Identifying critical transcriptional targets of the MYC oncogene using a novel competitive precision genome editing (CGE) assay MYC is an oncogenic transcription factor that controls major pathways promoting cell growth and proliferation. MYC has been implicated in the regulation of large number of genes, but the exact target genes responsible for its proliferative effects are still not known. Here, we use a novel competitive genome editing (CGE) assay for studying the functional consequence of precise mutations of MYC binding sites on cell proliferation. The CGE method is based on precision genome editing, where a CRISPR/Cas9-induced DNA break is repaired using a template that either reconstitutes the original feature or introduces an altered sequence. Both types of repair templates harbor sequence tags that allow direct comparison between cells that carry original and mutant features and generate a large number of replicate cultures. The CGE method overcomes the limitations of CRISPR/Cas9-technology in analyzing the effect of genotype on phenotype, namely the difficulty of cutting DNA exactly at the intended site, and the decreased cell proliferation caused by the DNA cuts themselves. Importantly, it provides a powerful method for studying subtle effects elicited by mutation of individual transcription factor binding sites. We show here that E-box mutations at several MYC target gene promoters resulted in reduced cellular fitness, demonstrating a direct correlation between MYC-regulated cellular processes and MYC binding and identifying important transcriptional targets responsible for its functions.
Comparative Analysis of non-coding small-RNAs in Pseudomonas aeruginosa Keratitis Strains with Different Antibiotic Susceptibility Pseudomonas aeruginosa, is a gram-negative bacterium causes opportunistic or nosocomial infections in immunocompromised individuals. In recent years, a steady increase in human corneal infections of P. aeruginosa has been reported with increased multi-drug resistance (MDR) or extensively drug resistance (XDR). Several non-coding sRNAs, has been identified to regulate various physiological processes in P. aeruginosa, including biofilm formation, quorum sensing. However, the regulatory mechanism of sRNAs in MDR/XDR pathways of P. aeruginosa keratitis strains is not yet studied. In this study, we identified bacterial sRNAs in publicly available P. aeruginosa keratitis genomes and investigated their regulatory role in MDR/XDR pathways using bioinformatic analysis. Totally, 46 P. aeruginosa keratitis strains from different geographical regions were included. Of 46, Eight (30%) out of Twenty-seven and Nine (52) out of Nineteen P. aeruginosa strains from India and Australia were identified as not-MDR. Whereas, 10 (38%) Indian and 9 (47%) Australian strains were identified as MDR. Eight Indian strains were identified as XDR. Out of 46 strains, 23 (50%) carried ExoU, 21(45%) carried ExoS and two (5%) strains carried both ExoU and ExoS, exotoxins for their virulence. The sRNA, SPA0021 was identified in 18 MDR/XDR and 6 not-MDR strains along with UCBPP-PA14. Interestingly, majority of the imipenem resistant P. aeruginosa keratitis strains from the present study was found to be carried SPA0023 sRNA (18 out of 30 strains). The outer membrane porin protein OprD, identified as binding target of SPA0023. Negative regulation or inactivation of OprD, reported in increased imipenem resistance in P. aeruginosa. Mutation analysis revealed that SPA0023 carrying P. aeruginosa keratitis strains contains a lesser number of amino acid changes in OprD protein than other strains. These findings indicate, imipenem resistance in SPA0023 carried strains might arose from the negative regulation or inhibition of OprD by SPA0023. However, functional studies are warranted with large number of P. aeruginosa keratitis strains to confirm the negative regulation of OprD by SPA0023 and imipenem resistance.
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. 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. Dipeptides are minimalistic but sufficient for liquid-liquid phase separation Liquid-liquid phase separation (LLPS) of proteins mediates the assembly of biomolecular condensates involved in physiological and pathological processes. Identifying the minimalistic building blocks and the sequence determinant of protein phase separation is of urgent importance but remains challenging due to the enormous sequence space and difficulties of existing methodologies in characterizing the phase behavior of ultrashort peptides. Here we demonstrate computational tools to efficiently quantify the microscopic fluidity and density of liquid-condensates/solid-aggregates and the temperature-dependent phase diagram of peptides. Utilizing our approaches, we comprehensively predict the LLPS abilities of all 400 dipeptide combinations of coded amino acids based on 492 micro-second molecular dynamics simulations, and observe the occurrences of spontaneous LLPS. We identify 54 dipeptides that form solid-like aggregates and three categories of dipeptides with high LLPS propensity. Our predictions are validated by turbidity assays and differential interference contrast (DIC) microscopy on four representative dipeptides (WW, QW, GF, and VI). Phase coexistence diagrams are constructed to explore the temperature dependence of LLPS. Our results reveal that aromatic moieties are crucial for a dipeptide to undergo LLPS, and hydrophobic and polar components are indispensable. We demonstrate for the first time that dipeptides, minimal but complete, possess multivalent interactions sufficient for LLPS, suggesting that LLPS is a general property of peptides/proteins, independent of their sequence length. This study provides a computational and experimental approach to the prediction and characterization of the phase behavior of minimalistic peptides, and will be helpful for understanding the sequence-dependence and molecular mechanism of protein phase separation.

SignificanceProtein liquid-liquid phase separation (LLPS) is associated with human health and diseases. Identifying the minimalistic building blocks and sequence determinants of LLPS is of urgent importance but remains computationally challenging partially due to the lack of methodologies characterizing the liquid condensates. Herein we provide approaches to evaluate LLPS ability of dipeptides, and screen all 400 dipeptides by MD simulations combined with multi-bead-per-residue models which capture key interactions driving LLPS that are missing in one-bead-per-residue models. Three categories of LLPS dipeptides are identified and the experimentally-verified QW dipeptide is by far the smallest LLPS system. Our results suggest that dipeptides, minimal but complete, possess multivalent interactions sufficient for LLPS, and LLPS is a general property of peptides/proteins, independent of their length. Investigation of ongoing recombination through genealogical reconstruction for SARS-CoV-2 AO_SCPLOWBSTRACTC_SCPLOWThe evolutionary process of genetic recombination has the potential to rapidly change the properties of a viral pathogen, and its presence is a crucial factor to consider in the development of treatments and vaccines. It can also significantly affect the results of phylogenetic analyses and the inference of evolutionary rates. The detection of recombination from samples of sequencing data is a very challenging problem, and is further complicated for SARS-CoV-2 by its relatively slow accumulation of genetic diversity. The extent to which recombination is ongoing for SARS-CoV-2 is not yet resolved. To address this, we use a parsimony-based method to reconstruct possible genealogical histories for samples of SARS-CoV-2 sequences, which enables us to pinpoint specific recombination events that could have generated the data. We propose a statistical framework for disentangling the effects of recurrent mutation from recombination in the history of a sample, and hence provide a way of estimating the probability that ongoing recombination is present. We apply this to samples of sequencing data collected in England and South Africa, and find evidence of ongoing recombination. Fatal COVID-19 and non-COVID-19 Acute Respiratory Distress Syndrome is Associated with Incomplete Alveolar Type 1 Epithelial Cell Differentiation from the Transitional State Without Fibrosis ARDS due to COVID-19 and other etiologies results from injury to the alveolar epithelial cell (AEC) barrier resulting in noncardiogenic pulmonary edema, which causes acute respiratory failure; clinical recovery requires epithelial regeneration. During physiologic regeneration in mice, AEC2s proliferate, exit the cell cycle, and transiently assume a transitional state before differentiating into AEC1s; persistence of the transitional state is associated with pulmonary fibrosis in humans. It is unknown whether transitional cells emerge and differentiate into AEC1s without fibrosis in human ARDS and why transitional cells differentiate into AEC1s during physiologic regeneration but persist in fibrosis. We hypothesized that incomplete but ongoing AEC1 differentiation from transitional cells without fibrosis may underlie persistent barrier permeability and fatal acute respiratory failure in ARDS. Immunostaining of postmortem ARDS lungs revealed abundant transitional cells in organized monolayers on alveolar septa without fibrosis. They were typically cuboidal or partially spread, sometimes flat, and occasionally expressed AEC1 markers. Immunostaining and/or interrogation of scRNAseq datasets revealed that transitional cells in mouse models of physiologic regeneration, ARDS, and fibrosis express markers of cell cycle exit but only in fibrosis express a specific senescence marker. Thus, in severe, fatal early ARDS, AEC1 differentiation from transitional cells is incomplete, underlying persistent barrier permeability and respiratory failure, but ongoing without fibrosis; senescence of transitional cells may be associated with pulmonary fibrosis. Embracing imperfection: machine-assisted invertebrate classification in difficult datasets O_LIDespite growing concerns over the health of global invertebrate diversity, terrestrial invertebrate monitoring efforts remain poorly geographically distributed. Machine-assisted classification has been proposed as a potential solution to quickly gather large amounts of data; however, previous studies have often used unrealistic or idealized datasets to train their models.
C_LIO_LIIn this study, we describe a practical methodology for including machine learning in ecological data acquisition pipelines. Here we train and test machine learning algorithms to classify over 56,000 bulk terrestrial invertebrate specimens from morphometric data and contextual metadata. All vouchered specimens were collected in pitfall traps by the National Ecological Observatory Network (NEON) at 27 locations across the United States in 2016. Specimens were photographed, and morphometric data was extracted as feature vectors using ImageJ. Issues stemming from inconsistent taxonomic label specificity were resolved by making classifications at the lowest identified taxonomic level (LITL). Taxa with too few specimens to be included in the training dataset were classified by the model using zero-shot classification.
C_LIO_LIWhen classifying specimens that were known and seen by our models, we reached an accuracy of 72.7% using extreme gradient boosting (XGBoost) at the LITL. Models that were trained without contextual metadata underperformed models with contextual metadata by an average of 7.2%. We also classified invertebrate taxa that were unknown to the model using zero-shot classification, with an accuracy of 39.4%, resulting in an overall accuracy of 71.5% across the entire NEON dataset.
C_LIO_LIThe general methodology outlined here represents a realistic application of machine learning as a tool for ecological studies. Hierarchical and LITL classifications allow for flexible taxonomic specificity at the input and output layers. These methods also help address the  long tail problem of underrepresented taxa missed by machine learning models. Finally, we encourage researchers to consider more than just morphometric data when training their models, as we have shown that the inclusion of contextual metadata can provide significant improvements to accuracy.
C_LI Common variants in breast cancer risk loci predispose to distinct tumor subtypes BackgroundGenome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER), but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear.

MethodsAmong 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes.

ResultsEighty-five of 173 variants were associated with at least one tumor feature (false discovery rate <5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at P<0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions.

ConclusionThis report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction. Supervised Learning Model Predicts Protein Adsorption to Carbon Nanotubes Engineered nanoparticles are advantageous for numerous biotechnology applications, including biomolecular sensing and delivery. However, testing the compatibility and function of nanotechnologies in biological systems requires a heuristic approach, where unpredictable biofouling via protein corona formation often prevents effective implementation. Moreover, rational design of biomolecule-nanoparticle conjugates requires prior knowledge of such interactions or extensive experimental testing. Toward better applying engineered nanoparticles in biological systems, herein, we develop a random forest classifier (RFC) trained with proteomic mass spectrometry data that identifies proteins that adsorb to nanoparticles, based solely on the proteins amino acid sequence. We model proteins that populate the corona of a single-walled carbon nanotube (SWCNT)-based optical nanosensor and study whether there is a relationship between the proteins amino acid-based properties and the proteins adsorption to SWCNTs. We optimize the classifier and characterize the classifier performance against other models. To evaluate the predictive power of our model, we apply the classifier to rapidly identify proteins with high binding affinity to SWCNTs, followed by experimental validation. We further determine protein features associated with increased likelihood of SWCNT binding: high content of solvent-exposed glycine residues and non-secondary structure-associated amino acids. Conversely, proteins with high content of leucine residues and beta-sheet-associated amino acids are less likely to form the SWCNT protein corona. The classifier presented herein provides a step toward undertaking the otherwise intractable problem of predicting protein-nanoparticle interactions, which is needed for more rapid and effective translation of nanobiotechnologies from in vitro synthesis to in vivo use.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=66 SRC="FIGDIR/small/449132v2_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@bbc175org.highwire.dtl.DTLVardef@9a0b94org.highwire.dtl.DTLVardef@16e22e1org.highwire.dtl.DTLVardef@1b40a84_HPS_FORMAT_FIGEXP  M_FIG C_FIG Venomics and antivenomics of Indian spectacled cobra (Naja naja) from the Western Ghats Venom proteome profiling of Naja naja from the Western Ghats region in Kerala was achieved through SDS-PAGE and RP-HPLC followed by Q-TOF LC-MS/MS analysis, incorporating PEAKS and Novor assisted de novo sequencing methodologies. A total of 115 proteins distributed across 17 different enzymatic and non-enzymatic venom protein families were identified through conventional and 39 peptides through homology-driven proteomics approaches. Fourteen peptides derived through de novo complements the Mascot data indicating the importance of homology-driven approaches in improving protein sequence information. Among the protein families identified, glutathione peroxidase and endonuclease were reported for the first time in the Indian cobra venom. Immunological cross-reactivity assessed using Indian polyvalent antivenoms suggested that VINS showed better EC50 (2.48 g/mL) value than that of PSAV (6.04 g/mL) and Virchow (6.03 g/mL) antivenoms. Western blotting experiments indicated that all the antivenoms elicited poor binding specificities, especially towards low molecular mass proteins. Second-generation antivenomics studies revealed that VINS antivenom was less efficient to detect many low molecular mass proteins such as three-finger toxins and Kunitz-type serine protease Inhibitors. Taken together, the present study enabled a large-scale characterization of the venom proteome of Naja naja from the Western Ghats and emphasized the need for developing more efficient antivenoms.

HighlightsO_LIProteomics of cobra venom resulted in the identification of 115 proteins representing 17 snake venom protein families.
C_LIO_LIDe novo approaches exclusively yielded 39 peptides harbouring multiple amino acid mutations.
C_LIO_LIGlutathione peroxidase and endonuclease were identified for the first time in Indian cobra venom.
C_LIO_LIIndian polyvalent antivenoms showed varying cross-reactivity towards cobra venom.
C_LIO_LIVINS antivenom was less efficient to detect many low molecular mass proteins (< 20 kDa).
C_LI SPICEMIX: Integrative single-cell spatial modeling of cell identity Spatial transcriptomics technologies promise to reveal spatial relationships of cell-type composition in complex tissues. However, the development of computational methods that can utilize the unique properties of spatial transcriptome data to unveil cell identities remains a challenge. Here, we introduce SO_SCPLOWPICEC_SCPLOWMO_SCPLOWIXC_SCPLOW, a new interpretable method based on probabilistic, latent variable modeling for effective joint analysis of spatial information and gene expression from spatial transcriptome data. Both simulation and real data evaluations demonstrate that SO_SCPLOWPICEC_SCPLOWMO_SCPLOWIXC_SCPLOW markedly improves upon the inference of cell types and their spatial patterns compared with existing approaches. By applying to spatial transcriptome data of brain regions in human and mouse acquired by seqFISH+, STARmap, and Visium, we show that SO_SCPLOWPICEC_SCPLOWMO_SCPLOWIXC_SCPLOW can enhance the inference of complex cell identities, reveal interpretable spatial metagenes, and uncover differentiation trajectories. SO_SCPLOWPICEC_SCPLOWMO_SCPLOWIXC_SCPLOW is a generalizable framework for analyzing spatial transcriptome data to provide critical insights into the cell type composition and spatial organization of cells in complex tissues. Exo-beta-N-acetylmuramidase NamZ of Bacillus subtilis is the founding member of a family of exo-lytic peptidoglycan hexosaminidases Endo-{beta}-N-acetylmuramidases, commonly known as lysozymes, are well-characterized antimicrobial enzymes that potentially lyse bacterial cells. They catalyze an endo-lytic cleavage of the peptidoglycan, the structural component of the bacterial cell wall; i.e. they hydrolyze glycosidic N-acetylmuramic acid (MurNAc)-{beta}-1,4-N-acetylglucosamine (GlcNAc)-bonds within the heteroglycan backbone of peptidoglycan. In contrast, little is known about exo-{beta}-N-acetylmuramidases, catalyzing an exo-lytic cleavage of {beta}-1,4-MurNAc entities from the non-reducing ends of peptidoglycan chains. Such an enzyme was identified earlier in the bacterium Bacillus subtilis, but the corresponding gene has remained unknown so far. We identified ybbC of B. subtilis, renamed namZ, as encoding the reported exo-{beta}-N-acetylmuramidase. A {Delta}namZ mutant accumulated specific cell wall fragments and showed growth defects under starvation conditions, indicating a role of NamZ in cell wall turnover. Recombinant NamZ protein specifically hydrolyzed the artificial substrate para-nitrophenyl {beta}-MurNAc and the peptidoglycan-derived disaccharide MurNAc-{beta}-1,4-GlcNAc. Together with the exo-{beta}-N-acetylglucosaminidase NagZ and the exo-muramoyl-L-alanine amidase AmiE, NamZ degraded intact peptidoglycan by sequential hydrolysis from the non-reducing ends. NamZ is a member of the DUF1343 protein family of unknown function and shows no significant sequence identity with known glycosidases. A structural model of NamZ revealed a putative active site located in a cleft within the interface of two subdomains, one of which constituting a Rossmann-fold-like domain, unusual for glycosidases. On this basis, we propose that NamZ represents the founding member of a novel family of peptidoglycan hexosaminidases, which is mainly present in the phylum Bacteroidetes and, less frequently, within Firmicutes (Bacilli, Clostridia), Actinobacteria and Gammaproteobacteria. Naming of human diseases on the wrong side of history BackgroundIn the medical sphere, understanding naming conventions strengthen the integrity of naming human diseases remains nominal rather than substantial yet. Since the current nosology-based standard for human diseases could not offer a one-size-fits-all corrective mechanism, many idiomatic but flawed names frequently appear in scientific literature and news outlets at the cost of sociocultural impacts.

ObjectiveWe attempt to examine the ethical oversights of current naming practices and propose heuristic rationales and approaches to determine a pithy name instead of an inopportune nosology.

MethodsFirst, we examined the compiled global online news volumes and emotional tones on some inopportune nosology like German measles, Middle Eastern Respiratory Syndrome, Spanish flu, Hong Kong flu, and Huntingtons disease in the wake of COVID-19. Second, we prototypically scrutinize the lexical dynamics and pathological differentials of German measles and common synonyms by leveraging the capacity of the Google Books Ngram Corpus. Third, we demonstrated the empirical approaches to curate an exclusive substitute for an anachronistic nosology German measles based on deep learning models and post-hoc explanations.

ResultsThe infodemiological study shows that the public informed the offensive names with extremely negative tones in textual and visual narratives. The findings of the historiographical study indicate that many synonyms of German measles did not survive, while German measles became an anachronistic usage, and rubella has taken the dominant place since 1994. The PubMedBERT model could identify rubella as a potential substitution for German measles with the highest semantic similarity. The results of the semantic drift experiments further indicate that rubella tends to survive during the ebb and flow of semantic drift.

ConclusionsOur findings indicate that the nosological evolution of anachronistic names could result in sociocultural impacts without a corrective mechanism. To mitigate such impacts, we introduce some ethical principles for formulating an improved naming scheme. Based on deep learning models and post-hoc explanations, our illustrated experiments could provide hallmark references to the remedial mechanism of naming practices and pertinent credit allocations. Robust and Remote Measurement of Heart Rate Based on A Surveillance Camera Arrhythmia is a marked symptom of many cardiovascular diseases (CVDs). The accurate and timely detection of heart rate can greatly reduce the harm of arrhythmia to people. However, it is still a challenge to robustly and remotely measure heart rate in daily life due to the changing environmental conditions during measurement, such as the varying light intensity, the movement of people, and the uncertain distance between the sensor to people. In this study, we propose a method to accurately measure human heart rate within a distance of 4.5 meters under different light intensities by simply using a surveillance camera. After a 20-second color video of a persons hand is captured by the camera, a method based on the Fast Fourier Transform (FFT) algorithm is designed to extract the blood volume pulse wave to calculate the heart rate. According to the comparison between the real heart rate and results measured by electrocardiography (ECG), the proposed method achieves an accuracy of 95.8% when the measurement is performed within a distance of 4.5 meters and 90% when within 5.0 meters. Our experiments show that when the illuminance varies between 100-1000 lux (lighting level indoor), we still get the correct results. Our experiments also demonstrate that the proposed method accurately obtain heart rate even when the light intensity is below 32 lux (300-500 lux in a workplace environment). The methods strong adaptability to changing environmental conditions makes it applicable to many scenarios, such as homes of the elderly, classrooms, and other public spaces. 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. Protective host-dependent antagonism among 	Pseudomonas in the Arabidopsis phyllosphere The plant microbiome is a rich biotic environment, comprising numerous taxa. The community structure of these colonizers is constrained by multiple factors, including host-microbe and microbe-microbe interactions, as well as the interplay between the two. While much can be learned from pairwise relationships between individual hosts and microbes, or individual microbes with themselves, the ensemble of interrelations between the host and microbial consortia may lead to different outcomes that are not easily predicted from the individual interactions. Their study can thus provide new insights into the complex relationship between plants and microbes. Of particular importance is how strain-specific such plant-microbe-microbe interactions are, and how they eventually affect plant health. Here, we test strain-level interactions in the phyllosphere between groups of co-existing commensal and pathogenic Pseudomonas among each other and with A. thaliana, by employing synthetic communities of genome-barcoded isolates. We found that commensal Pseudomonas prompted a host response leading to a selective inhibition of a specific pathogenic lineage, resulting in plant protection. The extent of plant protection, however, was dependent on plant genotype, indicating that these effects are host-mediated. There were similar genotype-specific effects on the microbe side, as we could pinpoint an individual Pseudomonas isolate as the predominant cause for this differential interaction. Collectively, our work highlights how within-species genetic differences on both the host and microbe side can have profound effects on host-microbe-microbe dynamics. The paradigm that we have established provides a platform for the study of host-dependent microbe-microbe competition and cooperation in the A. thaliana-Pseudomonas system. Population differences in the length and early-life dynamics of telomeres among European pied flycatchers Telomere length and shortening rate are increasingly used as biomarkers for long-term costs in ecological and evolutionary studies because of their relationships with survival and fitness. Both early-life conditions and growth, and later-life stressors can create variation in telomere shortening rate. Studies on between- population telomere length and dynamics are scarce, despite the expectation that populations exposed to varying environmental constraints would present divergent telomere length patterns. The pied flycatcher (Ficedula hypoleuca) is a passerine bird breeding across Eurasia (from Spain to western Siberia) and migrating through the Iberian Peninsula to spend the non-breeding period in sub-Saharan Africa. Thus, different populations show marked differences in migration distance. We studied the large-scale variation of telomere length and early-life dynamics in the pied flycatcher by comparing six European populations across a north- south gradient (Finland, Estonia, England, and Spain) predicting negative effect of migration distance on adult telomere length, and of nestling growth on nestling telomere dynamics. There were clear population differences in telomere length, with English birds from mid-latitudes having the longest telomeres. Telomere length did not thus show consistent latitudinal variation and was not linearly linked to differences in migration distance. Early-life telomere shortening rate tended to vary between populations. Fast growth was associated with shorter telomeres in the early life, but faster nestling growth affected telomeres more negatively in northern than southern populations. While the sources of between-population differences in telomere-related biology remain to be more intensively studied, our study illustrates the need to expand telomere studies at the between-population level. Macroscopic control of synchronous electrical signaling with chemically-excited gene expression Excitable cells can convert electrical signals into chemical outputs to facilitate the active transport of information across larger distances. This electrical-to-chemical conversion requires a tightly regulated expression of ion channels. Alterations of ion channel expression provide landmarks of numerous pathological diseases, such as cardiac arrhythmia, epilepsy, or cancer. Although the activity of ion channels can be locally regulated by external light or chemical stimulus, it remains challenging to coordinate the expression of ion channels on extended spatial-temporal scales in a non-invasive manner. Here, we have engineered yeast S. cerevisiae to read and convert local chemical concentrations into a dynamic electrical field distributed across cell populations. The core mechanism encodes a chemically-excitable dual-feedback gene circuit that precisely tunes the expression domain of potassium channels, globally coordinating cyclic firing of the plasma membrane potential (PMP). We demonstrate that this mechanism leverages an engineered constitutively open bacterial potassium channel KcsA to directly couple chemical stimuli with ion flux through gene expression and it can interface with the host ion channels through the pulsatile production of toxins. Our study provides a robust synthetic transcriptional toolbox underlying the conversion of local chemical environments into spatiotemporally organized electrical impulses for various cellular engineering, synthetic biology, and potential therapeutic applications. A Eukaryotic Circuit for Secrete-and-Sense Autonomy Cancers represent complex autonomous robust systems, displaying interconnectivity with feedback control. Autonomous growth is fueled by a cancer cells ability to  secrete-and-sense growth factors: a poorly understood phenomenon. Using an integrated systems and experimental approach, here we dissect the impact of a feedback-coupled GTPase circuit within the secretory pathway that imparts secretion-coupled autonomy. The circuit is assembled when the Ras-superfamily monomeric GTPase Arf1, and the heterotrimeric GTPase Giabg and their corresponding GAPs and GEFs are coupled by GIV/Girdin, a protein that is known to fuel aggressive traits in diverse cancers. One forward and two key negative feedback loops within the circuit create closed-loop control (CLC), allow the two GTPases to coregulate each other, and convert the expected switch-like behavior of Arf1-dependent secretion into an unexpected dose response alignment behavior of sensing and secretion. Such behavior translates into cell survival that is self-sustained by stimuli-proportionate secretion. Findings highlight how enhanced coupling of two biological switches in cancer cells is critical for multiscale feedback control to achieve secretion-coupled autonomy.

GRAPHIC ABSTRACT

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org.highwire.dtl.DTLVardef@183ff5corg.highwire.dtl.DTLVardef@f21de7org.highwire.dtl.DTLVardef@1893683org.highwire.dtl.DTLVardef@159d966_HPS_FORMAT_FIGEXP  M_FIG C_FIG In BriefThis work delivers an experimentally validated dynamical systems model of the cooperativity between two distinct classes of biological switches in eukaryotic cells and reveals the basis of secretion-coupled cellular autonomy in cancer.

HIGHLIGHTSO_LIModeling and experimental approaches were used to dissect a coupled GTPase circuit
C_LIO_LICoupling enables closed loop feedback and mutual control of GTPases
C_LIO_LICoupling generates dose response alignment behavior of sensing and secretion.
C_LIO_LICoupling is critical for multiscale feedback control to achieve secretion-coupled autonomy.
C_LI PAK1 and PAK2 in cell metabolism regulation P21-activated kinases (PAKs) regulate processes associated with cytoskeletal rearrangements, such as cell division, adhesion, and migration. The possible regulatory role of PAKs in cell metabolism has not been well explored, but increasing evidence suggests that a cell metabolic phenotype is related to cell interactions with the microenvironment. We analyzed the impact of PAK inhibition by small molecule inhibitors, small interfering RNA, or gene knockout on the rates of mitochondrial respiration and aerobic glycolysis. Pharmacological inhibition of PAK group I by IPA-3 induced a strong decrease in metabolic rates in human adherent cancer cell lines, leukemia/lymphoma cell lines, and primary leukemia cells. The immediate effect of FRAX597, which inhibits PAK kinase activity, was moderate, indicating that PAK nonkinase functions are essential for cell metabolism. Selective downregulation or deletion of PAK2 was associated with a shift toward oxidative phosphorylation. Alternatively, PAK1 knockout resulted in increased glycolysis. However, the overall metabolic capacity was not substantially reduced by PAK1 or PAK2 deletion, possibly due to partial redundancy in PAK1/PAK2 regulatory roles or to activation of other compensatory mechanisms. High resolution, serial imaging of early mouse and human liver bud morphogenesis in three dimensions BackgroundLiver organogenesis has thus far served as a paradigm for solid organ formation. The developing liver bud is a well established model of organogenesis, and murine genetic studies demonstrate key molecules involved in key morphogenetic changes. However, the analysis of the liver bud is typically limited to 2D tissue sections, which precludes extensive visualization, quantitation, and analysis. Further, the lack of human liver bud data has further hindered our understanding of human liver organogenesis. Therefore, new analytical and visualization approaches are needed to elicit further morphogenetic details of liver organogenesis and to elucidate differences between mouse and human liver bud growth.

ResultsTo address this need, we focused on high resolution imaging, visualization, and analysis of early liver growth by using available online databases for both mouse (EMAP, Toronto Phenogenomics center) and human (3D Atlas of Human Embryology), noninvasive multimodality imaging studies of the murine embryo, and mouse/human liver weight data. First, we performed three-dimensional (3D reconstructions) of stacked, digital tissue sections that had been initially segmented for the liver epithelium and the septum transversum mesenchyme (STM). 3D reconstruction of both mouse and human data sets enabled visualization and analysis of the dynamics of liver bud morphogenesis, including hepatic cord formation and remodeling, mechanisms of growth, and liver-epithelial STM interactions. These studies demonstrated potentially under-appreciated mechanisms of growth, including rapid exponential growth that is matched at the earliest stages by STM growth, and unique differences between mouse and human liver bud growth. To gain further insight into the exponential liver bud growth that was observed, we plotted volumetric data from 3D reconstruction together with fetal liver growth data from multimodality (optical projection tomography, magnetic resonance imaging, micro-CT) and liver weight data to compose complete growth curves during mouse (E8.5-E18) and human (day 25-300) liver development. For further analysis, we performed curve fitting and parameter estimation, using Gompertzian models, which enables the comparison between mouse and human liver bud growth, as well as comparisons to processes like liver regeneration. To demonstrate the importance of mesenchyme in rapid liver bud growth and morphogenesis in the human liver bud, we performed functional analysis in which human pluripotent stem cell (hPSC)-derived hepatic organoids were used to model collective migration that occurs in vivo, demonstrating that migration is strongly dependent upon mesenchyme.

DiscussionOur data demonstrates improved visualization with 3D images, under-appreciated and potentially new mechanisms of growth, complete liver growth curves with quantitative analysis through embryonic and fetal stages, and a new functional human stem cell-derived liver organoid assay demonstrating mesenchyme-driven collective migration. These data enhance our understanding of liver organogenesis. Do males know? Evidence-driven rainmaking mating strategy by male bonobos to meet the fertile window of females Female bonobos exhibit prolonged receptivity, one suggested function of which is to lower male mating competition. However, it is questionable whether easier access to receptive females can reduce male-male competition, given the exclusive nature of male reproductive success. We tested whether males could determine the fertile phase of females. We found that ovulation probability predicted male mating effort. High-ranking males copulated with females with higher fertility, and male-male agonistic interactions increased when there were fertile females in the party. When there were multiple females with maximal swelling, males concentrated their mating effort on females with an older infant whose maximal swelling started earlier, and they continued mating efforts until detumescence (rainmaking). These findings suggest that male bonobos distinguish between fertile and non-fertile phases of females and that having more receptive females in the party does not reduce male-male competition for fertile females.

TeaserMales use the rainmakers rule to meet the periovulatory phase of the female bonobo for better reproductive success. Mitochondrial pyruvate supports lymphoma proliferation by fueling a non-canonical glutamine metabolism pathway The fate of pyruvate, which is modulated by the activity of the mitochondrial pyruvate carrier (MPC), is a defining metabolic feature in many cancers. Diffuse large B-cell lymphomas (DLBCLs) are a genetically and metabolically heterogeneous cancer. Although MPC expression and activity differed between DLBCL subgroups, mitochondrial pyruvate was uniformly consumed by glutamate pyruvate transaminase 2 (GPT2) to support -ketoglutarate production as part of glutaminolysis. This led us to discover that glutamine exceeds pyruvate as a carbon source for the tricarboxylic acid (TCA) cycle in DLBCLs. Furthermore, we found that MPC inhibition unexpectedly leads to decreased glutaminolysis, which is contrary to previous observations in other cell types. We also discovered that MPC inhibition and depletion only decreased DLBCL proliferation in an extracellular matrix (ECM) environment and in vivo xenografts, but not in the typical DLBCL suspension environment. We also have found that the metabolic profile of DLBCL cells in ECM is markedly different from cells in suspension environment. Thus, we report that besides the canonical glutamate dehydrogenase (GDH)-mediated glutaminolysis, the non-canonical GPT2 mediated consumption and assimilation of glutamine and pyruvate in DLBCLs enables their proliferation in an extracellular environment-dependent manner.

HIGHLIGHTSO_LIGlutamine, but not glucose, is a major carbon source for the tricarboxylic acid cycle in diffuse large B-cell lymphomas.
C_LIO_LIMitochondrial pyruvate supports glutaminolysis in diffuse large B-cell lymphomas by supplying pyruvate for glutamate pyruvate transaminase 2-mediated  -ketoglutarate production.
C_LIO_LIMitochondrial pyruvate carrier inhibition leads to decreased glutaminolysis in diffuse large B-cell lymphomas.
C_LIO_LI -ketoglutarate production is important for diffuse large B-cell lymphoma proliferation in a solid extracellular matrix environment.
C_LIO_LIMitochondrial pyruvate carrier activity supports diffuse large B-cell lymphoma proliferation in a solid extracellular matrix environment and in mouse xenografts.
C_LI How voluntary and involuntary attention differentially shape spatial resolution Attention alters perception across the visual field. Typically, endogenous (voluntary) and exogenous (involuntary) attention similarly improve performance in many visual tasks, but they have differential effects in some tasks. Extant models of visual attention assume that the effects of these two types of attention are identical and consequently do not explain differences between them. Here, we develop a model of spatial resolution and attention that distinguishes between endogenous and exogenous attention. We focus on texture-based segmentation as a model system because it has revealed a clear dissociation between both attention types. For a texture for which performance peaks at parafoveal locations, endogenous attention improves performance across eccentricity, whereas exogenous attention improves performance where the resolution is low (peripheral locations) but impairs it where the resolution is high (foveal locations) for the scale of the texture. Our model emulates sensory encoding to segment figures from their background and predict behavioral performance. To explain attentional effects, endogenous and exogenous attention require separate operating regimes across visual detail (spatial frequency). Our model reproduces behavioral performance across several experiments and simultaneously resolves three unexplained phenomena: (1) the parafoveal advantage in segmentation, (2) the uniform improvements across eccentricity by endogenous attention and (3) the peripheral improvements and foveal impairments by exogenous attention. Overall, we unveil a computational dissociation between each attention type and provide a generalizable framework for predicting their effects on perception across the visual field. FcγR responses to soluble immune complexes are governed by solubility and size Fc-gamma receptor (Fc{gamma}R) activation by soluble IgG immune complexes (sICs) represents a major mechanism of inflammation in certain autoimmune diseases such as systemic lupus erythematosus (SLE). A robust and scalable test system allowing for the detection and quantification of sIC bioactivity is missing. Previously described Fc{gamma}R interaction assays are limited to certain Fc{gamma}Rs, lack scalability and flexibility, are not indicative of receptor activation or lack sensitivity towards sIC size. We developed a comprehensive reporter cell panel detecting individual activation of Fc{gamma}Rs from humans and the mouse. The reporter cell lines were integrated into an assay format that provides flexible read-outs enabling the quantification of sIC reactivity via ELISA or a fast detection using flow cytometry. This identified Fc{gamma}RIIA(H) and Fc{gamma}RIIIA as the most sIC-sensitive Fc{gamma}Rs in our test system. Applying the assay we demonstrate that sICs versus immobilized ICs are fundamentally different Fc{gamma}R-ligands with regard to Fc{gamma}R preference and signal strength. Reaching a detection limit in the very low nanomolar range, the assay proved also to be sensitive to sIC stoichiometry and size enabling for the first time a complete reproduction of the Heidelberger-Kendall precipitation curve in terms of immune receptor activation. Analyzing sera from SLE patients and mouse models of lupus and arthritis proved that sIC-dependent Fc{gamma}R activation has predictive capabilities regarding severity of SLE disease. The new methodology provides a sensitive, scalable and comprehensive tool to evaluate the size, amount and bioactivity of sICs in all settings.

One Sentence SummaryIn this study we established a comprehensive Fc{gamma}R reporter cell assay enabling the detection and quantification of soluble immune complexes generated in experimental and clinical settings.