Thermostable Proteins from HaCaT Keratinocytes Identify a Wide Breadth of Intrinsically Disordered Proteins and Candidates for Liquid-Liquid Phase Separation

Intrinsically disordered proteins (IDPs) move through an ensemble of conformations which allows multitudinous roles within a cell. Keratinocytes, the predominant cell type in mammalian epidermis, have had only a few individual proteins assessed for intrinsic disorder and its possible contribution to liquid-liquid phase separation (LLPS), especially in regard to what functions or structures these proteins provide. We took a holistic approach to keratinocyte IDPs starting with enrichment via the isolation of thermostable proteins. The keratinocyte protein involucrin, known for its resistance to heat denaturation, served as a marker. It and other thermostable proteins were identified by liquid chromatography tandem mass spectrometry and subjected to extensive bioinformatic analysis covering gene ontology, intrinsic disorder, and potential for LLPS. Numerous proteins unique to keratinocytes and other proteins with shared expression in multiple cell types were identified to have IDP traits (e.g., compositional bias, nucleic acid binding, and repeat motifs). Among keratinocyte-specific proteins, many that co-assemble with involucrin into the cell-specific structure known as the cornified envelope scored highly for intrinsic disorder and potential for LLPS. This suggests intrinsic disorder and LLPS are previously unrecognized traits for assembly of the cornified envelope, echoing the contribution of intrinsic disorder and LLPS to more widely encountered features such as stress granules and PML bodies.

A cascade biorefinery for grape marc: Recovery of materials and energy through thermochemical and biochemical processes

The agro-industrial sector makes a high contribution to greenhouse gas emissions; therefore, proper waste management is crucial to reduce the carbon footprint of the food chain. Hydrothermal carbonization (HTC) is a promising and flexible thermochemical process for converting organic materials into energy and added-value products that can be used in different applications. In this work, grape marc residues before and after an extraction process for recovering polyphenols were hydrothermally treated at 220 °C for 1 h. The resulting hydrochar and process water were investigated to test an innovative cascade approach aimed at a multiple product and energy recovery based on the integration of HTC with anaerobic digestion. The results show that this biorefinery approach applied to grape marc could allow to diversify and integrate its potential valorisation options. The produced hydrochars possess an increased fixed carbon content compared to the feedstock (up to +70 %) and, therefore, can be used in soil, immobilizing carbon in a stable form and partially replacing peat in growing media (up to 5 % in case of hydrochar from grape marc after extraction), saving the consumption of this natural substrate. In addition, energy can be recovered from both hydrochar by combustion and from process water through anaerobic digestion to produce biogas. Hydrochars show good properties as solid fuel similar to lignite, with an energy content of around 27 MJ kg^-1 (+30 % compared to the feedstock). The anaerobic digestion of the process water allowed obtaining up to 137 mL of biomethane per gram of fed COD. Finally, while HTC process waters are suitable for biological treatment, attention must be paid to the presence of inhibiting compounds that induce acute toxic effects in aerobic conditions. The proposed approach is consistent with the principles of circular economy and could increase the overall sustainability and resilience of the agro-industrial sector.

A Review of Current Evidence on the Relationship between Phosphate Metabolism and Metabolic Syndrome

Phosphorus, present as phosphate in biological systems, is an essential mineral for various biological activities and biochemical processes. Numerous studies have indicated that disturbed phosphate balance may contribute to the development of metabolic syndrome (MetS). However, no consistent result was found on the association between phosphorus intake and serum phosphate concentration with MetS. It is believed that both positive and negative impacts of phosphorus/phosphate co-exist in parallel during MetS condition. Reduced phosphate level contributed to the development of obesity and hyperglycaemia. Low phosphate is believed to compromise energy production, reduce exercise capacity, increase food ingestion, and impair glucose metabolism. On the other hand, the effects of phosphorus/phosphate on hypertension are rather complex depending on the source of phosphorus and subjects' health conditions. Phosphorus excess activates sympathetic nervous system, renin-angiotensin-aldosterone system, and induces hormonal changes under pathological conditions, contributing to the blood pressure-rising effects. For lipid metabolism, adequate phosphate content ensures a balanced lipid profile through regulation of fatty acid biosynthesis, oxidation, and bile acid excretion. In conclusion, phosphate metabolism serves as a potential key feature for the development and progression of MetS. Dietary phosphorus and serum phosphate level should be under close monitoring for the management of MetS.

Efficient Bayesian inference for stochastic agent-based models

The modelling of many real-world problems relies on computationally heavy simulations of randomly interacting individuals or agents. However, the values of the parameters that underlie the interactions between agents are typically poorly known, and hence they need to be inferred from macroscopic observations of the system. Since statistical inference rests on repeated simulations to sample the parameter space, the high computational expense of these simulations can become a stumbling block. In this paper, we compare two ways to mitigate this issue in a Bayesian setting through the use of machine learning methods: One approach is to construct lightweight surrogate models to substitute the simulations used in inference. Alternatively, one might altogether circumvent the need for Bayesian sampling schemes and directly estimate the posterior distribution. We focus on stochastic simulations that track autonomous agents and present two case studies: tumour growths and the spread of infectious diseases. We demonstrate that good accuracy in inference can be achieved with a relatively small number of simulations, making our machine learning approaches orders of magnitude faster than classical simulation-based methods that rely on sampling the parameter space. However, we find that while some methods generally produce more robust results than others, no algorithm offers a one-size-fits-all solution when attempting to infer model parameters from observations. Instead, one must choose the inference technique with the specific real-world application in mind. The stochastic nature of the considered real-world phenomena poses an additional challenge that can become insurmountable for some approaches. Overall, we find machine learning approaches that create direct inference machines to be promising for real-world applications. We present our findings as general guidelines for modelling practitioners.

Resveratrol Affects Sphingolipid Metabolism in A549 Lung Adenocarcinoma Cells

Resveratrol is a naturally occurring polyphenol which has various beneficial effects, such as anti-inflammatory, anti-tumor, anti-aging, antioxidant, and neuroprotective effects, among others. The anti-cancer activity of resveratrol has been related to alterations in sphingolipid metabolism. We analyzed the effect of resveratrol on the enzymes responsible for accumulation of the two sphingolipids with highest functional activity—apoptosis promoting ceramide (CER) and proliferation-stimulating sphingosine-1-phosphate (S1P)—in human lung adenocarcinoma A549 cells. Resveratrol treatment induced an increase in CER and sphingosine (SPH) and a decrease in sphingomyelin (SM) and S1P. Our results showed that the most common mode of CER accumulation, through sphingomyelinase-induced hydrolysis of SM, was not responsible for a CER increase despite the reduction in SM in A549 plasma membranes. However, both the activity and the expression of CER synthase 6 were upregulated in resveratrol-treated cells, implying that CER was accumulated as a result of stimulated de novo synthesis. Furthermore, the enzyme responsible for CER hydrolysis, alkaline ceramidase, was not altered, suggesting that it was not related to changes in the CER level. The enzyme maintaining the balance between apoptosis and proliferation, sphingosine kinase 1 (SK1), was downregulated, and its expression was reduced, resulting in a decrease in S1P levels in resveratrol-treated lung adenocarcinoma cells. In addition, incubation of resveratrol-treated A549 cells with the SK1 inhibitors DMS and fingolimod additionally downregulated SK1 without affecting its expression. The present studies provide information concerning the biochemical processes underlying the influence of resveratrol on sphingolipid metabolism in A549 lung cancer cells and reveal possibilities for combined use of polyphenols with specific anti-proliferative agents that could serve as the basis for the development of complex therapeutic strategies.

Targeting the Achilles’ Heel of Multidrug-Resistant Staphylococcus aureus by the Endocannabinoid Anandamide

Antibiotic-resistant Staphylococcus aureus is a major health issue that requires new therapeutic approaches. Accumulating data suggest that it is possible to sensitize these bacteria to antibiotics by combining them with inhibitors targeting efflux pumps, the low-affinity penicillin-binding protein PBP2a, cell wall teichoic acid, or the cell division protein FtsZ. We have previously shown that the endocannabinoid Anandamide (N-arachidonoylethanolamine; AEA) could sensitize drug-resistant S. aureus to a variety of antibiotics, among others, through growth arrest and inhibition of drug efflux. Here, we looked at biochemical alterations caused by AEA. We observed that AEA increased the intracellular drug concentration of a fluorescent penicillin and augmented its binding to membrane proteins with concomitant altered membrane distribution of these proteins. AEA also prevented the secretion of exopolysaccharides (EPS) and reduced the cell wall teichoic acid content, both processes known to require transporter proteins. Notably, AEA was found to inhibit membrane ATPase activity that is necessary for transmembrane transport. AEA did not affect the membrane GTPase activity, and the GTPase cell division protein FtsZ formed the Z-ring of the divisome normally in the presence of AEA. Rather, AEA caused a reduction in murein hydrolase activities involved in daughter cell separation. Altogether, this study shows that AEA affects several biochemical processes that culminate in the sensitization of the drug-resistant bacteria to antibiotics.

Thiamin stimulates growth, yield quality and key biochemical processes of cauliflower (Brassica oleracea L. var. Botrytis) under arid conditions

Thiamin is a crucial vitamin with a vast variety of anti-oxidative and physiological roles in plants subjected to abiotic stresses. We examined the efficiency of foliar-applied thiamin (50 and 100 mM) on growth, yield quality and key-biochemical characteristics of two cultivars (FD1 and FD3) of cauliflower (Brassica oleracea L.) under water-deficit stress. Water stress at the rate of 50% field capacity (F.C.) markedly decreased the plant biomass, leaf total phenolics and ascorbic acid (AsA) contents. In contrast, drought-induced increase was noted in the leaf [hydrogen peroxide (H2O2), AsA, proline, malondialdehyde (MDA), glycinebetaine (GB), total soluble proteins and oxidative defense system in terms of high activities of peroxidase (POD), and catalase (CAT) enzymes] and the inflorescence (total phenolics, proline, GB, MDA, H2O2, and activities of SOD and CAT enzymes) characteristics of cauliflower. However, foliar-applied thiamin significantly improved growth and physio-biochemical attributes except leaf and inflorescence MDA and H2O2 contents of both cauliflower cultivars under water stress. Overall, application of thiamin enhanced the plant growth may be associated with suppressed reactive oxygen species (ROS) and upregulated antioxidants defense system of cauliflower.

Vanilloid-dependent TRPV1 opening trajectory from cryoEM ensemble analysis

Single particle cryo-EM often yields multiple protein conformations within a single dataset, but experimentally deducing the temporal relationship of these conformers within a conformational trajectory is not trivial. Here, we use thermal titration methods and cryo-EM in an attempt to obtain temporal resolution of the conformational trajectory of the vanilloid receptor TRPV1 with resiniferatoxin (RTx) bound. Based on our cryo-EM ensemble analysis, RTx binding to TRPV1 appears to induce intracellular gate opening first, followed by selectivity filter dilation, then pore loop rearrangement to reach the final open state. This apparent conformational wave likely arises from the concerted, stepwise, additive structural changes of TRPV1 over many subdomains. Greater understanding of the RTx-mediated long-range allostery of TRPV1 could help further the therapeutic potential of RTx, which is a promising drug candidate for pain relief associated with advanced cancer or knee arthritis.

Self-Organization of Tissue Growth by Interfacial Mechanical Interactions in Multilayered Systems

Morphogenesis is a spatially and temporally regulated process involved in various physiological and pathological transformations. In addition to the associated biochemical factors, the physical regulation of morphogenesis has attracted increasing attention. However, the driving force of morphogenesis initiation remains elusive. Here, it is shown that during the growth of multilayered tissues, a morphogenetic process can be self-organized by the progression of compression gradient stemmed from the interfacial mechanical interactions between layers. In tissues with low fluidity, the compression gradient is progressively strengthened during growth and induces stratification by triggering symmetric-to-asymmetric cell division reorientation at the critical tissue size. In tissues with high fluidity, compression gradient is dynamic and induces cell rearrangement leading to 2D in-plane morphogenesis instead of 3D deformation. Morphogenesis can be tuned by manipulating tissue fluidity, cell adhesion forces, and mechanical properties to influence the progression of compression gradient during the development of cultured cell sheets and chicken embryos. Together, the dynamics of compression gradient arising from interfacial mechanical interaction provides a conserved mechanism underlying morphogenesis initiation and size control during tissue growth.

Prevalence and determinants of death registration and certification uptake in Uganda

Death registration in Uganda remains extremely low, yet mortality statistics are vital in health policy, planning, resource allocation and decision-making. According to NIRA, only 1% of deaths are registered annually, while Uganda Bureau of Statistics estimates death registration at 24% for the period 2011–2016. The wide variation between the administrative and survey statistics can be attributed to the restriction to only certified death registration by NIRA while survey statistics relate to all forms of death notification and registration at the different sub-national levels. Registration of deaths is of critical importance to individuals and a country’s government. Legally, it grants administrative rights in management of a deceased’s estate, and access to social (insurance and pension) benefits of a deceased person. It is also essential for official statistics and planning purposes. There is an urgent need for continuous and real-time collection of mortality data or statistics in Uganda. These statistics are of significance in public health for identifying the magnitude and distribution of major disease problems, and are essential for the design, implementation, monitoring, and assessment of health programmes and policies. Lack of such continuous and timely data has negative consequences for the achievement of both national and Sustainable Development Goals 3, 11, 16, and 17. This study assessed the determinants of death registration and certification, using a survey of 2018–2019 deaths in 2,100 households across four administrative regions of Uganda and Kampala district. Multivariate–binary logistic regression was used to model factors associated with the likelihood of a death being registered or certified. We find that around one-third of deaths were registered while death certificates were obtained for less than 5% of the total deaths. Death registration and certification varied notably within Uganda. Uptake of death registration and certification was associated with knowledge on death registration, region, access to mass media, age of the deceased, place of death, occupation of the deceased, relationship to household head and request for death certificate. There is need for decentralization of death registration services; massive sensitization of communities and creating demand for death registration.

Response of vertically-loaded pile in spatially-variable cement-treated soil

Despite the extensive application prospects of piles in cement-treated soil, few studies have explored the ultimate bearing capacity especially in consideration of the spatial variability of cement-treated soil. This study examines the performance of driven piles which were installed inside the cement-treated ground, considering the inherent spatial variability of the cemented soil and the positioning error during piles installation through finite element analyses. The deterministic and random finite element analysis results have shown that the shaft resistance mainly provided the ultimate bearing resistance of piles in cement-treated soil. The spatial variability reduced the global performance of pile installed through a cement-treated soil. The ultimate bearing resistance of the pile inserted in cement-treated soil was controlled by drained condition. Drained ultimate bearing resistance should be used to determine the design working compression load of pile in cement-treated soil.

Entropy Perspectives of Molecular and Evolutionary Biology

Attempts to find and quantify the supposed low entropy of organisms and its preservation are revised. The absolute entropy of the mixed components of non-living biomass (approximately −1.6 × 10³ J K⁻¹ L⁻¹) is the reference to which other entropy decreases would be ascribed to life. The compartmentation of metabolites and the departure from the equilibrium of metabolic reactions account for reductions in entropy of 1 and 40–50 J K⁻¹ L⁻¹, respectively, and, though small, are distinctive features of living tissues. DNA and proteins do not supply significant decreases in thermodynamic entropy, but their low informational entropy is relevant for life and its evolution. No other living feature contributes significantly to the low entropy associated with life. The photosynthetic conversion of radiant energy to biomass energy accounts for most entropy (2.8 × 10⁵ J K⁻¹ carbon kg⁻¹) produced by living beings. The comparatively very low entropy produced in other processes (approximately 4.8 × 10² J K⁻¹ L⁻¹ day⁻¹ in the human body) must be rapidly exported outside as heat to preserve low entropy decreases due to compartmentation and non-equilibrium metabolism. Enzymes and genes are described, whose control minimizes the rate of production of entropy and could explain selective pressures in biological evolution and the rapid proliferation of cancer cells.

BioCRNpyler: Compiling chemical reaction networks from biomolecular parts in diverse contexts

Biochemical interactions in systems and synthetic biology are often modeled with chemical reaction networks (CRNs). CRNs provide a principled modeling environment capable of expressing a huge range of biochemical processes. In this paper, we present a software toolbox, written in Python, that compiles high-level design specifications represented using a modular library of biochemical parts, mechanisms, and contexts to CRN implementations. This compilation process offers four advantages. First, the building of the actual CRN representation is automatic and outputs Systems Biology Markup Language (SBML) models compatible with numerous simulators. Second, a library of modular biochemical components allows for different architectures and implementations of biochemical circuits to be represented succinctly with design choices propagated throughout the underlying CRN automatically. This prevents the often occurring mismatch between high-level designs and model dynamics. Third, high-level design specification can be embedded into diverse biomolecular environments, such as cell-free extracts and in vivo milieus. Finally, our software toolbox has a parameter database, which allows users to rapidly prototype large models using very few parameters which can be customized later. By using BioCRNpyler, users ranging from expert modelers to novice script-writers can easily build, manage, and explore sophisticated biochemical models using diverse biochemical implementations, environments, and modeling assumptions.

This paper describes a new software package BioCRNpyler (pronounced “Biocompiler”) designed to support rapid development and exploration of mathematical models of biochemical networks and circuits by computational biologists, systems biologists, and synthetic biologists. BioCRNpyler allows its users to generate large complex models using very few lines of code in a way that is modular. To do this, BioCRNpyler uses a powerful new representation of biochemical circuits which defines their parts, underlying biochemical mechanisms, and chemical context independently. BioCRNpyler was developed as a Python scripting language designed to be accessible to beginning users as well as easily extendable and customizable for advanced users. Ultimately, we see Biocrnpyler being used to accelerate computer automated design of biochemical circuits and model driven hypothesis generation in biology.

Systems-based approaches to study immunometabolism

Technical advances at the interface of biology and computation, such as single-cell RNA-sequencing (scRNA-seq), reveal new layers of complexity in cellular systems. An emerging area of investigation using the systems biology approach is the study of the metabolism of immune cells. The diverse spectra of immune cell phenotypes, sparsity of immune cell numbers in vivo, limitations in the number of metabolites identified, dynamic nature of cellular metabolism and metabolic fluxes, tissue specificity, and high dependence on the local milieu make investigations in immunometabolism challenging, especially at the single-cell level. In this review, we define the systemic nature of immunometabolism, summarize cell- and system-based approaches, and introduce mathematical modeling approaches for systems interrogation of metabolic changes in immune cells. We close the review by discussing the applications and shortcomings of metabolic modeling techniques. With systems-oriented studies of metabolism expected to become a mainstay of immunological research, an understanding of current approaches toward systems immunometabolism will help investigators make the best use of current resources and push the boundaries of the discipline.

[Inflammation and infection: cellular and biochemical processes]

The terms inflammation and infection are often used interchangeably. Technically this is incorrect. Inflammation is defined as the body's response to a potentially damaging stimulus. Infection involves tissue invasion by microorganisms. An inflammatory reaction will be provoked when infection occurs in an otherwise healthy patient. Inflammation can be recognized clinically by 5 cardinal signs: rubor (redness), calor (warmth), tumor (swelling), dolor (pain), and functio laesa (loss of function). These clinical signs can be explained by the biochemical and cellular processes activated during the inflammatory response. Rubor and calor are the result of local vasodilation. Tumor, dolor and functio laesa result from extravasation of blood plasma, white blood cells, and inflammatory mediators. Pulpitis is an example of inflammation; a periapical abscess is an example of infection.