Phenotypic Heterogeneity Facilitates Survival While Hindering the Evolution of Drug Resistance Due to Intraspecific Competition Rising rates of resistance to antimicrobial drugs threatens the effective treatment of infections across the globe. Drug resistance has been established to emerge from non-genetic mechanisms, such as "persistence" in quiescent microbes and fluctuations in gene expression in actively replicating cells, as well as from genetic mutations. However, it is still unclear how non-genetic drug resistance affects the evolution of genetic drug resistance. We develop deterministic and stochastic population models that incorporate resource competition to quantitatively investigate the transition from non-genetic to genetic resistance during the exposure to static and cidal drugs. We find that non-genetic resistance facilitates the survival of cell populations during drug treatment, but that it hinders the development of genetic resistance due to the competition between the non-genetically and genetically resistant subpopulations. Non-genetic drug resistance in the presence of subpopulation competition is found to increase the first-appearance and fixation times of drug resistance mutations, while increasing the probability of mutation before population extinction during cidal drug treatment. Intense intraspecific competition during drug treatment leads to extinction of the susceptible and non-genetically resistant subpopulations. These findings advance our fundamental understanding of the evolution of drug resistance and may guide novel treatment strategies for patients with drug-resistant infections.

SIGNIFICANCEDrug resistance is predicted to kill as many as 10 million people per year and cost over 100 trillion USD in cumulative lost production globally by 2050. To mitigate these socio-economic costs, we need to fundamentally understand the drug resistance process. We investigate the effect that different forms of resistance have on the evolution of drug resistance using mathematical modeling and computer simulations. We find that the presence of non-genetically drug-resistant cells (whose resistance is temporary and not encoded in a genetic mutation) allows the population to survive drug treatment, while competition between these subpopoulations simultaneously slows down the evolution of permanent genetic drug resistance and in some cases drives them extinct. These findings have important implications for advancing evolutionary theory and for developing effective "resistance-proof" treatments.
Ion Permeation, Selectivity, and Electronic Polarization in Fluoride Channels Fluoride channels (Fluc) export toxic F- from the cytoplasm. Crystallography and mutagenesis have identified several conserved residues crucial for fluoride transport, but the permeation mechanism at the molecular level has remained elusive. Herein we have applied constant-pH molecular dynamics and free energy sampling methods to investigate fluoride permeation through a Fluc protein from Escherichia coli. We find that fluoride is facile to permeate in its charged form, i.e., F-, by traversing through a non-bonded network. The extraordinary F- selectivity is gained by the hydrogen-bonding capability of the central binding site and the Coulombic filter at the channel entrance. The F- permeation rate calculated using an electronically polarizable force field is significantly more accurate compared to the experimental value than that calculated using a more standard additive force field, suggesting an essential role for electronic polarization in the F- - Fluc interactions.

O_TEXTBOXSIGNIFICANCE

A comprehensive atomistic-level computational study is presented of the mechanism of fluoride permeation through fluoride channels. The mechanism of fluoride permeation of the F- anion is established and the microscopic determinants of F- selectivity revealed. The essential nature of electronic polarization during F- permeation is also demonstrated through the computational modeling.

C_TEXTBOX
An IPI based immune prognostic model for diffuse large B-cell lymphoma BackgroundInternational Prognostic Index (IPI) was widely used to better discriminate prognosis of patients with diffuse large B-cell lymphoma (DLBCL). However, there is a significant need to identify novel valuable biomarkers in the context of targeted therapies, such as immune checkpoint blockade (ICB) therapy.

MethodsGene expression data and clinical information of DLBCL were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. 371 immune-related hub genes in DLBCL patients with different IPI levels were identified by weighted gene co-expression network analysis (WGCNA), and 8 genes were selected to construct an IPI-based immune prognostic model (IPI-IPM). Afterward, the genetic, somatic mutational and molecular profiles of IPI-IPM subgroups were analyzed, as well as the potential clinical response of ICB in different IPI-IPM subgroups.

ResultsThe IPI-IPM was constructed based on the expression of CMBL, TLCD3B, SYNDIG1, ESM1, EPHA3, HUNK, PTX3 and IL12A, where high-risk patients had shorter overall survival (OS) than low-risk patients, consistent with the results in the GEO cohorts. The comprehensive results showed that high IPI-IPM risk scores were correlated with immune-related signaling pathways, high KMT2D and CD79B mutation rates, as well as up-regulation of inhibitory immune checkpoints including PD-L1, BTLA and SIGLEC7, indicating more potential response to ICB therapy.

ConclusionThe IPI-IPM has independent prognostic significance for DLBCL patients, which provides an immunological perspective to elucidate the mechanisms on tumor progression, also sheds a light on developing immunotherapy for DLBCL. Failure to account for behavioral variability significantly compromises accuracy in indirect population monitoring Indirect wildlife population surveying largely depends upon counts of artefacts of behavior (e.g., nests or dung). Likelihood to encounter these artefacts is derived from both artefact production and decay, and variability in artefact production behavior is considered to contribute minimally to inaccuracy in wildlife estimation. Here we demonstrate how ignoring behavioral variability contributes to significant population misestimation, using an example of an endangered ape, the bonobo (Pan paniscus). Until now, a single estimate of (i.e., nest construction) has been used to extrapolate bonobo densities, assumed to be broadly representative of bonobo sign production behavior. We estimated nest construction rate across seasons and social groups at the Kokolopori Bonobo Reserve, DRC and find that nest construction rates in bonobos to be highly variable across populations as well as seasonal. Failure to account for this variability led to potentially severe degradation in accuracy of bonobo population estimates of abundance, accounting for a likely overestimation of bonobo numbers by 34%, and at worst as high as 80%. With this example, we demonstrate that failure to account for inter- and intra-population behavioral variation compromises the ability to estimate both relative and absolute wildlife abundances. We argue that variation in sign production is but one of several potential ways that behavioral variability can affect conservation monitoring, should be measured across contexts whenever possible, and must be considered in population estimation confidence intervals. With increasing attention to behavioral variability as a potential tool for conservation, conservationists must also account for the impact that behavioral variability can play upon wildlife population estimation. Our results underline the importance of observational research to wildlife monitoring schemes as a critical but overlooked component of conservation management. We extensively discuss the various avenues through which behavioral variability is likely to impact wildlife monitoring accuracy and precision and propose potential avenues for accounting for behavioral variability in wildlife monitoring. Effects of substrate on shrimp growth, water quality and bacterial community in the biofloc system nursing Penaeus vannamei postlarvae This study aimed to investigate the effects of substrate on water quality, shrimp growth and bacterial community in the biofloc system with a salinity of 5{per thousand}. Two treatments, biofloc system with (sB) or without (nB) addition of elastic solid packing filler (nylon) as substrate, were set up. Penaeus vannamei postlarvae (PL, [~] stage 15) were stocked at a density of 4000 PL m-3 in each treatment with triplicates for a 28-days culture experiment, taking glucose as carbon source (C:N 15:1). Results showed that the survival rate (96.3{+/-}3.6%), FCR (0.76{+/-}0.06) and productivity (1.54{+/-}0.12 kg m-3) in sB treatment were significantly better than those in nB treatment (81.0{+/-}7.1%, 0.98{+/-}0.08 and 1.14{+/-}0.09 kg m-3, P<0.05). All water parameters were in the recommended ranges. Substrate showed significant effect on TAN, TSS, turbidity, biofloc volume, pH and carbonate alkalinity (P < 0.05). Actinobacteria (4.0-22.7%), Bacteroidetes (10.4-33.5%), Firmicutes (0.2-11.2%), Planctomycetes (4.0-14.9%) and Proteobacteria (29.4-59.0%) were the most dominant phyla for both treatments. However, the bacterial community in sB treatment showed to be significantly different from that in nB treatment (Jaccard distance 0.94{+/-}0.01, P=0.001). Substrate showed significant effects on Shannon, Heip, Pielou and Simpson index, as well as relative abundances of Actinobacteria, Bacteroidetes and Planctomycetes (P < 0.05). The results suggested that addition of substrate affected the shrimp growth, water quality and bacterial community in the biofloc system nursing P. vannamei PL with a 5{per thousand} salinity. An energy-dissipative state of the major antenna complex of plants Plants and algae are faced with a conundrum: harvesting sufficient light to drive their metabolic needs while dissipating light in excess to prevent photodamage, a process known as non-photochemical quenching. A slowly relaxing form of energy dissipation, termed qH, is critical for plants survival under abiotic stress. Here, we tested whether we could isolate photosynthetic subcomplexes (from plants in which qH was induced) that would remain in an energy-dissipative state. Interestingly chlorophyll fluorescence lifetimes were decreased by qH in isolated major trimeric antenna complexes, providing a natively quenched complex with physiological relevance to natural conditions. Next, we monitored the changes in thylakoid pigment, protein or lipid content of antenna with active or inactive qH, and no evident differences were detected. Finally, we investigated whether specific antenna subunits of the major antenna were required for qH but found it insensitive to trimer composition. Because qH can occur in the absence of specific xanthophylls, and no changes in pigments were detected, we propose that the energy-dissipative state reported here may stem from chlorophyll-chlorophyll excitonic interaction. Cycles of transcription and local translation support molecular long-term memory in the hippocampus Long-term memory requires transcription and translation of activity-regulated genes. Many of these are immediate early genes (IEGs) with short-lived mRNAs and proteins, decaying rapidly after stimulation. It remains unknown how an IEG with rapid mRNA and protein turnover can impact long-lasting changes at the synapses. Using fluorescently tagged endogenous Arc, an IEG important for memory consolidation, we performed high-resolution imaging of transcription and translation in individual neurons to identify the long-term gene dynamics after stimulation. Unexpectedly, once induced, Arc underwent transcriptional reactivation often at the same allele. Cycles of transcription were coordinated with localized translation. This cyclical regulation of an IEG, dependent on protein synthesis, reactivates subsequent transcription for maintaining mRNA supply to dendrites. The ensuing Arc mRNAs were preferentially localized at sites marked by previous Arc protein, thereby consolidating local "hubs" of dendritic Arc. These findings revealed the spatio-temporal dynamics of transcription-translation coupling of an IEG and provide a mechanism by which short-lived synaptic proteins can be sustained over the long-time scales of memory consolidation. The mechanism of full activation of tumor suppressor PTEN at the phosphoinositide-enriched membrane Tumor suppressor PTEN, the second most highly mutated protein in cancer, dephosphorylates signaling lipid PIP3 produced by PI3Ks. Excess PIP3 promotes cell proliferation. The mechanism at the membrane of this pivotal phosphatase is unknown hindering drug discovery. Exploiting explicit solvent simulations, we tracked full-length PTEN trafficking from the cytosol to the membrane. We observed its interaction with membranes composed of zwitterionic phosphatidylcholine, anionic phosphatidylserine, and phosphoinositides, including signaling lipids PIP2 and PIP3. We tracked its moving away from the zwitterionic and getting absorbed onto anionic membrane that harbors PIP3. We followed it localizing on microdomains enriched in signaling lipids, as PI3K does, and observed PIP3 allosterically unfolding the N-terminal PIP2 binding domain, positioning it favorably for the polybasic motif interaction with PIP2. Finally, we determined PTEN catalytic action at the membrane, all in line with experimental observations, deciphering the mechanisms of how PTEN anchors to the membrane and restrains cancer. Limited selection towards lighter seeds in Danish grasslands over an eight-year period Time-series analysis of cover data from 236 Danish grassland sites demonstrated community selection on seed mass. Across four grassland habitat types and during an eight-year period there was significant community selection towards lighter seeds. In the analysis, the continuous seed size variable was used to group plant species into functional types. This method was chosen in order to account for the sampling process of the abundance data, and is in contrast to most other analyses of trait selection, where the community weighted mean of the traits is used as the dependent variable. Generally, little is known on the underlying causes of possible plant trait community selection in semi-natural grasslands that are not subjected to successional processes. A new method for the sampling and preservation of placental specimens in low-resource settings for the identification of P. falciparum and analysis of nucleic acids Collection, preservation, and shipment of histological specimens in low-resource settings is challenging. We present a novel method that achieved excellent preservation of placental specimens from rural Mali by using formalin fixation, ethanol dehydration, and long-term storage in a solar-powered freezer. Sample preservation success was 92%, permitting evaluation of current and past malaria infection, anemia, placental maturity, and inflammation. Using RNAscope(R) hybridization we were able to visualize cell-specific gene expression patterns in the formalin-fixed paraffin-embedded (FFPE) specimens. Additionally, our method entailed mirrored sampling from the two cut faces of a cotyledon, one for the FFPE workflows and the other for storage in RNAlater and RNA-seq. Impact of glycosylation on a broad-spectrum vaccine against SARS-CoV-2 A major challenge to end the pandemic caused by SARS-CoV-2 is to develop a broadly protective vaccine. As the key immunogen, the spike protein is frequently mutated with conserved epitopes shielded by glycans. Here, we reveal that spike glycosylation has site-differential effects on viral infectivity and lung epithelial cells generate spike with more infective glycoforms. Compared to the fully glycosylated spike, immunization of spike protein with N-glycans trimmed to the monoglycosylated state (Smg) elicits stronger immune responses and better protection for hACE2 transgenic mice against variants of concern. In addition, a broadly neutralizing monoclonal antibody was identified from the Smg immunized mice, demonstrating that removal of glycan shields to better expose the conserved sequences is an effective and simple approach to broad-spectrum vaccine development.

One-Sentence SummaryRemoving glycan shields to expose conserved epitopes is an effective approach to develop a broad-spectrum SARS-CoV-2 vaccine. Understanding the Spin Crossover Dynamical Effects of the Dioxygen Binding and Activation on HOD Enzyme For the cofactor-free 1-H-3-hydroxy-4-oxoquinaldine-2,4-dioxygenase (HOD), the dioxygen (O2) dependent steps are rate-limiting along with a spin state crossover to the singlet spin state. Here, the primary triplet O2 molecule activation on the 2-methyl-3-hydroxy-4(1H)-quinolone (MHQ) is investigated, and the catalytic role of the intersystem crossing effects is highlighted by directly comparing results from the Born-Oppenheimer dynamics and non-adiabatic surface hopping dynamics. This work confirms non-adiabatic dynamical effects are essential to modulate the O2 activation on the substrate MHQ. The time scale of the equilibration and conversion from triplet to singlet state should be in the range of a few hundreds of femtoseconds. We hope this work provides us a fresh look at the underlying physics of dioxygen activation reactions involving more than one spin state. The IRE1/XBP1 signaling axis promotes skeletal muscle regeneration through a cell non-autonomous mechanism Skeletal muscle regeneration is regulated by coordinated activation of multiple signaling pathways activated in both injured myofibers and satellite cells. The unfolded protein response (UPR) is a major mechanism that detects and alleviates protein-folding stresses in ER. However, the role of individual arms of the UPR in skeletal muscle regeneration remains less understood. In the present study, we demonstrate that IRE1 (also known as ERN1) and its downstream target, XBP1, are activated in skeletal muscle of mice upon injury. Myofiber-specific ablation of IRE1 or XBP1 in mice diminishes skeletal muscle regeneration that is accompanied with reduced number of satellite cells and their fusion to injured myofibers. Ex vivo cultures of myofiber explants demonstrate that ablation of IRE1 reduces the proliferative capacity of myofiber- associated satellite cells. Myofiber-specific deletion of IRE1 dampens Notch signaling and canonical NF-{kappa}B pathway in skeletal muscle of mice. Our results also demonstrate that targeted ablation of IRE1 reduces skeletal muscle regeneration in the mdx mice, a model of Duchenne muscular dystrophy. Collectively, our results reveal that the IRE1-mediated signaling promotes muscle regeneration through augmenting the proliferation of satellite cells in a cell non- autonomous manner. HYBRID REACTION-DIFFUSION AND CLOCK-AND-WAVEFRONT MODEL FOR THE ARREST OF OSCILLATIONS IN THE SOMITOGENESIS SEGMENTATION CLOCK AO_SCPLOWBSTRACTC_SCPLOWThe clock and wavefront paradigm is arguably the most widely accepted model for explaining the embryonic process of somitogenesis. According to this model, somitogenesis is based upon the interaction between a genetic oscillator, known as segmentation clock, and a differentiation wavefront, which provides the positional information indicating where each pair of somites is formed. Shortly after the clock and wavefront paradigm was introduced, Meinhardt presented a conceptually different mathematical model for morphogenesis in general, and somitogenesis in particular. Recently, Cotterell et al. rediscovered an equivalent model by systematically enumerating and studying small networks performing segmentation. Cotterell et al. called it a progressive oscillatory reaction-diffusion (PORD) model. In the Meinhardt-PORD model, somitogenesis is driven by short-range interactions and the posterior movement of the front is a local, emergent phenomenon, which is not controlled by global positional information. With this model, it is possible to explain some experimental observations that are incompatible with the clock and wavefront model. However the Meinhardt-PORD model has some important disadvantages of its own. Namely, it is quite sensitive to fluctuations and depends on very specific initial conditions (which are not biologically realistic). In this work, we propose an equivalent Meinhardt-PORD model, and then amend it to couple it with a wavefront consisting of a receding morphogen gradient. By doing so, we get a hybrid model between the Meinhardt-PORD and the clock-and-wavefront ones, which overcomes most of the deficiencies of the two originating models.

Somitogenesis, the process by which somites are formed, is an essential developmental stage in many vertebrates. This process occurs with a strikingly regular periodicity, that is preserved among embryos of a single species. The clock and wavefront paradigm is arguably the most widely accepted model for explaining somitogenesis. However, it is incapable of explaining some experimental facts, like the appearance of somites in the absence of an external wavefront (i.e. a receding morphogen gradient). Shortly after the clock and wavefront paradigm was introduced, Meinhardt presented a conceptually different mathematical model for morphogenesis in general, and somitogenesis in particular. Recently, Cotterell et al. rediscovered an equivalent model by systematically enumerating and studying small networks performing segmentation, and called it a progressive oscillatory reaction-diffusion (PORD) model. The Meinhardt-PORD model tackles some of the deficiencies of the clock and wave-front models, but it has some serious issues of its own. In the present work, we introduce an equivalent Meinhardt-PORD model, and then amend it to couple it with a receding morphogen gradient. By doing so, we get a hybrid model that incorporates characteristics of the Meinhardt-PORD and clock-and-wavefront models. We show that this hybrid model under-goes a bifurcation, from a stable to an unstable limit cycle, as the value of the parameter accounting for a background regulatory input (associated to the receding morphogen gradient) decreases. This bifurcation allows the model to explain why somites can form in the absence of an external wavefront, reassesses the role of the receding morphogen gradient as a conductor for somitogenesis, and makes the model behavior robust to random fluctuations, as well as independent from specific initial conditions (the latter, are two of the weak points of the Meinhardt-PORD model). We argue that this findings provide convincing evidence that reaction-diffusion and positional information (receding morphogen gradient) mechanisms could work together in somitogenesis. The origins and drivers of Neotropical diversity The origins and evolution of the outstanding Neotropical biodiversity are still debated. A comprehensive understanding is hindered by the lack of deep-time comparative data across wide phylogenetic and ecological contexts. Here, we evaluate four evolutionary scenarios assuming different diversification trajectories and drivers of Neotropical diversification, and assess their variation across Neotropical regions and taxa. Our analysis of 150 phylogenies (12,512 species) of seed plants and tetrapods reveals that Neotropical diversity has mostly expanded through time (70% of the clades), while scenarios of saturated and declining diversity also account for 21% and 9% of Neotropical diversity, respectively. We identify five biogeographic areas that represent distinctive units of long-term Neotropical evolution (Pan-Amazonia, Dry Diagonal, Bahama-Antilles, Galapagos, and an  elsewhere region) and find that diversity dynamics do not differ across these areas, suggesting no geographic structure in long-term Neotropical diversification. In contrast, diversification dynamics differ substantially across taxa: plant diversity mostly expanded through time (88%), while a substantial fraction (43%) of tetrapod diversity accumulated at a slower pace or declined toward the present. These opposite evolutionary patterns may reflect different capacities for plants and tetrapods to cope with climate change, with potential implications for future adaptation and ecosystem resilience. spatialGE: Quantification and visualization of the tumor microenvironment heterogeneity using spatial transcriptomics SummarySpatially-resolved transcriptomics promises to increase our understanding of the tumor microenvironment and improve cancer prognosis and therapies. Nonetheless, analytical methods to explore associations between the spatial heterogeneity of the tumor and clinical data are not available. Hence, we have developed spatialGE, a software that provides visualizations and quantification of the tumor microenvironment heterogeneity through gene expression surfaces, spatial heterogeneity statistics (SThet) that can be compared against clinical information, spot-level cell deconvolution, and spatially-informed clustering (STclust), all using a new data object to store data and resulting analyses simultaneously.

Availability and implementationThe R package and tutorial/vignette are available at https://github.com/FridleyLab/spatialGE. A script to reproduce the analyses in this manuscript is available in Supplementary information.

ContactFridley.Lab@Moffitt.org or Brooke.Fridley@Moffitt.org

Supplementary informationAvailable at Bioinformatics online.



O_FIG O_LINKSMALLFIG WIDTH=198 HEIGHT=200 SRC="FIGDIR/small/454023v2_figG1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@191cbe7org.highwire.dtl.DTLVardef@e1b6c7org.highwire.dtl.DTLVardef@a6f68forg.highwire.dtl.DTLVardef@1853601_HPS_FORMAT_FIGEXP  M_FIG O_FLOATNOGraphical abstractC_FLOATNO Overview of spatialGE features. A. The STList data object from spatialGE can be creared from several sources, including comma- or tab-separated files containing gene counts and spatial coordinates. The object can also be created directly from Visium outputs, Seurat objects, or GeoMx outputs. B. Users can optionally provide a metadata file, containing information associated with each sample (one row per sample, or per ROI if GeoMx data). C. Methods for quality control of data are provided by spatialGE, including visualizations of counts and genes per spot, as well as filtering of spots or genes within user-determined thresholds. D. A novel method (STclust) performs spatially informed clustering of spots and tissue domain identification. E. spatialGE provides different types of data visualization, including gene expression at each spot ("quilt plots"), as well as adaptation of spatial interpolation ("kriging") to spatial transcriptomics data (transcriptomic surface). F. spatialGE also leverages spatial statistics (Morans I, Gearys C, Getis-Ord Gi) to quantitatively describe heterogeneity within the tumor microenvironment and to explore associations between spatial heterogeneity and clinical oucomes. G. Gene expression deconvolution can also be applied to each spot to detect immune cell types (xCell) and classification of spots as tumor or stroma (ESTIMATE).

C_FIG 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. 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. Balancing sensitivity and specificity in preclinical research The success of scientific discovery in preclinical drug development is based on the different roles of exploration and confirmation. Exploration requires sensitivity while confirmation needs to be specific. Based on published empirical data, we simulated two preclinical research trajectories to examine their effectiveness to detect true effects while keeping animal numbers low. We compare a conventional p-value based approach with a method based on an a priori determined smallest effect size of interest (SESOI). Using a SESOI increases transition rates from exploration to confirmation and results in higher detection rates across the trajectory. Specificity in the SESOI trajectory increases if the prior probability of true effects is low. We conclude that employing a SESOI is superior to a p-value based approach. Based on our findings, we propose a reconsideration of planning and conducting preclinical experiments, especially when the prior probability of true hypotheses is low. Define protein variant functions with high-complexity mutagenesis libraries and enhanced mutation detection software ASMv1.0 Open reading frame (ORF) variant libraries have advanced our ability to query the functions of a large number of variants of a protein simultaneously in a single experiment. Variant libraries targeting full-length ORFs typically consists of all possible single-amino-acid substitutions and a stop codon at each amino-acid position. Because a variant differs from the template ORF by a single codon variation, variant quantification presents the most profound challenge to this technology. Efforts such as dividing a library into sub-libraries for direct sequencing, or tag-directed subassembly are practical only for small ORFs. Our approach, however, features an enhanced variant-calling tool that processes massive shotgun sequencing data, allowing one to screen a single variant library for ORFs sized up to [~]3600 bases. The variant-calling tool detects variants reliably, and also presents variant annotations in datafiles enabling analyses that have reshaped our strategies governing library design, screen deconvolution, sequencing and sequencing data analysis. New Segmentation and Feature Extraction Algorithm for Classification of White Blood Cells in Peripheral Smear Images This article addresses a new method for the classification of white blood cells (WBCs) using image processing techniques and machine learning methods. The proposed method consists of three steps: detecting the nucleus and cytoplasm, extracting features, and classification. At first, a new algorithm is designed to segment the nucleus. For the cytoplasm to be detected, only a part of it located inside the convex hull of the nucleus is involved in the process. This attitude helps us overcome the difficulties of segmenting the cytoplasm. In the second phase, three shapes and four novel color features are devised and extracted. Finally, by using an SVM model, the WBCs are classified. The segmentation algorithm can detect the nucleus with a dice similarity coefficient of 0.9675. The proposed method can categorize WBCs in Raabin-WBC, LISC, and BCCD datasets with accuracies of 94.65 %, 92.21 %, and 94.20 %, respectively. It is worth mentioning that the hyperparameters of the classifier are fixed only with the Raabin-WBC dataset, and these parameters are not readjusted for LISC and BCCD datasets. The obtained results demonstrate that the proposed method is robust, fast, and accurate. 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. Lymph node swelling combined with temporary effector T cell retention aids T cell response in a model of adaptive immunity Swelling of lymph nodes is commonly observed during the adaptive immune response, yet the impact on T cell trafficking and subsequent immune response is not well known. To better understand the effect of macro-scale alterations, we developed an agent-based model of the lymph node para-cortex, describing T cell trafficking and response to antigen-presenting dendritic cells alongside swelling-induced changes in T cell recruitment and egress, and regulation of expression of egress-modulating T cell receptor Sphingosine-1-phosphate receptor-1. Analysis of effector T cell response under varying swelling conditions showed that swelling consistently aided T cell activation. However, subsequent effector CD8+ T cell production could be reduced if swelling occurred too early in the T cell proliferative phase or if T cell cognate frequency was low due to increased opportunity for T cell exit. Temporarily extending retention of newly differentiated effector T cells, mediated by Sphingosine-1-phosphate receptor-1 expression, mitigated any negative effects of swelling by allowing facilitation of activation to outweigh increased access to exit areas. These results suggest targeting temporary effector T cell retention and egress associated with swelling may offer new ways to modulate effector TC responses in, for example, immuno-suppressed patients and optimisation of vaccine design. Genetic architecture of natural variation of cardiac performance in flies Deciphering the genetic architecture of human cardiac disorders is of fundamental importance but their underlying complexity is a major hurdle. We investigated the natural variation of cardiac performance in the sequenced inbred lines of the Drosophila Genetic Reference Panel (DGRP)1. Genome Wide Associations Studies (GWAS) identified genetic networks associated with natural variation of cardiac traits which were used to gain insights as to the molecular and cellular processes affected. Non-coding variants that we identified were used to map potential regulatory non-coding regions, which in turn were employed to predict Transcription Factors (TFs) binding sites. Cognate TFs, many of which themselves bear polymorphisms associated with variations of cardiac performance, were also validated by heart specific knockdown. Additionally, we showed that the natural variations associated with variability in cardiac performance affect a set of genes overlapping those associated with average traits but through different variants in the same genes. Furthermore, we showed that phenotypic variability was also associated with natural variation of gene regulatory networks. More importantly, we documented correlations between genes associated with cardiac phenotypes in both flies and humans, which supports a conserved genetic architecture regulating adult cardiac function from arthropods to mammals. Specifically, roles for PAX9 and EGR2 in the regulation of the cardiac rhythm were established in both models, illustrating that the characteristics of natural variations in cardiac function identified in Drosophila can accelerate discovery in humans. Fusobacterium nucleatum induces pancreatic cancer cell proliferation and migration by regulating host autocrine and paracrine signaling Pancreatic ductal adenocarcinoma (PDAC) harbors a complex tumor microbiome that has been implicated in cancer progression and resistance to chemotherapy. Recent clinical investigations uncovered a correlation between high loads of intratumor Fusobacterium nucleatum and decreased patient survival. Here we show that healthy and cancerous pancreatic cell lines harboring intracellular F. nucleatum secrete increased levels of cancer-associated cytokines including GM-CSF, CXCL1, IL-8, and MIP-3. We report that GM-CSF (granulocyte-macrophage colony stimulating factor) secretion directly increases the proliferation and migration of pancreatic cancer cells via an autocrine mechanism, notably in the absence of immune cell participation. Furthermore, we show that non-cancerous pancreatic epithelial cells do not exhibit increased proliferation or migration in response to these cytokines, but nevertheless, their secreted cytokines stimulate these responses in cancerous cell lines through paracrine signaling. Our results provide evidence that intratumor F. nucleatum in the pancreas elicits an infection-specific cytokine secretion profile from both normal and cancerous cells that adversely contributes to cancer progression through autocrine and paracrine mechanisms. Therefore, these results support the importance of investigating the contributions of both microbiome and host driven processes in pancreatic cancer to guide future therapeutic interventions. Effect of a low concentration in chloride, sodium and potassium on oocyte maturation, oocyte hydration, ovulation and egg quality in rainbow trout. Water salinity is an important environmental factor known to have detrimental effects on salmonid reproduction, mostly when migrating female broodfish are held in sea water. In contrast, data obtained in freshwater are scarce and the impact of low water salinity, and more specifically of low water concentrations in sodium, chloride and potassium, during reproduction in freshwater is currently unknown. For this reason, and because ion and water fluxes are critical for the final steps of the female gamete formation, including oocyte hydration and ovulation, the aim of the present study was to investigate the impact of low salinity water on final oocyte maturation, ovulation and, ultimately, on egg quality, using rainbow trout as a physiological model and relevant aquaculture species.

Fish from the same commercial strain were raised either in a site characterized by low concentrations of Na+, K+, and Cl- ions in the water or in a closely located control site exhibiting higher concentration in these elements. Egg quality and duration of final oocyte maturation were investigated using innovative phenotyping tools such as automatic assessment of egg viability using the VisEgg system and non-invasive echograph-based monitoring of final oocyte maturation duration, respectively. Oocyte hydration during final oocyte maturation and after ovulation was also investigated. Finally, molecular phenotyping was performed using real-time PCR-based monitoring of several key players of final oocyte maturation and ovulation associated with ion and water transport, inflammation, proteolytic activity, and coagulation. Oocyte hydration and gene expression data were analyzed in the light of the duration of final oocyte maturation.

Here we show that low water salinity (i.e., low water concentration in chloride, sodium and potassium) negatively influences final oocyte maturation, ovulation and, ultimately, egg quality. Low water salinity triggered delayed ovulation and lower oocyte viability. When investigating the impact of low water salinity on final oocyte maturation duration, individuals presenting the most severe phenotypes exhibited impaired oocyte hydration and abnormally reduced gene expression levels of several key players of the ovulatory process. While the under expression of water (i.e., aquaporins) and ion (i.e., solute carriers) transporters is consistent with impaired oocyte hydration, our observations also indicate that the overall ovulatory gene expression program is disrupted. Our results raise the question of the mechanisms underlying the negative influence of low salinity water on the dynamics of the preovulatory phase, on the control of the oocyte homeostasis, including hydration, and on the overall success of the maturation-ovulation process.

HighlightsO_LILow water salinity impairs final oocyte maturation and egg quality in rainbow trout
C_LIO_LILow water salinity induces delayed ovulation and impaired oocyte hydration
C_LIO_LILow water salinity induces a dysregulation of several key ovulatory genes
C_LIO_LIMonitoring of final oocyte maturation can be performed using ultrasound staging
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