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During development, cells gain positional information through the interpretation of dynamic morphogen gradients. A proposed mechanism for interpreting opposing morphogen gradients is mutual inhibition of downstream transcription factors, but isolating the role of this specific motif within a natural network remains a challenge. Here, we engineer a synthetic morphogen-induced mutual inhibition circuit in E. coli populations and show that mutual inhibition alone is sufficient to produce stable domains of gene expression in response to dynamic morphogen gradients, provided the spatial average of the morphogens falls within the region of bistability at the single cell level. When we add sender devices, the resulting patterning circuit produces theoretically predicted self-organised gene expression domains in response to a single gradient. We develop computational models of our synthetic circuits parameterised to timecourse fluorescence data, providing both a theoretical and experimental framework for engineering morphogen-induced spatial patterning in cell populations. Morphogen gradients can be dynamic and transient yet give rise to stable cellular patterns. Here the authors show that a synthetic morphogen-induced mutual inhibition circuit produces stable boundaries when the spatial average of morphogens falls within the region of bistability.

Gene expression can be noisy, as can the growth of single cells. Such cell-to-cell variation has been implicated in survival strategies for bacterial populations. However, it remains unclear how single cells couple gene expression with growth to implement these strategies. Here, we show how noisy expression of a key stress-response regulator, RpoS, allows E . coli to modulate its growth dynamics to survive future adverse environments. We reveal a dynamic positive feedback loop between RpoS and growth rate that produces multi-generation RpoS pulses. We do so experimentally using single-cell, time-lapse microscopy and microfluidics and theoretically with a stochastic model. Next, we demonstrate that E . coli prepares for sudden stress by entering prolonged periods of slow growth mediated by RpoS. This dynamic phenotype is captured by the RpoS-growth feedback model. Our synthesis of noisy gene expression, growth, and survival paves the way for further exploration of functional phenotypic variability. Noisy gene expression leading to phenotypic variability can help organisms to survive in changing environments. Here, Patange et al. show that noisy expression of a stress response regulator, RpoS, allows E . coli cells to modulate their growth rates to survive future adverse environments.

Bidirectional intercellular signaling is an essential feature of multicellular organisms, and the engineering of complex biological systems will require multiple pathways for intercellular signaling with minimal crosstalk. Natural quorum‐sensing systems provide components for cell communication, but their use is often constrained by signal crosstalk. We have established new orthogonal systems for cell–cell communication using acyl homoserine lactone signaling systems. Quantitative measurements in contexts of differing receiver protein expression allowed us to separate different types of crosstalk between 3‐oxo‐C6‐ and 3‐oxo‐C12‐homoserine lactones, cognate receiver proteins, and DNA promoters. Mutating promoter sequences minimized interactions with heterologous receiver proteins. We used experimental data to parameterize a computational model for signal crosstalk and to estimate the effect of receiver protein levels on signal crosstalk. We used this model to predict optimal expression levels for receiver proteins, to create an effective two‐channel cell communication device. Establishment of a novel spatial assay allowed measurement of interactions between geometrically constrained cell populations via these diffusible signals. We built relay devices capable of long‐range signal propagation mediated by cycles of signal induction, communication and response by discrete cell populations. This work demonstrates the ability to systematically reduce crosstalk within intercellular signaling systems and to use these systems to engineer complex spatiotemporal patterning in cell populations. Synopsis The use of multiple homoserine lactone quorum‐sensing signals in synthetic circuits has been hampered by crosstalk. Measurement and modeling of the system allows for rational modifications to minimize crosstalk and create programmed spatial behavior. Quantitative measurements were used to build and parameterize a cellular model of synthetic signal transduction. Rationally designed changes to promoter sequences combined with model‐informed tuning of receiver protein expression reduce crosstalk to undetectable levels. A novel spatial assay allows measurement of confined bacterial populations in defined geometries. Relay devices demonstrate bidirectional communication resulting in initiation and spatial propagation of a signal. Graphical Abstract The use of multiple homoserine lactone quorum‐sensing signals in synthetic circuits has been hampered by crosstalk. Measurement and modeling of the system allows for rational modifications to minimize crosstalk and create programmed spatial behavior.

The rate at which organisms grow is influenced by their biotic environment. The nematode Caenorhabditis elegans grows slower in the presence of Actinobacteria, but it is unknown why. Here, we show how perturbed levels of hydrogen sulfide and cysteine modulate the growth rate of C. elegans on Actinobacteria. Using an unbiased forward genetic screen of C. elegans we discovered alleles of the conserved cystathionine gamma-lyase (cth-2/CTH) that improved animal growth rate on Actinobacteria. Conversely, null alleles of cth-2 cause developmental arrest of animals grown on Actinobacteria, which can be rescued by exogenous H2S. We also discovered a leucine rich repeat gene that regulates cysteine and H2S production, lrr-2/LRRC58. A wild isolate of C. elegans that naturally grows well on Actinobacteria has a mutant allele of lrr-2, suggesting this sulfur metabolism pathway is important for the regulation of animal growth rate in its natural ecological context. We propose a model in which wild-type worms use sulfurous compounds to promote growth of their favored bacterial food sources by inhibiting Actinobacteria growth. This strategy becomes a liability when Actinobacteria are the sole food source but can be bypassed by mutations in sulfur metabolism. This study reveals how the homeostasis of sulfurous compounds controls the growth rate of animals in an ecological context.

Gene expression can be noisy, as can the growth of single cells. Such cell-to-cell variation has been implicated in survival strategies for bacterial populations. However, it remains unclear how single cells couple gene expression with growth to implement these survival strategies. Here we show how noisy expression of a key stress response regulator, rpoS, allows E. coli to modulate its growth dynamics to survive future adverse environments. First, we demonstrate that rpoS has a long-tailed distribution of expression in an unstressed population of cells. We next reveal how a dynamic positive feedback loop between rpoS and growth rate produces multi-generation rpoS pulses, which are responsible for the rpoS heterogeneity. We do so experimentally with single-cell, time-lapse microscopy and microfluidics and theoretically with a stochastic model. Finally, we demonstrate the function of the coupling of heterogeneous rpoS activity and growth. It enables E. coli to survive oxidative attack by causing prolonged periods of slow growth. This dynamic phenotype is captured by the rpoS-growth feedback model. Our synthesis of noisy gene expression, growth, and survival paves the way for further exploration of functional phenotypic variability.

Background: Due to poor diabetes self-management awareness as well as heavy patient burden, management of diabetes in India is challenging for clinicians. Digital therapeutics platforms provide accessible and cost-efficient care through evidence-based guidance for lifestyle and behavioural modifications. Aim and Objectives: To evaluate the effectiveness of Diabefly® digital therapeutics platform for glycemic control among people with type 2 diabetes. Results: De-identified data of 144 participants referred by physicians (mean age: 46.42 years, 54.54 % females) on the 90 days Diabefly® program was analyzed. A mean significant reduction in HbA1C was observed by 1.56% (P< 0.001) from baseline 8.59%. Similarly, mean weight and BMI significantly reduced by 2.39 kg and 0.84 kg/m2 (P<0.001 for both) from a baseline of 75.63 kg and 27.34 kg/m2 respectively. Complete FBS and PPBS readings were provided by 56 and 39 participants respectively. A mean reduction in FBS and PPBS was observed by 53.93 mg/dL and 99.25 mg/dl (P < 0.001 for both) from a baseline of 168.2 mg/dL and 234.7 mg/dl respectively. Conclusion: Significant reduction in HbA1c, weight, BMI, FBS and PPBS was observed after participation in the Diabefly® program. The study thus showed significant improvement in glycemic control in people with diabetes after participation.

Farmers' participatory field trail was conducted in 33.18 ha representing rainfed cotton-growing region in Nanded district of the central zone, to evaluate the performance of Bt cotton hybrid MECH-162 under Integrated Pest Management (IPM), and to compare it with conventional cotton (CC) hybrids/varieties grown with and without IPM. There was significant reduction in bollworm incidence, particularly the American bollworm (Heliocoverpa armigera) and pink bollworm (Pectinophora gossypiella) and the damage caused by them to the fruiting bodies in Bt MECH-162 compared to CC with IPM. In Bt MECH-162, 11.5% of the fruiting bodies were damaged compared to 29.4% in CC with IPM. Maximum damage was observed in CC without IPM, where seven sprays of pesticides were made for control of insect pests in comparison to three on Bt MECH-162. Population of the sucking pests and two natural enemies monitored was also lower in Bt MECH-162 compared to CC. The latter without IPM recorded the lowest population of natural enemies. Seed cotton yield (12.4 q/ha), and net returns (Rs 16231/ha) were highest for Bt MECH-162. CC under IPM recorded an yield of 7.1 q/ha, and return of Rs 10507/ha. The results show that IPM in cotton was most effective with Bt MECH-162, and provided higher return though the initial seed cost for the farmers was higher.

In machining processes, monitoring the condition of the tool is a crucial aspect to ensure high productivity and quality of the product. Using different machine learning techniques in Tool Condition Monitoring TCM enables a better analysis of the large amount of data of different signals acquired during the machining processes. The real time force signals encountered during the process were acquired by performing numerous experiments. Different tool wear conditions were considered during the experimentation. A comprehensive statistical analysis of the data and feature selection using decision trees was conducted, and the KNN algorithm was used to perform classification. Hyperparameter tuning of the model was done to improve the models performance. Much research has been done to employ machine learning approaches in tool condition monitoring systems, however, a model agnostic approach to increase the interpretability of the process and get an in depth understanding of how the decision making is done is not implemented by many. This research paper presents a KNN based white box model, which allows us to dive deep into how the model performs the classification and how it prioritizes the different features included. This approach helps in detecting why the tool is in a certain condition and allows the manufacturer to make an informed decision about the tools maintenance.