BMAL1-Driven Tissue Clocks Respond Independently to Light to Maintain Homeostasis.

Circadian rhythms control organismal physiology throughout the day. At the cellular level, clock regulation is established by a self-sustained Bmal1-dependent transcriptional oscillator network. However, it is still unclear how different tissues achieve a synchronized rhythmic physiology. That is, do they respond independently to environmental signals, or require interactions with each other to do so? We show that unexpectedly, light synchronizes the Bmal1-dependent circadian machinery in single tissues in the absence of Bmal1 in all other tissues. Strikingly, light-driven tissue autonomous clocks occur without rhythmic feeding behavior and are lost in constant darkness. Importantly, tissue-autonomous Bmal1 partially sustains homeostasis in otherwise arrhythmic and prematurely aging animals. Our results therefore support a two-branched model for the daily synchronization of tissues: an autonomous response branch, whereby light entrains circadian clocks without any commitment of other Bmal1-dependent clocks, and a memory branch using other Bmal1-dependent clocks to "remember" time in the absence of external cues.

Defining the Independence of the Liver Circadian Clock.

Mammals rely on a network of circadian clocks to control daily systemic metabolism and physiology. The central pacemaker in the suprachiasmatic nucleus (SCN) is considered hierarchically dominant over peripheral clocks, whose degree of independence, or tissue-level autonomy, has never been ascertained in vivo. Using arrhythmic Bmal1-null mice, we generated animals with reconstituted circadian expression of BMAL1 exclusively in the liver (Liver-RE). High-throughput transcriptomics and metabolomics show that the liver has independent circadian functions specific for metabolic processes such as the NAD+ salvage pathway and glycogen turnover. However, although BMAL1 occupies chromatin at most genomic targets in Liver-RE mice, circadian expression is restricted to ∼10% of normally rhythmic transcripts. Finally, rhythmic clock gene expression is lost in Liver-RE mice under constant darkness. Hence, full circadian function in the liver depends on signals emanating from other clocks, and light contributes to tissue-autonomous clock function.

Regulatory T cells function in established systemic inflammation and reverse fatal autoimmunity.

The immunosuppressive function of regulatory T (Treg) cells is dependent on continuous expression of the transcription factor Foxp3. Foxp3 loss of function or induced ablation of Treg cells results in a fatal autoimmune disease featuring all known types of inflammatory responses with every manifestation stemming from Treg cell paucity, highlighting a vital function of Treg cells in preventing fatal autoimmune inflammation. However, a major question remains whether Treg cells can persist and effectively exert their function in a disease state, where a broad spectrum of inflammatory mediators can either inactivate Treg cells or render innate and adaptive pro-inflammatory effector cells insensitive to suppression. By reinstating Foxp3 protein expression and suppressor function in cells expressing a reversible Foxp3 null allele in severely diseased mice, we found that the resulting single pool of rescued Treg cells normalized immune activation, quelled severe tissue inflammation, reversed fatal autoimmune disease and provided long-term protection against them. Thus, Treg cells are functional in settings of established broad-spectrum systemic inflammation and are capable of affording sustained reset of immune homeostasis.

The genotype of barley cultivars influences multiple aspects of their associated microbiota via differential root exudate secretion.

Plant-associated microbes play vital roles in promoting plant growth and health, with plants secreting root exudates into the rhizosphere to attract beneficial microbes. Exudate composition defines the nature of microbial recruitment, with different plant species attracting distinct microbiota to enable optimal adaptation to the soil environment. To more closely examine the relationship between plant genotype and microbial recruitment, we analysed the rhizosphere microbiomes of landrace (Chevallier) and modern (NFC Tipple) barley (Hordeum vulgare) cultivars. Distinct differences were observed between the plant-associated microbiomes of the 2 cultivars, with the plant-growth promoting rhizobacterial genus Pseudomonas substantially more abundant in the Tipple rhizosphere. Striking differences were also observed between the phenotypes of recruited Pseudomonas populations, alongside distinct genotypic clustering by cultivar. Cultivar-driven Pseudomonas selection was driven by root exudate composition, with the greater abundance of hexose sugars secreted from Tipple roots attracting microbes better adapted to growth on these metabolites and vice versa. Cultivar-driven selection also operates at the molecular level, with both gene expression and the abundance of ecologically relevant loci differing between Tipple and Chevallier Pseudomonas isolates. Finally, cultivar-driven selection is important for plant health, with both cultivars showing a distinct preference for microbes selected by their genetic siblings in rhizosphere transplantation assays.

Correction: Plasmids manipulate bacterial behaviour through translational regulatory crosstalk.

[This corrects the article DOI: 10.1371/journal.pbio.3001988.].

Aquatic foods to nourish nations.

Despite contributing to healthy diets for billions of people, aquatic foods are often undervalued as a nutritional solution because their diversity is often reduced to the protein and energy value of a single food type ('seafood' or 'fish')1-4. Here we create a cohesive model that unites terrestrial foods with nearly 3,000 taxa of aquatic foods to understand the future impact of aquatic foods on human nutrition. We project two plausible futures to 2030: a baseline scenario with moderate growth in aquatic animal-source food (AASF) production, and a high-production scenario with a 15-million-tonne increased supply of AASFs over the business-as-usual scenario in 2030, driven largely by investment and innovation in aquaculture production. By comparing changes in AASF consumption between the scenarios, we elucidate geographic and demographic vulnerabilities and estimate health impacts from diet-related causes. Globally, we find that a high-production scenario will decrease AASF prices by 26% and increase their consumption, thereby reducing the consumption of red and processed meats that can lead to diet-related non-communicable diseases5,6 while also preventing approximately 166 million cases of inadequate micronutrient intake. This finding provides a broad evidentiary basis for policy makers and development stakeholders to capitalize on the potential of aquatic foods to reduce food and nutrition insecurity and tackle malnutrition in all its forms.

Reinforcement learning informs optimal treatment strategies to limit antibiotic resistance.

Antimicrobial resistance was estimated to be associated with 4.95 million deaths worldwide in 2019. It is possible to frame the antimicrobial resistance problem as a feedback-control problem. If we could optimize this feedback-control problem and translate our findings to the clinic, we could slow, prevent, or reverse the development of high-level drug resistance. Prior work on this topic has relied on systems where the exact dynamics and parameters were known a priori. In this study, we extend this work using a reinforcement learning (RL) approach capable of learning effective drug cycling policies in a system defined by empirically measured fitness landscapes. Crucially, we show that it is possible to learn effective drug cycling policies despite the problems of noisy, limited, or delayed measurement. Given access to a panel of 15 [Formula: see text]-lactam antibiotics with which to treat the simulated Escherichia coli population, we demonstrate that RL agents outperform two naive treatment paradigms at minimizing the population fitness over time. We also show that RL agents approach the performance of the optimal drug cycling policy. Even when stochastic noise is introduced to the measurements of population fitness, we show that RL agents are capable of maintaining evolving populations at lower growth rates compared to controls. We further tested our approach in arbitrary fitness landscapes of up to 1,024 genotypes. We show that minimization of population fitness using drug cycles is not limited by increasing genome size. Our work represents a proof-of-concept for using AI to control complex evolutionary processes.

Characterizing pathways of seafood access in small island developing states.

Ensuring healthy and sustainable food systems in increasing social, economic, and ecological change is a key global priority to protect human and environmental health. Seafood is an essential component of these food systems and a critical source of nutrients, especially in coastal communities. However, despite rapid transformations in aquatic food systems, and our urgent need to understand them, there is a dearth of data connecting harvested food production to actualized food consumption. Many analyses suggest institutional, legal, or technological innovations to improve food systems, but few have analyzed the pathways through which people already gain access to nutritious food. Here, using a random forest model and cluster analysis of a nationally representative data set from Kiribati, we operationalize access theory to trace the flows of consumptive benefit in a fisheries-based food system. We demonstrate that the market access mechanism is the key mechanism mediating seafood access in Kiribati, but importantly, the highest seafood consumption households showed lower market access, pointing to the importance of non-market acquisition (e.g., home production and gifting). We reveal six distinct household strategies that employ different sets of access mechanisms to ensure high levels of local seafood consumption in different contexts. We demonstrate the impacts of these strategies on the composition of household seafoods consumed, stressing the need to support these existing successful strategies. Finally, we point to key policy and management insights (e.g., improved infrastructure, shifts in species management) that may be more effective in reinforcing these existing pathways than commonly proposed food system interventions.

Plasmids manipulate bacterial behaviour through translational regulatory crosstalk.

Beyond their role in horizontal gene transfer, conjugative plasmids commonly encode homologues of bacterial regulators. Known plasmid regulator homologues have highly targeted effects upon the transcription of specific bacterial traits. Here, we characterise a plasmid translational regulator, RsmQ, capable of taking global regulatory control in Pseudomonas fluorescens and causing a behavioural switch from motile to sessile lifestyle. RsmQ acts as a global regulator, controlling the host proteome through direct interaction with host mRNAs and interference with the host's translational regulatory network. This mRNA interference leads to large-scale proteomic changes in metabolic genes, key regulators, and genes involved in chemotaxis, thus controlling bacterial metabolism and motility. Moreover, comparative analyses found RsmQ to be encoded on a large number of divergent plasmids isolated from multiple bacterial host taxa, suggesting the widespread importance of RsmQ for manipulating bacterial behaviour across clinical, environmental, and agricultural niches. RsmQ is a widespread plasmid global translational regulator primarily evolved for host chromosomal control to manipulate bacterial behaviour and lifestyle.

Fourth Dose of BNT162b2 mRNA Covid-19 Vaccine in a Nationwide Setting.

BACKGROUND: With large waves of infection driven by the B.1.1.529 (omicron) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), alongside evidence of waning immunity after the booster dose of coronavirus disease 2019 (Covid-19) vaccine, several countries have begun giving at-risk persons a fourth vaccine dose. METHODS: To evaluate the early effectiveness of a fourth dose of the BNT162b2 vaccine for the prevention of Covid-19-related outcomes, we analyzed data recorded by the largest health care organization in Israel from January 3 to February 18, 2022. We evaluated the relative effectiveness of a fourth vaccine dose as compared with that of a third dose given at least 4 months earlier among persons 60 years of age or older. We compared outcomes in persons who had received a fourth dose with those in persons who had not, individually matching persons from these two groups with respect to multiple sociodemographic and clinical variables. A sensitivity analysis was performed with the use of parametric Poisson regression. RESULTS: The primary analysis included 182,122 matched pairs. Relative vaccine effectiveness in days 7 to 30 after the fourth dose was estimated to be 45% (95% confidence interval [CI], 44 to 47) against polymerase-chain-reaction-confirmed SARS-CoV-2 infection, 55% (95% CI, 53 to 58) against symptomatic Covid-19, 68% (95% CI, 59 to 74) against Covid-19-related hospitalization, 62% (95% CI, 50 to 74) against severe Covid-19, and 74% (95% CI, 50 to 90) against Covid-19-related death. The corresponding estimates in days 14 to 30 after the fourth dose were 52% (95% CI, 49 to 54), 61% (95% CI, 58 to 64), 72% (95% CI, 63 to 79), 64% (95% CI, 48 to 77), and 76% (95% CI, 48 to 91). In days 7 to 30 after a fourth vaccine dose, the difference in the absolute risk (three doses vs. four doses) was 180.1 cases per 100,000 persons (95% CI, 142.8 to 211.9) for Covid-19-related hospitalization and 68.8 cases per 100,000 persons (95% CI, 48.5 to 91.9) for severe Covid-19. In sensitivity analyses, estimates of relative effectiveness against documented infection were similar to those in the primary analysis. CONCLUSIONS: A fourth dose of the BNT162b2 vaccine was effective in reducing the short-term risk of Covid-19-related outcomes among persons who had received a third dose at least 4 months earlier. (Funded by the Ivan and Francesca Berkowitz Family Living Laboratory Collaboration at Harvard Medical School and Clalit Research Institute.).

Nirmatrelvir Use and Severe Covid-19 Outcomes during the Omicron Surge.

BACKGROUND: The oral protease inhibitor nirmatrelvir has shown substantial efficacy in high-risk, unvaccinated patients infected with the B.1.617.2 (delta) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Data regarding the effectiveness of nirmatrelvir in preventing severe coronavirus disease 2019 (Covid-19) outcomes from the B.1.1.529 (omicron) variant are limited. METHODS: We obtained data for all members of Clalit Health Services who were 40 years of age or older at the start of the study period and were assessed as being eligible to receive nirmatrelvir therapy during the omicron surge. A Cox proportional-hazards regression model with time-dependent covariates was used to estimate the association of nirmatrelvir treatment with hospitalization and death due to Covid-19, with adjustment for sociodemographic factors, coexisting conditions, and previous SARS-CoV-2 immunity status. RESULTS: A total of 109,254 patients met the eligibility criteria, of whom 3902 (4%) received nirmatrelvir during the study period. Among patients 65 years of age or older, the rate of hospitalization due to Covid-19 was 14.7 cases per 100,000 person-days among treated patients as compared with 58.9 cases per 100,000 person-days among untreated patients (adjusted hazard ratio, 0.27; 95% confidence interval [CI], 0.15 to 0.49). The adjusted hazard ratio for death due to Covid-19 was 0.21 (95% CI, 0.05 to 0.82). Among patients 40 to 64 years of age, the rate of hospitalization due to Covid-19 was 15.2 cases per 100,000 person-days among treated patients and 15.8 cases per 100,000 person-days among untreated patients (adjusted hazard ratio, 0.74; 95% CI, 0.35 to 1.58). The adjusted hazard ratio for death due to Covid-19 was 1.32 (95% CI, 0.16 to 10.75). CONCLUSIONS: Among patients 65 years of age or older, the rates of hospitalization and death due to Covid-19 were significantly lower among those who received nirmatrelvir than among those who did not. No evidence of benefit was found in younger adults.

Threshold-awareness in adaptive cancer therapy.

Although adaptive cancer therapy shows promise in integrating evolutionary dynamics into treatment scheduling, the stochastic nature of cancer evolution has seldom been taken into account. Various sources of random perturbations can impact the evolution of heterogeneous tumors, making performance metrics of any treatment policy random as well. In this paper, we propose an efficient method for selecting optimal adaptive treatment policies under randomly evolving tumor dynamics. The goal is to improve the cumulative "cost" of treatment, a combination of the total amount of drugs used and the total treatment time. As this cost also becomes random in any stochastic setting, we maximize the probability of reaching the treatment goals (tumor stabilization or eradication) without exceeding a pre-specified cost threshold (or a "budget"). We use a novel Stochastic Optimal Control formulation and Dynamic Programming to find such "threshold-aware" optimal treatment policies. Our approach enables an efficient algorithm to compute these policies for a range of threshold values simultaneously. Compared to treatment plans shown to be optimal in a deterministic setting, the new "threshold-aware" policies significantly improve the chances of the therapy succeeding under the budget, which is correlated with a lower general drug usage. We illustrate this method using two specific examples, but our approach is far more general and provides a new tool for optimizing adaptive therapies based on a broad range of stochastic cancer models.

Diverse mutant selection windows shape spatial heterogeneity in evolving populations.

Mutant selection windows (MSWs), the range of drug concentrations that select for drug-resistant mutants, have long been used as a model for predicting drug resistance and designing optimal dosing strategies in infectious disease. The canonical MSW model offers comparisons between two subtypes at a time: drug-sensitive and drug-resistant. In contrast, the fitness landscape model with N alleles, which maps genotype to fitness, allows comparisons between N genotypes simultaneously, but does not encode continuous drug response data. In clinical settings, there may be a wide range of drug concentrations selecting for a variety of genotypes in both cancer and infectious diseases. Therefore, there is a need for a more robust model of the pathogen response to therapy to predict resistance and design new therapeutic approaches. Fitness seascapes, which model genotype-by-environment interactions, permit multiple MSW comparisons simultaneously by encoding genotype-specific dose-response data. By comparing dose-response curves, one can visualize the range of drug concentrations where one genotype is selected over another. In this work, we show how N-allele fitness seascapes allow for N * 2N-1 unique MSW comparisons. In spatial drug diffusion models, we demonstrate how fitness seascapes reveal spatially heterogeneous MSWs, extending the MSW model to more fully reflect the selection of drug resistant genotypes. Furthermore, using synthetic data and empirical dose-response data in cancer, we find that the spatial structure of MSWs shapes the evolution of drug resistance in an agent-based model. By simulating a tumor treated with cyclic drug therapy, we find that mutant selection windows introduced by drug diffusion promote the proliferation of drug resistant cells. Our work highlights the importance and utility of considering dose-dependent fitness seascapes in evolutionary medicine.

The potential of genomics for restoring ecosystems and biodiversity.

Billions of hectares of natural ecosystems have been degraded through human actions. The global community has agreed on targets to halt and reverse these declines, and the restoration sector faces the important but arduous task of implementing programmes to meet these objectives. Existing and emerging genomics tools offer the potential to improve the odds of achieving these targets. These tools include population genomics that can improve seed sourcing, meta-omics that can improve assessment and monitoring of restoration outcomes, and genome editing that can generate novel genotypes for restoring challenging environments. We identify barriers to adopting these tools in a restoration context and emphasize that regulatory and ethical frameworks are required to guide their use.

Impact of Bmal1 Rescue and Time-Restricted Feeding on Liver and Muscle Proteomes During the Active Phase in Mice.

Molecular clocks and daily feeding cycles support metabolism in peripheral tissues. Although the roles of local clocks and feeding are well defined at the transcriptional level, their impact on governing protein abundance in peripheral tissues is unclear. Here, we determine the relative contributions of local molecular clocks and daily feeding cycles on liver and muscle proteomes during the active phase in mice. LC-MS/MS was performed on liver and gastrocnemius muscle harvested 4 h into the dark phase from WT, Bmal1 KO, and dual liver- and muscle-Bmal1-rescued mice under either ad libitum feeding or time-restricted feeding during the dark phase. Feeding-fasting cycles had only minimal effects on levels of liver proteins and few, if any, on the muscle proteome. In contrast, Bmal1 KO altered the abundance of 674 proteins in liver and 80 proteins in muscle. Local rescue of liver and muscle Bmal1 restored ∼50% of proteins in liver and ∼25% in muscle. These included proteins involved in fatty acid oxidation in liver and carbohydrate metabolism in muscle. For liver, proteins involved in de novo lipogenesis were largely dependent on Bmal1 function in other tissues (i.e., the wider clock system). Proteins regulated by BMAL1 in liver and muscle were enriched for secreted proteins. We found that the abundance of fibroblast growth factor 1, a liver secreted protein, requires BMAL1 and that autocrine fibroblast growth factor 1 signaling modulates mitochondrial respiration in hepatocytes. In liver and muscle, BMAL1 is a more potent regulator of dark phase proteomes than daily feeding cycles, highlighting the need to assess protein levels in addition to mRNA when investigating clock mechanisms. The proteome is more extensively regulated by BMAL1 in liver than in muscle, and many metabolic pathways in peripheral tissues are reliant on the function of the clock system as a whole.

Integrating topic modeling and word embedding to characterize violent deaths.

SignificanceWe introduce an approach to identify latent topics in large-scale text data. Our approach integrates two prominent methods of computational text analysis: topic modeling and word embedding. We apply our approach to written narratives of violent death (e.g., suicides and homicides) in the National Violent Death Reporting System (NVDRS). Many of our topics reveal aspects of violent death not captured in existing classification schemes. We also extract gender bias in the topics themselves (e.g., a topic about long guns is particularly masculine). Our findings suggest new lines of research that could contribute to reducing suicides or homicides. Our methods are broadly applicable to text data and can unlock similar information in other administrative databases.

IL-13 and IL-13-induced periostin levels are specifically decreased in patients following endoscopic sinus surgery for chronic rhinosinusitis.

BACKGROUND: Type 2 (T2) inflammation plays a pathogenic role in chronic rhinosinusitis (CRS). The effects of endoscopic sinus surgery (ESS) on T2 inflammation are unknown. OBJECTIVE: The aim of this study was to compare T2 inflammatory biomarkers from middle meatal (MM) mucus for distinguishing patients with CRS from CRS-free patients, identifying major phenotypes (CRS without nasal polyps [CRSsNP] and CRS with nasal polyps [CRSwNP]), assessing endotypic change, and establishing cross-sectional and longitudinal outcomes in patients undergoing ESS. METHODS: MM mucus samples were collected from patients with CRSsNP and patients with CRSwNP before and 6 to 12 months after ESS and compared with samples from CRS-free control patients. T2 biomarkers were evaluated both continuously and using threshold-based definitions of T2 endotype to identify relationships with patient-reported (based on the 22-Item Sinonasal Outcomes Test and Chronic Rhinosinusitis Patient-Reported Outcomes Measure) and clinician-reported (radiographic and endoscopic) severity. Linear mixed models were developed to analyze clinical variables associated with T2 biomarker levels. RESULTS: A total of 154 patients with CRS (89 with CRSsNP and 65 with CRSwNP) were enrolled, with a mean interval of 9 months between ESS and follow-up. An analysis of pre-ESS MM mucus samples revealed elevated levels of T2 mediators in patients with CRSwNP versus in patients with CRSsNP and CRS-free controls. Temporally stable correlations between levels of IL-13 and IL-5, levels of periostin and complement 5a, and levels of eosinophil cationic protein (ECP) and eotaxin-3 were observed. On this basis and on the basis of pathologic significance, levels of IL-13, periostin and ECP were further analyzed. After ESS, levels of IL-13 and periostin decreased significantly, whereas ECP levels remained unchanged. Across pre- and post-ESS evaluation, the T2 endotype was associated with radiographic severity but did not predict outcomes. CRSwNP status and African American race were associated with higher levels of IL-13 and periostin, whereas ECP level was higher in patients undergoing extensive surgery. CONCLUSION: ESS decreased levels of IL-13 and periostin in the middle meatus. T2 inflammation after ESS was correlated with patient- and clinician-reported severity across phenotypes. Pre-ESS T2 inflammation did not predict post-ESS outcomes.

AAV-vectored expression of monospecific or bispecific monoclonal antibodies protects mice from lethal Pseudomonas aeruginosa pneumonia.

Pseudomonas aeruginosa poses a significant threat to immunocompromised individuals and those with cystic fibrosis. Treatment relies on antibiotics, but persistent infections occur due to intrinsic and acquired resistance of P. aeruginosa towards multiple classes of antibiotics. To date, there are no licensed vaccines for this pathogen, prompting the urgent need for novel treatment approaches to combat P. aeruginosa infection and persistence. Here we validated AAV vectored immunoprophylaxis as a strategy to generate long-term plasma and mucosal expression of highly protective monoclonal antibodies (mAbs) targeting the exopolysaccharide Psl (Cam-003) and the PcrV (V2L2MD) component of the type-III secretion system injectosome either as single mAbs or together as a bispecific mAb (MEDI3902) in a mouse model. When administered intramuscularly, AAV-αPcrV, AAV-αPsl, and AAV-MEDI3902 significantly protected mice challenged intranasally with a lethal dose of P. aeruginosa strains PAO1 and PA14 and reduced bacterial burden and dissemination to other organs. While all AAV-mAbs provided protection, AAV-αPcrV and AAV-MEDI3902 provided 100% and 87.5% protection from a lethal challenge with 4.47 × 107 CFU PAO1 and 87.5% and 75% protection from a lethal challenge with 3 × 107 CFU PA14, respectively. Serum concentrations of MEDI3902 were ~10× lower than that of αPcrV, but mice treated with this vector showed a greater reduction in bacterial dissemination to the liver, lung, spleen, and blood compared to other AAV-mAbs. These results support further investigation into the use of AAV vectored immunoprophylaxis to prevent and treat P. aeruginosa infections and other bacterial pathogens of public health concern for which current treatment strategies are limited.

Shared and unique heritability of hippocampal subregion volumes in children and adults.

Behavioral genetic analyses have not demonstrated robust, unique, genetic correlates of hippocampal subregion volume. Genetic differentiation of hippocampal longitudinal axis subregion volume has not yet been investigated in population-based samples, although this has been demonstrated in rodent and post-mortem human tissue work. The following study is the first population-based investigation of genetic factors that contribute to gray matter volume along the hippocampal longitudinal axis. Twin-based biometric analyses demonstrated that longitudinal axis subregions are associated with significant, unique, genetic variance, and that longitudinal axis subregions are also associated with significant shared, hippocampus-general, genetic factors. Our study's findings suggest that genetic differences in hippocampal longitudinal axis structure can be detected in individual differences in gray matter volume in population-level research designs.