Enhancing Fluorescence in Both Solution and Solid States Induced by Imine Cage Formation.

Developing luminescent materials that exhibit strong emissions in both solution and solid phases is highly desirable and challenging. Herein, we report imine-bond directed formation of a rigid organic cage (TPE-cage) that was synthesized by [2+4] imine condensation of a TPE-cored tetra-aldehyde (TPE-TA) with a clip-like diamine (XA) to illustrate confinement-induced fluorescence enhancement. Compared to the non-emissive TPE-TA (ϕF =0.26 %) in the dichloromethane (DCM) solution, the TPE-cage achieved a remarkable (~520-fold) emission enhancement (ϕF =70.38 %). In contrast, a monomeric tetra-imine model compound (TPE-model) showed only a minor enhancement (ϕF =0.56 %) in emission compared to the parent tetra-aldehyde TPE-TA. The emission of TPE-cage was further enhanced by ~1.5-fold (ϕF =80.96 %) in the aggregated state owing to aggregation-induced emission enhancement (AIEE). This approach establishes the potential for synthesizing luminescent materials with high emission in both solution and solid-state by employing a single-step imine condensation reaction.

Staphylococcal ClpXP protease targets the cellular antioxidant system to eliminate fitness-compromised cells in stationary phase.

The transition from growth to stationary phase is a natural response of bacteria to starvation and stress. When stress is alleviated and more favorable growth conditions return, bacteria resume proliferation without a significant loss in fitness. Although specific adaptations that enhance the persistence and survival of bacteria in stationary phase have been identified, mechanisms that help maintain the competitive fitness potential of nondividing bacterial populations have remained obscure. Here, we demonstrate that staphylococci that enter stationary phase following growth in media supplemented with excess glucose, undergo regulated cell death to maintain the competitive fitness potential of the population. Upon a decrease in extracellular pH, the acetate generated as a byproduct of glucose metabolism induces cytoplasmic acidification and extensive protein damage in nondividing cells. Although cell death ensues, it does not occur as a passive consequence of protein damage. Instead, we demonstrate that the expression and activity of the ClpXP protease is induced, resulting in the degeneration of cellular antioxidant capacity and, ultimately, cell death. Under these conditions, inactivation of either clpX or clpP resulted in the extended survival of unfit cells in stationary phase, but at the cost of maintaining population fitness. Finally, we show that cell death from antibiotics that interfere with bacterial protein synthesis can also be partly ascribed to the corresponding increase in clpP expression and activity. The functional conservation of ClpP in eukaryotes and bacteria suggests that ClpP-dependent cell death and fitness maintenance may be a widespread phenomenon in these domains of life.

Dissecting the metabolic reprogramming of maize root under nitrogen-deficient stress conditions.

The growth and development of maize (Zea mays L.) largely depends on its nutrient uptake through the root. Hence, studying its growth, response, and associated metabolic reprogramming to stress conditions is becoming an important research direction. A genome-scale metabolic model (GSM) for the maize root was developed to study its metabolic reprogramming under nitrogen stress conditions. The model was reconstructed based on the available information from KEGG, UniProt, and MaizeCyc. Transcriptomics data derived from the roots of hydroponically grown maize plants were used to incorporate regulatory constraints in the model and simulate nitrogen-non-limiting (N+) and nitrogen-deficient (N-) condition. Model-predicted flux-sum variability analysis achieved 70% accuracy compared with the experimental change of metabolite levels. In addition to predicting important metabolic reprogramming in central carbon, fatty acid, amino acid, and other secondary metabolism, maize root GSM predicted several metabolites (l-methionine, l-asparagine, l-lysine, cholesterol, and l-pipecolate) playing a regulatory role in the root biomass growth. Furthermore, this study revealed eight phosphatidylcholine and phosphatidylglycerol metabolites which, even though not coupled with biomass production, played a key role in the increased biomass production under N-deficient conditions. Overall, the omics-integrated GSM provides a promising tool to facilitate stress condition analysis for maize root and engineer better stress-tolerant maize genotypes.

Dissecting the regulatory roles of ORM proteins in the sphingolipid pathway of plants.

Sphingolipids are a vital component of plant cellular endomembranes and carry out multiple functional and regulatory roles. Different sphingolipid species confer rigidity to the membrane structure, facilitate trafficking of secretory proteins, and initiate programmed cell death. Although the regulation of the sphingolipid pathway is yet to be uncovered, increasing evidence has pointed to orosomucoid proteins (ORMs) playing a major regulatory role and potentially interacting with a number of components in the pathway, including both enzymes and sphingolipids. However, experimental exploration of new regulatory interactions is time consuming and often infeasible. In this work, a computational approach was taken to address this challenge. A metabolic network of the sphingolipid pathway in plants was reconstructed. The steady-state rates of reactions in the network were then determined through measurements of growth and cellular composition of the different sphingolipids in Arabidopsis seedlings. The Ensemble modeling framework was modified to accurately account for activation mechanisms and subsequently used to generate sets of kinetic parameters that converge to the measured steady-state fluxes in a thermodynamically consistent manner. In addition, the framework was appended with an additional module to automate screening the parameters and to output models consistent with previously reported network responses to different perturbations. By analyzing the network's response in the presence of different combinations of regulatory mechanisms, the model captured the experimentally observed repressive effect of ORMs on serine palmitoyltransferase (SPT). Furthermore, predictions point to a second regulatory role of ORM proteins, namely as an activator of class II (or LOH1 and LOH3) ceramide synthases. This activating role was found to be modulated by the concentration of free ceramides, where an accumulation of these sphingolipid species dampened the activating effect of ORMs on ceramide synthase. The predictions pave the way for future guided experiments and have implications in engineering crops with higher biotic stress tolerance.

Synergistic experimental and computational approach identifies novel strategies for polyhydroxybutyrate overproduction.

Polyhydroxybutyrate (PHB) is a sustainable bioplastic produced by bacteria that is a potential replacement for conventional plastics. This study delivers an integrated experimental and computational modeling approach to decipher metabolic factors controlling PHB production and offers engineering design strategies to boost production. In the metabolically robust Rhodopseudomonas palustris CGA009, PHB production significantly increased when grown on the carbon- and electron-rich lignin breakdown product p-coumarate (C9H8O3) compared to virtually no PHB titer from acetate (C2H3NaO2). The maximum yield did not improve further when grown on coniferyl alcohol (C10H12O3), but comparison of the PHB profiles showed that coniferyl alcohol's higher carbon content resulted in a higher rate of PHB production. Combined experimental results revealed that cytoplasmic space may be a limiting factor for maximum PHB titer. In order to obtain a systems-level understanding of factors driving PHB yield, a model-driven investigation was performed. The model yielded several engineering design strategies including utilizing reduced, high molecular weight substrates that bypass the thiolase reaction (phaA). Based on these strategies, utilization of butyrate was predicted and subsequently validated to produce PHB. Model analysis also explained why nitrogen starvation was not essential for PHB production and revealed that renewable and abundant lignin aromatics are ideal candidates for PHB production. Most importantly, the generality of the derived design rules allows them to be applied to any PHB-producing microbe with similar metabolic features.

Phosphine-Free and Reusable Palladium Nanoparticles-Catalyzed Domino Strategy: Synthesis of Indanone Derivatives.

The carbene migratory insertion involving a domino reaction by highly stable, reusable, and binaphthyl-stabilized Pd-nanoparticles (Pd-BNP) is disclosed. The reaction was catalyzed by 2 mol % of a heterogeneous Pd-BNP catalyst under external ligand-free conditions, and it afforded 3-aryl-substituted indanone derivatives in up to a 90% yield with exclusive E-selectivity. Furthermore, a one-pot reaction and derivatization of indanone derivatives were also successfully demonstrated.

Global Proteomic Analysis Reveals an Exclusive Role of Thylakoid Membranes in Bioenergetics of a Model Cyanobacterium.

Cyanobacteria are photosynthetic microbes with highly differentiated membrane systems. These organisms contain an outer membrane, plasma membrane, and an internal system of thylakoid membranes where the photosynthetic and respiratory machinery are found. This existence of compartmentalization and differentiation of membrane systems poses a number of challenges for cyanobacterial cells in terms of organization and distribution of proteins to the correct membrane system. Proteomics studies have long sought to identify the components of the different membrane systems in cyanobacteria, and to date about 450 different proteins have been attributed to either the plasma membrane or thylakoid membrane. Given the complexity of these membranes, many more proteins remain to be identified, and a comprehensive catalogue of plasma membrane and thylakoid membrane proteins is needed. Here we describe the identification of 635 differentially localized proteins in Synechocystis sp. PCC 6803 by quantitative iTRAQ isobaric labeling; of these, 459 proteins were localized to the plasma membrane and 176 were localized to the thylakoid membrane. Surprisingly, we found over 2.5 times the number of unique proteins identified in the plasma membrane compared with the thylakoid membrane. This suggests that the protein composition of the thylakoid membrane is more homogeneous than the plasma membrane, consistent with the role of the plasma membrane in diverse cellular processes including protein trafficking and nutrient import, compared with a more specialized role for the thylakoid membrane in cellular energetics. Thus, our data clearly define the two membrane systems with distinct functions. Overall, the protein compositions of the Synechocystis 6803 plasma membrane and thylakoid membrane are quite similar to that of the plasma membrane of Escherichia coli and thylakoid membrane of Arabidopsis chloroplasts, respectively. Synechocystis 6803 can therefore be described as a Gram-negative bacterium with an additional internal membrane system that fulfills the energetic requirements of the cell.

Assessing the metabolic impact of nitrogen availability using a compartmentalized maize leaf genome-scale model.

Maize (Zea mays) is an important C4 plant due to its widespread use as a cereal and energy crop. A second-generation genome-scale metabolic model for the maize leaf was created to capture C4 carbon fixation and investigate nitrogen (N) assimilation by modeling the interactions between the bundle sheath and mesophyll cells. The model contains gene-protein-reaction relationships, elemental and charge-balanced reactions, and incorporates experimental evidence pertaining to the biomass composition, compartmentalization, and flux constraints. Condition-specific biomass descriptions were introduced that account for amino acids, fatty acids, soluble sugars, proteins, chlorophyll, lignocellulose, and nucleic acids as experimentally measured biomass constituents. Compartmentalization of the model is based on proteomic/transcriptomic data and literature evidence. With the incorporation of information from the MetaCrop and MaizeCyc databases, this updated model spans 5,824 genes, 8,525 reactions, and 9,153 metabolites, an increase of approximately 4 times the size of the earlier iRS1563 model. Transcriptomic and proteomic data have also been used to introduce regulatory constraints in the model to simulate an N-limited condition and mutants deficient in glutamine synthetase, gln1-3 and gln1-4. Model-predicted results achieved 90% accuracy when comparing the wild type grown under an N-complete condition with the wild type grown under an N-deficient condition.

Nitrogen-use efficiency in maize (Zea mays L.): from 'omics' studies to metabolic modelling.

In this review, we will present the latest developments in systems biology with particular emphasis on improving nitrogen-use efficiency (NUE) in crops such as maize and demonstrating the application of metabolic models. The review highlights the importance of improving NUE in crops and provides an overview of the transcriptome, proteome, and metabolome datasets available, focusing on a comprehensive understanding of nitrogen regulation. 'Omics' data are hard to interpret in the absence of metabolic flux information within genome-scale models. These models, when integrated with 'omics' data, can serve as a basis for generating predictions that focus and guide further experimental studies. By simulating different nitrogen (N) conditions at a pseudo-steady state, the reactions affecting NUE and additional gene regulations can be determined. Such models thus provide a framework for improving our understanding of the metabolic processes underlying the more efficient use of N-based fertilizers.

Predictors of quitting behaviour with special reference to nicotine dependence among adult tobacco-users in a slum of Burdwan district, West Bengal, India.

BACKGROUND & OBJECTIVES: Information on predictors of quitting behaviour in adult tobacco users is scarce in Indian context. Hence, this study was undertaken to assess the intention of tobacco-users towards quitting and its predictors with reference to nicotine dependence. METHODS: A community-based observational, cross-sectional study was conducted on 128 adult tobacco-users (89.8% male) with mean age of 41.1 ± 15.7 yr selected by complete enumeration method. Data were collected by interview using pre-designed, pre-tested schedule. Nicotine dependence was assessed by Fagerstrφm Test for Nicotine Dependence (FTND) questionnaire. RESULT: Of the 128 users, 63.3 per cent had intention to quit. Majority of the tobacco users who did not intend to quit belonged to the age group of > 40 yr (66.0%), were illiterate (55.3%), started tobacco use at 11 - 15 yr of age (57.4%), had been using tobacco for 20 yr or more (70.2%), were daily tobacco users (91.5%), and highly dependent on nicotine (80.9%). Tobacco users having high FTND score and who started tobacco use early in life were 1.83 and 3.30 times more unintended to quit, respectively. INTERPRETATION & CONCLUSIONS: Suitable plan for quitting should be developed depending on the FTND score of an individual, the most important determinant of quitting that would be beneficial for categorization of the treatment leading to successful quitting.

Risk of tuberculosis among HAART receiving HIV patients attending an ART centre of West Bengal, India: a prospective cohort study.

This prospective study was conducted to find out the incidence density rate and to identify the attributed risk factors of Tuberculosis development among ART receivers. All patients who were registered in a nodal ART centre of India within 1st January 2008-31st December 2008 and had been initiated ART in the year of 2008 were considered as a cohort and were followed up till 31st December 2012. This study was started with 169 ART receivers and ended with 129 patients. During total 631.1 person-years observation, 39 TB cases (31 pulmonary and 8 extra pulmonary) were diagnosed. TB incidence density rate reduced from 12.08/100 to 1.12/100 person-years during the follow up periods. Cox regression model revealed that patients having past history of Tuberculosis were at 5 times higher risk (Hazard ratio = 5.205; 95 % CI 2.439-11.106; p = 0.000). Patients with WHO clinical stage 3 or 4 at the time of enrolment had 2 times more risk of development of TB (Hazard ratio = 2.081; 95 % CI 1.502-2.884; p = 0.000). This study highlighted that special attention should be paid on earliest identification of TB among the HIV patients who had past history of TB or suffering from WHO clinical stage 3 or 4 to prevent the silent transmission and multidrug resistance development of Tuberculosis in the community.

Optimal Protein Allocation Controls the Inhibition of GltA and AcnB in Neisseria gonorrhoeae.

Neisseria gonorrhea (Ngo) is a major concern for global public health due to its severe implications for reproductive health. Understanding its metabolic phenotype is crucial for comprehending its pathogenicity. Despite Ngo's ability to encode TCA cycle proteins, GltA and AcnB, their activities are notably restricted. To investigate this phenomenon, we used the iNgo_557 metabolic model and incorporated a constraint on total cellular protein content. Our results indicate that low cellular protein content severely limits GltA and AcnB activity, leading to a shift towards acetate overflow for ATP production, which is more efficient in terms of protein usage. Surprisingly, increasing cellular protein content alleviates this restriction on GltA and AcnB and delays the onset of acetate overflow, highlighting protein allocation as a critical determinant in understanding Ngo's metabolic phenotype. These findings underscore the significance of Ngo's metabolic adaptation in light of optimal protein allocation, providing a blueprint to understand Ngo's metabolic landscape.

Metabolic model guided CRISPRi identifies a central role for phosphoglycerate mutase in Chlamydia trachomatis persistence.

Upon nutrient starvation, Chlamydia trachomatis serovar L2 (CTL) shifts from its normal growth to a non-replicating form, termed persistence. It is unclear if persistence reflects an adaptive response or a lack thereof. To understand this, transcriptomics data were collected for CTL grown under nutrient-replete and nutrient-starved conditions. Applying K-means clustering on transcriptomics data revealed a global transcriptomic rewiring of CTL under stress conditions in the absence of any canonical global stress regulator. This is consistent with previous data that suggested that CTL's stress response is due to a lack of an adaptive response mechanism. To investigate the impact of this on CTL metabolism, we reconstructed a genome-scale metabolic model of CTL (iCTL278) and contextualized it with the collected transcriptomics data. Using the metabolic bottleneck analysis on contextualized iCTL278, we observed that phosphoglycerate mutase (pgm) regulates the entry of CTL to the persistence state. Our data indicate that pgm has the highest thermodynamics driving force and lowest enzymatic cost. Furthermore, CRISPRi-driven knockdown of pgm in the presence or absence of tryptophan revealed the importance of this gene in modulating persistence. Hence, this work, for the first time, introduces thermodynamics and enzyme cost as tools to gain a deeper understanding on CTL persistence. IMPORTANCE: This study uses a metabolic model to investigate factors that contribute to the persistence of Chlamydia trachomatis serovar L2 (CTL) under tryptophan and iron starvation conditions. As CTL lacks many canonical transcriptional regulators, the model was used to assess two prevailing hypotheses on persistence-that the chlamydial response to nutrient starvation represents a passive response due to the lack of regulators or that it is an active response by the bacterium. K-means clustering of stress-induced transcriptomics data revealed striking evidence in favor of the lack of adaptive (i.e., a passive) response. To find the metabolic signature of this, metabolic modeling pin-pointed pgm as a potential regulator of persistence. Thermodynamic driving force, enzyme cost, and CRISPRi knockdown of pgm supported this finding. Overall, this work introduces thermodynamic driving force and enzyme cost as a tool to understand chlamydial persistence, demonstrating how systems biology-guided CRISPRi can unravel complex bacterial phenomena.

Protocol to develop a synthetic biology toolkit for the non-model bacterium R. palustris.

Numerous biology tools are developed to work for model organisms, which, however, do not work effectively in non-model organisms. Here, we present a protocol for developing a synthetic biology toolkit for Rhodopseudomonas palustris CGA009, a non-model bacterium with unique metabolic properties. We describe steps for introducing and characterizing biological devices in non-model bacteria, such as the utilization of fluorescence markers and RT-qPCR. This protocol may also be applicable for other non-model organisms. For complete details on the use and execution of this protocol, please refer to Immethun et al..1.

Supplementation of Sulfide or Acetate and 2-Mercaptoethane Sulfonate Restores Growth of the Methanosarcina acetivorans ΔhdrABC Deletion Mutant during Methylotrophic Methanogenesis.

Methanogenic archaea are important organisms in the global carbon cycle that grow by producing methane gas. Methanosarcina acetivorans is a methanogenic archaeum that can grow using methylated compounds, carbon monoxide, or acetate and produces renewable methane as a byproduct. However, there is limited knowledge of how combinations of substrates may affect metabolic fluxes in methanogens. Previous studies have shown that heterodisulfide reductase, the terminal oxidase in the electron transport system, is an essential enzyme in all methanogens. Deletion of genes encoding the nonessential methylotrophic heterodisulfide reductase enzyme (HdrABC) results in slower growth rate but increased metabolic efficiency. We hypothesized that increased sulfide, supplementation of mercaptoethanesulfonate (coenzyme M, CoM-SH), or acetate would metabolically alleviate the effect of the ΔhdrABC mutation. Increased sulfide improved growth of the mutant as expected; however, supplementation of both CoM-SH and acetate together were necessary to reduce the effect of the ΔhdrABC mutation. Supplementation of CoM-SH or acetate alone did not improve growth. These results support our model for the role of HdrABC in methanogenesis and suggest M.acetivorans is more efficient at conserving energy when supplemented with acetate. Our study suggests decreased Hdr enzyme activity can be overcome by nutritional supplementation with sulfide or coenzyme M and acetate, which are abundant in anaerobic environments.

Opening the door to nitrogen fixation in oxygenic phototrophs.

Conveying biological nitrogen fixation (BNF) to photosynthetic species may be the next agricultural revolution, yet poses major engineering challenges. Liu et al. created a diazotrophic strain of a previously non-nitrogen-fixing species, the cyanobacterium Synechocystis sp. PCC 6803, and uncovered critical aspects of nitrogen fixation in an oxygenic species.

Erratum: Exploring the metabolic landscape of pancreatic ductal adenocarcinoma cells using genome-scale metabolic modeling.

[This corrects the article DOI: 10.1016/j.isci.2022.104483.].

Early detection of Parkinson disease using stacking ensemble method.

Parkinson's disease (PD) is a common progressive neurodegenerative disorder that occurs due to corrosion of the substantianigra, located in the thalamic region of the human brain, and is responsible for the transmission of neural signals throughout the human body using brain chemical, termed as "dopamine." Diagnosis of PD is difficult, as it is often affected by the characteristics of the medical data of the patients, which include the presence of various indicators, imbalance cases of patients' data records, similar cases of healthy/affected persons, etc. Hence, sometimes the process of diagnosis may also be affected by human error. To overcome this problem some intelligent models have been proposed; however, most of them are single classifier-based models and due to this these models cannot handle noisy and imbalanced data properly and thus sometimes overfit the model. To reduce bias and variance, and to avoid overfitting of a single classifier-based model, this paper proposes an ensemble-based PD diagnosis model, named Ensembled Expert System for Diagnosis of Parkinson's Disease (EESDPD) with relevant features and a simple stacking ensemble technique. The proposed EESDPD aggregates diverse assumptions for making the prediction. The performance of the proposed EESDPD is compared with the performances of logistic regression, SVM, Naïve Bayes, Random Forest, XGBoost, simple Decision Tree, B-TDS-PD and B-TESM-PD in terms of classification accuracy, precision, recall and F1-score measures.

Synthesis of Mixed-Phase TiO2-ZrO2 Nanocomposite for Photocatalytic Wastewater Treatment.

The use of TiO2 nanoparticles for photocatalysis for the degradation of organic dyes under UV light for wastewater treatment has been widely studied. However, the photocatalytic characteristics of TiO2 nanoparticles are inadequate due to their UV light response and higher band gap. In this work, three nanoparticles were synthesized: (i) TiO2 nanoparticle was synthesized by a sol-gel process. (ii) ZrO2 was prepared using a solution combustion process and (iii) mixed-phase TiO2-ZrO2 nanoparticles were synthesized by a sol-gel process to remove Eosin Yellow (EY) from aqueous solutions in the wastewater. XRD, FTIR, UV-VIS, TEM, and XPS analysis methods were used to examine the properties of the synthesized products. The XRD investigation supported the tetragonal and monoclinic crystal structures of the TiO2 and ZrO2 nanoparticles. TEM studies identified that mixed-phase TiO2-ZrO2 nanoparticles have the same tetragonal structure as pure mixed-phase. The degradation of Eosin Yellow (EY) was examined using TiO2, ZrO2, and mixed-phase TiO2-ZrO2 nanoparticles under visible light. The results confirmed that the mixed-phase TiO2-ZrO2nanoparticles show a higher level of photocatalytic activity, and the process is accomplished at a high degradation rate in lesser time and at a lower power intensity.

Quantitative Dynamic Analysis of de novo Sphingolipid Biosynthesis in Arabidopsis thaliana.

Sphingolipids are pivotal for plant development and stress responses. Growing interest has been directed towards fully comprehending the regulatory mechanisms of the sphingolipid pathway. We explore its de novo biosynthesis and homeostasis in Arabidopsis thaliana cell cultures, shedding light on fundamental metabolic mechanisms. Employing 15N isotope labeling and quantitative dynamic modeling approach, we developed a regularized and constraint-based Dynamic Metabolic Flux Analysis (r-DMFA) framework to predict metabolic shifts due to enzymatic changes. Our analysis revealed key enzymes such as sphingoid-base hydroxylase (SBH) and long-chain-base kinase (LCBK) to be critical for maintaining sphingolipid homeostasis. Disruptions in these enzymes were found to affect cellular viability and increase the potential for programmed cell death (PCD). Thus, this work enhances our understanding of sphingolipid metabolism and demonstrates the utility of dynamic modeling in analyzing complex metabolic pathways.