Optimization of the Lactococcus lactis nisin-controlled gene expression system NICE for industrial applications

BACKGROUND: The nisin-controlled gene expression system NICE of Lactococcus lactis is one of the most widely used expression systems in Gram-positive bacteria. Despite its widespread use, no optimization of the culture conditions and nisin induction has been carried out to obtain maximum yields. As a model system induced production of lysostaphin, an antibacterial protein (mainly against Staphylococcus aureus) produced by S. simulans biovar. Staphylolyticus, was used. Three main areas need optimization for maximum yields: cell density, nisin-controlled induction and protein production, and parameters specific for the target-protein. RESULTS: In a series of pH-controlled fermentations the following parameters were optimized: pH of the culture, use of NaOH or NH(4)OH as neutralizing agent, the addition of zinc and phosphate, the fermentation temperature, the time point of induction (cell density of the culture), the amount of nisin added for induction and the amount of three basic medium components, i.e. yeast extract, peptone and lactose. For each culture growth and lysostaphin production was followed. Lysostaphin production yields depended on all parameters that were varied. In the course of the optimization a three-fold increase in lysostaphin yield was achieved from 100 mg/l to 300 mg/l. CONCLUSION: Protein production with the NICE gene expression system in L. lactis strongly depends on the medium composition, the fermentation parameters and the amount of nisin added for induction. Careful optimization of key parameters lead to a significant increase in the yield of the target protein

Industrial-scale production and purification of a heterologous protein in Lactococcus lactis using the nisin-controlled gene expression system NICE: The case of lysostaphin

BACKGROUND: The NIsin-Controlled gene Expression system NICE of Lactococcus lactis is one of the most widespread used expression systems of Gram-positive bacteria. It is used in more than 100 laboratories for laboratory-scale gene expression experiments. However, L. lactis is also a micro-organism with a large biotechnological potential. Therefore, the aim of this study was to test whether protein production in L. lactis using the NICE system can also effectively be performed at the industrial-scale of fermentation. RESULTS: Lysostaphin, an antibacterial protein (mainly against Staphylococcus aureus) from S. simulans biovar. Staphylolyticus, was used as a model system. Food-grade lysostaphin expression constructs in L. lactis were grown at 1L-, 300-L and 3000-L scale and induced with nisin for lysostaphin production. The induction process was equally effective at all scales and yields of about 100 mg/L were obtained. Up-scaling was easy and required no specific effort. Furthermore, we describe a simple and effective way of downstream processing to obtain a highly purified lysostaphin, which has been used for clinical phase I trials. CONCLUSION: This is the first example that shows that nisin-regulated gene expression in L. lactis can be used at industrial scale to produce large amounts of a target protein, such as lysostaphin. Downstream processing was simple and in a few steps produced a highly purified and active enzyme

Contingent Valuation and Social Choice

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. How can you measure the net benefits to society from actions that impact environmental resources? An economist's answer is to employ Hicksian consumer surplus, determining the equivalent variation in income that leaves each consumer indifferent to the action. When consumers are rational and consumer surplus can be measured reliably from market demand functions, this is a satisfactory basis for welfare calculation, subject to the customary caveats about distributional equity and consistency if compensation is not actually paid. When externalities, public goods, or informational asymmetries interfere with the determination of consumer surplus from market demand functions, one can try to set up a hypothetical market to elicit an individual's equivalent variation, or willingness-to-pay (WTP). This is called the contingent valuation method (CVM). The approach elicits stated preferences from a sample of consumers using either openended questions that ask directly for WTP, or referendum (closed-ended) questions that present a bid or a sequence of bids to the consumer, and ask for a yes or no vote on whether each bid exceeds the subject's WTP. A single referendum experiment presents only one bid; a double referendum experiment presents a second bid that is conditioned on the subject's response to the first bid, lower if the first response is no and higher if it is yes. Agricultural & Applied Economics Association and Oxford University Press An extensive literature has investigated the use of CVM to value environmental goods, and in recent years has promoted it for evaluation of goods such as endangered species and wilderness areas whose value comes primarily from existence rather than active use.' The typical CVM experiment in environmental economics asks about a single commodity, often with a fairly abbreviated or stylized description that assumes the consumer can draw upon prior knowledge. Typically, there is no training of the consumer to reduce inconsistent (e.g. In assessing CVM, there are three commonsense questions that can be asked: (a) Is the method psychometrically robust, in that results cannot be altered substantively by changes in survey format, questionnaire design, and instructions that should be inconsequential when behavior is driven by maximization of rational preferences? (b) Is the method statistically reliable, in that the distribution of WTP can be estimated with acceptable precision using practical sample sizes? Reliability is a particular issue if CV surveys produce extreme responses with some probability, perhaps due to strategic misrepresentation. (c) Is the method economically sensible, in that the individual preferences measured by CVM are consistent with the logical requirements of rationality (e.g., transitivity), and at least broadly consistent with sensible features of economic preferences (e.g., plausible budget shares and income elasticities)? CVM might fail to meet these criteria because respondents receive incomplete information on the consequences of the available choices, or are given inadequate incentives to be truthful and avoid strategic misrepresentation, or because the experimental design is not sufficiently rich to detect and compensate for systematic and random response errors. Beyond such technical problems, there could be a fundamental failure of CVM if consumers do not have stable, classical preferences for the class of commodities, so that the foundations of Hicksian welfare analysis break down. Intuitively, the further removed a class of commodities from market goods where the consumer has the experience of repeated choices and the discipline of market forces, the greater the possibility of both technical and fundamental failures. The broad sweep of evidence from market research, cognitive psychology, and experimental economics suggests that the existence value of natural resources, involving very complex commodities that are far outside consumers' market experience, will be vulnerable to these failures (McFadden 1986). The following sections discuss, in turn, a series of statistical issues in analyzing WTP data, parametric methods for estimating mean WTP, an experiment that was designed to detect and quantify technical failures of CVM, and the results from the experiment. Using referendum questions complicates matters only slightly, since votes at a sufficiently broad and closely spaced range of bid levels can be used to estimate directly the distribution of WTP, and this in turn can be used to estimate the population mean. This claim is proved in McFadden (1994), which gives practical nonparametric estimators, and describes the restrictions necessary on referendum experimental design for these estimators to have good largesample properties. In overview, the result is that with truthful referendum data there are estimators whose mean square error is inversely proportional to sample size, provided the experimental design "undersmooths" by taking a relatively large number of bid levels, with relatively small samples at each bid.2 For example, when WTP is restricted a priori to a finite interval, one could distribute the bids evenly over this interval, with one respondent at each level. The common practice in CV referendum studies of taking a relatively small number of bid levels leads to estimators whose mean square errors decline more slowly with sample size. Statistical Issues in CV Data 2 When the support of the WTP distribution is not finite, additional restrictions on tail behavior are needed to assure the existence of mean WTP and the stated rate of convergence of nonparametric estimators

Antibody Recognition of Cancer-Related Gangliosides and Their Mimics Investigated Using in silico Site Mapping

Modified gangliosides may be overexpressed in certain types of cancer, thus, they are considered a valuable target in cancer immunotherapy. Structural knowledge of their interaction with antibodies is currently limited, due to the large size and high flexibility of these ligands. In this study, we apply our previously developed site mapping technique to investigate the recognition of cancer-related gangliosides by anti-ganglioside antibodies. The results reveal a potential ganglioside-binding motif in the four antibodies studied, suggesting the possibility of structural convergence in the anti-ganglioside immune response. The structural basis of the recognition of ganglioside-mimetic peptides is also investigated using site mapping and compared to ganglioside recognition. The peptides are shown to act as structural mimics of gangliosides by interacting with many of the same binding site residues as the cognate carbohydrate epitopes. These studies provide important clues as to the structural basis of immunological mimicry of carbohydrates

Decoration of T-independent antigen with ligands for CD22 and Siglec-G can suppress immunity and induce B cell tolerance in vivo

Autoreactive B lymphocytes first encountering self-antigens in peripheral tissues are normally regulated by induction of anergy or apoptosis. According to the “two-signal” model, antigen recognition alone should render B cells tolerant unless T cell help or inflammatory signals such as lipopolysaccharide are provided. However, no such signals seem necessary for responses to T-independent type 2 (TI-2) antigens, which are multimeric antigens lacking T cell epitopes and Toll-like receptor ligands. How then do mature B cells avoid making a TI-2–like response to multimeric self-antigens? We present evidence that TI-2 antigens decorated with ligands of inhibitory sialic acid–binding Ig-like lectins (siglecs) are poorly immunogenic and can induce tolerance to subsequent challenge with immunogenic antigen. Two siglecs, CD22 and Siglec-G, contributed to tolerance induction, preventing plasma cell differentiation or survival. Although mutations in CD22 and its signaling machinery have been associated with dysregulated B cell development and autoantibody production, previous analyses failed to identify a tolerance defect in antigen-specific mutant B cells. Our results support a role for siglecs in B cell self-/nonself-discrimination, namely suppressing responses to self-associated antigens while permitting rapid “missing self”–responses to unsialylated multimeric antigens. The results suggest use of siglec ligand antigen constructs as an approach for inducing tolerance

Prognostic indicators and outcomes of hospitalised COVID-19 patients with neurological disease: An individual patient data meta-analysis

BACKGROUND: Neurological COVID-19 disease has been reported widely, but published studies often lack information on neurological outcomes and prognostic risk factors. We aimed to describe the spectrum of neurological disease in hospitalised COVID-19 patients; characterise clinical outcomes; and investigate factors associated with a poor outcome. METHODS: We conducted an individual patient data (IPD) meta-analysis of hospitalised patients with neurological COVID-19 disease, using standard case definitions. We invited authors of studies from the first pandemic wave, plus clinicians in the Global COVID-Neuro Network with unpublished data, to contribute. We analysed features associated with poor outcome (moderate to severe disability or death, 3 to 6 on the modified Rankin Scale) using multivariable models. RESULTS: We included 83 studies (31 unpublished) providing IPD for 1979 patients with COVID-19 and acute new-onset neurological disease. Encephalopathy (978 [49%] patients) and cerebrovascular events (506 [26%]) were the most common diagnoses. Respiratory and systemic symptoms preceded neurological features in 93% of patients; one third developed neurological disease after hospital admission. A poor outcome was more common in patients with cerebrovascular events (76% [95% CI 67-82]), than encephalopathy (54% [42-65]). Intensive care use was high (38% [35-41]) overall, and also greater in the cerebrovascular patients. In the cerebrovascular, but not encephalopathic patients, risk factors for poor outcome included breathlessness on admission and elevated D-dimer. Overall, 30-day mortality was 30% [27-32]. The hazard of death was comparatively lower for patients in the WHO European region. INTERPRETATION: Neurological COVID-19 disease poses a considerable burden in terms of disease outcomes and use of hospital resources from prolonged intensive care and inpatient admission; preliminary data suggest these may differ according to WHO regions and country income levels. The different risk factors for encephalopathy and stroke suggest different disease mechanisms which may be amenable to intervention, especially in those who develop neurological symptoms after hospital admission

Autoantibodies neutralizing type I IFNs are present in ~4% of uninfected individuals over 70 years old and account for ~20% of COVID-19 deaths

Publisher Copyright: © 2021 The Authors, some rights reserved.Circulating autoantibodies (auto-Abs) neutralizing high concentrations (10 ng/ml; in plasma diluted 1:10) of IFN-alpha and/or IFN-omega are found in about 10% of patients with critical COVID-19 (coronavirus disease 2019) pneumonia but not in individuals with asymptomatic infections. We detect auto-Abs neutralizing 100-fold lower, more physiological, concentrations of IFN-alpha and/or IFN-omega (100 pg/ml; in 1:10 dilutions of plasma) in 13.6% of 3595 patients with critical COVID-19, including 21% of 374 patients >80 years, and 6.5% of 522 patients with severe COVID-19. These antibodies are also detected in 18% of the 1124 deceased patients (aged 20 days to 99 years; mean: 70 years). Moreover, another 1.3% of patients with critical COVID-19 and 0.9% of the deceased patients have auto-Abs neutralizing high concentrations of IFN-beta. We also show, in a sample of 34,159 uninfected individuals from the general population, that auto-Abs neutralizing high concentrations of IFN-alpha and/or IFN-omega are present in 0.18% of individuals between 18 and 69 years, 1.1% between 70 and 79 years, and 3.4% >80 years. Moreover, the proportion of individuals carrying auto-Abs neutralizing lower concentrations is greater in a subsample of 10,778 uninfected individuals: 1% of individuals 80 years. By contrast, auto-Abs neutralizing IFN-beta do not become more frequent with age. Auto-Abs neutralizing type I IFNs predate SARS-CoV-2 infection and sharply increase in prevalence after the age of 70 years. They account for about 20% of both critical COVID-19 cases in the over 80s and total fatal COVID-19 cases.Peer reviewe

Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes.

OBJECTIVE: Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS: We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS: Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS: We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis

The risk of COVID-19 death is much greater and age dependent with type I IFN autoantibodies

SignificanceThere is growing evidence that preexisting autoantibodies neutralizing type I interferons (IFNs) are strong determinants of life-threatening COVID-19 pneumonia. It is important to estimate their quantitative impact on COVID-19 mortality upon SARS-CoV-2 infection, by age and sex, as both the prevalence of these autoantibodies and the risk of COVID-19 death increase with age and are higher in men. Using an unvaccinated sample of 1,261 deceased patients and 34,159 individuals from the general population, we found that autoantibodies against type I IFNs strongly increased the SARS-CoV-2 infection fatality rate at all ages, in both men and women. Autoantibodies against type I IFNs are strong and common predictors of life-threatening COVID-19. Testing for these autoantibodies should be considered in the general population

Prognostic indicators and outcomes of hospitalised COVID-19 patients with neurological disease: An individual patient data meta-analysis.

BackgroundNeurological COVID-19 disease has been reported widely, but published studies often lack information on neurological outcomes and prognostic risk factors. We aimed to describe the spectrum of neurological disease in hospitalised COVID-19 patients; characterise clinical outcomes; and investigate factors associated with a poor outcome.MethodsWe conducted an individual patient data (IPD) meta-analysis of hospitalised patients with neurological COVID-19 disease, using standard case definitions. We invited authors of studies from the first pandemic wave, plus clinicians in the Global COVID-Neuro Network with unpublished data, to contribute. We analysed features associated with poor outcome (moderate to severe disability or death, 3 to 6 on the modified Rankin Scale) using multivariable models.ResultsWe included 83 studies (31 unpublished) providing IPD for 1979 patients with COVID-19 and acute new-onset neurological disease. Encephalopathy (978 [49%] patients) and cerebrovascular events (506 [26%]) were the most common diagnoses. Respiratory and systemic symptoms preceded neurological features in 93% of patients; one third developed neurological disease after hospital admission. A poor outcome was more common in patients with cerebrovascular events (76% [95% CI 67-82]), than encephalopathy (54% [42-65]). Intensive care use was high (38% [35-41]) overall, and also greater in the cerebrovascular patients. In the cerebrovascular, but not encephalopathic patients, risk factors for poor outcome included breathlessness on admission and elevated D-dimer. Overall, 30-day mortality was 30% [27-32]. The hazard of death was comparatively lower for patients in the WHO European region.InterpretationNeurological COVID-19 disease poses a considerable burden in terms of disease outcomes and use of hospital resources from prolonged intensive care and inpatient admission; preliminary data suggest these may differ according to WHO regions and country income levels. The different risk factors for encephalopathy and stroke suggest different disease mechanisms which may be amenable to intervention, especially in those who develop neurological symptoms after hospital admission