Bacterial aerobic respiration is a major consumer of oxygen in sputum from patients with acute lower respiratory tract infection.

Bacterial aerobic respiration may determine the outcome of antibiotic treatment in experimental settings, but the clinical relevance of bacterial aerobic respiration for the outcome of antibiotic treatment has not been tested. Therefore, we hypothesized that bacterial aerobic respiration is higher in sputum from patients with acute lower respiratory tract infections (aLRTI), than in sputum from patients with chronic LRTI (cLRTI), where the bacteria persist despite antibiotic treatment. The bacterial aerobic respiration was determined according to the dynamics of the oxygen (O2 ) concentration in sputum from aLRTI patients (n = 52). This result was evaluated by comparison to previously published data from patients with cLRTI. O2 consumption resulting in anoxic zones was more frequent in sputum with detected bacterial pathogens. The bacterial aerobic respiration in aLRTI sputum approximated 55% of the total O2 consumption, which was significantly higher than previously published for cLRTI. The bacterial aerobic respiration in sputum was higher in aLRTI patients than previously seen in cLRTI patients, indicating the presence of bacteria with a sensitive physiology in aLRTI. These variations in bacterial physiology between aLRTI patients and cLRTI patients may contribute the huge difference in treatment success between the two patient groups.

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

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 (R2) 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.

Production of docosahexaenoic acid from spruce sugars using Aurantiochytrium limacinum.

In this study lignocellulosic sugars from Norway spruce were used for production of docosahexaenoic acid (DHA) by the marine thraustochytrid Aurantiochytrium limacinum SR21. Enzymatically prepared spruce hydrolysate was combined with a complex nitrogen source and different amounts of salts. Shake flask batch cultivations revealed that addition of extra salts was not needed for optimal growth. Upscaling to fed-batch bioreactors yielded up to 55 g/L cell dry mass and a total fatty acid content of 44% (w/w) out of which 1/3 was DHA. Fourier transform infrared spectroscopy was successfully applied as a rapid method for monitoring lipid accumulation in A. limacinum SR21. Thus, this proof-of-principle study clearly demonstrates that crude spruce hydrolysates can be directly used as a novel and sustainable resource for production of DHA.

Spruce sugars and poultry hydrolysate as growth medium in repeated fed-batch fermentation processes for production of yeast biomass.

The production of microbial protein in the form of yeast grown on lignocellulosic sugars and nitrogen-rich industrial residues is an attractive approach for reducing dependency on animal and plant protein. Growth media composed of enzymatically saccharified sulfite-pulped spruce wood, enzymatic hydrolysates of poultry by-products and urea were used for the production of single-cell protein. Strains of three different yeast species, Cyberlindnera jadinii, Wickerhamomyces anomalus and Blastobotrys adeninivorans, were cultivated aerobically using repeated fed-batch fermentation up to 25 L scale. Wickerhamomyces anomalus was the most efficient yeast with yields of 0.6 g of cell dry weight and 0.3 g of protein per gram of glucose, with cell and protein productivities of 3.92 g/L/h and 1.87 g/L/h, respectively. Using the conditions developed here for producing W. anomalus, it would take 25 industrial (200 m3) continuously operated fermenters to replace 10% of the fish feed protein used in Norway.

High-Throughput Sequencing-Based Investigation of Viruses in Human Cancers by Multienrichment Approach.

BACKGROUND: Viruses and other infectious agents cause more than 15% of human cancer cases. High-throughput sequencing-based studies of virus-cancer associations have mainly focused on cancer transcriptome data. METHODS: In this study, we applied a diverse selection of presequencing enrichment methods targeting all major viral groups, to characterize the viruses present in 197 samples from 18 sample types of cancerous origin. Using high-throughput sequencing, we generated 710 datasets constituting 57 billion sequencing reads. RESULTS: Detailed in silico investigation of the viral content, including exclusion of viral artefacts, from de novo assembled contigs and individual sequencing reads yielded a map of the viruses detected. Our data reveal a virome dominated by papillomaviruses, anelloviruses, herpesviruses, and parvoviruses. More than half of the included samples contained 1 or more viruses; however, no link between specific viruses and cancer types were found. CONCLUSIONS: Our study sheds light on viral presence in cancers and provides highly relevant virome data for future reference.

Identification of Known and Novel Recurrent Viral Sequences in Data from Multiple Patients and Multiple Cancers.

Virus discovery from high throughput sequencing data often follows a bottom-up approach where taxonomic annotation takes place prior to association to disease. Albeit effective in some cases, the approach fails to detect novel pathogens and remote variants not present in reference databases. We have developed a species independent pipeline that utilises sequence clustering for the identification of nucleotide sequences that co-occur across multiple sequencing data instances. We applied the workflow to 686 sequencing libraries from 252 cancer samples of different cancer and tissue types, 32 non-template controls, and 24 test samples. Recurrent sequences were statistically associated to biological, methodological or technical features with the aim to identify novel pathogens or plausible contaminants that may associate to a particular kit or method. We provide examples of identified inhabitants of the healthy tissue flora as well as experimental contaminants. Unmapped sequences that co-occur with high statistical significance potentially represent the unknown sequence space where novel pathogens can be identified.