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Influential theories of motivated reasoning, as well as real-world anecdotal examples, would suggest that voters do not always penalize legislators from their own party for alleged immoral behavior, such as sexual harassment. But very little empirical evidence exists on how voters react to sexual misconduct allegations, especially since the start of the #MeToo movement. We examine how partisanship and sexist attitudes shape individuals’ reactions to sexual harassment allegations about a politician. Using a pretest–posttest online experiment, we randomize both the party affiliation of the accused legislator as well as the severity of the allegations. Overall, we find some evidence of partisan bias, but that there may be a limit. Subjects were more forgiving of an accused co-partisan legislator than a legislator of the opposing party in their overall evaluation and their perceptions of punitive repercussions, but their levels of electoral support decreased just as much for co-partisans as they did for opposing partisans. Importantly, these reactions are strongly conditioned by sexism; as subjects’ levels of sexism increase, the otherwise large and negative effect of allegations on evaluations of favorability and electoral support disappears.

Plant-associated microbiota affect pant growth and development by regulating plant hormones homeostasis. Indole-3-acetic acid (IAA), a well-known plant hormone, can be produced by various plant-associated bacteria. However, the prevalence of bacteria with the capacity to degrade IAA in the rhizosphere has not been systematically studied. In this study, we analyzed the IAA degradation capabilities of bacterial isolates from the roots of Arabidopsis and rice. Using genomics analysis and in vitro assays, we found that 21 out of 183 taxonomically diverse bacterial isolates possess the ability to degrade IAA. Through comparative genomics and transcriptomic assays, we identified iac-like or iad-like operon in the genomes of these IAA degraders. Additionally, the putative regulator of the operon was found to be highly conserved among these strains through protein structure similarity analysis. Some of the IAA degraders could utilize IAA as their carbon and energy source. In planta, most of the IAA degrading strains mitigated Arabidopsis and rice seedling root growth inhibition (RGI) triggered by exogenous IAA. Moreover, RGI caused by complex synthetic bacterial community can be alleviated by introducing IAA degraders. Importantly, we observed increased colonization preference of IAA degraders from soil to root according to the frequency of the biomarker genes in metagenome-assembled genomes (MAGs) collected from different habitats, suggesting that there is a close association between IAA degraders and IAA producers. In summary, our findings further the understanding of the functional diversity and potential biological roles of plant-associated bacteria in host plant root morphogenesis.

Abstract Plasmids are pivotal in driving bacterial evolution through horizontal gene transfer. Here, we investigated 3467 human gut microbiome samples across continents and disease states, analyzing 11,086 plasmids. Our analyses reveal that plasmid dispersal is predominantly stochastic, indicating neutral processes as the primary driver of their wide distribution. We find that only 20-25% of plasmid DNA is being selected in various disease states, constraining its distribution across hosts. Selective pressures shape specific plasmid segments with distinct ecological functions, influenced by plasmid mobilization lifestyle, antibiotic usage, and inflammatory gut diseases. Notably, these elements are more commonly shared within groups of individuals with similar health conditions, such as Inflammatory Bowel Disease (IBD), regardless of geographic location across continents. These segments contain essential genes such as iron transport mechanisms- a distinctive gut signature of IBD that impacts the severity of inflammation. Our findings shed light on mechanisms driving plasmid dispersal and selection in the human gut, highlighting their role as carriers of vital gene pools impacting bacterial hosts and ecosystem dynamics.

Abstract Background Dogs with degenerative mitral valve disease are commonly presented to small animal clinicians. Diagnosis, clinical staging, and therapeutic design are based on a combination of clinical examination, radiography, and echocardiography. To support diagnosis and clinical monitoring, a multi-marker-based approach would be conceivable. The aim of this study was to investigate the suitability of Galectin-3 and interleukin-1 receptor-like 1 protein (ST2) in dogs with degenerative mitral valve disease in accordance with N-terminal-prohormone-B-type natriuretic peptide (NT-proBNP) and cardiac troponin I (cTnI). For this purpose, serum concentrations of Galectin-3 and ST2 of 64 dogs with different stages of mitral valve disease and 21 dogs without cardiac disease were analyzed at the first examination and six months later. Echocardiography, blood cell count and clinical chemistry were performed and established biomarkers NT-proBNP and cTnI were measured additionally. Differences in the biomarker concentrations between all groups at both timepoints and the change in biomarker concentrations from first to second evaluation was investigated. Furthermore, correlations of each biomarker, between biomarkers and echocardiographic measurements, were calculated. Finally, the receiver-operating characteristic curve and the area under the curve analysis were performed to differentiate between disease stages and controls. Results Serum concentrations of Galectin-3 and ST2 were not statistically different between canine patients in the respective stages of mitral valve disease or in comparison to dogs in the control group at any timepoint. A significant increase in ST2 concentrations from the baseline to the follow-up examination was observed in dogs classified as stage B1 and the control group. The concentrations of NT-proBNP and cTnI in stage C dogs were significantly increased in comparison to the other groups. Conclusions In this study, no relation between Galectin-3 and ST2 levels to the presence or stage of mitral valve disease could be detected. Nevertheless, considering the increase in ST2 concentrations from the first to second measurement, its value on monitoring disease progress could be feasible. In agreement with previous studies, NT-proBNP and cTnI have once more proven their utility in assessing disease severity. The approach of examining new cardiac biomarkers in dogs is still worth pursuing.

Detection of moving sources over a complicated background is important for several reasons. First is measuring the astrophysical motion of the source. Second is that such motion resulting from atmospheric scintillation, color refraction, or astrophysical reasons is a major source of false alarms for image-subtraction methods. We extend the Zackay, Ofek, and Gal-Yam image-subtraction formalism to deal with moving sources. The new method, named the translient (translational transient) detector, applies hypothesis testing between the hypothesis that the source is stationary and that the source is moving. It can be used to detect source motion or to distinguish between stellar variability and motion. For moving source detection, we show the superiority of translient over the proper image subtraction, using the improvement in the receiver-operating characteristic curve. We show that in the small translation limit, translient is an optimal detector of point-source motion in any direction. Furthermore, it is numerically stable, fast to calculate, and presented in a closed form. Efficient transient detection requires both the proper image-subtraction statistics and the translient statistics: When the translient statistic is higher, then the subtraction residual is likely due to motion. We test our algorithm both on simulated data and on real images obtained by the Large Array Survey Telescope. We demonstrate the ability of translient to distinguish between motion and variability, which has the potential to reduce the number of false alarms in transients detection. We provide the translient implementation in Python and MATLAB.

ABSTRACT Predicting interspecies interactions is a key challenge in microbial ecology given that interactions shape the composition and functioning of microbial communities. However, predicting microbial interactions is challenging because they can vary considerably depending on species’ metabolic capabilities and environmental conditions. Here, we employ machine learning models to predict pairwise interactions between culturable bacteria based on their phylogeny, monoculture growth capabilities, and interactions with other species. We trained our models on one of the largest available pairwise interactions data set containing over 7,500 interactions between 20 species from two taxonomic groups that were cocultured in 40 different carbon environments. Our models accurately predicted both the sign (accuracy of 88%) and the strength of effects (R2 of 0.87) species had on each other’s growth. Encouragingly, predictions with comparable accuracy could be made even when not relying on information about interactions with other species, which are often hard to measure. However, species’ monoculture growth was essential to the model, as predictions based solely on species’ phylogeny and inferred metabolic capabilities were significantly less accurate. These results bring us one step closer to a predictive understanding of microbial communities, which is essential for engineering beneficial microbial consortia. IMPORTANCE In order to understand the function and structure of microbial communities, one must know all pairwise interactions that occur between the different species within the community, as these interactions shape the community’s structure and functioning. However, measuring all pairwise interactions can be an extremely difficult task especially when dealing with big complex communities. Because of that, predicting interspecies interactions is a key challenge in microbial ecology. Here, we use machine learning models in order to accurately predict the type and strength of interactions. We trained our models on one of the largest available pairwise interactions data set, containing over 7,500 interactions between 20 different species that were cocultured in 40 different environments. Our results show that, in general, accurate predictions can be made, and that the ability of each species to grow on its own in the given environment contributes the most to predictions. Being able to predict microbial interactions would put us one step closer to predicting the functionality of microbial communities and to rationally microbiome engineering.

Microorganisms are found in diverse communities whose structure and function are determined by interspecific interactions. Just as single species seldom exist in isolation, communities as a whole are also constantly challenged and affected by external species. Though much work has been done on characterizing how individual species affect each other through pairwise interactions, the joint effects of multiple species on a single (focal) species remain underexplored. As such, it is still unclear how single-species effects combine to a community-level effect on a species of interest. To explore this relationship, we assayed thousands of communities of two, three, and four bacterial species, measuring the effect of single, pairs of, and trios of 61 affecting species on six different focal species. We found that when multiple species each have a negative effect on a focal species, their joint effect is typically not given by the sum of the effects of individual affecting species. Rather, they are dominated by the strongest individual-species effect. Therefore, while joint effects of multiple species are often non-additive, they can still be derived from the effects of individual species, making it plausible to map complex interaction networks based on pairwise measurements. This finding is important for understanding the fate of species introduced into an occupied environment and is relevant for applications in medicine and agriculture, such as probiotics and biocontrol agents, as well as for ecological questions surrounding migrating and invasive species.

Microbial communities employ a variety of strategies to compete against competitors sharing their niche, for instance, by producing antibiotics. This study reveals that antibiotics produced by Bacillus subtilis act synergistically to eliminate phylogenetically distinct competitors and are regulated accordingly.

Abstract Background Pimobendan is a widely used medication for the treatment of dogs with congestive heart failure (CHF) and preclinical degenerative mitral valve disease (DMVD) with cardiomegaly. The benefit of a treatment in dogs with preclinical DMVD but without cardiomegaly has not yet been elucidated. Some positive effects concerning life quality and a decrease in cardiac biomarkers could be verified. This study aimed to further investigate these results using a placebo-controlled double-blinded crossover design. Out of a total of 15 dogs, eight were allocated to sequence-group AB, in which dogs received pimobendan (A) during the first treatment period and placebo (B) during the second period. Accordingly, sequence-group BA was treated first with placebo followed by pimobendan. Each treatment period lasted six months and included a baseline investigation and follow-ups after 90 and 180 days. The investigations included a questionnaire completed by the owners, echocardiographic examination, and measurements of NT-proBNP, cTnI and lactate before and after a standardised submaximal exercise test. Results NT-proBNP values decreased significantly during the treatment period with pimobendan, and the post-exercise increase was attenuated at day 180. No significant treatment effects could be verified for cTnI and lactate, neither pre- nor post-exercise. Left ventricular size decreased under treatment, whereas no significant changes in left atrial size were detected. The owners described their dogs under treatment with pimobendan as being more active at day 90 (11/15) and day 180 (12/15). Those animals treated with placebo were described as being more active at day 90 (2/15) and day 180 (5/15). Conclusions Pimobendan had reducing effects on the concentrations of pre- and post-exercise cardiac biomarkers and the size of the left ventricle in dogs with DMVD ACVIM B1. Exercise testing in addition to an assessment of cardiac biomarkers might improve the decision when to initiate pimobendan treatment in dogs with DMVD.

We propose a physical mechanism of conformation-induced proton pumping in mitochondrial Complex I. The structural conformations of this protein are modeled as the motion of a piston having positive charges on both sides. A negatively charged electron attracts the piston, moving the other end away from the proton site, thereby reducing its energy and allowing a proton to populate the site. When the electron escapes, elastic forces assist the return of the piston, increasing proton site energy and facilitating proton transfer. We derive the Heisenberg equations of motion for electron and proton operators and rewrite them in the form of rate equations coupled to the phenomenological Langevin equation describing piston dynamics. This set of coupled equations is solved numerically. We show that proton pumping can be achieved within this model for a reasonable set of parameters. The dependencies of proton current on geometry, temperature, and other parameters are examined.

ABSTRACT Antibiotic-resistant microbial pathogens are becoming a major threat to human health. Therefore, there is an urgent need to develop new alternatives to conventional antibiotics. One such promising alternative is antimicrobial peptides (AMPs), which are produced by virtually all organisms and typically inhibit bacteria via membrane disruption. However, previous studies demonstrated that bacteria can rapidly develop AMP resistance. Here, we study whether combination therapy, known to be able to inhibit the evolution of resistance to conventional antibiotics, can also hinder the evolution of AMP resistance. To do so, we evolved the opportunistic pathogen Staphylococcus aureus in the presence of individual AMPs, AMP pairs, and a combinatorial antimicrobial peptide library. Treatment with some AMP pairs indeed hindered the evolution of resistance compared with individual AMPs. In particular, resistance to pairs was delayed when resistance to the individual AMPs came at a cost of impaired bacterial growth and did not confer cross-resistance to other tested AMPs. The lowest level of resistance evolved during treatment with the combinatorial antimicrobial peptide library termed random antimicrobial peptide mixture, which contains more than a million different peptides. A better understanding of how AMP combinations affect the evolution of resistance is a crucial step in order to design “resistant proof” AMP cocktails that will offer a sustainable treatment option for antibiotic-resistant pathogens. IMPORTANCE The main insights gleaned from this study are the following. (i) AMP combination treatment can delay the evolution of resistance in S. aureus. Treatment with some AMP pairs resulted in significantly lower resistance then treatment with either of the individual AMPs. Treatment with a random AMP library resulted in no detectable resistance. (ii) The rate at which resistance to combination arises correlates with the cost of resistance to individual AMPs and their cross-resistance. In particular, combinations to which the least resistance arose involved AMPs with high fitness cost of resistance and low cross-resistance. (iii) No broad-range AMP resistance evolved. Strains that evolved resistance to some AMPs typically remained sensitive to other AMPs, alleviating concerns regarding the evolution of resistance to immune system AMPs in response to AMP treatment.

Evolution affects microbial community composition, but it is still unknown how commonly compositions change, and how predictable such changes are. Using experimental evolution, Meroz et al. show that compositional changes typically occur within ~400 generations, and are predictable by a bottom-up approach.

Here, the authors develop a genome evolution model to investigate the origin of functional redundancy in the human microbiome by analyzing its genomic content network and illustrate potential ecological and evolutionary processes that may contribute to its resilience.

The NBA has undergone formative changes since commissioner David Stern began his tenure. Stern has endeavored to make the NBA a consumer-friendly and marketable league by implementing sanctions on physical violence. This study takes a closer look at Stern's efforts by examining the interplay between two forms of violence in NBA basketball players on the court: "old fashioned" physical violence (PV) and symbolic violence (SV). Of the 117 NBA finals broadcast for twenty years from 1998 to 2018, a stratified random sample (36 games or 30.8%) of the violations and commentators' comments were coded, providing a wide perspective on forms of violence over time. The findings reveal that although the number of PV incidents decreased, SV increased starting in 2014, to the extent that SV incidents were more frequent than PV. A thematic analysis of the commentators' remarks associated with these incidents showed that they support and encourage PV, whereas SV tends to be perceived as harmless and therefore permissible to ignore. Unlike PV, SV is not perceived to be as worthy of media coverage. The relative lack of commentator interest is indicative of the lack of "glamour" of SV in the NBA league. It is suggested that since viewers of professional sports often emulate the players, the increase of SV within the NBA is likely to be mirrored in fans in their everyday lives and in amateur basketball players. Although the rise in SV causes fewer physical injuries in professional basketball players, it nevertheless can cause psychological harm.

The US government invests substantial sums to control the HIV/AIDS epidemic. To monitor progress toward epidemic control, PEPFAR, or the President’s Emergency Plan for AIDS Relief, oversees a data reporting system that includes standard indicators, reporting formats, information systems, and data warehouses. These data, reported quarterly, inform understanding of the global epidemic, resource allocation, and identification of trouble spots. PEPFAR has developed tools to assess the quality of data reported. These tools made important contributions but are limited in the methods used to identify anomalous data points. The most advanced consider univariate probability distributions, whereas correlations between indicators suggest a multivariate approach is better suited. For temporal analysis, the same tool compares values to the averages of preceding periods, though does not consider underlying trends and seasonal factors. To that end, we apply two methods to identify anomalous data points among routinely collected facility-level HIV/AIDS data. One approach is Recommender Systems, an unsupervised machine learning method that captures relationships between users and items. We apply the approach in a novel way by predicting reported values, comparing predicted to reported values, and identifying the greatest deviations. For a temporal perspective, we apply time series models that are flexible to include trend and seasonality. Results of these methods were validated against manual review (95% agreement on non-anomalies, 56% agreement on anomalies for recommender systems; 96% agreement on non-anomalies, 91% agreement on anomalies for time series). This tool will apply greater methodological sophistication to monitoring data quality in an accelerated and standardized manner.

Climate change is having significant impacts on Earth’s ecosystems and carbon budgets, and in the Arctic may drive a shift from an historic carbon sink to a source. Large uncertainties in terrestrial biosphere models (TBMs) used to forecast Arctic changes demonstrate the challenges of determining the timing and extent of this possible switch. This spread in model predictions can limit the ability of TBMs to guide management and policy decisions. One of the most influential sources of model uncertainty is model parameterization. Parameter uncertainty results in part from a mismatch between available data in databases and model needs. We identify that mismatch for three TBMs, DVM-DOS-TEM, SIPNET and ED2, and four databases with information on Arctic and boreal above- and belowground traits that may be applied to model parametrization. However, focusing solely on such data gaps can introduce biases towards simple models and ignores structural model uncertainty, another main source for model uncertainty. Therefore, we develop a causal loop diagram (CLD) of the Arctic and boreal ecosystem that includes unquantified, and thus unmodeled, processes. We map model parameters to processes in the CLD and assess parameter vulnerability via the internal network structure. One important substructure, feed forward loops (FFLs), describe processes that are linked both directly and indirectly. When the model parameters are data-informed, these indirect processes might be implicitly included in the model, but if not, they have the potential to introduce significant model uncertainty. We find that the parameters describing the impact of local temperature on microbial activity are associated with a particularly high number of FFLs but are not constrained well by existing data. By employing ecological models of varying complexity, databases, and network methods, we identify the key parameters responsible for limited model accuracy. They should be prioritized for future data sampling to reduce model uncertainty.

Summary:. Bullous pemphigoid is an autoimmune blistering disease where patients suffer from painful bullae, often covering large portions of the skin and requiring management with immune-suppression. Our case report of recurring bullous pemphigoid illustrates the importance of considering immunosuppressive perioperative management in patients with a history of autoimmune blistering even when the disease has been quiescent for some time. With multidisciplinary care and immune suppressive therapies in the perioperative period, a free flap complicated by recurrent bullous pemphigoid can be salvaged.

Environmental stress can affect the outcome of ecological competition. Here, the authors use theory and experiments with a synthetic microbial community to show that a tradeoff between growth rate and competitive ability determines which species prevails when the population faces variable mortality rates.

Dogs suffering from Myxomatous Mitral Valve Disease (MMVD) show a potential heart enlargement, especially in the left atrium, detectable by radiography. Due to digital radiography, different radiographic measurements estimate cardiac size quite uncomplicatedly. The Vertebral Heart Size (VHS), Radiographic Left Atrial Dimension (RLAD), Left Atrial Width (LAWidth), and the Vertebral Left Atrial Size (VLAS) used anatomical landmarks for measuring cardiac size in relation to the vertebral column. This study aimed to compare VHS, RLAD, LAWidth, and VLAS measured in conventional and inverted radiographs by veterinarians with different levels of experience in healthy dogs and dogs with MMVD. The reliability and user-friendliness of these measurements were evaluated, and the staging was compared to the echocardiography staging. A total of 50 unaffected dogs and 150 dogs with MMVD in stages B1, B2, and C were assessed. Three veterinarians with different levels of experience examined 200 conventional radiographs and their corresponding inverted radiographs blinded to the echocardiographic and clinical examination results. Analyses were performed to compare the measurements’ grading and determine anatomical landmarks with measurement difficulties. Additionally, inter- and intraobserver agreement was assessed using intraclass correlation coefficient, and the agreement between radiographic and echocardiographic staging was compared using the kappa coefficient. The VHS, LAWidth, and VLAS were easier to define than the RLAD. The interobserver agreement was almost perfect for VHS (0.962) and good for the other radiographic measurements (RLAD: 0.778, LAWidth: 0.772, VLAS: 0.858). The VHS assigned the most dogs to the correct stage. However, VHS, RLAD, LAWidth, and VLAS presented an almost perfect intraobserver agreement. The dorsal left atrial margin of the RLAD was the most difficult measurement point to identify. The VHS is the most reproducible radiographic method for measuring the canine heart size and shows the highest agreement with echocardiography. An observer-related influence could be detected for RLAD, LAWidth, and VLAS.

Introduction: The intraosseous (IO) route is one of the primary means of vascular access in critically ill and injured patients. The most common sites used are the proximal humerus, proximal tibia, and sternum. Sternal IO placement remains an often-overlooked option in emergency and prehospital medicine. Due to the conflicts in Afghanistan and Iraq the use of sternal IOs have increased. Methods: The authors conducted a limited review, searching PubMed and Google Scholar databases for “sternal IO,” “sternal intraosseous,” and “intraosseous” without specific date limitations. A total of 47 articles were included in this review. Results: Sternal IOs are currently FDA approved for ages 12 and older. Sternal IO access offers several anatomical, pharmacokinetic, hemodynamic, and logistical advantages over peripheral intravenous and other IO points of access. Sternal IO use carries many of the same risks and limitations as the humeral and tibial sites. Sternal IO gravity flow rates are sufficient for transfusing blood and resuscitation. In addition, studies demonstrated they are safe during active CPR. Conclusion: The sternal IO route remains underutilized in civilian settings. When considering IO vascular access in adults or older children, medical providers should consider the sternum as the recommended IO access, particularly if the user is a novice with IO devices, increased flow rates are required, the patient has extremity trauma, or administration of a lipid soluble drug is anticipated.

Dysfunction of the mitochondrial electron transport chain (mETC) is a major cause of human mitochondrial diseases. To identify determinants of mETC function, we screened a genome-wide human CRISPRi library under oxidative metabolic conditions with selective inhibition of mitochondrial Complex III and identified ovarian carcinoma immunoreactive antigen (OCIA) domain-containing protein 1 (OCIAD1) as a Complex III assembly factor. We find that OCIAD1 is an inner mitochondrial membrane protein that forms a complex with supramolecular prohibitin assemblies. Our data indicate that OCIAD1 is required for maintenance of normal steady-state levels of Complex III and the proteolytic processing of the catalytic subunit cytochrome c1 (CYC1). In OCIAD1 depleted mitochondria, unprocessed CYC1 is hemylated and incorporated into Complex III. We propose that OCIAD1 acts as an adaptor within prohibitin assemblies to stabilize and/or chaperone CYC1 and to facilitate its proteolytic processing by the IMMP2L protease.

Positive interactions, including intraspecies cooperation and interspecies mutualisms, play crucial roles in shaping the structure and function of many ecosystems, ranging from plant communities to the human microbiome. While the evolutionary forces that form and maintain positive interactions have been investigated extensively, the influence of positive interactions on the ability of species to adapt to new environments is still poorly understood. Here, we use numerical simulations and theoretical analyses to study how positive interactions impact the likelihood that populations survive after an environment deteriorates, such that survival in the new environment requires quick adaptation via the rise of new mutants-a scenario known as evolutionary rescue. We find that the probability of evolutionary rescue in populations engaged in positive interactions is reduced significantly. In cooperating populations, this reduction is largely due to the fact that survival may require at least a minimal number of individuals, meaning that adapted mutants must arise and spread before the population declines below this threshold. In mutualistic populations, the rescue probability is decreased further due to two additional effects-the need for both mutualistic partners to adapt to the new environment, and competition between the two species. Finally, we show that the presence of cheaters reduces the likelihood of evolutionary rescue even further, making it extremely unlikely. These results indicate that while positive interactions may be beneficial in stable environments, they can hinder adaptation to changing environments and thereby elevate the risk of population collapse. Furthermore, these results may hint at the selective pressures that drove co-dependent unicellular species to form more adaptable organisms able to differentiate into multiple phenotypes, including multicellular life.

The effect of environmental fluctuations is a major question in ecology. While it is widely accepted that fluctuations and other types of disturbances can increase biodiversity, there are fewer examples of other types of outcomes in a fluctuating environment. Here we explore this question with laboratory microcosms, using cocultures of two bacterial species, P. putida and P. veronii. At low dilution rates we observe competitive exclusion of P. veronii, whereas at high dilution rates we observe competitive exclusion of P. putida. When the dilution rate alternates between high and low, we do not observe coexistence between the species, but rather alternative stable states, in which only one species survives and initial species' fractions determine the identity of the surviving species. The Lotka-Volterra model with a fluctuating mortality rate predicts that this outcome is independent of the timing of the fluctuations, and that the time-averaged mortality would also lead to alternative stable states, a prediction that we confirm experimentally. Other pairs of species can coexist in a fluctuating environment, and again consistent with the model we observe coexistence in the time-averaged dilution rate. We find a similar time-averaging result holds in a three-species community, highlighting that simple linear models can in some cases provide powerful insight into how communities will respond to environmental fluctuations.

Response to comments by George Baca, Christian Giordano, Giacomo Loperfido and Piero Vereni on Jonathan Friedman, Politicamente corretto. Il conformismo morale come regime, edited by Piero Zanini, translation by Francesca Nicola and Piero Zanini, Milano, Meltemi, 2018, pp. 348

Abstract Background Oleate-enriched triacylglycerides are well-suited for lubricant applications that require high oxidative stability. Fatty acid carbon chain length and degree of desaturation are key determinants of triacylglyceride properties and the ability to manipulate fatty acid composition in living organisms is critical to developing a source of bio-based oil tailored to meet specific application requirements. Results We sought to engineer the oleaginous yeast Yarrowia lipolytica for production of high-oleate triacylglyceride oil. We studied the effect of deletions and overexpressions in the fatty acid and triacylglyceride synthesis pathways to identify modifications that increase oleate levels. Oleic acid accumulation in triacylglycerides was promoted by exchanging the native ∆9 fatty acid desaturase and glycerol-3-phosphate acyltransferase with heterologous enzymes, as well as deletion of the Δ12 fatty acid desaturase and expression of a fatty acid elongase. By combining these engineering steps, we eliminated polyunsaturated fatty acids and created a Y. lipolytica strain that accumulates triglycerides with > 90% oleate content. Conclusions High-oleate content and lack of polyunsaturates distinguish this triacylglyceride oil from plant and algal derived oils. Its composition renders the oil suitable for applications that require high oxidative stability and further demonstrates the potential of Y. lipolytica as a producer of tailored lipid profiles.