Trade-offs in biosensor optimization for dynamic pathway engineering Recent progress in synthetic biology allows the construction of dynamic control circuits for metabolic engineering. This technology promises to overcome many challenges encountered in traditional pathway engineering, thanks to their ability to self-regulate gene expression in response to bioreactor perturbations. The central components in these control circuits are metabolite biosensors that read out pathway signals and actuate enzyme expression. However, the construction of metabolite biosensors is a major bottleneck for strain design, and a key challenge is to understand the relation between biosensor dose-response curves and pathway performance. Here we employ multiobjective optimization to quantify performance trade-offs that arise in the design and calibration of metabolite biosensors. Our approach reveals strategies for tuning dose-response curves along an optimal trade-off between production flux and the cost of an increased expression burden on the host. We explore properties of control architectures built in the literature, and identify their advantages and caveats in terms of performance and robustness to growth conditions and leaky promoters. We demonstrate the optimality of a control circuit for glucaric acid production in Escherichia coli, which has been shown to increase titer by 2.5-fold as compared to static designs. Our results lay the groundwork for the automated design of control circuits for pathway engineering, with applications in the food, energy and pharmaceutical sectors.
Data-Driven Network Models for Genetic Circuits From Time-Series Data with Incomplete Measurements Synthetic gene networks are frequently conceptualized and visualized as static graphs. This view of biological programming stands in stark contrast to the transient nature of biomolecular interaction, which is frequently enacted by labile molecules that are often unmeasured. Thus, the network topology and dynamics of synthetic gene networks can be difficult to verify in vivo or in vitro, due to the presence of unmeasured biological states. Here we introduce the dynamical structure function as a new mesoscopic, data-driven class of models to describe gene networks with incomplete measurements. We introduce a network reconstruction algorithm and a code base for reconstructing the dynamical structure function from data, to enable discovery and visualization of graphical relationships in a genetic circuit diagram as time-dependent functions rather than static, unknown weights. We prove a theorem, showing that dynamical structure functions can provide a data-driven estimate of the size of crosstalk fluctuations from an idealized model. We illustrate this idea with numerical examples. Finally, we show how data-driven estimation of dynamical structure functions can explain failure modes in two experimentally implemented genetic circuits, a historical genetic circuit and a new E. coli based transcriptional event detector.
Genetic analysis of DinG-family helicase YoaA and its interaction with replication clamp-loader protein HolC in E. coli The XP-D/DinG family of DNA helicases contribute to genomic stability in all three domains of life. We investigate here the role of one of these proteins,YoaA, of Escherichia coli. In E. coli,YoaA aids tolerance to the nucleoside azidothymidine (AZT), a DNA replication inhibitor and physically interacts with a subunit of the DNA polymerase III holoenzyme, HolC. We map the residues of YoaA required for HolC interaction to its C-terminus by yeast two-hybrid analysis. We propose that this interaction competes with HolCs interaction with HolD and the rest of the replisome;YoaA indeed inhibits growth when overexpressed, dependent on this interaction region. By gene fusions we show YoaA is repressed by LexA and induced in response to DNA damage as part of the SOS response. Induction of YoaA by AZT is biphasic with an immediate response after treatment and a slower response that peaks in the late log phase of growth. This growth-phase dependent induction by AZT is not blocked by lexA3 (Ind-), which normally negates its self-cleavage, implying another means to induce the DNA damage response that responds to the nutritional state of the cell. We propose that YoaA helicase activity increases access to the 3 nascent strand during replication; consistent with this,YoaA appears to aid removal of potential A-to-T transversion mutations in ndk mutants, which are prone to nucleotide misincorporation. YoaA and its paralog DinG also may initiate template-switching that leads to deletions between tandem repeats in DNA.

IMPORTANCEMaintaining genomic stability is crucial for all living organisms. Replication of DNA frequently encounters barriers that must be removed to complete genome duplication. Balancing DNA synthesis with its repair is critical and not entirely understood at a mechanistic level.The YoaA protein, studied here, is required for certain types of DNA repair and interacts in an alternative manner with proteins that catalyze DNA replication. YoaA is part of the well-studied LexA-regulated response to DNA damage, the SOS response. We describe an unusual feature of its regulation that promotes induction after DNA damage as the culture begins to experience starvation. Replication fork repair integrates both DNA damage and nutritional signals. We also show that YoaA affects genomic stability. High school science fair: Experiences of two groups of undergraduate bioscience students Science fairs offer potential opportunities for students to learn first-hand about the practices of science. Over the past six years we have been carrying out voluntary and anonymous surveys with regional and national groups of high school and post high school students to learn about their high school science fair experiences regarding help received, obstacles encountered, and opinions about the value and impact of science fair. Understanding what students think about science fairs will help educators make science fairs more effective learning opportunities. In this paper, we focus on the findings with two national groups of post high school students - undergraduate research fellows (SURF students) who did research at UT Southwestern Medical Center during 2014-2019 and undergraduates biology students attending the 2019 Howard Hughes Medical Institute Science Education Alliance (SEA) summer symposium. About 25% of the students who completed surveys indicated that they had participated in high school science fair, but more than half attended high schools where science fairs were unavailable. Effectively, 6 out of every 10 students participated in science fair if available. Students who could have participated in high school science fair but chose not to do so identified not enough time and coming up with their project idea as major reasons why not. About half the SURF students favored requiring non-competitive science fair regardless whether they themselves had participated in science fair. On the other hand, less than 1 in 5 thought that competitive science fair should be required. Introduction to the scientific process and general learning were mentioned most frequently as the reasons to require non-competitive science fair; these reasons were mentioned rarely in connection with competitive science fair. Unlike the national cohort of high school students we surveyed previously, who mostly did science fair in 9th and 10th grades, SURF students participated in science fair throughout high school and were twice as likely as high school students to have carried out science fair more than once. In conclusion, our findings suggest that participation of the undergraduate bioscience majors in high school science fairs occurs far more frequently than recognized previously. The findings emphasize further the importance of incentivizing rather than requiring science fair participation, especially in 9th and 10th grades, and the potential value of developing non-competitive science fairs. Developing High-Affinity Decoy Receptor Optimized for Multiple Myeloma and Diffuse Large B Cell Lymphoma Treatment Recent T Cell therapies have been effective in the treatment of hematological cancers. However, immunotoxicity and treatment relapse pose significant clinical challenges. Here, we revealed distinctive requirement for neutralizing TNF receptor ligands APRIL and BAFF in MM and DLBCL. Furthermore, we investigated the use of BCMA decoy receptor (sBCMA-Fc) as a therapeutic inhibitor of ARPIL and BAFF. While wild-type sBCMA-Fc successfully blocked APRIL signaling with picomolar binding affinity, inhibiting tumor growth in MM models, it lacked efficacy in inhibiting DLBCL progression due to its weak binding for BAFF. To expand the therapeutic utility of sBCMA-Fc, using a protein engineering approach, we generated an affinity enhanced mutant sBCMA-Fc fusion molecule (sBCMA-Fc V3) with 4-folds and 500-folds enhancement in binding to APRIL and BAFF respectively. The sBCMA-Fc V3 clone significantly enhanced antitumor activity against both MM and DLBCL. Importantly, sBCMA-Fc V3 was proven to be a viable clinical candidate by showing adequate toxicity profile and on-target mechanism of action in nonhuman primates.

SUMMARYThis study demonstrates the dichotomous function of APRIL and BAFF in MM and DLBCL, that can be safely targeted by an engineered fusion protein designed to trap APRIL and BAFF with ultra-high binding affinity. 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. 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. Estimating the rate of plasmid transfer with an adapted Luria-Delbrück fluctuation analysis To increase our basic understanding of the ecology and evolution of conjugative plasmids, we need a reliable estimate of their rate of transfer between bacterial cells. However, accurate estimates of plasmid transfer have remained elusive due to biological and experimental complexity. Current methods to measure transfer rate can be confounded by many factors. A notable example involves plasmid transfer between different strains or species where the rate that one type of cell donates the plasmid is not equal to the rate at which the other cell type donates. Asymmetry in these rates has the potential to bias or constrain current transfer estimates, thereby limiting our capabilities for estimating transfer in microbial communities. Inspired by the classic fluctuation analysis of Luria and Delbruck, we develop a novel approach, the Luria-Delbruck method ( LDM), for estimating plasmid transfer rate. Our new approach embraces the stochasticity of conjugation departing from the current deterministic population dynamic methods. In addition, the LDM overcomes obstacles of traditional methods by not being affected by different growth and transfer rates for each population within the assay. Using stochastic simulations and experiments, we show that the LDM has high accuracy and precision for estimation of transfer rates compared to the most widely used methods, which can produce estimates that differ from the LDM estimate by orders of magnitude.

Significance StatementConjugative plasmids play significant roles in the ecology and evolution of microbial communities. Notably, antibiotic resistance genes are often encoded on conjugative plasmids. Thus, conjugation--the transfer of a plasmid copy from one cell to another--is a common way for antibiotic resistance to spread between important clinical pathogens. For both public health modeling and a basic understanding of microbial population biology, accurate estimates of this fundamental rate are of great consequence. We show that widely used methods can lead to biased estimates, deviating from true values by several orders of magnitude. Therefore, we developed a new approach, inspired by the classic fluctuation analysis of Luria and Delbruck, for accurately assessing the rate of plasmid conjugation under a variety of conditions. Epidural Electrical Stimulation of the Cervical Dorsal Roots Restores Voluntary Upper Limb Control In Paralyzed Monkeys Recovering arm control is a top priority for people with paralysis. Unfortunately, the complexity of the neural mechanisms underlying arm control practically limited the effectiveness of neurotechnology approaches. Here, we exploited the neural function of surviving spinal circuits to restore voluntary arm and hand control in three monkeys with spinal cord injury using spinal cord stimulation. Our neural interface leverages the functional organization of the dorsal roots to convey artificial excitation via electrical stimulation to relevant spinal segments at appropriate movement phases. Stimulation bursts targeting specific spinal segments produced sustained arm movements enabling monkeys with arm paralysis to perform an unconstrained reach-and-grasp task. Stimulation specifically improved strength, task performances and movement quality. Electrophysiology suggested that residual descending inputs were necessary to produce coordinated movements. The efficacy and reliability of our approach hold realistic promises of clinical translation. Elucidation of SARS-CoV-2 budding mechanisms through molecular dynamics simulations of M and E protein complexes SARS-CoV-2 and other coronaviruses pose major threats to global health, yet computational efforts to understand them have largely overlooked the process of budding, a key part of the coronavirus life cycle. When expressed together, coronavirus M and E proteins are sufficient to facilitate budding into the ER-Golgi intermediate compartment (ERGIC). To help elucidate budding, we ran atomistic molecular dynamics (MD) simulations using the Feig laboratorys refined structural models of the SARS-CoV-2 M protein dimer and E protein pentamer. Our MD simulations consisted of M protein dimers and E protein pentamers in patches of membrane. By examining where these proteins induced membrane curvature in silico, we obtained insights around how the budding process may occur. Multiple M protein dimers acted together to induce global membrane curvature through protein-lipid interactions while E protein pentamers kept the membrane planar. These results could eventually help guide development of antiviral therapeutics which inhibit coronavirus budding. Fungicide resistance characterised across seven modes of action in a Botrytis cinerea isolated from Australian vineyards BACKGROUNDBotrytis bunch rot, caused by Botrytis cinerea, is an economically important disease of grapes in Australia and across grape growing regions worldwide. Control of this disease relies on canopy management and the application of fungicides. Fungicide application can lead to the selection of resistant B. cinerea populations, which has an adverse effect on management of the disease. Characterising the distribution and severity of resistant B. cinerea populations is needed to inform resistance management strategies.

RESULTSIn this study, 725 isolates were sampled from 75 Australian vineyards during 2013 - 2016 and were screened against seven fungicides with different modes of action (MOAs). The resistance frequencies for azoxystrobin, boscalid, fenhexamid, fludioxonil, iprodione, pyrimethanil and tebuconazole were 5, 2.8, 2.1, 6.2, 11.6, 7.7 and 2.9% respectively. Nearly half of the resistant isolates (43.8%) were resistant to more than one of the fungicides tested. The frequency of vineyards with at least one isolate simultaneously resistant to 1, 2, 3, 4 or 5 fungicides was 19.5, 7.8, 6.5, 10.4 and 2.6%. Resistance was associated with previously published genotypes in CytB (G143A), SdhB (H272R/Y), Erg27 (F412S), Mrr1 (D354Y), Bos1 (I365S, N373S + Q369P, I365S + D757N) and Pos5 (V273I, P319A, L412F/V). Novel genotypes were also described in Mrr1 (S611N, D616G) Pos5 (V273L) and Cyp51 (P347S). Expression analysis was used to characterise fludioxonil resistant isolates exhibiting overexpression (6.3-9.6-fold) of the ABC transporter gene AtrB (MDR1 phenotype).

CONCLUSIONResistance frequencies were lower when compared to most previously published surveys of B. cinerea resistance in grape and other crops. Nevertheless, continued monitoring of critical MOAs used in Australian vineyards is recommended. A novel two-generation approach to the population dynamics of gregarious parasitoids Parasitoids, as important natural enemies, help maintain balance in natural ecosystems. Their population dynamics is generally predicted from the number of individuals. Here, using gregarious parasitoids as models, we show that this traditional approach omits one important parameter: the mothers manipulation of offspring fertility due to the clutch size-body size- fertility correlation. As a result of this correlation, when females deliberately adjust the number of offspring laid in a host, they determine not only the number but also the body sizes and reproductive potentials of those offspring. For the first time in the model species Anaphes flavipes, we determined the parasitoids offspring fertility from clutch size. Using this, we experimentally clarified the advantage of specific clutch size combinations and we show that identical fertility in the F1 generation can lead to distinctly different fertility values in the F2 generation. Even with the same number of hosts, lower fertility in the F1 generation can cause higher fertility in the F2 generation. Based on these results, we propose a novel two-generation approach which includes the clutch size-body size-fertility correlation. Our novel approach provides a new perspective for determining the individual fitness levels of gregarious parasitoids with new options for the modelling of parasitoid population dynamics. Full-likelihood analysis of genomic data clarifies a complex history of species divergence and introgression in the erato-sara group of Heliconius butterflies AO_SCPLOWBSTRACTC_SCPLOWIntrogressive hybridization plays a key role in adaptive evolution and species diversification in many groups of species. However, frequent hybridization and gene flow between species makes estimation of the species phylogeny and key population parameters challenging. Here, we show that by accounting for phasing and using full-likelihood analysis methods, introgression histories and population parameters can be estimated reliably from whole-genome sequence data. We employ full-likelihood methods under the multispecies coalescent (MSC) model with and without gene flow to analyze the genomic data from six members of the erato-sara clade of Heliconius butterflies and infer the species phylogeny and cross-species introgression events. The methods naturally accommodate random fluctuations in genealogical history across the genome due to deep coalescence. To avoid heterozygote phasing errors in haploid sequences commonly produced by genome assembly methods, we process and compile unphased diploid sequence alignments and use analytical methods to average over uncertainties in heterozygote phase resolution. There is robust evidence for introgression across the genome, both among distantly related species deep in the phylogeny and between sister species in shallow parts of the tree. We obtain chromosome-specific estimates of key population parameters such as introgression directions, times and probabilities, as well as species divergence times and population sizes for modern and ancestral species. We confirm ancestral gene flow between the sara clade and an ancestral population of H. telesiphe, a likely hybrid speciation origin for H. hecalesia, and gene flow between sister species H. erato and H. himera. Inferred introgression among ancestral species also explains the history of two chromosomal inversions deep in the phylogeny of the group. This study illustrates how a full-likelihood approach based on the multispecies coalescent makes it possible to extract rich historical information of species divergence and gene flow from genomic data. G2 stem cells orchestrate time-directed, long-range coordination of calcium signaling during skin epidermal regeneration Skin epidermal homeostasis is maintained via constant regeneration by stem cells, which must communicate to balance their self-renewal and differentiation. A key molecular pathway, Ca2+ signaling has been implicated as a signal integrator in developing and wounded epithelial tissues[1, 2, 3, 4]. Yet how stem cells carry out this signaling across a regenerative tissue remains unknown due to significant challenges in studying signaling dynamics in live mice, limiting our understanding of the mechanisms of stem cell communication during homeostasis. To interpret high dimensional signals that have complex spatial and temporal patterns, we combined optimized imaging of Ca2+ signaling in thousands of epidermal stem cells in living mice with a new machine learning tool, Geometric Scattering Trajectory Homology (GSTH). Using a combination of signal processing, data geometry, and topology, GSTH captures patterns of signaling at multiple scales, either between direct or distant stem cell neighbors. Here we show that epidermal stem cells display dynamic intercellular Ca2+ signaling among neighborhoods of up to 10 cells that is surprisingly coordinated and directed through time across a pool of thousands of stem cells. We find that this collective coordination is an emergent property of the stem cell compartment, distinct from excitatory quiescent neuronal tissues. We demonstrate that cycling stem cells, specifically G2 cells, govern homeostatic patterns of Ca2+ signaling. Stem cells in different cell cycle stages dynamically regulate localization of the gap junction component Connexin43 (Cx43). Lastly, we uncouple global from local communication and identify Cx43 as the molecular mediator necessary for connectivity between local signaling neighborhoods. This work provides resolution in how stem cells at different stages of the cell cycle communicate and how that diversity of phases is essential for tissue wide communication and signaling flow during epidermal regeneration. Our approach provides a framework to investigate stem cell populations and their signaling dynamics, previously not possible. Fatal neuroinvasion and SARS-CoV-2 tropism in K18-hACE2 mice is partially independent on hACE2 expression Animal models recapitulating distinctive features of severe COVID-19 are critical to enhance our understanding of SARS-CoV-2 pathogenesis. Transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) under the cytokeratin 18 promoter (K18-hACE2) represent a lethal model of SARS-CoV-2 infection. The precise mechanisms of lethality in this mouse model remain unclear. Here, we evaluated the spatiotemporal dynamics of SARS-CoV-2 infection for up to 14 days post-infection. Despite infection and moderate pneumonia, rapid clinical decline or death of mice was invariably associated with viral neuroinvasion and direct neuronal injury (including brain and spinal neurons). Neuroinvasion was observed as early as 4 dpi, with virus initially restricted to the olfactory bulb supporting axonal transport via the olfactory neuroepithelium as the earliest portal of entry. No evidence of viremia was detected suggesting neuroinvasion occurs independently of entry across the blood brain barrier. SARS-CoV-2 tropism was not restricted to ACE2-expressing cells (e.g., AT1 pneumocytes), and some ACE2-positive lineages were not associated with the presence of viral antigen (e.g., bronchiolar epithelium and brain capillaries). Detectable ACE2 expression was not observed in neurons, supporting overexpression of ACE2 in the nasal passages and neuroepithelium as more likely determinants of neuroinvasion in the K18-hACE2 model. Although our work incites caution in the utility of the K18-hACE2 model to study global aspects of SARS-CoV-2 pathogenesis, it underscores this model as a unique platform for exploring the mechanisms of SARS-CoV-2 neuropathogenesis that may have clinical relevance acknowledging the growing body of evidence that suggests COVID-19 may result in long-standing neurologic consequences.

IMPORTANCECOVID-19 is predominantly a respiratory disease caused by SARS-CoV-2 that has infected more than 191 million people with over 4 million fatalities (2021-07-20). The development of animal models recapitulating distinctive features of severe COVID-19 is critical to enhancing our understanding of SARS-CoV-2 pathogenesis and in the evaluation of vaccine and therapeutic efficacy. Transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) under the cytokeratin 18 promoter (K18-hACE2) represent a lethal model of SARS-CoV-2 infection. Here, we show lethality of this model is invariably associated with viral neuroinvasion linked with viral replication and assembly. Importantly, pneumonia albeit invariably present was generally moderate with the absence of culturable infectious virus at peak neuroinvasion. The dynamics of viral neuroinvasion and pneumonia were only partially dependent on hACE2. Overall, this study provides an in-depth sequential characterization of the K18-hACE2 model following SARS-CoV-2 infection, highlighting its significance to further study the mechanisms of SARS-CoV-2 neuropathogenesis. Reducing Movement Synchronization to Increase Interest Improves Interpersonal Liking Synchronization has been identified as a key aspect of achieving mutual goals and enhancing social bonding. While synchronization could be maximized by increasing the predictability of an interaction, such predictability is in tension with individuals level of interest, which is tied to the interactions complexity and novelty. In this study, we tested the interplay between synchronization and interest. We asked 104 female dyads to play the Mirror Game, in which they were instructed to move their hands as coordinately as possible, and then report how much they liked each other. Utilizing information theory and video processing tools, we found that a combination of movement synchronization and complexity explained liking almost two times better than movement synchronization alone. Moreover, we found that people initiated novel and challenging interactions, even though they paid a price - being less synchronized. Examining the interactions dynamics, we found that people who liked each other moved in a more synchronized, complex, and novel manner during most of the interaction. This suggests that in addition to synchronization, maintaining interest may be critical for positive social bonding. Thus, we propose a new framework in which balancing synchronization and interest, rather than merely maximizing synchronization, optimizes the interaction quality. Active enhancers strengthen insulation by RNA-mediated CTCF binding at TAD boundaries Vertebrate genomes are partitioned into Topologically Associating Domains (TADs), which are typically bound by head-to-head pairs of CTCF binding sites. Transcription at TAD boundaries correlates with better insulation, however, it is not known whether the boundary transcripts themselves contribute to boundary function. Here we characterize boundary-associated RNAs genome-wide, focusing on the disease-relevant INK4a/ARF TAD. Using CTCF site deletions and boundary-associated RNA knockdowns, we observe that boundary-associated RNAs facilitate recruitment and clustering of CTCF at TAD borders. The resulting CTCF enrichment enhances TAD insulation, enhancer:promoter interactions and TAD gene expression. Importantly, knockdown of boundary-associated RNAs results in loss of boundary insulation function. Using enhancer deletions and CRISPRi of promoters we show that active TAD enhancers but not promoters induce boundary-associated RNA transcription, thus defining a novel class of regulatory enhancer RNAs. plantR: An R package and workflow for managing species records from biological collections O_LISpecies records from biological collections are becoming increasingly available online. This unprecedented availability of records has largely supported recent studies in taxonomy, biogeography, macroecology, and biodiversity conservation. Biological collections vary in their documentation and notation standards, which have changed through time. For different reasons, neither collections nor data repositories perform the editing, formatting, and standardization of the data, leaving these tasks to the final users of the species records (e.g. taxonomists, ecologists and conservationists). These tasks are challenging, particularly when working with millions of records from hundreds of biological collections.
C_LIO_LITo help collection curators and final users perform those tasks, we introduce plantR, an open-source package that provides a comprehensive tool-box to manage species records from biological collections. The package is accompanied by the proposal of a reproducible workflow to manage this type of data in taxonomy, ecology, and biodiversity conservation. It is implemented in R and designed to handle relatively large data sets as fast as possible. Initially designed to handle plant species records, many of the plantR features also apply to other groups of organisms, given that the data structure is similar.
C_LIO_LIThe plantR workflow includes tools to (1) download records from different data repositories, (2) standardize typical fields associated with species records, (3) validate the locality, geographical coordinates, taxonomic nomenclature, and species identifications, including the retrieval of duplicates across collections, and (4) summarize and export records, including the construction of species checklists with vouchers.
C_LIO_LIOther R packages provide tools to tackle some of the workflow steps described above. But in addition to the new features and resources related to the data editing and validation, the greatest strength of plantR is to provide a comprehensive and user-friendly workflow in one single environment, performing all tasks from data retrieval to export. Thus, plantR can help researchers better assess data quality and avoid data leakage in a wide variety of studies using species records.
C_LI Proteomic phenotyping of stimulated Müller cells uncovers profound pro-inflammatory signaling and antigen-presenting capacity Muller cells are the main macroglial cells of the retina exerting a wealth of functions to maintain retinal homoeostasis. Upon pathological changes in the retina, they become gliotic with both protective and detrimental consequences. Accumulating data also provide evidence for a pivotal role of Muller cells in the pathogenesis of diabetic retinopathy (DR). While microglial cells, the resident immune cells of the retina are considered as main players in inflammatory processes associated with DR, the implication of activated Muller cells in chronic retinal inflammation remains to be elucidated. In order to assess the signaling capacity of Muller cells and their role in retinal inflammation, we performed in-depth proteomic analysis of Muller cell proteomes and secretomes after stimulation with INF{gamma}, TNF, IL-4, IL-6, IL-10, VEGF, TGF{beta}1, TGF{beta}2 and TGF{beta}3. We used both, primary porcine Muller cells and the human Muller cell line MIO-M1 for our hypothesis generating approach. Our results point towards an intense signaling capacity of Muller cells, which reacted in a highly discriminating manner upon treatment with different cytokines. Stimulation of Muller cells resulted in a primarily pro-inflammatory phenotype with secretion of cytokines and components of the complement system. Furthermore, we observed evidence for mitochondrial dysfunction, implying oxidative stress after treatment with the various cytokines. Finally, both MIO-M1 cells and primary porcine Muller cells showed several characteristics of atypical antigen-presenting cells, as they are capable of inducing MHC class I and MHC class II with co-stimulatory molecules. In line with this, they express proteins associated with formation and maturation of phagosomes. Thus, our findings underline the importance of Muller cell signaling in the inflamed retina, indicating an active role in chronic retinal inflammation underlying the pathogenesis of diabetic retinopathy. The SLIM1 transcription factor is required for arsenic resistance in Arabidopsis thaliana The transcriptional regulators of arsenic-induced gene expression remain largely unknown. Sulfur assimilation is tightly linked with arsenic detoxification. Here we report that mutant alleles in the SLIM1 transcription factor are substantially more sensitive to arsenic than cadmium. Arsenic treatment caused high levels of oxidative stress in the slim1 mutants, and slim1 alleles were impaired in both thiol and sulfate accumulation. We further found enhanced arsenic accumulation in roots of slim1 mutants. Transcriptome analyses indicate an important role for SLIM1 in arsenic-induced tolerance mechanisms. The present study identifies the SLIM1 transcription factor as an essential component in arsenic tolerance and arsenic-induced gene expression. Our results suggest that the severe arsenic sensitivity of the slim1 mutants is caused by altered redox status. Flexibility of Short-chain dehydrogenase is interconnected to its promiscuity for the reduction of multiple ketone intermediates Short-chain dehydrogenases/reductases (SDRs) are a convenient class of enzymes used to synthesize enantiopure alcohols. Several studies describe native or engineered SDRs for converting substrates of interest using cost and time-intensive high-throughput approaches. The classification of SDRs is based on chain length and cofactor binding site. Of these, the shorter  Classical and the longer  Extended enzymes participate in ketoreduction. However, comparative analysis of various modelled SDRs reveals a length independent conserved N-terminal Rossmann fold and a variable C-terminus region for both types. The general hypothesis is that the latter domain influences the enzymes flexibility that may affect the observed promiscuity of the enzyme. We have used a machine learning algorithm on this flexible domain to build a rationale to screen promiscuous candidates. We have built a data set consisting of physicochemical properties derived from the amino-acid composition of enzymes to select closely associated promiscuous mesophilic enzymes. The resulting in vitro studies on pro-pharmaceutical substrates illustrate a direct correlation between the C-terminal lid-loop structure, enzyme melting temperature and the turnover number. We present a walkthrough for exploring promiscuous SDRs for catalyzing enantiopure alcohols of industrial importance. Greater spear nosed bats in Panama do not use social proximity to improve foraging efficiency Group foraging animals may change their spatial relationships in response to the resource landscape. The strength of social network ties across foraging groups could then reflect the energy balance of individual group members through their effect on foraging efficiency. Greater spear-nosed bats (Phyllostomus hastatus) live in social groups where unrelated females develop group-specific social calls, defend each others offspring, and are hypothesized to coordinate social foraging to feed on balsa flowers. To test if social groups forage together, and if this increases foraging efficiency, we tracked 18 individuals from three social groups of P. hastatus on Isla Colon, Panama using high frequency GPS for 1 - 3 days each. We found that individuals commuted alone but then joined group members in small foraging patches with high densities of flowering balsas, 25 km from their roost on the mainland. Proximity-based social network measures did not predict foraging efficiency or energy expenditure, but individuals with higher social associations spent more time outside of the cave. Individuals did not coordinate movement, but close proximity among individuals increased resting bout duration and synchrony, particularly when in the same patch. These results show that stronger social proximity associations were more closely tied to resting behavior, and indicate that factors other than increased feeding efficiency may structure network relationships of group members while foraging.

Lay SummarySocial foraging can increase foraging efficiency on hard-to-find food sources. Miniaturized high-frequency GPS allowed us to test this on groups of greater spear-nosed bats. We estimated food intake rates, energy expenditure, and the strength of bat social relationships. In contrast to our expectations, we did not find a relationship between bat social relationships and energy expenditure or foraging efficiency. However, bats took longer resting breaks when group members were close. Why these bats commute 25 km individually across the ocean to then forage near each other thus requires further investigation. Pathways of savannization in a mesic African savanna-forest mosaic following an extreme fire O_LIFires in savannas limit tree cover, thereby promoting flammable grass accumulation and fuelling further frequent fires. Meanwhile, forests and thickets form dense canopies that reduce C4-grass fuel loads and creating a humid microclimate, thereby excluding fires under typical climatic conditions.
C_LIO_LIHowever, extreme fires occasionally burn into these closed-canopy systems. Although these rare fires cause substantial tree mortality and can make repeat fires more likely, the long-term consequences of an extreme fire for closed canopy vegetation structure and potential to convert to savanna (hereafter "savannization") remain largely unknown.
C_LIO_LIHere, we analysed whether an extreme fire could, alone, alter species composition, vegetation structure, and fire regimes of closed-canopy ecosystems in an intact savanna-forest-thicket mosaic, or whether successive fires after an initial extreme fire were necessary to trigger a biome transition between from forest to savanna.
C_LIO_LIWe found that forests that only burned once recovered, whereas those that burned again following an initial extreme fire transitioned from closed-canopy forests towards open, grassy savannas.
C_LIO_LIWhile thickets had less tree mortality in fires than forests, repeat fires nonetheless precipitated a transition towards savannas.
C_LIO_LIColonization of the savanna tree community lagged behind the grass community, but also began to transition.
C_LI

SynthesisOur results suggest that rare extreme fires, followed by repeated burning can indeed result in savannization in places where savanna and forest represent alternative stable states. Cellular feedback to organotelluranes displays modulation of antioxidant proteins gene expression Organotelluranes RT3 and RT4 are thiol reagents that induce mitochondrial transition pore (MTP) opening in a sensitive and insensitive manner to cyclosporin A. Although RT3 and RT4 promote glutathione depletion, paradoxically, they are also an efficient antioxidant for membrane lipids. These compounds antagonistic effects elicited the challenging question of how the gene expression of antioxidant enzymes would respond to treatment with these compounds. The influence of RT3 and RT4 on antioxidant enzyme expression was investigated in cultured aortic smooth muscle cells (ASMC). RT3 and RT4 promoted disruption of ionic calcium homeostasis, mitochondrial transmembrane potential ({Delta}{Psi}), and cell death in a dose-dependent manner. The cell death mechanisms responded qualitatively to the increase of the organotellurane concentration and changed from apoptosis to necrosis. RT3 and RT4 increased the expression of thioredoxin significantly. RT3 also increased the expression of glutaredoxin and glutathione peroxidase, slightly the catalase expression without significant effects on SOD expression. The results are consistent with GSH and protein thiol depletion and discussed based on the cell toxicity mechanism exhibited by these compounds.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/425411v4_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@52bb82org.highwire.dtl.DTLVardef@19476d9org.highwire.dtl.DTLVardef@6aa99org.highwire.dtl.DTLVardef@1aa605e_HPS_FORMAT_FIGEXP  M_FIG C_FIG E156G and Arg158, Phe-157/del mutation in NTD of spike protein in B.1.617.2 lineage of SARS-CoV-2 leads to immune evasion through antibody escape Emerging variants of SARS-CoV-2 with better immune escape mechanisms and higher transmissibility remains a persistent threat across the globe. B.1.617.2 (Delta) variant was first emerged from Maharashtra, India in December, 2020. This variant is classified to be a major cause and concern of the second wave of COVID-19 in India. In the present study, we explored the genomic and structural basis of this variant through computational analysis, protein modelling and molecular dynamics (MD) simulations approach. B.1.617.2 variant carried E156G and Arg158, Phe-157/del mutations in NTD of spike protein. These mutations in N-terminal domain (NTD) of spike protein of B.1.617.2 variant revealed more rigidity and reduced flexibility compared to spike protein of Wuhan isolate. Further, docking and MD simulation study with 4A8 monoclonal antibody which was reported to bind NTD of spike protein suggested reduced binding of B.1.617.2 spike protein compared to that of spike protein of Wuhan isolate. The results of the present study demonstrate the possible case of immune escape and thereby fitness advantage of the new variant and further warrants demonstration through experimental evidence. Our study identified the probable mechanism through which B.1.617.2 variant is more pathogenically evolved with higher transmissibility as compared to the wild-type.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC="FIGDIR/small/447321v3_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@b92cborg.highwire.dtl.DTLVardef@1d261f7org.highwire.dtl.DTLVardef@11da73eorg.highwire.dtl.DTLVardef@1cef6ca_HPS_FORMAT_FIGEXP  M_FIG C_FIG FGF8-mediated signaling regulates tooth developmental pace during odontogenesis The developing human and mouse teeth constitute an ideal model system to study the regulatory mechanism underlying organ growth control due to the fact that their teeth share highly conserved and well-characterized developmental processes and their developmental tempo vary notably. In the current study, we manipulated heterogenous recombination between human and mouse dental tissues and demonstrate that the dental mesenchyme dominates the tooth developmental tempo and FGF8 could be a critical player during this developmental process. Forced activation of FGF8 signaling in the dental mesenchyme of mice promoted cell proliferation, prevented cell apoptosis via p38 and perhaps PI3K-Akt intracellular signaling, and impelled the transition of the cell cycle from G1- to S-phase in the tooth germ, resulting in the slowdown of the tooth developmental pace. Our results provide compelling evidence that extrinsic signals can profoundly affect tooth developmental tempo and the dental mesenchymal FGF8 could be a pivotal factor in controlling developmental pace in a non-cell-autonomous manner during mammalian odontogenesis.