Seetharaman Vaidyanathan

Flow-injection electrospray ionization mass spectrometry of crude cell extracts for high-throughput bacterial identification

Flow-injection electrospray ionization mass spectrometry (FI-ESI-MS) of unfractionated cell-free extracts obtained from bacterial cells suspended in a solvent mixture was investigated as a rapid analytical method for reproducible, high-throughput bacterial identification. Five bacterial strains (two Escherichia coli, two Bacillus spp. and one Brevibacillus laterosporus) were studied in this investigation. Axenically grown bacterial cells were suspended in an acidic organic solvent and the cell-free extract was sequentially injected into a solvent flow stream that was sprayed into the ionization chamber of the ESI-MS. The spectra produced contained reproducible information, which was useful for discriminating between the bacteria. Tandem mass spectrometry was used to characterize further the peaks, and at least three classes of macromolecules, namely phospholipids, glycolipids, and proteins, were found to contribute most to the spectral information. Bacterial extracts stored under different conditions gave very similar mass spectra for each of the five bacterial strains, indicating that the extracts were stable even at room temperature for up to 24 h, with no loss of information content, which has obvious implications for automated high-throughput analysis. An analysis of the components of the extracting solvent mixture and their effects on the spectral information showed that acetonitrile contributes most significantly to the extraction process and hence to the information content of the spectra.

At-line monitoring of a submerged filamentous bacterial cultivation using near-infrared spectroscopy

The use of near infra-red spectroscopy (NIRS) to monitor a submerged filamentous bacterial bioprocess was investigated. An industrial strain of the filamentous bacterium Streptomyces fradiae was cultured in a 12 litre stirred tank reactor (STR) using a complex medium. This mycelial 4 phase (oil, water, gas and solid) system produced highly complex and variable matrices, therefore monitoring such a complex fluid with NIRS represented a considerable challenge. Nevertheless, successful models for four key analytes (methyl oleate, glucose, glutamate and ammonium) were built at-line (rapid off-line) using NIRS. In the present study, the methods used to formulate, select and validate the models for the key analytes are discussed, with particular emphasis on how the model performance can be critically evaluated. Since previous reports on NIRS in monitoring bioprocesses have either involved simpler matrices, or, in filamentous systems, have not discussed how NIRS models can be critically assessed, the emphasis in the present study on providing an insight into the modelling process in such a complex matrix, may be particularly important to the applicability of NIRS to such industrial bioprocesses.

HILIC- and SCX-based quantitative proteomics of Chlamydomonas reinhardtii during nitrogen starvation induced lipid and carbohydrate accumulation

Nitrogen starvation induced changes in carbohydrate and lipid content is described in several algal species. Although these phenotypic changes are desirable, such manipulations also significantly deteriorate culture health, ultimately halting growth. To optimize biofuel production from algae, it is desirable to induce lipid accumulation without compromising cell growth and survival. In this study, we utilized an 8-plex iTRAQ-based proteomic approach to assess the model alga Chlamydomonas reinhardtii CCAP 11/32CW15+ under nitrogen starvation. First-dimension fractionation was conducted using HILIC and SCX. A total of 587 proteins were identified (≥3 peptides) of which 71 and 311 were differentially expressed at significant levels (p<0.05), during nitrogen stress induced carbohydrate and lipid production, respectively. Forty-seven percent more changes with significance were observed with HILIC compared to SCX. Several trends were observed including increase in energy metabolism, decrease in translation machinery, increase in cell wall production and a change of balance between photosystems I and II. These findings point to a severely compromised system where lipid is accumulated at the expense of normal functioning of the organism, suggesting that a more informed and controlled method of lipid induction than gross nutrient manipulation would be needed for development of sustainable processes.

Monitoring of Submerged Bioprocesses

ABSTRACT: Monitoring is an important exercise in the operation of submerged bioprocesses and is a subject that has attracted intense research activity in recent years. In order to achieve optimal production or conversion, the factors that influence the performance of a bioprocess should be measured, preferably on-line, so that the process can be monitored in real-time and appropriate control or remedial action implemented. Such measurements can be achieved either in situ or ex situ. Ideally, in situ approaches are desirable. Where such an option is difficult to implement, ex situ approaches with appropriate sample handling techniques can be employed. In cases where direct analytical information is not available, inferential approaches can be adopted. In addition, analytical information not yet accessible on-line can be obtained off-line. Computational techniques have enabled the compilation of measurement data before utilizing the information for process diagnosis. Current developments in the different me...

Subsurface biomolecular imaging of Streptomyces coelicolor using secondary ion mass spectrometry

Imaging using time-of-flight secondary ion mass spectrometry (TOF-SIMS) with buckministerfullerene (C(60)) primary ions offers the possibility of mapping the chemical distribution of molecular species from biological surfaces. Here we demonstrate the capability of the technique to provide biomolecular information from the cell surface as well as from within the surface, as illustrated with the distribution of two antibiotics in Streptomyces coelicolor (a mycelial bacterium). Differential production of the two pigmented antibiotics under salt-stressed and normal conditions in submerged cultivations could be detected from the TOF-SIMS spectra of the bacteria, demonstrating the potential of the technique in studying microbial physiology. Although both the antibiotics were detected on the cell surface, sputter etching with C(60)(+) revealed the spectral features of only one of the antibiotics within the cells. Exploratory analysis of the images using principal component analysis assisted in analyzing the spectral information with respect to peak contributions and their spatial distributions. The technique allows the study of not only lateral but also the depthwise distribution of biomolecules, uniquely enabling exploration of the processes within biological systems with minimal system intervention and with little a priori biochemical knowledge of relevance.

Deconvolution of near-infrared spectral information for monitoring mycelial biomass and other key analytes in a submerged fungal bioprocess

Near-infrared spectroscopy is a promising technique for the rapid monitoring of submerged culture bioprocesses. However, despite the key role of mycelial (filamentous fungal and bacterial) micro-organisms in the manufacture of antibiotics and other valuable therapeutics, there is little information on the application of the technique to monitor mycelial bioprocesses. In part, this is due to the complex and spectroscopically challenging matrices, which result from the growth of these micro-organisms. Moreover, there is a particular lack of any detailed mechanistic information on how models for the prediction of the concentration of key analytes (e.g. biomass, substrates, product) can be constructed, evaluated and improved using the spectral data arising from such complex matrices. We investigated the near-infrared spectra of culture fluid from a submerged fungal bioprocess, for monitoring the concentrations of mycelial biomass and other key analytes. Several empirical models were developed for predicting the concentration of the analytes, using multivariate statistical techniques. Despite the filamentous nature of the biomass and the resulting complexity of the spectral variations, empirical models could be developed for the prediction of this analyte, using biomass ‘specific’ information. SEP values of <1 g/l could be achieved on external validation, for models developed in the concentration range of 0–20 g/l. The concentrations of the substrates, total sugars (as glucose equivalents) and ammonium, could also be predicted, simultaneously. However, the product (penicillin) and by product (extracellular proteins) levels had to be monitored on the cell free culture fluid, due to their relatively low concentration. Here we report upon how the spectral information can be deconvoluted for predicting the levels of the analytes and upon how the ‘analyte specific’ information in the spectral data can be used to inform and assist the modelling process, in order to increase confidence in exactly what is being modelled.

Critical Evaluation of Models Developed for Monitoring an Industrial Submerged Bioprocess for Antibiotic Production Using Near‐Infrared Spectroscopy

Near‐infrared spectroscopy (NIRS) is known to have potential for cost‐effective monitoring of bioprocesses. Although this has been demonstrated in many instances and several models have been reported, information regarding the complexity of models required and their utility over extended periods of time is lacking. In the present study, the complexity of the models required for the NIRS prediction of substrate (oil) and product (tylosin) concentration in an industrial bioprocess that employs a physicochemically heterogeneous medium for antibiotic production was assessed. Measurements made by both the diffuse reflectance and transmittance modes were investigated. SEP values for the prediction of the analytes averaged 5% or less, for the successful models, when evaluated using an external validation set, 2 years after the initial model development exercise. Diffuse reflectance measurements showed poorer results, compared to transmittance measurements, especially for monitoring tylosin. In general, this investigation provides evidence to support the fact that models built for the prediction of analytes in a commercial bioprocess that employs a physicochemically complex production medium can be robust in performance over an extended period of time and that simple models based on fewer terms or latent variables can perform well, even in the context of matrices that are relatively complex. It also indicates that sample presentation is likely to be a critical factor in the successful application of NIRS in bioprocess monitoring, which merits further detailed investigation.

Fundamental investigations on the near-infrared spectra of microbial biomass as applicable to bioprocess monitoring

The near-infrared (NIR) spectrum of microbial biomass was studied for a range of microorganisms, with relevance to applicability in bioprocess monitoring and control. Three experiments were carried out to investigate the validity of measuring biomass using NIR spectroscopy (NIRS). (1) A comparative study of the NIR reflectance spectra of five representative microorganisms, of interest in a bioprocessing context, showed that the spectral signature of biomass, with respect to the wavelength regions, is essentially identical for all five microorganisms. The signature wavelengths are listed. (2) The spectral signature correlated well quantitatively with dry cell mass measurements, when the biomass of a filamentous microorganism was isolated from its matrix and analysed. The observation was clearer with reflectance measurements of dried biomass than with transmittance measurements of aqueous suspensions. (3) The biomass reflectance spectral signature remained the same at different culture ages of Penicillium chrysogenum, and showed quantitative correlation with dry cell mass measurements at the relevant wavelengths. This study therefore indicates those spectral regions which are likely to be the basis for quantitative modelling of microbial biomass in bioprocesses using NIRS, regardless of the microbial type and the culture age.

Simultaneous assay of pigments, carbohydrates, proteins and lipids in microalgae

Biochemical compositional analysis of microbial biomass is a useful tool that can provide insight into the behaviour of an organism and its adaptational response to changes in its environment. To some extent, it reflects the physiological and metabolic status of the organism. Conventional methods to estimate biochemical composition often employ different sample pretreatment strategies and analytical steps for analysing each major component, such as total proteins, carbohydrates, and lipids, making it labour-, time- and sample-intensive. Such analyses when carried out individually can also result in uncertainties of estimates as different pre-treatment or extraction conditions are employed for each of the component estimations and these are not necessarily standardised for the organism, resulting in observations that are not easy to compare within the experimental set-up or between laboratories. We recently reported a method to estimate total lipids in microalgae (Chen, Vaidyanathan, Anal. Chim. Acta, 724, 67-72). Here, we propose a unified method for the simultaneous estimation of the principal biological components, proteins, carbohydrates, lipids, chlorophyll and carotenoids, in a single microalgae culture sample that incorporates the earlier published lipid assay. The proposed methodology adopts an alternative strategy for pigment assay that has a high sensitivity. The unified assay is shown to conserve sample (by 79%), time (67%), chemicals (34%) and energy (58%) when compared to the corresponding assay for each component, carried out individually on different samples. The method can also be applied to other microorganisms, especially those with recalcitrant cell walls.

A simple, reproducible and sensitive spectrophotometric method to estimate microalgal lipids.

Quantification of total lipids is a necessity for any study of lipid production by microalgae, especially given the current interest in microalgal carbon capture and biofuels. In this study, we employed a simple yet sensitive method to indirectly measure the lipids in microalgae by measuring the fatty acids (FA) after saponification. The fatty acids were reacted with triethanolamine-copper salts (TEA-Cu) and the ternary TEA-Cu-FA complex was detected at 260 nm using a UV-visible spectrometer without any colour developer. The results showed that this method could be used to analyse low levels of lipids in the range of nano-moles from as little as 1 mL of microalgal culture. Furthermore, the structure of the TEA-Cu-FA complex and related reaction process are proposed to better understand this assay. There is no special instrument required and the method is very reproducible. To the best of our knowledge, this is the first report of the use of UV absorbance of copper salts with FA as a method to estimate lipids in algal cultures. It will pave the way for a more convenient assay of lipids in microalgae and can readily be expanded for estimating lipids in other biological systems.