An estimate of the deepest branches of the tree of life from ancient vertically-evolving genes Core gene phylogenies provide a window into early evolution, but different gene sets and analytical methods have yielded substantially different views of the tree of life. Trees inferred from a small set of universal core genes have typically supported a long branch separating the archaeal and bacterial domains. By contrast, recent analyses of a broader set of non-ribosomal genes have suggested that Archaea may be less divergent from Bacteria, and that estimates of inter-domain distance are inflated due to accelerated evolution of ribosomal proteins along the inter-domain branch. Resolving this debate is key to determining the diversity of the archaeal and bacterial domains, the shape of the tree of life, and our understanding of the early course of cellular evolution. Here, we investigate the evolutionary history of the marker genes key to the debate. We show that estimates of a reduced Archaea-Bacteria (AB) branch length result from inter-domain gene transfers and hidden paralogy in the expanded marker gene set. By contrast, analysis of a broad range of manually curated marker gene datasets from an evenly sampled set of 700 Archaea and Bacteria reveal that current methods likely underestimate the AB branch length due to substitutional saturation and poor model fit; that the best-performing phylogenetic markers tend to support longer inter-domain branch lengths; and that the AB branch lengths of ribosomal and non-ribosomal marker genes are statistically indistinguishable. Furthermore, our phylogeny inferred from the 27 highest-ranked marker genes recovers a clade of DPANN at the base of the Archaea, and places CPR within Bacteria as the sister group to the Chloroflexota.
Single-cell phenotypic characteristics of tolerance under recurring antibiotic exposure in Escherichia coli. Non-heritable drug resistance, such as tolerance and persistence towards antibiotics, is little characterized compared to genetic resistance. Tolerance and persistence allow cells to survive application of antibiotics that are bactericidal to non-tolerant cells. Non-heritable drug resistance challenges antibiotic treatment, particularly of recurrent infections, and have implications towards heritable resistance evolution. Tolerant cells have commonly been characterized as growth arrested cells prior and during antibiotic application that quickly resume growth post-application. Here, we explore characteristic of tolerant and susceptible E. coli single bacteria cells to different levels of recurrent antibiotic exposure and quantify their occurrence. In using a high throughput single-cell microfluidic device, we find that tolerant cells reduce their growth rate by about 50%, but contrary to previous findings do not go into growth arrest or near growth arrest. The growth reduction is induced by antibiotic exposure and not caused by a stochastic switch or predetermined state as previously described. Cells exhibiting constant intermediate growth survived best under antibiotic exposure and selection did not primarily act on fast growing cells, as expected for a {beta}-lactam antibiotic. Control experiments on population cultures confirmed and challenged scaling of single cell findings to population level processes. Our findings suggest a prevalent type of tolerance that differs from previously described tolerance and persister characteristics. Our described characteristics and its high frequency of occurrence supports acclaims of an underappreciated role of tolerant cells towards resistance evolution.

Author SummaryResistance to antibiotics is a major cause of treatment failure in modern medicine. In addition to genetic resistance, bacterial cells can sustain periods of bactericidal application in a so-called tolerant state. Previously tolerant cells were characterized by growth arrest prior and during exposure to antibiotics. Here, we show a distinctive type of tolerance that arises out of normally growing cells, where during antibiotic exposure, cell growth is slowed but does not go into growth arrest. Cells with an intermediate growth have the best survival, which is contrary to the assumptions of exposure to a {beta}-lactam antibiotic where selection is assumed to act against the fastest growing cells and the least against non-growing cells. The novel characteristics of tolerance that we have uncovered provides bacteria with another route to evade antibiotics and that could be a considerable threat to the efficiency of antibiotic treatment.
Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes IntroductionIncreasingly, logistic regression methods for genetic association studies of binary phenotypes must be able to accommodate data sparsity, which arises from unbalanced case-control ratios and/or rare genetic variants. Sparseness leads to maximum likelihood estimators (MLEs) of log-OR parameters that are biased away from their null value of zero and tests with inflated type 1 errors. Different penalized-likelihood methods have been developed to mitigate sparse-data bias. We study penalized logistic regression using a class of log-F priors indexed by a shrinkage parameter m to shrink the biased MLE towards zero.

MethodsWe propose a two-step approach to the analysis of a genetic association study: first, a set of variants that show evidence of association with the trait is used to estimate m; and second, the estimated m is used for log-F -penalized logistic regression analyses of all variants using data augmentation with standard software. Our estimate of m is the maximizer of a marginal likelihood obtained by integrating the latent log-ORs out of the joint distribution of the parameters and observed data. We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation.

ResultsWe evaluate the statistical properties of our proposed two-step method and compared its performance to other shrinkage methods by a simulation study. Our simulation studies suggest that the proposed log-F -penalized approach has lower bias and mean squared error than other methods considered. We also illustrate the approach on data from a study of genetic associations with "super senior" cases and middle aged controls.

Discussion/ConclusionWe have proposed a method for single rare variant analysis with binary phenotypes by logistic regression penalized by log-F priors. Our method has the advantage of being easily extended to correct for confounding due to population structure and genetic relatedness through a data augmentation approach. 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. A general framework to learn tertiary structure for protein sequence characterization During the past five years, deep-learning algorithms have enabled ground-breaking progress towards the prediction of tertiary structure from a protein sequence. Very recently, we developed SAdLSA, a new computational algorithm for protein sequence comparison via deep-learning of protein structural alignments. SAdLSA shows significant improvement over established sequence alignment methods. In this contribution, we show that SAdLSA provides a general machine-learning framework for structurally characterizing protein sequences. By aligning a protein sequence against itself, SAdLSA generates a fold distogram for the input sequence, including challenging cases whose structural folds were not present in the training set. About 70% of the predicted distograms are statistically significant. Although at present the accuracy of the intra-sequence distogram predicted by SAdLSA self-alignment is not as good as deep-learning algorithms specifically trained for distogram prediction, it is remarkable that the prediction of single protein structures is encoded by an algorithm that learns ensembles of pairwise structural comparisons, without being explicitly trained to recognize individual structural folds. As such, SAdLSA can not only predict protein folds for individual sequences, but also detects subtle, yet significant, structural relationships between multiple protein sequences using the same deep-learning neural network. The former reduces to a special case in this general framework for protein sequence annotation. 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. 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. Common coupling map advances GPCR-G protein selectivity Two-thirds of human hormones and one-third of clinical drugs act on membrane receptors that couple to G proteins to achieve appropriate functional responses. While G protein transducers from literature are annotated in the Guide to Pharmacology database, two recent large-scale datasets now expand the receptor-G protein  couplome. However, these three datasets differ in scope and reported G protein couplings giving different coverage and conclusions on GPCR-G protein signaling. Here, we report a common coupling map uncovering novel couplings supported by both large-scale studies, the selectivity/promiscuity of GPCRs and G proteins, and how the co-coupling and co-expression of G proteins compare to the families from phylogenetic relationships. The coupling map and insights on GPCR-G protein selectivity will catalyze advances in receptor research and cellular signaling towards the exploitation of G protein signaling bias in design of safer drugs. Repeated introduction of micropollutants enhances microbial succession despite stable degradation patterns The increasing-volume release of micropollutants into natural surface waters has raised great concern due to their environmental accumulation. Persisting micropollutants can impact multiple generations of organisms, but their microbially-mediated degradation and their influence on community assembly remain understudied. Here, freshwater microbes were treated with several common micropollutants, alone or in combination, and then transferred every 5 days to fresh medium containing the same micropollutants to mimic the repeated exposure of microbes. Metabarcoding of 16S rRNA gene makers was chosen to study the succession of bacterial assemblages following micropollutant exposure. The removal rates of micropollutants were then measured to assess degradation capacity of the associated communities. The degradation of micropollutants did not accelerate over time but altered the microbial community composition. Community assembly was dominated by stochastic processes during early exposure, via random community changes and emergence of seedbanks, and deterministic processes later in the exposure, via advanced community succession. Early exposure stages were characterized by the presence of sensitive microorganisms such as Actinobacteria and Planctomycetes, which were then replaced by more tolerant bacteria such as Bacteroidetes and Gammaproteobacteria. Our findings have important implication for ecological feedback between microbe-micropollutants under anthropogenic climate change scenarios. Targeting MLL methyltransferases enhance the anti-tumor effects of PI3K inhibition in hormone receptor-positive breast cancer The high frequency of aberrant PI3K pathway activation in hormone receptor-positive (HR+) breast cancer has led to the development, clinical testing, and approval of the p110-selective PI3K inhibitor alpelisib. The limited clinical efficacy of alpelisib and other PI3K inhibitors is partially attributed to the functional antagonism between PI3K and estrogen receptor (ER) signaling, which is mitigated via combined PI3K inhibition and endocrine therapy. We and others have previously demonstrated a chromatin-associated mechanism by which PI3K supports cancer development and antagonizes ER signaling through the modulation of H3K4 methylation. Here we show that inhibition of the H3K4 histone methyltransferase MLL1 in combination with PI3K inhibition impairs HR+ breast cancer clonogenicity and cell proliferation. While combined PI3K/MLL1 inhibition reduces AKT effector signaling and H3K4 methylation, MLL1 inhibition increases PI3K effector signaling and upregulates the expression of receptor tyrosine kinase signaling cascades upstream of and including AKT. These data reveal a feedback loop between MLL1 and AKT in which MLL1 inhibition reactivates AKT. We additionally show that combined PI3K and MLL1 inhibition synergizes to cause cell death in in vitro and in vivo models of HR+ breast cancer, which is enhanced by the additional genetic ablation of the H3K4 methyltransferase and AKT target MLL4. Together, our data provide evidence of a feedback mechanism connecting histone methylation with AKT and may support the preclinical development and testing of pan-MLL inhibitors.

Significance StatementPharmacological inhibition of PI3K provides limited efficacy in PIK3CA-mutated, HR+ breast cancers. Here the authors leverage PI3K/AKT-driven chromatin modification to identify MLL histone methyltransferases as a therapeutic target. Dual PI3K and MLL inhibition synergize to reduce clonogenicity and cell proliferation while enhancing apoptosis in in vitro models, and induces tumor regression in xenograft models of PI3K-activated, HR+ breast cancer. Furthermore, MLL1 inhibition reveals a feedback loop leading to AKT hyperactivation, which is relieved with combined PI3K/MLL inhibition. These findings demonstrate the utility of MLL inhibitors for the treatment of some solid cancers, as patients with HR+ breast cancer characterized by PIK3CA mutation may derive clinical benefit from combined PI3K/MLL inhibition. SPIRO - the automated Petri plate imaging platform designed by biologists, for biologists The imaging of plant seedlings, fungal mycelia and bacterial colonies grown on Petri plates is common in phenotyping assays, and is typically done manually despite the procedures being time-consuming and laborious. The main reason for this is the still limited availability of existing automated phenotyping tools and facilities. Additionally, constructing a custom-made automated solution is a daunting task for most research groups specializing in biology.

Here, we describe SPIRO, the Smart Plate Imaging Robot, an automated platform that acquires time-lapse photos of up to four vertically oriented Petri plates in a single experiment. SPIRO was designed for biologists by biologists; thus, its assembly does not require experience in engineering or programming and its operation is sufficiently intuitive to be carried out without training. SPIRO has a small footprint optimal for fitting into standard incubators for plants and microbes, and is equipped with an LED light source for imaging in the dark, thus allowing acquisition of photos under optimal growth conditions. SPIROs web-based user interface allows setting up experiments and downloading data remotely, without interfering with samples growth. SPIROs excellent image quality is optimal for automated image processing, which we demonstrate with two semi-automated assays for analysis of commonly used phenotypic traits: seed germination and root growth.

Moreover, the robot can be easily customized for a specific use, as all information about SPIRO, including the models for 3D-printed structural components, control software, and scripts for image analysis, are released under permissive open-source licenses. Highly efficient synthetic CRISPR RNA/Cas9-based mutagenesis for rapid cardiovascular phenotypic screening in F0 zebrafish The zebrafish is a valuable vertebrate model to study cardiovascular formation and function due to the facile visualization and rapid development of the circulatory system in its externally growing embryos. Despite having distinct advantages, zebrafish have paralogs of many important genes, making reverse genetics approaches inefficient since generating animals bearing multiple gene mutations requires substantial efforts. Here, we present a simple and robust synthetic CRISPR RNA/Cas9-based mutagenesis approach for generating biallelic F0 zebrafish knockouts. Using a dual-guide synthetic CRISPR RNA/Cas9 ribonucleoprotein (dgRNP) system, we compared the efficiency of biallelic gene disruptions following the injections of one, two, and three dgRNPs per gene into the cytoplasm or yolk. We show that simultaneous cytoplasmic injections of three distinct dgRNPs per gene into one-cell stage embryos resulted in the most efficient and consistent biallelic gene disruptions. Importantly, this triple dgRNP approach enables efficient inactivation of cell autonomous and cell non-autonomous gene function, likely due to the low mosaicism of biallelic disruptions. In support of this finding, we provide evidence that the F0 animals generated by this method fully phenocopied the endothelial and peri-vascular defects observed in corresponding stable mutant homozygotes. Moreover, this approach faithfully recapitulated the trunk vessel phenotypes resulting from the genetic interaction between two vegfr2 zebrafish paralogs. Mechanistically, investigation of genome editing and mRNA decay indicates that the combined mutagenic actions of three dgRNPs per gene lead to an increased probability of frameshift mutations, enabling efficient biallelic gene disruptions. Therefore, our approach offers a highly robust genetic platform to quickly assess novel and redundant gene function in F0 zebrafish. An alternatively spliced TREM2 isoform lacking the ligand binding domain is expressed in human brain BackgroundGenetic variants in TREM2 are strongly associated with Alzheimers Disease (AD) risk but alternative splicing in TREM2 transcripts has not been comprehensively described.

ObjectiveRecognizing that alternative splice variants can result in reduced gene expression and/or altered function, we sought to fully characterize splice variation in TREM2.

MethodsHuman blood and anterior cingulate autopsy tissue from 61 donors were used for end-point and quantitative PCR and Western blotting to identify and quantify novel TREM2 isoforms.

ResultsIn addition to previously described transcripts lacking exon 3 or exon 4, or retaining part of intron 3, we identified novel isoforms lacking exon 2, along with isoforms lacking multiple exons. Isoforms lacking exon 2 were predominant at approximately 10% of TREM2 mRNA in the brain. Expression of TREM2 and frequency of exon 2 skipping did not differ between AD samples and non-AD controls (p = 0.1268 and p = 0.4909, respectively). Further, these novel splice isoforms were also observed across multiple tissues with similar frequency (range 5.3 - 13.0%). We found that the exon 2 skipped isoform D2-TREM2 is translated to protein and localizes similarly to full-length TREM2 protein, that both proteins are primarily retained in the Golgi complex, and that D2-TREM2 is expressed in AD and non-AD brain.

ConclusionSince the TREM2 ligand binding domain is encoded by exon 2, and skipping this exon retains reading frame while conserving localization, we hypothesize that D2-TREM2 acts as an inhibitor of TREM2 and targeting TREM2 splicing may be a novel therapeutic pathway for AD. Discovery and functional assessment of a novel adipocyte population driven by intracellular Wnt/β-catenin signaling in mammals Wnt/{beta}-catenin signaling has been well established as a potent inhibitor of adipogenesis. Here, we identified a population of adipocytes that exhibit persistent activity of Wnt/{beta}-catenin signaling, as revealed by the Tcf/Lef-Gfp reporter allele, in embryonic and adult mouse fat depots, named as Wnt+ adipocytes. We showed that the {beta}-catenin-mediated signaling activation in these cells is Wnt ligand- and receptor-independent but relies on AKT/mTOR pathway and is essential for cell survival. Such adipocytes are distinct from classical ones in transcriptomic and genomic signatures and can be induced from various sources of mesenchymal stromal cells including human cells. Genetic lineage-tracing and targeted cell ablation studies revealed that these adipocytes convert into beige adipocytes directly and are also required for beige fat recruitment under thermal challenge, demonstrating both cell autonomous and non-cell autonomous roles in adaptive thermogenesis. Furthermore, mice bearing targeted ablation of these adipocytes exhibited glucose intolerance, while mice receiving exogenously supplied such cells manifested enhanced glucose utilization. Our studies uncover a unique adipocyte population in regulating beiging in adipose tissues and systemic glucose homeostasis. First detection of herpesvirus and frequency of mycoplasma infection in free-ranging Hermann s tortoises (Testudo hermanni), and in potential pet vectors AO_SCPLOWBSTRACTC_SCPLOWTwo types of pathogens cause highly contagious upper respiratory tract diseases (URTD) in Chelonians: testudinid herpesviruses (TeHV) and a mycoplasma (Mycoplasma agassizii). In captivity, these infections are frequent and can provoke outbreaks. Pet trade generates international flow of tortoises, often without sanitary checking; individuals intentionally or accidentally released in the wild may spread pathogens. A better understanding of the transmission of infectious agents from captivity to wild tortoises is needed. Many exotic individuals have been introduced in populations of the endangered western Hermanns tortoise (Testudo hermanni hermanni), notably spur-thighed tortoises (Testudo graeca). We assessed the presence of TeHV and mycoplasma in native western Hermanns tortoises and in potential pet vectors in south-eastern France. Using a large sample (N=572 tortoises), this study revealed, by PCR, the worrying presence of herpesvirus in 7 free-ranging individuals (3 sub-populations). Additionally, Mycoplasma agassizii was detected, by PCR, in 15 of the 18 populations sampled with a frequency ranging from 3.4% (1 of 29 tortoises) to 25% (3 of 12 tortoises). Exotic spur-thighed tortoises showed high frequency of mycoplasma infection in captivity (18.2%) and in individuals (50%) found in native Hermanns tortoise sub-populations, suggesting that this species could be a significant vector. The paucity of information of TeHV on European tortoise URTD in natural settings, especially in combination with mycoplasma, prompts for further studies. Indeed, sick tortoises remain concealed and may not be easily detected in the field. Our results indicate a good health for most infected tortoise but it should be screened in the field as well as in captivity. The OCT2 Transporter Regulates Dopamine D1 Receptor Signaling at the GolgiApparatus Dopamine is the main catecholamine in the brain and the kidney, where it controls a number of physiological functions such as locomotion, cognition, emotion, endocrine regulation and renal function. As a membrane impermeant hormone and neurotransmitter, dopamine is thought to signal by binding and activating dopamine receptors, members of the G protein couple receptor (GPCR) family, only on the plasma membrane. Here, using novel nanobody-based biosensors, we demonstrate for the first time that the dopamine D1 receptor (D1DR), the primary mediator of dopaminergic signaling in the brain and kidney, not only functions on the plasma membrane but becomes activated at the Golgi apparatus in the presence of its ligand. We present evidence that activation of the Golgi pool of D1DR is dependent on Organic Cation Transporter 2 (OCT2), a dopamine transporter, providing an explanation for how the membrane impermeant dopamine accesses subcellular pools of D1DR. We further demonstrate that dopamine activates Golgi-D1DR in the striatal medium spiny neurons (MSN) and this activity depends on OCT2 function. We also introduce a new approach to selectively interrogate compartmentalized D1DR signaling by inhibiting Gs coupling, using a nanobody-based chemical recruitment system. Using this strategy, we show that Golgi-localized D1DRs regulate cAMP production and mediate local protein kinase A activation. Together, our data suggest that spatially compartmentalized signaling hubs are previously unappreciated regulatory aspects of D1DR signaling. Our data also provide further evidence for the role of transporters in regulating subcellular GPCR activity. Shortcuts in stochastic systems and control of biophysical processes The biochemical reaction networks that regulate living systems are all stochastic to varying degrees. The resulting randomness affects biological outcomes at multiple scales, from the functional states of single proteins in a cell to the evolutionary trajectory of whole populations. Controlling how the distribution of these outcomes changes over time--via external interventions like time-varying concentrations of chemical species--is a complex challenge. In this work, we show how counterdiabatic (CD) driving, first developed to control quantum systems, provides a versatile tool for steering biological processes. We develop a practical graph-theoretic framework for CD driving in discrete-state continuous-time Markov networks. Though CD driving is limited to target trajectories that are instantaneous stationary states, we show how to generalize the approach to allow for non-stationary targets and local control--where only a subset of system states are targeted. The latter is particularly useful for biological implementations where there may be only a small number of available external control knobs, insufficient for global control. We derive simple graphical criteria for when local versus global control is possible. Finally, we illustrate the formalism with global control of a genetic regulatory switch and local control in chaperone-assisted protein folding. The derived control protocols in the chaperone system closely resemble natural control strategies seen in experimental measurements of heat shock response in yeast and E. coli. Mathematical Modeling and Analysis of Mitochondrial Retrograde Signaling Dynamics Mitochondria, semi-autonomous eukaryotic organelles, participate in energy production and metabolism, making mitochondrial quality control crucial. As most mitochondrial proteins are encoded by nuclear genes, quality control depends on proper mitochondria-nucleus communication, designated mitochondrial retrograde signaling. Early studies focused on retrograde signaling participants and specific gene knockouts. However, mitochondrial signal modulation remains elusive. Using yeast, we simulated signal propagation following mitochondrial damage and proposed a mathematical model based ordinary differential equations. Mitochondrial retrograde signaling decisions were described using a Boolean model. Dynamics were analyzed through an ordinary differential equation-based model and extended to evaluate the model response to noisy damage signals. Simulation revealed localized protein concentration dynamics, including waveforms, frequency response, and robustness under noise. Retrograde signaling is bistable with three localized steady states, and increased damage compromises robustness. We elucidated mitochondrial retrograde signaling, thus providing a basis for drug design against yeast and fungi.

Author SummaryThe yeast RTG pathway regulates mitochondrial metabolism and mitochondrial quality through passing mitochondrial signal to the nucleus to modulate gene expressions. Using microscopic data of RTG proteins translocation from cytosol to nucleus, the parameters were found by fitting 16 knockout conditions simulated from the proposed differential equation-based model. Further, through dose response, ultrasensitivity, frequency response and noise interference, we demonstrated a switch-like property of RTG pathway activation, a capacity charging property of RTG protein translocation, a low pass filter property of signals in different frequencies, and noise amplification due to mitochondrial signal. The proposed mathematical model enables us to understand the dynamics and mechanisms in mitochondrial retrograde signaling in yeast and provides potential antifungal treatment strategies. Sniffing Out New Friends: Similarity in Body-Odor Predicts the Quality of Same-Sex Non-Romantic Dyadic Interactions Most are familiar with the notion of socially "clicking" with someone, namely sensing an immediate bond that can lead to strong and often long-lasting friendships. The mechanisms underlying such rapid bonding remain unclear. Given that body-odor similarity is a critical cue for social interaction in non-human mammals, we tested the hypothesis that body-odor similarly contributes to bonding in same-sex non-romantic human dyads. We observed that objective ratings obtained with an electronic nose, and subjective ratings obtained from human smellers, converged to suggest that click-friends smell more similar to each other than random dyads. Remarkably, we then found that we could use the electronic nose to predict which strangers would later form better dyadic interactions. Thus, humans may literally sniff-out new friends based on similarities in body-odor. 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. If Research is Not the Evidence, What is it? The Lack of Research Citations in Health Vlogs Doctor-influencers have the knowledge needed to understand scientific research, and they have the social media popularity to share it with large audiences. In this article, I explore the treatment of evidence in vlogs by Egyptian doctor-influencers: how they present it and what they use instead of it. I answer the following questions: 1) How do doctor-influencers present evidence on social media? 2) If evidence is not the research, then what is it? The data was collected through in-depth interviews with 12 Egyptian doctor-influencers from different specializations; two focus groups; and a critical discourse analysis of 48 of the influencers most popular and most engaging videos. I found that the doctor-influencers cited academic research only in the videos about medical controversies, new treatments, misinformation, or common medical mistakes. In most of their videos, the Egyptian doctor-influencers scarcely referred to medical research. This is because they believe that their audiences would not understand evidence due to their low educational attainment, weak research skills, and the language barrier (as most medical research is published in English rather than Arabic). These findings highlight the challenges of communicating science in societies with a low level of education. In these settings, communicators may need to move beyond mediating research studies on social media and instead focus on simplifying, translating, and connecting evidence-based information to the cultural context. Coordinated changes in gene expression, H1 variant distribution and genome 3D conformation in response to H1 depletion Up to seven members of the histone H1 family may contribute to chromatin compaction and its regulation in human somatic cells. In breast cancer cells, knock-down of multiple H1 variants deregulates many genes, promotes the appearance of genome-wide accessibility sites and triggers an interferon response via activation of heterochromatic repeats. However, how these changes in the expression profile relate to the re-distribution of H1 variants as well as to genome conformational changes have not been yet studied. Here, we combined ChIP-seq of five endogenous H1 variants with Chromosome Conformation Capture analysis in wild-type and H1 knock-down T47D cells. The results indicate that H1 variants coexist in the genome in two large groups depending on the local DNA GC content and that their distribution is robust with respect to multiple H1 depletion. Despite the small changes in H1 variants distribution, knock-down of H1 translated into more isolated but de-compacted chromatin structures at the scale of Topologically Associating Domains or TADs. Such changes in TAD structure correlated with a coordinated gene expression response of their resident genes. This is the first report describing simultaneous profiling of five endogenous H1 variants within a cell line and giving functional evidence of genome topology alterations upon H1 depletion in human cancer cells. Liver environment-imposed constraints diversify movement strategies of liver-localized CD8 T cells Pathogen-specific CD8 T cells face the problem of finding rare cells that present their cognate antigen either in the lymph node or infected tissue. While quantitative details of T cell movement strategies in some tissues such lymph nodes or skin have been relatively well characterized, we still lack quantitative understanding of T cell movement in many other important tissues such as the spleen, lung, liver, and gut. Furthermore, how environmental constraints influence movement patterns of T cells in tissues remains incompletely characterized. Liver is one of the major organs in mice and humans and is the target site for many pathogens such as hepatitis B and C viruses in humans and Plasmodium parasites in multiple mammalian species. We developed a protocol to generate stable numbers of liver-located CD8 T cells, used intravital microscopy to record movement patterns of CD8 T cells in livers of live mice, and analyzed these and previously published data using well-established statistical and computational methods. We show that in most of our experiments Plasmodium-specific liver-localized CD8 T cells perform correlated random walks characterized by transiently superdiffusive displacement with persistence times of 10-15 min that exceed those observed for T cells in lymph nodes. Liver-localized CD8 T cells typically crawl on the lumenal side of liver sinusoids (i.e., are in the blood); simulating T cell movement in digital structures derived from the liver sinusoids illustrates that liver structure alone is sufficient to explain the relatively long superdiffusive displacement of T cells. In experiments when CD8 T cells in the liver poorly attach to the sinusoids (e.g., one week post immunization with radiation-attenuated Plasmodium sporozoites) T cells also undergo Levy flights - large displacements occurring due to cell deattaching from the endothelium, floating with the blood flow, and re-attaching at another location. Our analysis, thus, provides quantitative details of movement patterns of liver-localized CD8 T cells and illustrates how structural and physiological details of the tissue may impact T cell movement patterns. Advanced Functional Biotextiles for a Circular Materials Economy A circular materials economy can disrupt linear production models and mitigate its environmental threats. We harness extracellular biosynthesis of microbial nanocellulose (MC), coupled to a protocol that represents a serendipitous intersection between ancient textile techniques and green processing as a route to high-performance bioleather with a circular life cycle. Specifically, a plant-based lecithin phosphocholine treatment modulates cellulose cross-linking through phosphate and methylene groups, to yield a biodegradable material with superior mechanical and flame-retardant properties. A broad color palette and controlled color modulation was achieved with cultural heritage dyes and waste-to-resource strategies. Life cycle impact assessment shows up to an order of magnitude reduction in environmental impacts relative to conventional textiles, making MC relevant for widespread application in fashion, interiors, construction and insulating materials. The translational potential of this approach is tremendous, as use of microbes and green chemistry to engineer regenerative, high-performance products can accelerate a paradigm shift to a circular bioeconomy. Game of theories: an agent-based model of how variation in contest cost-benefits determines the evolution of contest resolution rules Game-theory based models are used to understand rules that animals use to settle contests over indivisible resources. However, the empirical literature of contests indicates controversial support to models, with some species supporting different models and other species showing no support to any model. Since strategies used to resolve contests may have different associated costs, it is possible that different conditions have determined the evolution of distinct assessment strategies used by animals. We used an agent-based model to explore the importance of the following conditions: resource availability, probability of reproduction with resource, and damage costs on evolution of assessment strategies. We used self- and mutual-assessment models as a heurist framework to build agents with different assessment strategies. In our model, agents competed for resources in scenarios with different combinations of resource availability, probability of reproduction with resource, and damage costs. We found that agents following the self-assessment with damage strategy were prevalent in scenarios with no probability of reproduction without the resource, independently of other variables. We also found that agents following the non-aggressive strategy occurred in all scenarios. However, agents using the non-aggressive strategy were prevalent only in scenarios with probability of reproduction with the resource. Finally, we observed that agents using mutual-assessment occurred only in a scenario with high risk of damage, low availability of resources, and with probability of reproduction without the resource. These results indicate that agents following the self-assessment with damage and non-aggressive strategies may be able to stay at most scenarios. In vitro susceptibility to β-lactam antibiotics and viability of Neisseria gonorrhoeae strains producing plasmid-mediated broad- and extended-spectrum β-lactamases N. gonorrhoeae strains producing plasmid-mediated broad- and extended-spectrum {beta}-lactamases (ESBLs) have been obtained in vitro and studied for their viability and susceptibility to {beta}-lactam antibiotics. The artificial pblaTEM-1 and pblaTEM-20 plasmids were constructed by site-directed mutagenesis from a pblaTEM-135 plasmid of the Toronto/Rio type, which was extracted from the clinical isolate. MIC values were determined for a series of {beta}-lactam antibiotics, including benzylpenicillin, ampicillin, cefuroxime, ceftriaxone, cefixime, cefotaxime, cefepime, meropenem, imipenem, and doripenem. The N. gonorrhoeae strain carrying the pblaTEM-20 plasmid exhibited a high level of resistance to penicillins and II-IV generation cephalosporins (MIC [&ge;] 2 mg/L) but not to carbapenems (MIC [&le;] 0.008 mg/L). However, this strain stopped growing after 6 hours of cultivation. The reduced viability was not associated with the plasmid loss but can be explained by the following factors: the presence of the plasmid itself, which requires additional costs for its reproduction, and the expression of ESBL, which can affect the structure of the peptidoglycan layer in the cell membrane. The cell growth was mathematically modeled using the generalized Verhulst equation. The parameter, characterizing the maximum possible number of cells grown under given conditions, decreased within the wild type (without plasmids) - pblaTEM-135 - pblaTEM-1 - pblaTEM-20 series, i.e., the plasmid-bearing strains had reduced viability compared to that of the wild-type strain. The kinetics for the cell death of N. gonorrhoeae strains without the pblaTEM-20 plasmid in the presence of ceftriaxone can be described by a modified Chick-Watson law. For the N. gonorrhoeae strain that harbors the pblaTEM-20 plasmid, the kinetics for cell number changes with time reflected several processes: the hydrolysis of ceftriaxone by TEM-20 {beta}-lactamase, growth and gradual death of cells. The demonstrated reduced viability of N. gonorrhoeae strains with the pblaTEM-20 plasmid probably explains the absence of clinical isolates of N. gonorrhoeae that produce ESBL.