Microbiology for chemical engineers - from macro to micro scale

Recent developments in microbial techniques (such as PCR, GE, FISH) have allowed researchers to detect, identify and quantify microorganisms without the limitation of culture-dependent methods. This has given both engineers and scientists a more fundamental understanding about systems containing microorganisms. These techniques can be used to monitor bacteria in wastewater treatment systems, soil and sea, industrial fermentation, food technology, and improve floccability, etc. However, despite these techniques being readily available and relatively cheap, they are not widely used by engineers. Hence, the aim of this paper is to introduce these techniques, and their applications, to chemical engineers. Two different studies related to industrial wastewater treatment, but applicable to general microorganism systems, will be presented: (1) microbial stability of pure cultures, and (2) bioreactor population shifts during alternating operational conditions. In (1), two bioreactors, inoculated with two different pure cultures, (A) Xanthobacter aut GJ10 and (B) Bulkholderia sp JS150, degrading 1,2-dichloroethane (DCE) and monochlorobenzene (MCB), respectively, were followed over time (Emanuelsson et al ., 2005). Specific and universal 16S rRNA oligonucleotide probes were used to identify the bacteria. It was found that bioreactor (A) remained pure for 290 days, whereas bioreactor (B) became contaminated within one week. The difference in behaviour is attributed to the pathway required to degrade DCE. In (2), the stability of a bacterial strain, which was isolated on the basis of its capability to degrade 2-fluorobenzoate from contaminated soil, in three different, up-flow fixed bed reactors operated under shock loads and starvation periods, was followed by denaturing gradient gel electrophoresis (DGGE) (Emanuelsson et al ., 2006). All bioreactors were rapidly colonised by different bacteria; however, the communities remained fairly stable over time, and shifts in bacterial populations were mainly found during the starvation periods

A universal mechanism generating clusters of differentiated loci during divergence-with-migration

Genome-wide patterns of genetic divergence reveal mechanisms of adaptation under gene flow. Empirical data show that divergence is mostly concentrated in narrow genomic regions. This pattern may arise because differentiated loci protect nearby mutations from gene flow, but recent theory suggests this mechanism is insufficient to explain the emergence of concentrated differentiation during biologically realistic timescales. Critically, earlier theory neglects an inevitable consequence of genetic drift: stochastic loss of local genomic divergence. Here we demonstrate that the rate of stochastic loss of weak local differentiation increases with recombination distance to a strongly diverged locus and, above a critical recombination distance, local loss is faster than local 'gain' of new differentiation. Under high migration and weak selection this critical recombination distance is much smaller than the total recombination distance of the genomic region under selection. Consequently, divergence between populations increases by net gain of new differentiation within the critical recombination distance, resulting in tightly-linked clusters of divergence. The mechanism responsible is the balance between stochastic loss and gain of weak local differentiation, a mechanism acting universally throughout the genome. Our results will help to explain empirical observations and lead to novel predictions regarding changes in genomic architectures during adaptive divergence. This article is protected by copyright. All rights reserved

Ceased grazing management changes the ecosystem services of semi-natural grasslands

Understanding how drivers of change affect ecosystem services (ES) is of great importance. Indicators of ES can be developed based on biophysical measures and be used to investigate the service flow from ecosystems to socio-ecological systems. However, the ES concept is multivariate and the use of normalized composite indicators reduces complexity and facilitates communication between science and policy. The aim of this study is to analyze how land use change affects ES and species richness and how the effects are modified by environmental factors by using composite indicators based on biophysical indicators. Using multivariate and regression analyses, we analyze the effect of grazing management abandonment in semi-natural grasslands in Norway on six ES: nutrient cycling, pollination, forage quality, aesthetics and global and regional climate regulation in addition to species richness along soil and climate gradients. Nutrient cycling, forage quality, regional climate regulation, aesthetics and species richness are larger in managed compared to abandoned grasslands. There are trade-offs among ES as different management strategies provide various ES and these trade-offs vary along environmental gradients. Management policies that aim to conserve ES need to have conservation goals that are context dependent, should recognize ES trade-offs and be adapted to local conditions

Measurement of Aromatic-hydrocarbons With the DOAS Technique

Long-path DOAS (differential optical absorption spectroscopy) in the ultraviolet spectral region has been shown to be applicable for low-concentration measurements of light aromatic hydrocarbons. However, because of spectral interferences among different aromatics as well as with oxygen, ozone, and sulfur dioxide, the application of the DOAS technique for this group of components is not without problems. This project includes a study of the differential absorption characteristics, between 250 and 280 nm, of twelve light aromatic hydrocarbons representing major constituents in technical solvents used in the automobile industry. Spectral overlapping between the different species, including oxygen, ozone, and sulfur dioxide, has been investigated and related to the chemical structure of the different aromatics. Interference effects in the DOAS application due to spectral overlapping have been investigated both in quantitative and in qualitative terms, with data from a field campaign at a major automobile manufacturing plant

Biotreatment of industrial wastewaters under transient-state conditions: process stability with fluctuations of organic load, substrates, toxicants, and environmental parameters

Biotreatment of industrial wastewater is often challenged by operation under transient states with respect to organic loads, pollutants, and physical characteristics. Furthermore, the potential presence of inhibitory compounds requires careful monitoring and adequate process design. This review describes difficulties encountered in biological treatment of wastewater with highly variable influent characteristics. Typical design aspects of biological processes are presented and discussed with respect to their success in treating highly fluctuating wastewaters. In general, biomass retention is a key factor for dealing with highly fluctuating and/or inhibitory wastewater, but the how it operates also affects the stability of performance, as it was shown that dynamic operation instead of operation at a constant flow enhances biodegradation onset and more evenly distributed activity. Although ultimately stable effluent quality must be achieved, the microbial population stability is not necessarily high, as it was shown that microbial diversity and flexibility may play a critical role in functional stability.info:eu-repo/semantics/acceptedVersio

Treatment of halogenated organic compounds and monitoring of microbial dynamics in up-flow fixed bed reactors under sequentially alternating pollutant scenarios

Two up-flow fixed bed reactors (UFBR) were operated for 8 months treating a model synthetic wastewater containing 2-fluorobenzoate (2-FB) and dichloromethane (DCM). The stability of the reactors under dynamic conditions, that is, sequentially alternating pollutants (SAP), shock loads, and starvation periods was assessed. Two support materials were used: expanded clay (EC) that does not adsorb 2-FB or DCM, and granular-activated carbon (GAC) that adsorbs 180 mg gg⁻¹ of 2-FB and 390 mg gg⁻¹ of DCM. The reactors were inoculated with a 2-FB-degrading strain (FB2) and a DCM degrader (TM1). 2-FB was fed at organic loads ranging from 0 to 800 mg L⁻¹ d⁻¹, while DCM was fed at 0–250 mg L⁻¹ d⁻¹. 2-FB or DCM were never detected at the outlet of the GAC reactor, while in the EC reactor outlet small amounts were observed. Nevertheless, the highest biological elimination capacity was observed in the EC reactor (over 700 mg L⁻¹ d⁻¹ of 2-FB). DGGE analysis revealed a fairly stable bacterial community with the largest shifts occurring during starvation periods and changes in feed composition. Several bacterial strains isolated from the reactors showed capacity for 2-FB degradation, while only strain TM1 degraded DCM

Enhanced adsorption of cationic and anionic dyes from aqueous solutions by polyacid doped polyaniline

A new high surface area polyaniline (PANI) adsorbent was synthesized by matrix polymerization of aniline in the presence of a polyacid, poly(2-acrylamido-2-methyl-1-propanesulfonic acid) (PAMPSA). Morphological and physicochemical properties of PANI-PAMPSA were characterized by field emission scanning electron microscope (FESEM), Fourier transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), nitrogen adsorption/desorption and zeta potential measurement. Adsorption properties were evaluated using methylene blue (MB) and rose bengal (RB) as model dyes.The results showed that PANI-PAMPSA obtained a well-defined porous structure with a specific surface area (126 m2 g−1) over 10 times larger than that of the emeraldine base PANI (PANI-EB) (12 m2 g−1). The maximum adsorption capacities were 466.5 mg g−1 for MB and 440.0 mg g−1 for RB, higher than any other PANI-based materials reported in the literature. The FTIR analysis and zeta potential measurement revealed that the adsorption mechanisms involved π-π interaction and electrostatic interaction. The adsorption kinetics were best described by a pseudo-second-order model, and the adsorption isotherms followed the Langmuir model. The thermodynamic study indicated that the adsorption was a spontaneous endothermic process. Overall, the convenient synthesis and the high adsorption capacity make PANI-PAMPSA a promising adsorbent material for dye removal

Convolutional LSTM Networks for Subcellular Localization of Proteins

Machine learning is widely used to analyze biological sequence data. Non-sequential models such as SVMs or feed-forward neural networks are often used although they have no natural way of handling sequences of varying length. Recurrent neural networks such as the long short term memory (LSTM) model on the other hand are designed to handle sequences. In this study we demonstrate that LSTM networks predict the subcellular location of proteins given only the protein sequence with high accuracy (0.902) outperforming current state of the art algorithms. We further improve the performance by introducing convolutional filters and experiment with an attention mechanism which lets the LSTM focus on specific parts of the protein. Lastly we introduce new visualizations of both the convolutional filters and the attention mechanisms and show how they can be used to extract biological relevant knowledge from the LSTM networks

Isolation of a Xanthobacter sp. degrading dichloromethane and characterization of the gene involved in the degradation

A bacterial strain able to degrade dichloromethane (DCM) as the sole carbon source was isolated from a wastewater treatment plant receiving domestic and pharmaceutical effluent. 16S rDNA studies revealed the strain to be a Xanthobacter sp. (strain TM1). The new isolated strain when grown aerobically on DCM showed Luong type growth kinetics, with lmax of 0.094 h-1 and Sm of 1,435 mg l-1. Strain TM1 was able to degrade other aromatic and aliphatic halogenated compounds, such as halobenzoates, 2-chloroethanol and dichloroethane. The gene for DCM dehalogenase, which is the key enzyme in DCM degradation, was amplified through PCR reactions. Strain TM1 contains type A DCM dehalogenase (dcmAa), while no product could be obtained for type B dehalogense (dcmAb). The sequence was compared against 12 dcmAa from other DCM degrading strains and 98% or 99% similarity was observed with all other previously isolated DCM dehalogenase genes. This is the first time a Xanthobacter sp. is reported to degrade DCM.info:eu-repo/semantics/acceptedVersio

High-resolution continuous-flow analysis setup for water isotopic measurement from ice cores using laser spectroscopy

Here we present an experimental setup for water stable isotope (&delta;¹⁸O and δD) continuous-flow measurements and provide metrics defining the performance of the setup during a major ice core measurement campaign (Roosevelt Island Climate Evolution; RICE). We also use the metrics to compare alternate systems. Our setup is the first continuous-flow laser spectroscopy system that is using off-axis integrated cavity output spectroscopy (OA-ICOS; analyzer manufactured by Los Gatos Research, LGR) in combination with an evaporation unit to continuously analyze water samples from an ice core. <br><br> A Water Vapor Isotope Standard Source (WVISS) calibration unit, manufactured by LGR, was modified to (1) enable measurements on several water standards, (2) increase the temporal resolution by reducing the response time and (3) reduce the influence from memory effects. While this setup was designed for the continuous-flow analysis (CFA) of ice cores, it can also continuously analyze other liquid or vapor sources. <br><br> The custom setups provide a shorter response time (~ 54 and 18 s for 2013 and 2014 setup, respectively) compared to the original WVISS unit (~ 62 s), which is an improvement in measurement resolution. Another improvement compared to the original WVISS is that the custom setups have a reduced memory effect. <br><br> Stability tests comparing the custom and WVISS setups were performed and Allan deviations (&sigma;_Allan) were calculated to determine precision at different averaging times. For the custom 2013 setup the precision after integration times of 10³ s is 0.060 and 0.070 &permil; for δ¹⁸O and δD, respectively. The corresponding &sigma;_Allan values for the custom 2014 setup are 0.030, 0.060 and 0.043 &permil; for &delta;¹⁸O, δD and &delta;¹⁷O, respectively. For the WVISS setup the precision is 0.035, 0.070 and 0.042 &permil; after 10³ s for δ¹⁸O, δD and &delta;¹⁷O, respectively. Both the custom setups and WVISS setup are influenced by instrumental drift with δ¹⁸O being more drift sensitive than δD. The &sigma;_Allan values for δ¹⁸O are 0.30 and 0.18 &permil; for the custom 2013 and WVISS setup, respectively, after averaging times of 10⁴ s (2.78 h). Using response time tests and stability tests, we show that the custom setups are more responsive (shorter response time), whereas the University of Copenhagen (UC) setup is more stable. More broadly, comparisons of different setups address the challenge of integrating vaporizer/spectrometer isotope measurement systems into a CFA campaign with many other analytical instruments