Valeria Tafintseva

Norwegian University of Life Sciences

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Trends

Author Order

Document Type

Co-Authors

Achim Köhler

Norwegian University of Life Sciences

Boris Zimmermann

Norwegian University of Life Sciences

Volha Shapaval

Norwegian University of Life Sciences

Simona Dzurendová

Norwegian University of Life Sciences

Johanne Heitmann Solheim

Norwegian University of Life Sciences

Isaac O. Afara

University of Eastern Finland

Rubina Shaikh

University of Eastern Finland

Boris Mizaikoff

Universität Ulm

Svein Jarle Horn

Norwegian University of Life Sciences

Kristin Tøndel

Norwegian University of Life Sciences

Cooperative Institutions

Norwegian University of Life Sciences

Nofima

Fafo Foundation

The Research Council of Norway

University of Eastern Finland

Consejo Nacional de Investigaciones Científicas y Técnicas

University of California, Davis

Norwegian University of Science and Technology

Finland University

Aarhus University

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Field

Microcultivation and FTIR spectroscopy-based screening revealed a nutrient-induced co-production of high-value metabolites in oleaginous Mucoromycota fungi

PLoS ONE (2020)

Simona Dzurendová Boris Zimmermann Achim Köhler Valeria Tafintseva Ondrej Slaný

Mucoromycota fungi possess a versatile metabolism and can utilize various substrates for production of industrially important products, such as lipids, chitin/chitosan, polyphosphates, pigments, alcohols and organic acids. However, as far as commercialisation is concerned, establishing industrial biotechnological processes based on Mucoromycota fungi is still challenging due to the high production costs compared to the final product value. Therefore, the development of co-production concept is highly desired since more than one valuable product could be produced at the time and the process has a potentially higher viability. To develop such biotechnological strategy, we applied a high throughput approach consisting of micro-titre cultivation and FTIR spectroscopy. This approach allows single-step biochemical fingerprinting of either fungal biomass or growth media without tedious extraction of metabolites. The influence of two types of nitrogen sources and different levels of inorganic phosphorus on the co-production of lipids, chitin/chitosan and polyphosphates for nine different oleaginous Mucoromycota fungi was evaluated. FTIR analysis of biochemical composition of Mucoromycota fungi and biomass yield showed that variation in inorganic phosphorus had higher effect when inorganic nitrogen source–ammonium sulphate–was used. It was observed that: (1) Umbelopsis vinacea reached almost double biomass yield compared to other strains when yeast extract was used as nitrogen source while phosphorus limitation had little effect on the biomass yield; (2) Mucor circinelloides, Rhizopus stolonifer, Amylomyces rouxii, Absidia glauca and Lichtheimia corymbifera overproduced chitin/chitosan under the low pH caused by the limitation of inorganic phosphorus; (3) Mucor circinelloides, Amylomyces rouxii, Rhizopus stolonifer and Absidia glauca were able to store polyphosphates in addition to lipids when high concentration of inorganic phosphorus was used; (4) the biomass and lipid yield of high-value lipid producers Mortierella alpina and Mortierella hyalina were significantly increased when high concentrations of inorganic phosphorus were combined with ammonium sulphate, while the same amount of inorganic phosphorus combined with yeast extract showed negative impact on the growth and lipid accumulation. FTIR spectroscopy revealed the co-production potential of several oleaginous Mucoromycota fungi forming lipids, chitin/chitosan and polyphosphates in a single cultivation process.

Mucor circinelloides

Rhizopus

10.1371/journal.pone.0234870

Cite

Citations (59)

Discrimination of grass pollen of different species by FTIR spectroscopy of individual pollen grains

Analytical and Bioanalytical Chemistry (2020)

Sabrina Diehn Boris Zimmermann Valeria Tafintseva Murat Bağcıoğlu Achim Köhler

Abstract Fourier-transform infrared (FTIR) spectroscopy enables the chemical characterization and identification of pollen samples, leading to a wide range of applications, such as paleoecology and allergology. This is of particular interest in the identification of grass (Poaceae) species since they have pollen grains of very similar morphology. Unfortunately, the correct identification of FTIR microspectroscopy spectra of single pollen grains is hindered by strong spectral contributions from Mie scattering. Embedding of pollen samples in paraffin helps to retrieve infrared spectra without scattering artifacts. In this study, pollen samples from 10 different populations of five grass species ( Anthoxanthum odoratum , Bromus inermis , Hordeum bulbosum , Lolium perenne , and Poa alpina ) were embedded in paraffin, and their single grain spectra were obtained by FTIR microspectroscopy. Spectra were subjected to different preprocessing in order to suppress paraffin influence on spectral classification. It is shown that decomposition by non-negative matrix factorization (NMF) and extended multiplicative signal correction (EMSC) that utilizes a paraffin constituent spectrum, respectively, leads to good success rates for the classification of spectra with respect to species by a partial least square discriminant analysis (PLS-DA) model in full cross-validation for several species. PLS-DA, artificial neural network, and random forest classifiers were applied on the EMSC-corrected spectra using an independent validation to assign spectra from unknown populations to the species. Variation within and between species, together with the differences in classification results, is in agreement with the systematics within the Poaceae family. The results illustrate the great potential of FTIR microspectroscopy for automated classification and identification of grass pollen, possibly together with other, complementary methods for single pollen chemical characterization.

10.1007/s00216-020-02628-2

Cite

Citations (25)

Laser-irradiating infrared attenuated total reflection spectroscopy of articular cartilage: Potential and challenges for diagnosing osteoarthritis

Osteoarthritis and Cartilage Open (2024)

Patrick Krebs M. Nägele Polina Fomina Vesa Virtanen Ervin Nippolainen

Attenuated total reflection

Reflection

10.1016/j.ocarto.2024.100466

Cite

Citations (0)

A robust metabolomics approach for the evaluation of human embryos fromin vitrofertilization

The Analyst (2021)

Cecilia Beatriz Fígoli Marcelo Garcea Claudio Bisioli Valeria Tafintseva Volha Shapaval

The identification of the most competent embryos for transfer to the uterus constitutes the main challenge of in vitro fertilization (IVF). We established a metabolomic-based approach by applying Fourier transform infrared (FTIR) spectroscopy on 130 samples of 3-day embryo culture supernatants from 26 embryos that implanted and 104 embryos that failed. On examining the internal structure of the data by unsupervised multivariate analysis, we found that the supernatant spectra of nonimplanted embryos constituted a highly heterogeneous group. Whereas ∼40% of these supernatants were spectroscopically indistinguishable from those of successfully implanted embryos, ∼60% exhibited diverse, heterogeneous metabolic fingerprints. This observation proved to be the direct result of pregnancy's multifactorial nature, involving both intrinsic embryonic traits and external characteristics. Our data analysis strategy thus involved one-class modelling techniques employing soft independent modelling of class analogy that identified deviant fingerprints as unsuitable for implantation. From these findings, we could develop a noninvasive Fourier-transform-infrared-spectroscopy-based approach that represents a shift in the fundamental paradigm for data modelling applied in assisted-fertilization technologies.

10.1039/d1an01191j

Cite

Citations (10)

Raman spectroscopy online monitoring of biomass production, intracellular metabolites and carbon substrates during submerged fermentation of oleaginous and carotenogenic microorganisms

Microbial Cell Factories (2023)

Simona Dzurendová Pernille Margrethe Olsen Dana Byrtusová Valeria Tafintseva Volha Shapaval

Abstract Background Monitoring and control of both growth media and microbial biomass is extremely important for the development of economical bioprocesses. Unfortunately, process monitoring is still dependent on a limited number of standard parameters (pH, temperature, gasses etc.), while the critical process parameters, such as biomass, product and substrate concentrations, are rarely assessable in-line. Bioprocess optimization and monitoring will greatly benefit from advanced spectroscopy-based sensors that enable real-time monitoring and control. Here, Fourier transform (FT) Raman spectroscopy measurement via flow cell in a recirculatory loop, in combination with predictive data modeling, was assessed as a fast, low-cost, and highly sensitive process analytical technology (PAT) system for online monitoring of critical process parameters. To show the general applicability of the method, submerged fermentation was monitored using two different oleaginous and carotenogenic microorganisms grown on two different carbon substrates: glucose fermentation by yeast Rhodotorula toruloides and glycerol fermentation by marine thraustochytrid Schizochytrium sp. Additionally, the online FT-Raman spectroscopy approach was compared with two at-line spectroscopic methods, namely FT-Raman and FT-infrared spectroscopies in high throughput screening (HTS) setups. Results The system can provide real-time concentration data on carbon substrate (glucose and glycerol) utilization, and production of biomass, carotenoid pigments, and lipids (triglycerides and free fatty acids). Robust multivariate regression models were developed and showed high level of correlation between the online FT-Raman spectral data and reference measurements, with coefficients of determination (R 2 ) in the 0.94–0.99 and 0.89–0.99 range for all concentration parameters of Rhodotorula and Schizochytrium fermentation, respectively. The online FT-Raman spectroscopy approach was superior to the at-line methods since the obtained information was more comprehensive, timely and provided more precise concentration profiles. Conclusions The FT-Raman spectroscopy system with a flow measurement cell in a recirculatory loop, in combination with prediction models, can simultaneously provide real-time concentration data on carbon substrate utilization, and production of biomass, carotenoid pigments, and lipids. This data enables monitoring of dynamic behaviour of oleaginous and carotenogenic microorganisms, and thus can provide critical process parameters for process optimization and control. Overall, this study demonstrated the feasibility of using FT-Raman spectroscopy for online monitoring of fermentation processes.

10.1186/s12934-023-02268-y

Cite

Citations (1)

Infrared Fiber-Optic Spectroscopy Detects Bovine Articular Cartilage Degeneration

Cartilage (2021)

Vesa Virtanen Ervin Nippolainen Rubina Shaikh Isaac O. Afara Juha Töyräs

Objective Joint injuries may lead to degeneration of cartilage tissue and initiate development of posttraumatic osteoarthritis. Arthroscopic surgeries can be used to treat joint injuries, but arthroscopic evaluation of articular cartilage quality is subjective. Fourier transform infrared spectroscopy combined with fiber optics and attenuated total reflectance crystal could be used for the assessment of tissue quality during arthroscopy. We hypothesize that fiber-optic mid-infrared spectroscopy can detect enzymatically and mechanically induced damage similar to changes occurring during progression of osteoarthritis. Design Bovine patellar cartilage plugs were extracted and degraded enzymatically and mechanically. Adjacent untreated samples were utilized as controls. Enzymatic degradation was done using collagenase and trypsin enzymes. Mechanical damage was induced by (1) dropping a weight impactor on the cartilage plugs and (2) abrading the cartilage surface with a rotating sandpaper. Fiber-optic mid-infrared spectroscopic measurements were conducted before and after treatments, and spectral changes were assessed with random forest, partial least squares discriminant analysis, and support vector machine classifiers. Results All models had excellent classification performance for detecting the different enzymatic and mechanical damage on cartilage matrix. Random forest models achieved accuracies between 90.3% and 77.8%, while partial least squares model accuracies ranged from 95.8% to 84.7%, and support vector machine accuracies from 91.7% to 80.6%. Conclusions The results suggest that fiber-optic Fourier transform infrared spectroscopy attenuated total reflectance spectroscopy is a viable way to detect minor and major degeneration of articular cartilage. Objective measures provided by fiber-optic spectroscopic methods could improve arthroscopic evaluation of cartilage damage.

10.1177/1947603521993221

Cite

Citations (14)

Global structure of sloppiness in a nonlinear model

Journal of Chemometrics (2014)

Valeria Tafintseva Kristin Tøndel Arcady Ponosov Harald Martens

The problem of structural ambiguity or “sloppiness” of a mathematical model is here studied by multivariate metamodeling techniques. If a given model is “sloppy”, it means that a number of different parameter combinations—“a neutral parameter set”—can give more or less the same model behavior and thus equally good fit to data. This paper presents a way to characterize the structure of such sloppiness. The model used for illustration is a nonlinear dynamic model of reaction kinetics—a simple version of the S‐system model. When fitted to time series data by various nonlinear curve fitting methods, an unexpected problem was discovered: For every time series, a large neutral parameter set was observed. Each of these sets was analyzed by principal component analysis and found to have clear, but nonlinear, subspace structure. The neutral parameter sets were found for many different time series data, and the global sloppiness structure of the model was characterized. This global sloppiness structure of the model allowed us to find strong correlations between parameters, and on this basis to simplify the original model. A method to reduce the ambiguity in kinetic model parameter estimates based on combining several time series is suggested. Copyright © 2014 John Wiley & Sons, Ltd.

10.1002/cem.2651

Cite

Citations (13)

Metabolites (2020)

Mihai Victor Curtasu Valeria Tafintseva Zachary A. Bendiks Maria L. Marco Achim Köhler

The metabolome and gut microbiota were investigated in a juvenile Göttingen minipig model. This study aimed to explore the metabolic effects of two carbohydrate sources with different degrees of risk in obesity development when associated with a high fat intake. A high-risk (HR) high-fat diet containing 20% fructose was compared to a control lower-risk (LR) high-fat diet where a similar amount of carbohydrate was provided as a mix of digestible and resistant starch from high amylose maize. Both diets were fed ad libitum. Non-targeted metabolomics was used to explore plasma, urine, and feces samples over five months. Plasma and fecal short-chain fatty acids were targeted and quantified. Fecal microbiota was analyzed using genomic sequencing. Data analysis was performed using sparse multi-block partial least squares regression. The LR diet increased concentrations of fecal and plasma total short-chain fatty acids, primarily acetate, and there was a higher relative abundance of microbiota associated with acetate production such as Bacteroidetes and Ruminococcus. A higher proportion of Firmicutes was measured with the HR diet, together with a lower alpha diversity compared to the LR diet. Irrespective of diet, the ad libitum exposure to the high-energy diets was accompanied by well-known biomarkers associated with obesity and diabetes, particularly branched-chain amino acids, keto acids, and other catabolism metabolites.

Metabolome

Ruminococcus

Resistant Starch

10.3390/metabo10110456

Cite

Citations (19)

Microcultivation and FTIR spectroscopy-based screening revealed a nutrient-induced co-production of high-value metabolites in oleaginous Mucoromycota fungi. Dataset

Zenodo (CERN European Organization for Nuclear Research) (2020)

Simona Dzurendová Boris Zimmermann Achim Köhler Valeria Tafintseva Ondrej Slaný

Dataset- publication Microcultivation and FTIR spectroscopy-based screening revealed a nutrient-induced co-production of high-value metabolites in oleaginous Mucoromycota fungi

Value (mathematics)

10.5281/zenodo.4569842

Cite

Citations (0)

Robust Metabolomics Approach For The Evaluation Of Human Embryos From In-Vitro Fertilization.

Research Square (Research Square) (2021)

Cecilia Beatriz Fígoli Marcelo Garcea Claudio Bisioli Valeria Tafintseva Volha Shapaval

Abstract The identification of the most competent embryos for transfer to the uterus constitutes the main challenge of in-vitro fertilization (IVF). We established a metabolomic-based approach applying Fourier Transform Infrared spectroscopy (FTIR) on 130 samples of 3-days embryo culture supernatants from 26 embryos that implanted and 104 that failed. Examining the internal structure of the data by unsupervised multivariate analysis, it was observed that the supernatants of nonimplanted embryos contained highly heterogeneous spectral features. These features were overlapping with metabolic-implantation fingerprints, thus demonstrating that in establishing embryo-assessment models a one-class modelling involving only the samples with positive-implantation outcomes should be applied. Analysis of variance confirmed that the women´s age (>40 years) undermined the implantation of the embryos exhibiting implantation metabolomics, and also that constituted a condition triggering embryos to express nonimplantation metabolomics. We conclude that IVF-success rates can be significantly improved if FTIR spectroscopy is used as an embryo-selection criterion.

10.21203/rs.3.rs-153253/v1

Cite

Citations (0)