Cell-cell metabolite exchange creates a pro-survival metabolic environment that extends lifespan.

Metabolism is deeply intertwined with aging. Effects of metabolic interventions on aging have been explained with intracellular metabolism, growth control, and signaling. Studying chronological aging in yeast, we reveal a so far overlooked metabolic property that influences aging via the exchange of metabolites. We observed that metabolites exported by young cells are re-imported by chronologically aging cells, resulting in cross-generational metabolic interactions. Then, we used self-establishing metabolically cooperating communities (SeMeCo) as a tool to increase metabolite exchange and observed significant lifespan extensions. The longevity of the SeMeCo was attributable to metabolic reconfigurations in methionine consumer cells. These obtained a more glycolytic metabolism and increased the export of protective metabolites that in turn extended the lifespan of cells that supplied them with methionine. Our results establish metabolite exchange interactions as a determinant of cellular aging and show that metabolically cooperating cells can shape the metabolic environment to extend their lifespan.

The proteomic landscape of genome-wide genetic perturbations.

Functional genomic strategies have become fundamental for annotating gene function and regulatory networks. Here, we combined functional genomics with proteomics by quantifying protein abundances in a genome-scale knockout library in Saccharomyces cerevisiae, using data-independent acquisition mass spectrometry. We find that global protein expression is driven by a complex interplay of (1) general biological properties, including translation rate, protein turnover, the formation of protein complexes, growth rate, and genome architecture, followed by (2) functional properties, such as the connectivity of a protein in genetic, metabolic, and physical interaction networks. Moreover, we show that functional proteomics complements current gene annotation strategies through the assessment of proteome profile similarity, protein covariation, and reverse proteome profiling. Thus, our study reveals principles that govern protein expression and provides a genome-spanning resource for functional annotation.

Complement activation induces excessive T cell cytotoxicity in severe COVID-19.

Severe COVID-19 is linked to both dysfunctional immune response and unrestrained immunopathology, and it remains unclear whether T cells contribute to disease pathology. Here, we combined single-cell transcriptomics and single-cell proteomics with mechanistic studies to assess pathogenic T cell functions and inducing signals. We identified highly activated CD16+ T cells with increased cytotoxic functions in severe COVID-19. CD16 expression enabled immune-complex-mediated, T cell receptor-independent degranulation and cytotoxicity not found in other diseases. CD16+ T cells from COVID-19 patients promoted microvascular endothelial cell injury and release of neutrophil and monocyte chemoattractants. CD16+ T cell clones persisted beyond acute disease maintaining their cytotoxic phenotype. Increased generation of C3a in severe COVID-19 induced activated CD16+ cytotoxic T cells. Proportions of activated CD16+ T cells and plasma levels of complement proteins upstream of C3a were associated with fatal outcome of COVID-19, supporting a pathological role of exacerbated cytotoxicity and complement activation in COVID-19.

Changes of Cell Biochemical States Are Revealed in Protein Homomeric Complex Dynamics.

We report here a simple and global strategy to map out gene functions and target pathways of drugs, toxins, or other small molecules based on "homomer dynamics" protein-fragment complementation assays (hdPCA). hdPCA measures changes in self-association (homomerization) of over 3,500 yeast proteins in yeast grown under different conditions. hdPCA complements genetic interaction measurements while eliminating the confounding effects of gene ablation. We demonstrate that hdPCA accurately predicts the effects of two longevity and health span-affecting drugs, the immunosuppressant rapamycin and the type 2 diabetes drug metformin, on cellular pathways. We also discovered an unsuspected global cellular response to metformin that resembles iron deficiency and includes a change in protein-bound iron levels. This discovery opens a new avenue to investigate molecular mechanisms for the prevention or treatment of diabetes, cancers, and other chronic diseases of aging.

Spontaneously established syntrophic yeast communities improve bioproduction.

Nutritional codependence (syntrophy) has underexplored potential to improve biotechnological processes by using cooperating cell types. So far, design of yeast syntrophic communities has required extensive genetic manipulation, as the co-inoculation of most eukaryotic microbial auxotrophs does not result in cooperative growth. Here we employ high-throughput phenotypic screening to systematically test pairwise combinations of auxotrophic Saccharomyces cerevisiae deletion mutants. Although most coculture pairs do not enter syntrophic growth, we identify 49 pairs that spontaneously form syntrophic, synergistic communities. We characterized the stability and growth dynamics of nine cocultures and demonstrated that a pair of tryptophan auxotrophs grow by exchanging a pathway intermediate rather than end products. We then introduced a malonic semialdehyde biosynthesis pathway split between different pairs of auxotrophs, which resulted in increased production. Our results report the spontaneous formation of stable syntrophy in S. cerevisiae auxotrophs and illustrate the biotechnological potential of dividing labor in a cooperating intraspecies community.

Inorganic sulfur fixation via a new homocysteine synthase allows yeast cells to cooperatively compensate for methionine auxotrophy.

The assimilation, incorporation, and metabolism of sulfur is a fundamental process across all domains of life, yet how cells deal with varying sulfur availability is not well understood. We studied an unresolved conundrum of sulfur fixation in yeast, in which organosulfur auxotrophy caused by deletion of the homocysteine synthase Met17p is overcome when cells are inoculated at high cell density. In combining the use of self-establishing metabolically cooperating (SeMeCo) communities with proteomic, genetic, and biochemical approaches, we discovered an uncharacterized gene product YLL058Wp, herein named Hydrogen Sulfide Utilizing-1 (HSU1). Hsu1p acts as a homocysteine synthase and allows the cells to substitute for Met17p by reassimilating hydrosulfide ions leaked from met17Δ cells into O-acetyl-homoserine and forming homocysteine. Our results show that cells can cooperate to achieve sulfur fixation, indicating that the collective properties of microbial communities facilitate their basic metabolic capacity to overcome sulfur limitation.

Real-world evidence on clinical outcomes of people with type 1 diabetes using open-source and commercial automated insulin dosing systems: A systematic review.

AIMS: Several commercial and open-source automated insulin dosing (AID) systems have recently been developed and are now used by an increasing number of people with diabetes (PwD). This systematic review explored the current status of real-world evidence on the latest available AID systems in helping to understand their safety and effectiveness. METHODS: A systematic review of real-world studies on the effect of commercial and open-source AID system use on clinical outcomes was conducted employing a devised protocol (PROSPERO ID 257354). RESULTS: Of 441 initially identified studies, 21 published 2018-2021 were included: 12 for Medtronic 670G; one for Tandem Control-IQ; one for Diabeloop DBLG1; two for AndroidAPS; one for OpenAPS; one for Loop; three comparing various types of AID systems. These studies found that several types of AID systems improve Time-in-Range and haemoglobin A1c (HbA1c ) with minimal concerns around severe hypoglycaemia. These improvements were observed in open-source and commercially developed AID systems alike. CONCLUSIONS: Commercially developed and open-source AID systems represent effective and safe treatment options for PwD of several age groups and genders. Alongside evidence from randomized clinical trials, real-world studies on AID systems and their effects on glycaemic outcomes are a helpful method for evaluating their safety and effectiveness.

Comparative Evaluation of Disinfection Protocols for Dental Impressions in Prosthodontics.

BACKGROUND: In prosthodontics, dental impressions are essential for creating precise dental restorations. However, these impressions are susceptible to microbial contamination, which can pose a risk of infection to patients. Consequently, effective disinfection methods are crucial to prevent postoperative infections. This study aims to evaluate the effectiveness of various disinfection techniques for dental impressions used in prosthodontics. MATERIALS AND METHODS: A total of 148 poured dental impressions were randomized into three disinfection groups: immersed in 0.5% sodium hypochlorite, 2% glutaraldehyde, or 0.2% chlorhexidine solution. The bacterial contamination was evaluated by direct colony-forming unit (CFU) counting, while the dimensional accuracy and surface detail duplication of each resin sample were determined as physical properties. Data were analyzed using SPSS version 23.0 (IBM Corp., Armonk, NY). Either analysis of variance (ANOVA) with the option for post-hoc or non-parametric tests was used to investigate and compare the efficacy of the better disinfection protocols where the p-value was considered significant if less than 0.05. RESULTS: Glutaraldehyde showed the lowest mean CFU count (2.5 log10 CFUs), followed by sodium hypochlorite (3.2 log10 CFUs) and chlorhexidine (3.5 log10 CFUs). All disinfection protocols were able to significantly reduce microbial contamination when compared with the control group (p < 0.05). The results of the physical property assessment demonstrated acceptable dimensional accuracy in all tested protocols, with slight differences recorded between them regarding the reproduction of surface detail. More specifically, the mean dimensional deviation was in the range between 0.02 and 0.04 mm, while scores for surface detail reproduction ranged from 2 to 4. The ANOVA results revealed significant differences in microbial contamination levels (F(2, 145) = 5.72, p = 0.007) and dimensional accuracy (F(2, 145) = 3.45, p = 0.032) between the various disinfection protocols. CONCLUSION: This study enlightens the effective sterilization protocol to be adopted in prosthodontics for dental impressions. Glutaraldehyde was most effective in microbial reduction, while sodium hypochlorite and chlorhexidine were equally effective. Therefore, clinicians must be vigilant in assessing the type of microbial flora that can be encountered during prosthodontic procedures while choosing disinfection protocols for patient safety and quality of impressions.

A Comparative Evaluation of the Bonding Strength, Marginal Adaptation, and Microleakage of Dental Cements in Prosthodontics: An In Vitro Comparative Study.

BACKGROUND: The primary function of dental cement is to seal and support prosthodontic restorative materials. Proper selection of the dental cement contributes to the clinical success of the restoration. METHODS: A total of 166 molar tooth samples were prepared to simulate the type of tooth commonly found in prosthodontic practice. Each sample was restored using one of the tested dental cement materials employing a prestabilized methodology. The performance of resin-modified glass ionomer cement (RMGIC) (GC Fuji PLUS Capsule, GC America, Alsip, IL), zinc phosphate cement (ZPC) (Dentsply Sirona, Charlotte, NC), and resin cement (RC) (RelyX ARC, 3M ESPE, Saint Paul, MN) in bonding strength, marginal adaptation, and microleakage was evaluated and compared. The bonding strength, marginal adaptation, and microgroove were tested using specific established methodologies. The outcomes were then analyzed using statistical analyses for means and standard deviations to compare different types of dental cement. RESULTS: The total outcome shows that the highest bonding strength with the highest mean was the resin cement, rating 24.8 MPa, followed by RMGIC and ZPC at 20.5 and 18.9 MPa, respectively. The marginal adaptation scores indicate that RC had the highest score at a mean of 4, followed by ZPC at 3.2 and RMGIC at 2.5. The dye penetration measurements in millimeters revealed that ZPC had a penetration of 0.31 mm, RMGIC had a penetration of 0.25 mm, and RC had the least penetration at 0.20 mm. The results of the statistical data analysis show significant differences between the dental cements in bonding strength and marginal adaptation. CONCLUSION: In conclusion, resin cement demonstrated superior performance in bonding strength, marginal adaptation, and resistance to microleakage compared to RMGIC and zinc phosphate cement. These findings highlight the importance of selecting resin cement for achieving optimal clinical outcomes in prosthodontic restorations.

Oxonium ion scanning mass spectrometry for large-scale plasma glycoproteomics.

Protein glycosylation, a complex and heterogeneous post-translational modification that is frequently dysregulated in disease, has been difficult to analyse at scale. Here we report a data-independent acquisition technique for the large-scale mass-spectrometric quantification of glycopeptides in plasma samples. The technique, which we named 'OxoScan-MS', identifies oxonium ions as glycopeptide fragments and exploits a sliding-quadrupole dimension to generate comprehensive and untargeted oxonium ion maps of precursor masses assigned to fragment ions from non-enriched plasma samples. By applying OxoScan-MS to quantify 1,002 glycopeptide features in the plasma glycoproteomes from patients with COVID-19 and healthy controls, we found that severe COVID-19 induces differential glycosylation in IgA, haptoglobin, transferrin and other disease-relevant plasma glycoproteins. OxoScan-MS may allow for the quantitative mapping of glycoproteomes at the scale of hundreds to thousands of samples.

Metabolic heterogeneity and cross-feeding within isogenic yeast populations captured by DILAC.

Genetically identical cells are known to differ in many physiological parameters such as growth rate and drug tolerance. Metabolic specialization is believed to be a cause of such phenotypic heterogeneity, but detection of metabolically divergent subpopulations remains technically challenging. We developed a proteomics-based technology, termed differential isotope labelling by amino acids (DILAC), that can detect producer and consumer subpopulations of a particular amino acid within an isogenic cell population by monitoring peptides with multiple occurrences of the amino acid. We reveal that young, morphologically undifferentiated yeast colonies contain subpopulations of lysine producers and consumers that emerge due to nutrient gradients. Deconvoluting their proteomes using DILAC, we find evidence for in situ cross-feeding where rapidly growing cells ferment and provide the more slowly growing, respiring cells with ethanol. Finally, by combining DILAC with fluorescence-activated cell sorting, we show that the metabolic subpopulations diverge phenotypically, as exemplified by a different tolerance to the antifungal drug amphotericin B. Overall, DILAC captures previously unnoticed metabolic heterogeneity and provides experimental evidence for the role of metabolic specialization and cross-feeding interactions as a source of phenotypic heterogeneity in isogenic cell populations.

Metal ion availability and homeostasis as drivers of metabolic evolution and enzyme function.

Metal ions are potent catalysts and have been available for cellular biochemistry at all stages of evolution. Growing evidence suggests that metal catalysis was critical for the origin of the very first metabolic reactions. With approximately 80% of modern metabolic pathways being dependent on metal ions, metallocatalysis and homeostasis continue to be essential for intracellular metabolic networks and physiology. However, the genetic network that controls metal ion homeostasis and the impact of metal availability on metabolism is poorly understood. Here, we review recent work on gene and protein evolution relevant for better understanding metal ion biology and its role in metabolism. We highlight the importance of analysing the origin and evolution of enzyme catalysis in the context of catalytically relevant metal ions, summarise unanswered questions essential for developing a comprehensive understanding of metal ion homeostasis and advocate for the consideration of metal ion properties and availability in the design and directed evolution of novel enzymes and pathways.

A proteomic survival predictor for COVID-19 patients in intensive care.

Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care.

The metabolic growth limitations of petite cells lacking the mitochondrial genome.

Eukaryotic cells can survive the loss of their mitochondrial genome, but consequently suffer from severe growth defects. 'Petite yeasts', characterized by mitochondrial genome loss, are instrumental for studying mitochondrial function and physiology. However, the molecular cause of their reduced growth rate remains an open question. Here we show that petite cells suffer from an insufficient capacity to synthesize glutamate, glutamine, leucine and arginine, negatively impacting their growth. Using a combination of molecular genetics and omics approaches, we demonstrate the evolution of fast growth overcomes these amino acid deficiencies, by alleviating a perturbation in mitochondrial iron metabolism and by restoring a defect in the mitochondrial tricarboxylic acid cycle, caused by aconitase inhibition. Our results hence explain the slow growth of mitochondrial genome-deficient cells with a partial auxotrophy in four amino acids that results from distorted iron metabolism and an inhibited tricarboxylic acid cycle.

A time-resolved proteomic and prognostic map of COVID-19.

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease.

NOX2 Is Critical to Endocardial to Mesenchymal Transition and Heart Development.

NADPH oxidases (NOX) are a major source of reactive oxygen species (ROS) production in the heart. ROS signaling regulates gene expression, cell proliferation, apoptosis, and migration. However, the role of NOX2 in embryonic heart development remains elusive. We hypothesized that deficiency of Nox2 disrupts endocardial to mesenchymal transition (EndMT) and results in congenital septal and valvular defects. Our data show that 34% of Nox2-/- neonatal mice had various congenital heart defects (CHDs) including atrial septal defects (ASD), ventricular septal defects (VSD), atrioventricular canal defects (AVCD), and malformation of atrioventricular and aortic valves. Notably, Nox2-/- embryonic hearts show abnormal development of the endocardial cushion as evidenced by decreased cell proliferation and an increased rate of apoptosis. Additionally, Nox2 deficiency disrupted EndMT of atrioventricular cushion explants ex vivo. Furthermore, treatment with N-acetylcysteine (NAC) to reduce ROS levels in the wild-type endocardial cushion explants decreased the number of cells undergoing EndMT. Importantly, deficiency of Nox2 was associated with reduced expression of Gata4, Tgfß2, Bmp2, Bmp4, and Snail1, which are critical to endocardial cushion and valvoseptal development. We conclude that NOX2 is critical to EndMT, endocardial cushion cell proliferation, and normal embryonic heart development.

A Global Screen for Assembly State Changes of the Mitotic Proteome by SEC-SWATH-MS.

Living systems integrate biochemical reactions that determine the functional state of each cell. Reactions are primarily mediated by proteins. In proteomic studies, these have been treated as independent entities, disregarding their higher-level organization into complexes that affects their activity and/or function and is thus of great interest for biological research. Here, we describe the implementation of an integrated technique to quantify cell-state-specific changes in the physical arrangement of protein complexes concurrently for thousands of proteins and hundreds of complexes. Applying this technique to a comparison of human cells in interphase and mitosis, we provide a systematic overview of mitotic proteome reorganization. The results recall key hallmarks of mitotic complex remodeling and suggest a model of nuclear pore complex disassembly, which we validate by orthogonal methods. To support the interpretation of quantitative SEC-SWATH-MS datasets, we extend the software CCprofiler and provide an interactive exploration tool, SECexplorer-cc.

CT-based interstitial brachytherapy in advanced gynecologic malignancies: outcomes from a single institution experience.

PURPOSE: To evaluate the clinical outcomes of women receiving a "short" course of high-dose-rate gynecologic interstitial brachytherapy (HDR-ISBT) boost with CT-based 3D planning. METHODS AND MATERIALS: Forty-seven women with no prior radiation received HDR-ISBT from August 2004 to February 2012. The mean external beam radiotherapy dose was 45 Gy. A mean HDR-ISBT boost dose of 18.4 Gy was delivered over 2-4 fractions. Dose volume histograms (DVHs) were computed for organs at risk and clinical target volume. RESULTS: With a median followup of 34.8 months, the 3-year local control rate was 68%. Sixteen patients were identified to have tumor recurrence (including eight local). The median time to any recurrence was 26.8 months. Relapse-free survival and overall survival at 3 years was 65% and 73%, respectively. Ten patients experienced Grade 3 late toxicity, mainly vaginal (5) and proctitis (3). The mean prescription volume (V100) was 85 cc and the mean D90 to CTV was 98%. The mean cumulative dose to tumor was 69.9 Gy (equivalent dose in 2 Gy). The mean cumulative equivalent dose in 2 Gy to D2cc of bladder and rectum was 60.9 Gy and 63.0 Gy, respectively. CONCLUSION: A "short" course HDR-ISBT is effective, safe, and convenient with acceptable local control and toxicity. Higher dose per fraction is similar to an external beam radiotherapy stereotactic boost with the inherent advantages of brachytherapy. A shorter overall time for HDR-ISBT means less time that patients are immobilized and in hospital, making it less resource intensive than a longer course.