Near-infrared hyperspectral image analysis for monitoring the cheese-ripening process.

Ripening is the most crucial process step in cheese manufacturing and constitutes multiple biochemical alterations that describe the final cheese quality and its perceived sensory attributes. The assessment of the cheese-ripening process is challenging and requires the effective analysis of a multitude of biochemical changes occurring during the process. This study monitored the biochemical and sensory attribute changes of paraffin wax-covered long-ripening hard cheeses (n = 79) during ripening by collecting samples at different stages of ripening. Near-infrared hyperspectral (NIR-HS) imaging, together with free amino acid, chemical composition, and sensory attributes, was studied to monitor the biochemical changes during the ripening process. Orthogonal projection-based multivariate calibration methods were used to characterize ripening-related and orthogonal components as well as the distribution map of chemical components. The results approve the NIR-HS imaging as a rapid tool for monitoring cheese maturity during ripening. Moreover, the pixelwise evaluation of images shows the homogeneity of cheese maturation at different stages of ripening. Among the chemical compositions, fat content and moisture are the most important variables correlating to NIR-HS images during the ripening process.

Hierarchical time-series analysis of dynamic bioprocess systems.

BACKGROUND: Monoclonal antibodies (mAbs) are leading types of 'blockbuster' biotherapeutics worldwide; they have been successfully used to treat various cancers and chronic inflammatory and autoimmune diseases. Biotherapeutics process development and manufacturing are complicated due to lack of understanding the factors that impact cell productivity and product quality attributes. Understanding complex interactions between cells, media, and process parameters on the molecular level is essential to bring biomanufacturing to the next level. This can be achieved by analyzing cell culture metabolic levels connected to vital process parameters like viable cell density (VCD). However, VCD and metabolic profiles are dynamic parameters and inherently correlated with time, leading to a significant correlation without actual causality. Many time-series methods deal with such issues. However, with metabolic profiling, the number of measured variables vastly exceeds the number of experiments, making most of existing methods ill-suited and hard to interpret. METHODS AND MAJOR RESULTS: Here we propose an alternative workflow using hierarchical dimension reduction to visualize and interpret the relation between evolution of metabolic profiles and dynamic process parameters. The first step of proposed method is focused on finding predictive relation between metabolic profiles and process parameter at all time points using OPLS regression. For each time point, the p(corr) obtained from OPLS model is considered as a differential metabogram and is further assessed using principal components analysis (PCA). CONCLUSIONS: Compared to traditional batch modeling, applying proposed methodology on metabolic data from Chinese Hamster Ovary (CHO) antibody production characterized the dynamic relation between metabolic profiles and critical process parameters.

Optimization of ultrasound-assisted production of ergosterol from Penicillium brevicompactum by Taguchi statistical method.

Ergosterol as a primary metabolite and precursor of vitamin D2, is the most plentiful mycosterols in fungal cell membrane. Process optimization to increase the yield and productivity of biological products is a topic of interest. Ultrasonic waves have many applications in biotechnology, like cell disruption, and enhancement of primary and secondary metabolites production. This study disclosed an optimal condition for ultrasound-assisted production (UAP) of ergosterol from Penicillium brevicompactum MUCL 19,011 using L9 Taguchi statistical method. The intensity (IS), time of sonication (TS), treatment frequency (TF), and number of days of treatment (DT) were allocated to study the effects of ultrasound on ergosterol production. The results were analyzed using Minitab version 19. The maximum ergosterol, 11 mg/g cell dry weight (CDW), was produced on the tenth day while all factors were at a low level. The days of treatment with a contribution of 45.48% was the most significant factor for ergosterol production. For the first time, this study revealed the positive effect of ultrasound on the production of ergosterol. Ergosterol production increased 73% (4.63 mg/g CDW) after process optimization. Finally, a mathematical model of ultrasound factors with a regression coefficient of R2 = 0.978 was obtained for the ergosterol production during ultrasound treatment.

Direct Implementation of Intestinal Permeability Test in NMR Metabolomics for Simultaneous Biomarker Discovery-A Feasibility Study in a Preterm Piglet Model.

Measurement of intestinal permeability (IP) is often used in the examination of inflammatory gastrointestinal disorders. IP can be assessed by measurement of urinary recovery of ingested non-metabolizable lactulose (L) and mannitol (M). The present study aimed to examine how measurements of IP can be integrated in a NMR-based metabolomics approach for a simultaneous quantification of L/M ratio and biomarker exploration. For this purpose, plasma and urine samples were collected from five-day-old preterm piglets (n = 20) with gastrointestinal disorders (subjected to intra-amniotic lipopolysaccharide (LPS, 1 mg/fetus)) after they had been administrated a 5% lactulose and 5% mannitol solution (15 mL/kg). The collected plasma and urine samples were analyzed by 1H NMR-based metabolomics. Urine L/M ratio measured by 1H NMR spectroscopy showed high correlation with the standard measurement of the urinary recoveries by enzymatic assays (r = 0.93, p < 0.05). Partial least squares (PLS) regressions and correlation analyses between L/M ratio and NMR metabolomics data revealed that L/M ratio was positively correlated with plasma lactate, acetate and succinate levels and negatively correlated with urinary hippuric acid and glycine. In conclusion, the present study demonstrated that NMR metabolomics enables simultaneous IP testing and discovery of biomarkers associated with an impaired intestinal permeability.

Common and distinct variation in data fusion of designed experimental data.

INTRODUCTION: Integrative analysis of multiple data sets can provide complementary information about the studied biological system. However, data fusion of multiple biological data sets can be complicated as data sets might contain different sources of variation due to underlying experimental factors. Therefore, taking the experimental design of data sets into account could be of importance in data fusion concept. OBJECTIVES: In the present work, we aim to incorporate the experimental design information in the integrative analysis of multiple designed data sets. METHODS: Here we describe penalized exponential ANOVA simultaneous component analysis (PE-ASCA), a new method for integrative analysis of data sets from multiple compartments or analytical platforms with the same underlying experimental design. RESULTS: Using two simulated cases, the result of simultaneous component analysis (SCA), penalized exponential simultaneous component analysis (P-ESCA) and ANOVA-simultaneous component analysis (ASCA) are compared with the proposed method. Furthermore, real metabolomics data obtained from NMR analysis of two different brains tissues (hypothalamus and midbrain) from the same piglets with an underlying experimental design is investigated by PE-ASCA. CONCLUSIONS: This method provides an improved understanding of the common and distinct variation in response to different experimental factors.

Rapid Cerebral Metabolic Shift during Neonatal Sepsis Is Attenuated by Enteral Colostrum Supplementation in Preterm Pigs.

Sepsis, the clinical manifestation of serious infection, may disturb normal brain development, especially in preterm infants with an immature brain. We hypothesized that neonatal sepsis induces systemic metabolic alterations that rapidly affect metabolic signatures in immature brain and cerebrospinal fluid (CSF). Cesarean-delivered preterm pigs systemically received 108 CFU/kg Staphylococcus epidermidis (SE) and were provided total parenteral nutrition (n = 9) or enteral supplementation with bovine colostrum (n = 10) and compared with uninfected pigs receiving parenteral nutrition (n = 7). Plasma, CSF, and brain tissue samples were collected after 24 h and analyzed by ¹H NMR-based metabolomics. Both plasma and CSF metabolomes revealed SE-induced changes in metabolite levels that reflected a modified energy metabolism. Hence, increased plasma lactate, alanine, and succinate levels, as well as CSF lactate levels, were observed during SE infection (all p < 0.05, ANOVA analysis). Myo-inositol, a glucose derivative known for beneficial effects on lung maturation in preterm infants, was also increased in plasma and CSF following SE infection. Enteral colostrum supplementation attenuated the lactate accumulation in blood and CSF. Bloodstream infection in preterm newborns was found to induce a rapid metabolic shift in both plasma and CSF, which was modulated by colostrum feeding.