NIR spectroscopy applied to the determination of 2Phenylethanol and LPhenylalanine concentrations in culture medium of Yarrowia lipolytica

BACKGROUND: This work aims at developing a method, based on near infrared (NIR) spectroscopy, to quantify 2phenylethanol (2PE) and Lphenylalanine (LPhe) concentrations during its microbial production by Yarrowia lipolytica. For this purpose, 197 samples obtained from different batch cultures were analyzed using Fourier transform near infrared (FTNIR) transmission spectroscopy in the range of 200 cm1 to 14000 cm1. RESULTS: A principal components analysis (PCA) was performed for clusters identification and outliers removal. A partial least square (PLS) regression was next applied to develop the calibration models, by an iterative method. The predictive ability of the models was confirmed by an external validation procedure with an independent sample set. The obtained results could be considered as promising with coefficients of determination (R2) of 0.92 for LPhe and 0.95 for 2PE, and residual prediction deviation (RPD) above three, for the ensemble data. CONCLUSIONS: The described methodology, using NIR spectroscopy and chemometrics, can be seen as a promising fast tool to determine both studied flavor compounds during biotechnological processes as alternative to chromatographic methods.The authors thank the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469 unit, COMPETE 2020 (POCI-01-0145FEDER-006684) and BioTecNorte operation (NORTE-01-0145FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 – Programa Operacional Regional do Norte. The authors also acknowledge financial support to Cristina Quintelas through a postdoctoral grant (SFRH/BPD/101338/2014) provided by FCT – Portugal.info:eu-repo/semantics/publishedVersio

New PLS analysis approach to wine volatile compounds characterization by near infrared spectroscopy (NIR)

This work aims to explore the potential of near infrared (NIR) spectroscopy to quantify volatile compounds in Vinho Verde wines, commonly determined by gas chromatography. For this purpose, 105 Vinho Verde wine samples were analyzed using Fourier transform near infrared (FT-NIR) transmission spectroscopy in the range of 5435cm1 to 6357cm1. Boxplot and principal components analysis (PCA) were performed for clusters identification and outliers removal. A partial least square (PLS) regression was then applied to develop the calibration models, by a new iterative approach. The predictive ability of the models was confirmed by an external validation procedure with an independent sample set. The obtained results could be considered as quite good with coefficients of determination (R2) varying from 0.94 to 0.97. The current methodology, using NIR spectroscopy and chemometrics, can be seen as a promising rapid tool to determine volatile compounds in Vinho Verde wines.The authors thank the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/ 04469/2013 unit, COMPETE 2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020–ProgramaOperacionalRegionaldoNorte.Theauthorsalso acknowledge the financial support to Zlatina Genisheva and Cristina Quintelas through the postdoctoral Grants (SFRH/BPD/108868/2015 and SFRH/BPD/101338/2014) provided by FCT – Portugal.info:eu-repo/semantics/publishedVersio

Simultaneous partial nitrification and 2-fluorophenol biodegradation with aerobic granular biomass: reactor performance and microbial communities

Supplementary data associated with this article can be found, in the online version, at: http://dx.doi.org/10.1016/j.biortech.2017.03.173.An aerobic granular bioreactor was operated for over 4 months, treating a synthetic wastewater with a high ammonium content (100 mg L-1). The inoculum was collected from a bioreactor performing simultaneous partial nitrification and aromatic compounds biodegradation. From day-56 onwards, 2-fluorophenol (2-FP) (12.4 mg L-1) was added to the feeding wastewater and the system was bioaugmented with a 2-FP degrading bacteria (Rhodococcus sp. FP1). By the end of operation, complete 2-FP biodegradation and partial nitrification were simultaneously achieved. Aerobic granules remained stable over time. During the 2-FP loading, a shift in the community structure occurred, coinciding with the improvement of 2-FP degradation. DGGE analysis did not allow to infer on the bioaugmented strain presence but pyrosequencing analysis detected Rhodococcus genus by the end of operation. Together with other potential phenolic-degraders within granules, these microorganisms were probably responsible for 2-FP degradation.This work was supported by Portuguese Funds from FCT - Fundação para a Ciência e a Tecnologia through the strategic funding of UID/Multi/ 50016/2013 and UID/BIO/04469/2013 units and COMPETE 2020 (POCI-01-0145-FEDER-006684) and Spanish Funds from Ministerio de Educación y Ciencia through the ONLYBIO project (CTQ2011-24745/PPQ). C.L. Amorim and D.P Mesquita wish to acknowledge the research grant from FCT (Ref. SFRH/BPD/96481/2013 and SFRH/BPD/82558/2011, respectively). C. Ramos wants to thank the Universitat Autònoma de Barcelona for his internship grant. The authors also thank to COST Action ES1202: Conceiving Wastewater Treatment in 2020 - Energetic, environmental and economic challenges; BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 – Programa Operacional Regional do Norte; and to TRITON thematic network (316RT0508) from the CYTED Programme. Thanks to Dr R.C. Pullar for helping to edit the English.info:eu-repo/semantics/publishedVersio

Polyhydroxyalkanoate granules quantification in mixed microbial cultures using image analysis: Sudan Black B versus Nile Blue A staining

Polyhydroxyalkanoates (PHA) can be produced and intracellularly accumulated as inclusions by mixed microbial cultures (MMC) for bioplastic production and in enhanced biological phosphorus removal (EBPR) systems. Classical methods for PHA quantification use a digestion step prior to chromatography analysis, rendering them labor intensive and time-consuming. The present work investigates the use of two quantitative image analysis (QIA) procedures specifically developed for PHA inclusions identification and quantification. MMC obtained from an EBPR system were visualized by bright-field and fluorescence microscopy for PHA inclusions detection, upon Sudan Black B (SBB) and Nile Blue A (NBA) staining, respectively. The captured color images were processed by QIA techniques and the image analysis data were further treated using multivariate statistical analysis. Partial least squares (PLS) regression coefficients of 0.90 and 0.86 were obtained between QIA parameters and PHA concentrations using SBB and NBA, respectively. It was found that both staining procedures might be seen as alternative methodologies to classical PHA determination.The authors thank the Fundacao para a Ciencia e a Tecnologia (FCT) Strategic Project PEst-OE/EQB/LA0023/2013 and the Project "BioEnv - Biotechnology and Bioengineering for a sustainable world", REF. NORTE-07-0124-FEDER-000048, co-funded by the Programa Operacional Regional do Norte (ON.2 - O Novo Norte), QREN, FEDER. The authors also acknowledge the financial support to Daniela P. Mesquita through the postdoctoral grant (SFRH/BPD/82558/2011) and the project PTDC/EBB-EBI/103147/2008 provided by FCT

Long-term stability of a non-adapted aerobic granular sludge process treating fish canning wastewater associated to EPS producers in the core microbiome

The tolerance of aerobic granular sludge (AGS) to variable wastewater composition is perceived as one of its greatest advantages compared to other aerobic processes. However, research studies select optimal operational conditions for evaluating AGS performance, such as the use of pre-adapted biomass and the control of wastewater composition. In this study, non-adapted granular sludge was used to treat fish canning wastewater presenting highly variable organic, nutrient and salt levels over a period of ca. 8 months. Despite salt levels up to 14 g NaCl L−1, the organic loading rate (OLR) was found to be the main factor driving AGS performance. Throughout the first months of operation, the OLR was generally lower than 1.2 kg COD m−3 day−1, resulting in stable nitrification and low COD and phosphorous levels at the outlet. An increase in OLR up to 2.3 kg COD m−3 day−1 disturbed nitrification and COD and phosphate removal, but a decrease to average values between 1 and 1.6 kg COD m−3 day−1 led to resuming of those processes. Most of the bacteria present in the AGS core microbiome were associated to extracellular polymeric substances (EPS) production, such as Thauera and Paracoccus, which increased during the higher OLR period. Ammonium-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) species were detected in AGS biomass; while AOB were identified throughout the operation, NOB were no further identified after the period of increased OLR. Different polyphosphate-accumulating organisms (PAOs) were detected along the process: Candidatus Accumulibacter, Tetrasphaera and Gemmatimonas. A non-adapted granular sludge was able to treat the fish canning wastewater and to tolerate salinity fluctuations up to 14 g L−1. Overall, a high microbial diversity associated to EPS producers allowed to preserve bacterial groups responsible for nutrients removal, contributing to the adaptation and long-term stability of the AGS system.info:eu-repo/semantics/publishedVersio

Quantification of pharmaceutical compounds in wastewater samples by Near Infrared Spectroscopy (NIR)

The quantification of pollutants, as pharmaceuticals, in wastewater is an issue of special concern. Usually, typical methods to quantify these products are time and reagent consuming. This paper describes the development and validation of a Fourier transform near-infrared (FT-NIR) spectroscopy methodology for the quantification of pharmaceuticals in wastewaters. For this purpose, 276 samples obtained from an activated sludge wastewater treatment process were analyzed in the range of 200 cm1 to 14000 cm1, and further treated by chemometric techniques to develop and validate the quantification models. The obtained results were found adequate for the prediction of ibuprofen, sulfamethoxazole, 17-estradiol and carbamazepine with coefficients of determination (R2) around 0.95 and residual prediction deviation (RPD) values above four, for the overall (training and validation) data points. These results are very promising and confirm that this technology can be seen as an alternative for the quantification of pharmaceuticals in wastewater.The authors thank the Portuguese Foundation for Science and Technology(FCT)under the scope of the strategic funding of UID/BIO/04469 unit, COMPETE 2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. The authors also acknowledge the financial support to Cristina Quintelas through the postdoctoral grant (SFRH/BPD/101338/2014) provided by FCT – Portugal.info:eu-repo/semantics/publishedVersio

Volatile fatty acids (VFA) production from wastewaters with high salinity-influence of pH, salinity and reactor configuration

The hydrocarbon-based economy is moving at a large pace to a decarbonized sustainable bioeconomy based on biorefining all types of secondary carbohydrate-based raw materials. In this work, 50 g L1 in COD of a mixture of food waste, brine and wastewater derived from a biodiesel production facility were used to produce organic acids, important building-blocks for a biobased industry. High salinity (1218 g L1), different reactors configuration operated in batch mode, and different initial pH were tested. In experiment I, a batch stirred reactor (BSR) at atmospheric pressure and a granular sludge bed column (GSBC) were tested with an initial pH of 5. In the end of the experiment, the acidification yield (a) was similar in both reactors (2224%, w/w); nevertheless, lactic acid was in lower concentrations in BSR (6.3 g L1 in COD), when compared to GSBC (8.0 g L1 in COD), and valeric was the dominant acid, reaching 17.3% (w/w) in the BSR. In experiment II, the BSR and a pressurized batch stirred reactor (PBSR, operated at 6 bar) were tested with initial pH 7. The a and the VFA concentration were higher in the BSR (46%, 22.8 g L1 in COD) than in the PBSR (41%, 20.3 g/L in COD), and longer chain acids were more predominant in BSR (24.4% butyric, 6.7% valeric, and 6.2% caproic acids) than in PBSR (23.2%, 6.2%, and 4.2%, respectively). The results show that initial pH of 7 allows achieving higher a, and the BSR presents the most suitable reactor among tested configurations to produce VFA from wastes/wastewaters with high salinity.This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04469/2020 unit, and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020-Programa Operacional Regional do Norte. Research of M. Carvalho was supported by the SALTIPHA project (PTDC/BTA-BTA/30902/2017), under the funding program 02/SAICT/2017-Projetos de Investigação Científica e Desenvolvimento Tecnológico (IC&DT) with reference NORTE-01-0145-FEDER-030902. J.V. Oliveira acknowledges the financial support of the FCT through the grant attributed (SFRH/BD/111911/2015).info:eu-repo/semantics/publishedVersio

Quantitative image analysis of polyhydroxyalkanoates inclusions from microbial mixed cultures under different SBR operation strategies

Polyhydroxyalkanoates (PHAs) produced from mixed microbial cultures (MMC), regarded as potential substitutes of petrochemical plastics, can be found as intracellular granules in various microorganisms under limited nutrient conditions and excess of carbon source. PHA is traditionally quantified by laborious and time-consuming chromatography analysis, and a simpler and faster method to assess PHA contents from MMC, such as quantitative image analysis (QIA), is of great interest. The main purpose of the present work was to upgrade a previously developed QIA methodology (Mesquita et al., 2013a, 2015) for MMC intracellular PHA contents quantification, increase the studied intracellular PHA concentration range and extend to different sequencing batch reactor (SBR) operation strategies. Therefore, the operation of a new aerobic dynamic feeding (ADF) SBR allowed further extending the studied operating conditions, dataset, and range of the MMC intracellular PHA contents from the previously reported anaerobic/aerobic cycle SBR. Nile Blue A (NBA) staining was employed for epifluorescence microscope visualization and image acquisition, further fed to a custom developed QIA. Data from each of the feast and famine cycles of both SBR were individually processed using chemometrics analysis, obtaining the correspondent partial least squares (PLS) models. The PHA concentrations determined from PLS models were further plotted against the results obtained in the standard chromatographic method. For both SBR the predicted ability was higher at the end of the feast stage than for the famine stage. Indeed, an independent feast and famine QIA data treatment was found to be fundamental to obtain the best prediction abilities. Furthermore, a promising overall correlation (R2 of 0.83) could be found combining the overall QIA data regarding the PHA prediction up to a concentration of 1785.1 mgL-1 (37.3 wt%). Thus, the results confirm that the presented QIA methodology can be seen as promising for estimating higher intracellular PHA concentrations for a larger reactors operation systems and further extending the prediction range of previous studies.This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE01-0145-FEDER-000004) funded by European Regional Development Fundunder the scope ofNorte2020 - ProgramaOperacional Regional do Norte.The authors also acknowledge the financial support to Cristiano S. Leal (PTDC/EBB-EBI/103147/2008, FCOMP-01-0124-FEDER009704) and Daniela P. Mesquita through the FCT postdoctoral grant (SFRH/BPD/82558/2011).info:eu-repo/semantics/publishedVersio

Monitoring biological wastewater treatment processes: Recent advances in spectroscopy applications

Biological processes based on aerobic and anaerobic technologies have been continuously developed to wastewater treatment and are currently routinely employed to reduce the contaminants discharge levels in the environment. However, most methodologies commonly applied for monitoring key parameters are labor intensive, time-consuming and just provide a snapshot of the process. Thus, spectroscopy applications in biological processes are, nowadays, considered a rapid and effective alternative technology for real-time monitoring though still lacking implementation in full-scale plants. In this review, the application of spectroscopic techniques to aerobic and anaerobic systems is addressed focusing on UV--Vis, infrared, and fluorescence spectroscopy. Furthermore, chemometric techniques, valuable tools to extract the relevant data, are also referred. To that effect, a detailed analysis is performed for aerobic and anaerobic systems to summarize the findings that have been obtained since 2000. Future prospects for the application of spectroscopic techniques in biological wastewater treatment processes are further discussed.The authors thank the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, COMPETE 2020 (POCI-01-0145-FEDER-006684) and the project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. The authors also acknowledge the financial support to Daniela P. Mesquita and Cristina Quintelas through the postdoctoral Grants (SFRH/BPD/82558/2011 and SFRH/BPD/101338/2014) provided by FCT - Portugal.info:eu-repo/semantics/publishedVersio

Three new pancreatic cancer susceptibility signals identified on chromosomes 1q32.1, 5p15.33 and 8q24.21.

Genome-wide association studies (GWAS) have identified common pancreatic cancer susceptibility variants at 13 chromosomal loci in individuals of European descent. To identify new susceptibility variants, we performed imputation based on 1000 Genomes (1000G) Project data and association analysis using 5,107 case and 8,845 control subjects from 27 cohort and case-control studies that participated in the PanScan I-III GWAS. This analysis, in combination with a two-staged replication in an additional 6,076 case and 7,555 control subjects from the PANcreatic Disease ReseArch (PANDoRA) and Pancreatic Cancer Case-Control (PanC4) Consortia uncovered 3 new pancreatic cancer risk signals marked by single nucleotide polymorphisms (SNPs) rs2816938 at chromosome 1q32.1 (per allele odds ratio (OR) = 1.20, P = 4.88x10 -15), rs10094872 at 8q24.21 (OR = 1.15, P = 3.22x10 -9) and rs35226131 at 5p15.33 (OR = 0.71, P = 1.70x10 -8). These SNPs represent independent risk variants at previously identified pancreatic cancer risk loci on chr1q32.1 ( NR5A2), chr8q24.21 ( MYC) and chr5p15.33 ( CLPTM1L- TERT) as per analyses conditioned on previously reported susceptibility variants. We assessed expression of candidate genes at the three risk loci in histologically normal ( n = 10) and tumor ( n = 8) derived pancreatic tissue samples and observed a marked reduction of NR5A2 expression (chr1q32.1) in the tumors (fold change -7.6, P = 5.7x10 -8). This finding was validated in a second set of paired ( n = 20) histologically normal and tumor derived pancreatic tissue samples (average fold change for three NR5A2 isoforms -31.3 to -95.7, P = 7.5x10 -4-2.0x10 -3). Our study has identified new susceptibility variants independently conferring pancreatic cancer risk that merit functional follow-up to identify target genes and explain the underlying biology