay filter and wavelet denoising. Improvement in the signal-to-noise ratio values ranges from 20% to 80%, depending on the initial signal-to-noise ratio. Thus, we proved that tissue analysis could be done in a shorter time without any need for instrumental enhancement.